[09/22 03:16:44] libai INFO: Rank of current process: 0. World size: 8
[09/22 03:16:44] libai INFO: Command line arguments: Namespace(config_file='configs/swin_imagenet.py', eval_only=False, fast_dev_run=False, opts=[], resume=False)
[09/22 03:16:44] libai INFO: Contents of args.config_file=configs/swin_imagenet.py:
from libai.config import LazyCall
from .common.models.swin.swin_tiny_patch4_window7_224 import model
from .common.models.graph import graph
from .common.train import train
from .common.optim import optim
from .common.data.imagenet import dataloader

from flowvision.data import Mixup
from flowvision.loss.cross_entropy import SoftTargetCrossEntropy

# Refine data path to imagenet
dataloader.train.dataset[0].root = "/data/ImageNet/extract/"
dataloader.test[0].dataset.root = "/data/ImageNet/extract/"

# Add Mixup Func
dataloader.train.mixup_func = LazyCall(Mixup)(
    mixup_alpha=0.8,
    cutmix_alpha=1.0,
    prob=1.0,
    switch_prob=0.5,
    mode="batch",
    num_classes=1000,
)

# Refine model cfg for vit training on imagenet
model.cfg.num_classes = 1000
model.cfg.loss_func = SoftTargetCrossEntropy()
# Refine optimizer cfg for vit model
optim.lr = 1e-3
optim.eps = 1e-8
optim.weight_decay = 0.05

# Refine train cfg for vit model
train.train_micro_batch_size = 128
train.test_micro_batch_size = 128
train.train_epoch = 300
train.warmup_ratio = 20 / 300
train.eval_period = 1000
train.log_period = 100
train.output_dir = "./commit_swin"
# Scheduler
train.scheduler.warmup_factor = 0.001
train.scheduler.alpha = 0.01
train.scheduler.warmup_method = "linear"

# Set fp16 ON
train.amp.enabled = True

[09/22 03:16:44] libai INFO: Full config saved to ./commit_swin/config.yaml
[09/22 03:16:44] lb.engine.default INFO: > compiling dataset index builder ...
[09/22 03:16:44] lb.engine.default INFO: >>> done with dataset index builder. Compilation time: 0.072 seconds
[09/22 03:16:44] lb.engine.default INFO: >>> done with compiling. Compilation time: 0.073 seconds
[09/22 03:16:44] lb.engine.default INFO: Prepare training, validating, testing set
[09/22 03:16:47] lb.engine.default INFO: Prepare testing set
[09/22 03:16:47] lb.engine.default INFO: Auto-scaling the config to train.train_iter=375342, train.warmup_iter=25023
[09/22 03:16:57] lb.engine.default INFO: Model:
SwinTransformer(
  (patch_embed): PatchEmbed(
    (proj): Conv2d(3, 96, kernel_size=(4, 4), stride=(4, 4))
    (norm): LayerNorm((96,), eps=1e-05, elementwise_affine=True)
  )
  (pos_drop): Dropout(p=0.0, inplace=False)
  (layers): ModuleList(
    (0): BasicLayer(
      (blocks): ModuleList(
        (0): SwinTransformerBlock(
          (norm1): LayerNorm((96,), eps=1e-05, elementwise_affine=True)
          (attn): WindowAttention(
            (qkv): Linear1D(in_features=96, out_features=288, bias=True, parallel=data)
            (attn_drop): Dropout(p=0.0, inplace=False)
            (proj): Linear1D(in_features=96, out_features=96, bias=True, parallel=data)
            (proj_drop): Dropout(p=0.0, inplace=False)
            (softmax): Softmax(dim=-1)
          )
          (drop_path): Identity()
          (norm2): LayerNorm((96,), eps=1e-05, elementwise_affine=True)
          (mlp): MLP(
            bias_gelu_fusion=True, bias_dropout_fusion=True, dropout=0.0
            (dense_h_to_4h): Linear1D(in_features=96, out_features=384, bias=True, parallel=col)
            (dense_4h_to_h): Linear1D(in_features=384, out_features=96, bias=True, parallel=row)
          )
        )
        (1): SwinTransformerBlock(
          (norm1): LayerNorm((96,), eps=1e-05, elementwise_affine=True)
          (attn): WindowAttention(
            (qkv): Linear1D(in_features=96, out_features=288, bias=True, parallel=data)
            (attn_drop): Dropout(p=0.0, inplace=False)
            (proj): Linear1D(in_features=96, out_features=96, bias=True, parallel=data)
            (proj_drop): Dropout(p=0.0, inplace=False)
            (softmax): Softmax(dim=-1)
          )
          (drop_path): DropPath()
          (norm2): LayerNorm((96,), eps=1e-05, elementwise_affine=True)
          (mlp): MLP(
            bias_gelu_fusion=True, bias_dropout_fusion=True, dropout=0.0
            (dense_h_to_4h): Linear1D(in_features=96, out_features=384, bias=True, parallel=col)
            (dense_4h_to_h): Linear1D(in_features=384, out_features=96, bias=True, parallel=row)
          )
        )
      )
      (downsample): PatchMerging(
        (reduction): Linear1D(in_features=384, out_features=192, bias=False, parallel=data)
        (norm): LayerNorm((384,), eps=1e-05, elementwise_affine=True)
      )
    )
    (1): BasicLayer(
      (blocks): ModuleList(
        (0): SwinTransformerBlock(
          (norm1): LayerNorm((192,), eps=1e-05, elementwise_affine=True)
          (attn): WindowAttention(
            (qkv): Linear1D(in_features=192, out_features=576, bias=True, parallel=data)
            (attn_drop): Dropout(p=0.0, inplace=False)
            (proj): Linear1D(in_features=192, out_features=192, bias=True, parallel=data)
            (proj_drop): Dropout(p=0.0, inplace=False)
            (softmax): Softmax(dim=-1)
          )
          (drop_path): DropPath()
          (norm2): LayerNorm((192,), eps=1e-05, elementwise_affine=True)
          (mlp): MLP(
            bias_gelu_fusion=True, bias_dropout_fusion=True, dropout=0.0
            (dense_h_to_4h): Linear1D(in_features=192, out_features=768, bias=True, parallel=col)
            (dense_4h_to_h): Linear1D(in_features=768, out_features=192, bias=True, parallel=row)
          )
        )
        (1): SwinTransformerBlock(
          (norm1): LayerNorm((192,), eps=1e-05, elementwise_affine=True)
          (attn): WindowAttention(
            (qkv): Linear1D(in_features=192, out_features=576, bias=True, parallel=data)
            (attn_drop): Dropout(p=0.0, inplace=False)
            (proj): Linear1D(in_features=192, out_features=192, bias=True, parallel=data)
            (proj_drop): Dropout(p=0.0, inplace=False)
            (softmax): Softmax(dim=-1)
          )
          (drop_path): DropPath()
          (norm2): LayerNorm((192,), eps=1e-05, elementwise_affine=True)
          (mlp): MLP(
            bias_gelu_fusion=True, bias_dropout_fusion=True, dropout=0.0
            (dense_h_to_4h): Linear1D(in_features=192, out_features=768, bias=True, parallel=col)
            (dense_4h_to_h): Linear1D(in_features=768, out_features=192, bias=True, parallel=row)
          )
        )
      )
      (downsample): PatchMerging(
        (reduction): Linear1D(in_features=768, out_features=384, bias=False, parallel=data)
        (norm): LayerNorm((768,), eps=1e-05, elementwise_affine=True)
      )
    )
    (2): BasicLayer(
      (blocks): ModuleList(
        (0): SwinTransformerBlock(
          (norm1): LayerNorm((384,), eps=1e-05, elementwise_affine=True)
          (attn): WindowAttention(
            (qkv): Linear1D(in_features=384, out_features=1152, bias=True, parallel=data)
            (attn_drop): Dropout(p=0.0, inplace=False)
            (proj): Linear1D(in_features=384, out_features=384, bias=True, parallel=data)
            (proj_drop): Dropout(p=0.0, inplace=False)
            (softmax): Softmax(dim=-1)
          )
          (drop_path): DropPath()
          (norm2): LayerNorm((384,), eps=1e-05, elementwise_affine=True)
          (mlp): MLP(
            bias_gelu_fusion=True, bias_dropout_fusion=True, dropout=0.0
            (dense_h_to_4h): Linear1D(in_features=384, out_features=1536, bias=True, parallel=col)
            (dense_4h_to_h): Linear1D(in_features=1536, out_features=384, bias=True, parallel=row)
          )
        )
        (1): SwinTransformerBlock(
          (norm1): LayerNorm((384,), eps=1e-05, elementwise_affine=True)
          (attn): WindowAttention(
            (qkv): Linear1D(in_features=384, out_features=1152, bias=True, parallel=data)
            (attn_drop): Dropout(p=0.0, inplace=False)
            (proj): Linear1D(in_features=384, out_features=384, bias=True, parallel=data)
            (proj_drop): Dropout(p=0.0, inplace=False)
            (softmax): Softmax(dim=-1)
          )
          (drop_path): DropPath()
          (norm2): LayerNorm((384,), eps=1e-05, elementwise_affine=True)
          (mlp): MLP(
            bias_gelu_fusion=True, bias_dropout_fusion=True, dropout=0.0
            (dense_h_to_4h): Linear1D(in_features=384, out_features=1536, bias=True, parallel=col)
            (dense_4h_to_h): Linear1D(in_features=1536, out_features=384, bias=True, parallel=row)
          )
        )
        (2): SwinTransformerBlock(
          (norm1): LayerNorm((384,), eps=1e-05, elementwise_affine=True)
          (attn): WindowAttention(
            (qkv): Linear1D(in_features=384, out_features=1152, bias=True, parallel=data)
            (attn_drop): Dropout(p=0.0, inplace=False)
            (proj): Linear1D(in_features=384, out_features=384, bias=True, parallel=data)
            (proj_drop): Dropout(p=0.0, inplace=False)
            (softmax): Softmax(dim=-1)
          )
          (drop_path): DropPath()
          (norm2): LayerNorm((384,), eps=1e-05, elementwise_affine=True)
          (mlp): MLP(
            bias_gelu_fusion=True, bias_dropout_fusion=True, dropout=0.0
            (dense_h_to_4h): Linear1D(in_features=384, out_features=1536, bias=True, parallel=col)
            (dense_4h_to_h): Linear1D(in_features=1536, out_features=384, bias=True, parallel=row)
          )
        )
        (3): SwinTransformerBlock(
          (norm1): LayerNorm((384,), eps=1e-05, elementwise_affine=True)
          (attn): WindowAttention(
            (qkv): Linear1D(in_features=384, out_features=1152, bias=True, parallel=data)
            (attn_drop): Dropout(p=0.0, inplace=False)
            (proj): Linear1D(in_features=384, out_features=384, bias=True, parallel=data)
            (proj_drop): Dropout(p=0.0, inplace=False)
            (softmax): Softmax(dim=-1)
          )
          (drop_path): DropPath()
          (norm2): LayerNorm((384,), eps=1e-05, elementwise_affine=True)
          (mlp): MLP(
            bias_gelu_fusion=True, bias_dropout_fusion=True, dropout=0.0
            (dense_h_to_4h): Linear1D(in_features=384, out_features=1536, bias=True, parallel=col)
            (dense_4h_to_h): Linear1D(in_features=1536, out_features=384, bias=True, parallel=row)
          )
        )
        (4): SwinTransformerBlock(
          (norm1): LayerNorm((384,), eps=1e-05, elementwise_affine=True)
          (attn): WindowAttention(
            (qkv): Linear1D(in_features=384, out_features=1152, bias=True, parallel=data)
            (attn_drop): Dropout(p=0.0, inplace=False)
            (proj): Linear1D(in_features=384, out_features=384, bias=True, parallel=data)
            (proj_drop): Dropout(p=0.0, inplace=False)
            (softmax): Softmax(dim=-1)
          )
          (drop_path): DropPath()
          (norm2): LayerNorm((384,), eps=1e-05, elementwise_affine=True)
          (mlp): MLP(
            bias_gelu_fusion=True, bias_dropout_fusion=True, dropout=0.0
            (dense_h_to_4h): Linear1D(in_features=384, out_features=1536, bias=True, parallel=col)
            (dense_4h_to_h): Linear1D(in_features=1536, out_features=384, bias=True, parallel=row)
          )
        )
        (5): SwinTransformerBlock(
          (norm1): LayerNorm((384,), eps=1e-05, elementwise_affine=True)
          (attn): WindowAttention(
            (qkv): Linear1D(in_features=384, out_features=1152, bias=True, parallel=data)
            (attn_drop): Dropout(p=0.0, inplace=False)
            (proj): Linear1D(in_features=384, out_features=384, bias=True, parallel=data)
            (proj_drop): Dropout(p=0.0, inplace=False)
            (softmax): Softmax(dim=-1)
          )
          (drop_path): DropPath()
          (norm2): LayerNorm((384,), eps=1e-05, elementwise_affine=True)
          (mlp): MLP(
            bias_gelu_fusion=True, bias_dropout_fusion=True, dropout=0.0
            (dense_h_to_4h): Linear1D(in_features=384, out_features=1536, bias=True, parallel=col)
            (dense_4h_to_h): Linear1D(in_features=1536, out_features=384, bias=True, parallel=row)
          )
        )
      )
      (downsample): PatchMerging(
        (reduction): Linear1D(in_features=1536, out_features=768, bias=False, parallel=data)
        (norm): LayerNorm((1536,), eps=1e-05, elementwise_affine=True)
      )
    )
    (3): BasicLayer(
      (blocks): ModuleList(
        (0): SwinTransformerBlock(
          (norm1): LayerNorm((768,), eps=1e-05, elementwise_affine=True)
          (attn): WindowAttention(
            (qkv): Linear1D(in_features=768, out_features=2304, bias=True, parallel=data)
            (attn_drop): Dropout(p=0.0, inplace=False)
            (proj): Linear1D(in_features=768, out_features=768, bias=True, parallel=data)
            (proj_drop): Dropout(p=0.0, inplace=False)
            (softmax): Softmax(dim=-1)
          )
          (drop_path): DropPath()
          (norm2): LayerNorm((768,), eps=1e-05, elementwise_affine=True)
          (mlp): MLP(
            bias_gelu_fusion=True, bias_dropout_fusion=True, dropout=0.0
            (dense_h_to_4h): Linear1D(in_features=768, out_features=3072, bias=True, parallel=col)
            (dense_4h_to_h): Linear1D(in_features=3072, out_features=768, bias=True, parallel=row)
          )
        )
        (1): SwinTransformerBlock(
          (norm1): LayerNorm((768,), eps=1e-05, elementwise_affine=True)
          (attn): WindowAttention(
            (qkv): Linear1D(in_features=768, out_features=2304, bias=True, parallel=data)
            (attn_drop): Dropout(p=0.0, inplace=False)
            (proj): Linear1D(in_features=768, out_features=768, bias=True, parallel=data)
            (proj_drop): Dropout(p=0.0, inplace=False)
            (softmax): Softmax(dim=-1)
          )
          (drop_path): DropPath()
          (norm2): LayerNorm((768,), eps=1e-05, elementwise_affine=True)
          (mlp): MLP(
            bias_gelu_fusion=True, bias_dropout_fusion=True, dropout=0.0
            (dense_h_to_4h): Linear1D(in_features=768, out_features=3072, bias=True, parallel=col)
            (dense_4h_to_h): Linear1D(in_features=3072, out_features=768, bias=True, parallel=row)
          )
        )
      )
    )
  )
  (norm): LayerNorm((768,), eps=1e-05, elementwise_affine=True)
  (avgpool): AdaptiveAvgPool1d()
  (head): Linear1D(in_features=768, out_features=1000, bias=True, parallel=data)
  (loss_func): SoftTargetCrossEntropy()
)
[09/22 03:16:57] lb.engine.trainer INFO: Starting training from iteration 0
[09/22 03:16:59] lb.models.utils.graph_base INFO: Start compling the train graph which may take some time. Please wait for a moment ...
[09/22 03:17:58] lb.utils.events INFO:  eta: 20:14:30  iteration: 99/375342  consumed_samples: 102400  total_loss: 6.957  time: 0.3083 s/iter  data_time: 0.2007 s/iter total_throughput: 3321.65 samples/s lr: 4.91e-06  
[09/22 03:18:30] lb.utils.events INFO:  eta: 19:37:07  iteration: 199/375342  consumed_samples: 204800  total_loss: 6.934  time: 0.3150 s/iter  data_time: 0.2308 s/iter total_throughput: 3250.30 samples/s lr: 8.86e-06  
[09/22 03:19:03] lb.utils.events INFO:  eta: 17:18:23  iteration: 299/375342  consumed_samples: 307200  total_loss: 6.906  time: 0.3194 s/iter  data_time: 0.2047 s/iter total_throughput: 3205.89 samples/s lr: 1.28e-05  
[09/22 03:19:36] lb.utils.events INFO:  eta: 16:53:55  iteration: 399/375342  consumed_samples: 409600  total_loss: 6.883  time: 0.3227 s/iter  data_time: 0.2024 s/iter total_throughput: 3173.23 samples/s lr: 1.68e-05  
[09/22 03:20:08] lb.utils.events INFO:  eta: 16:46:37  iteration: 499/375342  consumed_samples: 512000  total_loss: 6.863  time: 0.3233 s/iter  data_time: 0.2065 s/iter total_throughput: 3167.36 samples/s lr: 2.07e-05  
[09/22 03:20:41] lb.utils.events INFO:  eta: 16:42:38  iteration: 599/375342  consumed_samples: 614400  total_loss: 6.844  time: 0.3244 s/iter  data_time: 0.2081 s/iter total_throughput: 3157.03 samples/s lr: 2.47e-05  
[09/22 03:21:14] lb.utils.events INFO:  eta: 16:38:43  iteration: 699/375342  consumed_samples: 716800  total_loss: 6.828  time: 0.3251 s/iter  data_time: 0.1993 s/iter total_throughput: 3149.40 samples/s lr: 2.86e-05  
[09/22 03:21:48] lb.utils.events INFO:  eta: 16:34:41  iteration: 799/375342  consumed_samples: 819200  total_loss: 6.809  time: 0.3261 s/iter  data_time: 0.2054 s/iter total_throughput: 3139.70 samples/s lr: 3.26e-05  
[09/22 03:22:21] lb.utils.events INFO:  eta: 16:31:05  iteration: 899/375342  consumed_samples: 921600  total_loss: 6.785  time: 0.3269 s/iter  data_time: 0.2209 s/iter total_throughput: 3132.39 samples/s lr: 3.65e-05  
[09/22 03:22:54] lb.utils.events INFO:  eta: 16:29:58  iteration: 999/375342  consumed_samples: 1024000  total_loss: 6.766  time: 0.3273 s/iter  data_time: 0.1994 s/iter total_throughput: 3128.48 samples/s lr: 4.05e-05  
[09/22 03:23:28] lb.utils.events INFO:  eta: 16:23:12  iteration: 1099/375342  consumed_samples: 1126400  total_loss: 6.738  time: 0.3280 s/iter  data_time: 0.2107 s/iter total_throughput: 3121.61 samples/s lr: 4.44e-05  
[09/22 03:24:01] lb.utils.events INFO:  eta: 16:17:43  iteration: 1199/375342  consumed_samples: 1228800  total_loss: 6.711  time: 0.3285 s/iter  data_time: 0.2072 s/iter total_throughput: 3117.34 samples/s lr: 4.83e-05  
[09/22 03:24:34] lb.utils.events INFO:  eta: 16:17:05  iteration: 1299/375342  consumed_samples: 1331200  total_loss: 6.672  time: 0.3287 s/iter  data_time: 0.2140 s/iter total_throughput: 3114.92 samples/s lr: 5.23e-05  
[09/22 03:25:07] lb.utils.events INFO:  eta: 16:12:45  iteration: 1399/375342  consumed_samples: 1433600  total_loss: 6.641  time: 0.3290 s/iter  data_time: 0.2060 s/iter total_throughput: 3112.35 samples/s lr: 5.62e-05  
[09/22 03:25:40] lb.utils.events INFO:  eta: 16:10:41  iteration: 1499/375342  consumed_samples: 1536000  total_loss: 6.609  time: 0.3290 s/iter  data_time: 0.2021 s/iter total_throughput: 3112.22 samples/s lr: 6.02e-05  
[09/22 03:26:14] lb.utils.events INFO:  eta: 16:10:54  iteration: 1599/375342  consumed_samples: 1638400  total_loss: 6.582  time: 0.3292 s/iter  data_time: 0.2150 s/iter total_throughput: 3110.49 samples/s lr: 6.41e-05  
[09/22 03:26:47] lb.utils.events INFO:  eta: 16:10:38  iteration: 1699/375342  consumed_samples: 1740800  total_loss: 6.559  time: 0.3293 s/iter  data_time: 0.2074 s/iter total_throughput: 3109.33 samples/s lr: 6.81e-05  
[09/22 03:27:20] lb.utils.events INFO:  eta: 16:12:51  iteration: 1799/375342  consumed_samples: 1843200  total_loss: 6.531  time: 0.3294 s/iter  data_time: 0.1994 s/iter total_throughput: 3109.01 samples/s lr: 7.20e-05  
[09/22 03:27:53] lb.utils.events INFO:  eta: 16:16:52  iteration: 1899/375342  consumed_samples: 1945600  total_loss: 6.506  time: 0.3295 s/iter  data_time: 0.2033 s/iter total_throughput: 3108.16 samples/s lr: 7.60e-05  
[09/22 03:28:26] lb.utils.events INFO:  eta: 16:13:50  iteration: 1999/375342  consumed_samples: 2048000  total_loss: 6.484  time: 0.3298 s/iter  data_time: 0.2064 s/iter total_throughput: 3105.33 samples/s lr: 7.99e-05  
[09/22 03:29:00] lb.utils.events INFO:  eta: 16:13:35  iteration: 2099/375342  consumed_samples: 2150400  total_loss: 6.461  time: 0.3301 s/iter  data_time: 0.2166 s/iter total_throughput: 3101.93 samples/s lr: 8.39e-05  
[09/22 03:29:34] lb.utils.events INFO:  eta: 16:13:01  iteration: 2199/375342  consumed_samples: 2252800  total_loss: 6.441  time: 0.3304 s/iter  data_time: 0.2113 s/iter total_throughput: 3099.49 samples/s lr: 8.78e-05  
[09/22 03:30:07] lb.utils.events INFO:  eta: 16:12:27  iteration: 2299/375342  consumed_samples: 2355200  total_loss: 6.426  time: 0.3304 s/iter  data_time: 0.2105 s/iter total_throughput: 3099.14 samples/s lr: 9.18e-05  
[09/22 03:30:40] lb.utils.events INFO:  eta: 16:17:46  iteration: 2399/375342  consumed_samples: 2457600  total_loss: 6.404  time: 0.3305 s/iter  data_time: 0.2137 s/iter total_throughput: 3098.42 samples/s lr: 9.57e-05  
[09/22 03:31:13] lb.utils.events INFO:  eta: 16:18:22  iteration: 2499/375342  consumed_samples: 2560000  total_loss: 6.383  time: 0.3304 s/iter  data_time: 0.2032 s/iter total_throughput: 3099.20 samples/s lr: 9.97e-05  
[09/22 03:31:46] lb.utils.events INFO:  eta: 16:17:44  iteration: 2599/375342  consumed_samples: 2662400  total_loss: 6.359  time: 0.3305 s/iter  data_time: 0.2189 s/iter total_throughput: 3098.58 samples/s lr: 1.04e-04  
[09/22 03:32:20] lb.utils.events INFO:  eta: 16:17:28  iteration: 2699/375342  consumed_samples: 2764800  total_loss: 6.34  time: 0.3307 s/iter  data_time: 0.2082 s/iter total_throughput: 3096.50 samples/s lr: 1.08e-04  
[09/22 03:32:53] lb.utils.events INFO:  eta: 16:20:57  iteration: 2799/375342  consumed_samples: 2867200  total_loss: 6.324  time: 0.3308 s/iter  data_time: 0.2037 s/iter total_throughput: 3095.22 samples/s lr: 1.12e-04  
[09/22 03:33:26] lb.utils.events INFO:  eta: 16:17:11  iteration: 2899/375342  consumed_samples: 2969600  total_loss: 6.312  time: 0.3308 s/iter  data_time: 0.2030 s/iter total_throughput: 3095.47 samples/s lr: 1.15e-04  
[09/22 03:34:00] lb.utils.events INFO:  eta: 16:19:07  iteration: 2999/375342  consumed_samples: 3072000  total_loss: 6.297  time: 0.3309 s/iter  data_time: 0.2114 s/iter total_throughput: 3094.35 samples/s lr: 1.19e-04  
[09/22 03:34:33] lb.utils.events INFO:  eta: 16:21:54  iteration: 3099/375342  consumed_samples: 3174400  total_loss: 6.277  time: 0.3310 s/iter  data_time: 0.1962 s/iter total_throughput: 3093.75 samples/s lr: 1.23e-04  
[09/22 03:35:06] lb.utils.events INFO:  eta: 16:23:46  iteration: 3199/375342  consumed_samples: 3276800  total_loss: 6.262  time: 0.3311 s/iter  data_time: 0.1944 s/iter total_throughput: 3093.07 samples/s lr: 1.27e-04  
[09/22 03:35:40] lb.utils.events INFO:  eta: 16:24:11  iteration: 3299/375342  consumed_samples: 3379200  total_loss: 6.24  time: 0.3312 s/iter  data_time: 0.2080 s/iter total_throughput: 3091.95 samples/s lr: 1.31e-04  
[09/22 03:36:13] lb.utils.events INFO:  eta: 16:23:14  iteration: 3399/375342  consumed_samples: 3481600  total_loss: 6.213  time: 0.3312 s/iter  data_time: 0.2102 s/iter total_throughput: 3091.69 samples/s lr: 1.35e-04  
[09/22 03:36:47] lb.utils.events INFO:  eta: 16:21:10  iteration: 3499/375342  consumed_samples: 3584000  total_loss: 6.197  time: 0.3315 s/iter  data_time: 0.2077 s/iter total_throughput: 3088.76 samples/s lr: 1.39e-04  
[09/22 03:37:21] lb.utils.events INFO:  eta: 16:20:58  iteration: 3599/375342  consumed_samples: 3686400  total_loss: 6.193  time: 0.3318 s/iter  data_time: 0.2105 s/iter total_throughput: 3086.24 samples/s lr: 1.43e-04  
[09/22 03:37:55] lb.utils.events INFO:  eta: 16:20:17  iteration: 3699/375342  consumed_samples: 3788800  total_loss: 6.172  time: 0.3319 s/iter  data_time: 0.2094 s/iter total_throughput: 3084.81 samples/s lr: 1.47e-04  
[09/22 03:38:29] lb.utils.events INFO:  eta: 16:18:53  iteration: 3799/375342  consumed_samples: 3891200  total_loss: 6.137  time: 0.3321 s/iter  data_time: 0.2088 s/iter total_throughput: 3083.78 samples/s lr: 1.51e-04  
[09/22 03:39:03] lb.utils.events INFO:  eta: 16:19:54  iteration: 3899/375342  consumed_samples: 3993600  total_loss: 6.125  time: 0.3322 s/iter  data_time: 0.2053 s/iter total_throughput: 3082.69 samples/s lr: 1.55e-04  
[09/22 03:39:36] lb.utils.events INFO:  eta: 16:19:38  iteration: 3999/375342  consumed_samples: 4096000  total_loss: 6.109  time: 0.3323 s/iter  data_time: 0.2136 s/iter total_throughput: 3081.12 samples/s lr: 1.59e-04  
[09/22 03:40:11] lb.utils.events INFO:  eta: 16:16:41  iteration: 4099/375342  consumed_samples: 4198400  total_loss: 6.092  time: 0.3326 s/iter  data_time: 0.2224 s/iter total_throughput: 3078.50 samples/s lr: 1.63e-04  
[09/22 03:40:45] lb.utils.events INFO:  eta: 16:14:11  iteration: 4199/375342  consumed_samples: 4300800  total_loss: 6.078  time: 0.3327 s/iter  data_time: 0.2098 s/iter total_throughput: 3077.44 samples/s lr: 1.67e-04  
[09/22 03:41:19] lb.utils.events INFO:  eta: 16:13:55  iteration: 4299/375342  consumed_samples: 4403200  total_loss: 6.064  time: 0.3329 s/iter  data_time: 0.2061 s/iter total_throughput: 3075.84 samples/s lr: 1.71e-04  
[09/22 03:41:52] lb.utils.events INFO:  eta: 16:13:21  iteration: 4399/375342  consumed_samples: 4505600  total_loss: 6.043  time: 0.3329 s/iter  data_time: 0.2036 s/iter total_throughput: 3075.65 samples/s lr: 1.75e-04  
[09/22 03:42:26] lb.utils.events INFO:  eta: 16:14:16  iteration: 4499/375342  consumed_samples: 4608000  total_loss: 6.027  time: 0.3331 s/iter  data_time: 0.2072 s/iter total_throughput: 3074.49 samples/s lr: 1.79e-04  
[09/22 03:43:00] lb.utils.events INFO:  eta: 16:13:30  iteration: 4599/375342  consumed_samples: 4710400  total_loss: 6.016  time: 0.3332 s/iter  data_time: 0.2121 s/iter total_throughput: 3073.40 samples/s lr: 1.83e-04  
[09/22 03:43:34] lb.utils.events INFO:  eta: 16:14:02  iteration: 4699/375342  consumed_samples: 4812800  total_loss: 5.994  time: 0.3333 s/iter  data_time: 0.2129 s/iter total_throughput: 3072.24 samples/s lr: 1.87e-04  
[09/22 03:44:08] lb.utils.events INFO:  eta: 16:10:45  iteration: 4799/375342  consumed_samples: 4915200  total_loss: 5.984  time: 0.3335 s/iter  data_time: 0.2114 s/iter total_throughput: 3070.78 samples/s lr: 1.91e-04  
[09/22 03:44:41] lb.utils.events INFO:  eta: 16:09:24  iteration: 4899/375342  consumed_samples: 5017600  total_loss: 5.977  time: 0.3335 s/iter  data_time: 0.2042 s/iter total_throughput: 3070.05 samples/s lr: 1.94e-04  
[09/22 03:45:16] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0004999
[09/22 03:45:16] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/22 03:45:16] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/22 03:45:18] lb.models.utils.graph_base INFO: Start compling the eval graph which may take some time. Please wait for a moment ...
[09/22 03:45:23] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0205 s/iter. Inference: 0.1834 s/iter. Eval: 0.0021 s/iter. Total: 0.2060 s/iter. ETA=0:00:07
[09/22 03:45:28] lb.evaluation.evaluator INFO: Inference done 28672/50000. Dataloading: 0.0498 s/iter. Inference: 0.2204 s/iter. Eval: 0.0020 s/iter. Total: 0.2723 s/iter. ETA=0:00:05
[09/22 03:45:33] lb.evaluation.evaluator INFO: Inference done 47104/50000. Dataloading: 0.0296 s/iter. Inference: 0.2447 s/iter. Eval: 0.0020 s/iter. Total: 0.2764 s/iter. ETA=0:00:00
[09/22 03:45:34] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/22 03:45:34] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.160068 (0.000243 s / iter per device, on 8 devices)
[09/22 03:45:34] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:10 (0.000217 s / iter per device, on 8 devices)
[09/22 03:45:34] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/22 03:45:34] lb.evaluation.utils INFO: copypaste: Acc@1=16.724
[09/22 03:45:34] lb.evaluation.utils INFO: copypaste: Acc@5=36.738
[09/22 03:45:34] lb.engine.hooks INFO: Saved first model at 16.72400 @ 4999 steps
[09/22 03:45:34] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/22 03:45:34] lb.utils.events INFO:  eta: 16:09:24  iteration: 4999/375342  consumed_samples: 5120000  total_loss: 5.955  time: 0.3337 s/iter  data_time: 0.2181 s/iter total_throughput: 3068.52 samples/s lr: 1.98e-04  
[09/22 03:46:05] lb.utils.events INFO:  eta: 16:15:42  iteration: 5099/375342  consumed_samples: 5222400  total_loss: 5.934  time: 0.3332 s/iter  data_time: 0.2531 s/iter total_throughput: 3073.00 samples/s lr: 2.02e-04  
[09/22 03:46:38] lb.utils.events INFO:  eta: 16:15:55  iteration: 5199/375342  consumed_samples: 5324800  total_loss: 5.91  time: 0.3332 s/iter  data_time: 0.2051 s/iter total_throughput: 3073.44 samples/s lr: 2.06e-04  
[09/22 03:47:11] lb.utils.events INFO:  eta: 16:15:50  iteration: 5299/375342  consumed_samples: 5427200  total_loss: 5.883  time: 0.3331 s/iter  data_time: 0.2123 s/iter total_throughput: 3074.15 samples/s lr: 2.10e-04  
[09/22 03:47:45] lb.utils.events INFO:  eta: 16:15:34  iteration: 5399/375342  consumed_samples: 5529600  total_loss: 5.883  time: 0.3331 s/iter  data_time: 0.2290 s/iter total_throughput: 3073.95 samples/s lr: 2.14e-04  
[09/22 03:48:18] lb.utils.events INFO:  eta: 16:18:28  iteration: 5499/375342  consumed_samples: 5632000  total_loss: 5.879  time: 0.3330 s/iter  data_time: 0.1937 s/iter total_throughput: 3074.84 samples/s lr: 2.18e-04  
[09/22 03:48:50] lb.utils.events INFO:  eta: 16:19:46  iteration: 5599/375342  consumed_samples: 5734400  total_loss: 5.857  time: 0.3329 s/iter  data_time: 0.1989 s/iter total_throughput: 3075.76 samples/s lr: 2.22e-04  
[09/22 03:49:23] lb.utils.events INFO:  eta: 16:15:26  iteration: 5699/375342  consumed_samples: 5836800  total_loss: 5.84  time: 0.3328 s/iter  data_time: 0.1980 s/iter total_throughput: 3076.57 samples/s lr: 2.26e-04  
[09/22 03:49:56] lb.utils.events INFO:  eta: 16:17:28  iteration: 5799/375342  consumed_samples: 5939200  total_loss: 5.812  time: 0.3328 s/iter  data_time: 0.2024 s/iter total_throughput: 3077.22 samples/s lr: 2.30e-04  
[09/22 03:50:29] lb.utils.events INFO:  eta: 16:18:08  iteration: 5899/375342  consumed_samples: 6041600  total_loss: 5.801  time: 0.3327 s/iter  data_time: 0.1965 s/iter total_throughput: 3078.12 samples/s lr: 2.34e-04  
[09/22 03:51:02] lb.utils.events INFO:  eta: 16:19:20  iteration: 5999/375342  consumed_samples: 6144000  total_loss: 5.801  time: 0.3327 s/iter  data_time: 0.2068 s/iter total_throughput: 3078.09 samples/s lr: 2.38e-04  
[09/22 03:51:35] lb.utils.events INFO:  eta: 16:12:21  iteration: 6099/375342  consumed_samples: 6246400  total_loss: 5.785  time: 0.3326 s/iter  data_time: 0.1911 s/iter total_throughput: 3078.73 samples/s lr: 2.42e-04  
[09/22 03:52:08] lb.utils.events INFO:  eta: 16:11:42  iteration: 6199/375342  consumed_samples: 6348800  total_loss: 5.773  time: 0.3326 s/iter  data_time: 0.2038 s/iter total_throughput: 3079.17 samples/s lr: 2.46e-04  
[09/22 03:52:42] lb.utils.events INFO:  eta: 16:08:47  iteration: 6299/375342  consumed_samples: 6451200  total_loss: 5.762  time: 0.3327 s/iter  data_time: 0.2072 s/iter total_throughput: 3078.22 samples/s lr: 2.50e-04  
[09/22 03:53:15] lb.utils.events INFO:  eta: 16:07:01  iteration: 6399/375342  consumed_samples: 6553600  total_loss: 5.748  time: 0.3326 s/iter  data_time: 0.2120 s/iter total_throughput: 3078.62 samples/s lr: 2.54e-04  
[09/22 03:53:48] lb.utils.events INFO:  eta: 16:06:40  iteration: 6499/375342  consumed_samples: 6656000  total_loss: 5.746  time: 0.3326 s/iter  data_time: 0.2113 s/iter total_throughput: 3078.75 samples/s lr: 2.58e-04  
[09/22 03:54:21] lb.utils.events INFO:  eta: 16:04:09  iteration: 6599/375342  consumed_samples: 6758400  total_loss: 5.734  time: 0.3326 s/iter  data_time: 0.2223 s/iter total_throughput: 3078.82 samples/s lr: 2.62e-04  
[09/22 03:54:55] lb.utils.events INFO:  eta: 16:04:57  iteration: 6699/375342  consumed_samples: 6860800  total_loss: 5.715  time: 0.3327 s/iter  data_time: 0.2128 s/iter total_throughput: 3078.24 samples/s lr: 2.66e-04  
[09/22 03:55:28] lb.utils.events INFO:  eta: 16:03:05  iteration: 6799/375342  consumed_samples: 6963200  total_loss: 5.699  time: 0.3326 s/iter  data_time: 0.1996 s/iter total_throughput: 3078.35 samples/s lr: 2.69e-04  
[09/22 03:56:02] lb.utils.events INFO:  eta: 15:59:59  iteration: 6899/375342  consumed_samples: 7065600  total_loss: 5.678  time: 0.3328 s/iter  data_time: 0.2194 s/iter total_throughput: 3077.37 samples/s lr: 2.73e-04  
[09/22 03:56:36] lb.utils.events INFO:  eta: 15:58:46  iteration: 6999/375342  consumed_samples: 7168000  total_loss: 5.67  time: 0.3328 s/iter  data_time: 0.2150 s/iter total_throughput: 3076.61 samples/s lr: 2.77e-04  
[09/22 03:57:09] lb.utils.events INFO:  eta: 15:59:15  iteration: 7099/375342  consumed_samples: 7270400  total_loss: 5.658  time: 0.3328 s/iter  data_time: 0.2116 s/iter total_throughput: 3076.56 samples/s lr: 2.81e-04  
[09/22 03:57:43] lb.utils.events INFO:  eta: 15:57:58  iteration: 7199/375342  consumed_samples: 7372800  total_loss: 5.656  time: 0.3328 s/iter  data_time: 0.2034 s/iter total_throughput: 3076.48 samples/s lr: 2.85e-04  
[09/22 03:58:16] lb.utils.events INFO:  eta: 15:57:51  iteration: 7299/375342  consumed_samples: 7475200  total_loss: 5.637  time: 0.3329 s/iter  data_time: 0.2202 s/iter total_throughput: 3075.94 samples/s lr: 2.89e-04  
[09/22 03:58:50] lb.utils.events INFO:  eta: 15:59:42  iteration: 7399/375342  consumed_samples: 7577600  total_loss: 5.609  time: 0.3329 s/iter  data_time: 0.2164 s/iter total_throughput: 3075.84 samples/s lr: 2.93e-04  
[09/22 03:59:23] lb.utils.events INFO:  eta: 16:02:18  iteration: 7499/375342  consumed_samples: 7680000  total_loss: 5.611  time: 0.3329 s/iter  data_time: 0.1971 s/iter total_throughput: 3076.17 samples/s lr: 2.97e-04  
[09/22 03:59:57] lb.utils.events INFO:  eta: 16:02:30  iteration: 7599/375342  consumed_samples: 7782400  total_loss: 5.602  time: 0.3330 s/iter  data_time: 0.2218 s/iter total_throughput: 3074.90 samples/s lr: 3.01e-04  
[09/22 04:00:31] lb.utils.events INFO:  eta: 16:01:55  iteration: 7699/375342  consumed_samples: 7884800  total_loss: 5.582  time: 0.3331 s/iter  data_time: 0.2127 s/iter total_throughput: 3074.49 samples/s lr: 3.05e-04  
[09/22 04:01:04] lb.utils.events INFO:  eta: 16:01:40  iteration: 7799/375342  consumed_samples: 7987200  total_loss: 5.578  time: 0.3331 s/iter  data_time: 0.2175 s/iter total_throughput: 3074.09 samples/s lr: 3.09e-04  
[09/22 04:01:38] lb.utils.events INFO:  eta: 16:04:41  iteration: 7899/375342  consumed_samples: 8089600  total_loss: 5.578  time: 0.3331 s/iter  data_time: 0.1976 s/iter total_throughput: 3073.94 samples/s lr: 3.13e-04  
[09/22 04:02:12] lb.utils.events INFO:  eta: 16:08:17  iteration: 7999/375342  consumed_samples: 8192000  total_loss: 5.551  time: 0.3332 s/iter  data_time: 0.2043 s/iter total_throughput: 3073.39 samples/s lr: 3.17e-04  
[09/22 04:02:45] lb.utils.events INFO:  eta: 16:08:33  iteration: 8099/375342  consumed_samples: 8294400  total_loss: 5.543  time: 0.3332 s/iter  data_time: 0.2051 s/iter total_throughput: 3073.02 samples/s lr: 3.21e-04  
[09/22 04:03:19] lb.utils.events INFO:  eta: 16:10:41  iteration: 8199/375342  consumed_samples: 8396800  total_loss: 5.549  time: 0.3333 s/iter  data_time: 0.2161 s/iter total_throughput: 3072.23 samples/s lr: 3.25e-04  
[09/22 04:03:53] lb.utils.events INFO:  eta: 16:11:07  iteration: 8299/375342  consumed_samples: 8499200  total_loss: 5.529  time: 0.3334 s/iter  data_time: 0.2021 s/iter total_throughput: 3071.69 samples/s lr: 3.29e-04  
[09/22 04:04:27] lb.utils.events INFO:  eta: 16:10:37  iteration: 8399/375342  consumed_samples: 8601600  total_loss: 5.52  time: 0.3335 s/iter  data_time: 0.2122 s/iter total_throughput: 3070.92 samples/s lr: 3.33e-04  
[09/22 04:05:01] lb.utils.events INFO:  eta: 16:08:20  iteration: 8499/375342  consumed_samples: 8704000  total_loss: 5.494  time: 0.3335 s/iter  data_time: 0.2109 s/iter total_throughput: 3070.69 samples/s lr: 3.37e-04  
[09/22 04:05:34] lb.utils.events INFO:  eta: 16:10:11  iteration: 8599/375342  consumed_samples: 8806400  total_loss: 5.494  time: 0.3335 s/iter  data_time: 0.2014 s/iter total_throughput: 3070.82 samples/s lr: 3.41e-04  
[09/22 04:06:08] lb.utils.events INFO:  eta: 16:09:32  iteration: 8699/375342  consumed_samples: 8908800  total_loss: 5.498  time: 0.3335 s/iter  data_time: 0.2114 s/iter total_throughput: 3070.16 samples/s lr: 3.45e-04  
[09/22 04:06:42] lb.utils.events INFO:  eta: 16:09:24  iteration: 8799/375342  consumed_samples: 9011200  total_loss: 5.473  time: 0.3336 s/iter  data_time: 0.2158 s/iter total_throughput: 3069.57 samples/s lr: 3.48e-04  
[09/22 04:07:16] lb.utils.events INFO:  eta: 16:06:45  iteration: 8899/375342  consumed_samples: 9113600  total_loss: 5.451  time: 0.3337 s/iter  data_time: 0.2272 s/iter total_throughput: 3068.79 samples/s lr: 3.52e-04  
[09/22 04:07:49] lb.utils.events INFO:  eta: 16:04:38  iteration: 8999/375342  consumed_samples: 9216000  total_loss: 5.438  time: 0.3337 s/iter  data_time: 0.1901 s/iter total_throughput: 3068.73 samples/s lr: 3.56e-04  
[09/22 04:08:23] lb.utils.events INFO:  eta: 16:01:24  iteration: 9099/375342  consumed_samples: 9318400  total_loss: 5.426  time: 0.3337 s/iter  data_time: 0.2020 s/iter total_throughput: 3068.44 samples/s lr: 3.60e-04  
[09/22 04:08:58] lb.utils.events INFO:  eta: 16:00:54  iteration: 9199/375342  consumed_samples: 9420800  total_loss: 5.428  time: 0.3338 s/iter  data_time: 0.2159 s/iter total_throughput: 3067.25 samples/s lr: 3.64e-04  
[09/22 04:09:32] lb.utils.events INFO:  eta: 16:00:49  iteration: 9299/375342  consumed_samples: 9523200  total_loss: 5.441  time: 0.3339 s/iter  data_time: 0.2051 s/iter total_throughput: 3066.38 samples/s lr: 3.68e-04  
[09/22 04:10:06] lb.utils.events INFO:  eta: 16:00:33  iteration: 9399/375342  consumed_samples: 9625600  total_loss: 5.438  time: 0.3340 s/iter  data_time: 0.2104 s/iter total_throughput: 3065.85 samples/s lr: 3.72e-04  
[09/22 04:10:40] lb.utils.events INFO:  eta: 16:02:00  iteration: 9499/375342  consumed_samples: 9728000  total_loss: 5.414  time: 0.3341 s/iter  data_time: 0.2047 s/iter total_throughput: 3065.30 samples/s lr: 3.76e-04  
[09/22 04:11:14] lb.utils.events INFO:  eta: 15:59:41  iteration: 9599/375342  consumed_samples: 9830400  total_loss: 5.393  time: 0.3341 s/iter  data_time: 0.2297 s/iter total_throughput: 3064.54 samples/s lr: 3.80e-04  
[09/22 04:11:48] lb.utils.events INFO:  eta: 16:00:30  iteration: 9699/375342  consumed_samples: 9932800  total_loss: 5.379  time: 0.3342 s/iter  data_time: 0.2180 s/iter total_throughput: 3064.06 samples/s lr: 3.84e-04  
[09/22 04:12:22] lb.utils.events INFO:  eta: 16:00:15  iteration: 9799/375342  consumed_samples: 10035200  total_loss: 5.379  time: 0.3343 s/iter  data_time: 0.2138 s/iter total_throughput: 3063.56 samples/s lr: 3.88e-04  
[09/22 04:12:56] lb.utils.events INFO:  eta: 15:58:52  iteration: 9899/375342  consumed_samples: 10137600  total_loss: 5.363  time: 0.3343 s/iter  data_time: 0.2098 s/iter total_throughput: 3062.87 samples/s lr: 3.92e-04  
[09/22 04:13:30] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0009999
[09/22 04:13:31] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/22 04:13:31] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/22 04:13:35] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0998 s/iter. Inference: 0.1564 s/iter. Eval: 0.0021 s/iter. Total: 0.2583 s/iter. ETA=0:00:09
[09/22 04:13:40] lb.evaluation.evaluator INFO: Inference done 29696/50000. Dataloading: 0.1091 s/iter. Inference: 0.1793 s/iter. Eval: 0.0020 s/iter. Total: 0.2905 s/iter. ETA=0:00:05
[09/22 04:13:45] lb.evaluation.evaluator INFO: Inference done 48128/50000. Dataloading: 0.0911 s/iter. Inference: 0.1920 s/iter. Eval: 0.0020 s/iter. Total: 0.2852 s/iter. ETA=0:00:00
[09/22 04:13:45] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/22 04:13:45] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.365212 (0.000247 s / iter per device, on 8 devices)
[09/22 04:13:45] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:08 (0.000169 s / iter per device, on 8 devices)
[09/22 04:13:45] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/22 04:13:45] lb.evaluation.utils INFO: copypaste: Acc@1=34.82
[09/22 04:13:45] lb.evaluation.utils INFO: copypaste: Acc@5=60.27400000000001
[09/22 04:13:45] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 34.82000, better than last best score 16.72400 @ iteration 4999.
[09/22 04:13:45] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/22 04:13:46] lb.utils.events INFO:  eta: 15:58:28  iteration: 9999/375342  consumed_samples: 10240000  total_loss: 5.348  time: 0.3344 s/iter  data_time: 0.2264 s/iter total_throughput: 3062.48 samples/s lr: 3.96e-04  
[09/22 04:14:19] lb.utils.events INFO:  eta: 16:01:09  iteration: 10099/375342  consumed_samples: 10342400  total_loss: 5.346  time: 0.3343 s/iter  data_time: 0.2213 s/iter total_throughput: 3063.38 samples/s lr: 4.00e-04  
[09/22 04:14:53] lb.utils.events INFO:  eta: 16:00:16  iteration: 10199/375342  consumed_samples: 10444800  total_loss: 5.332  time: 0.3343 s/iter  data_time: 0.2062 s/iter total_throughput: 3062.86 samples/s lr: 4.04e-04  
[09/22 04:15:27] lb.utils.events INFO:  eta: 15:58:58  iteration: 10299/375342  consumed_samples: 10547200  total_loss: 5.309  time: 0.3344 s/iter  data_time: 0.2049 s/iter total_throughput: 3062.30 samples/s lr: 4.08e-04  
[09/22 04:16:01] lb.utils.events INFO:  eta: 15:59:17  iteration: 10399/375342  consumed_samples: 10649600  total_loss: 5.305  time: 0.3344 s/iter  data_time: 0.2146 s/iter total_throughput: 3061.79 samples/s lr: 4.12e-04  
[09/22 04:16:35] lb.utils.events INFO:  eta: 15:59:27  iteration: 10499/375342  consumed_samples: 10752000  total_loss: 5.305  time: 0.3345 s/iter  data_time: 0.2125 s/iter total_throughput: 3061.29 samples/s lr: 4.16e-04  
[09/22 04:17:09] lb.utils.events INFO:  eta: 15:59:40  iteration: 10599/375342  consumed_samples: 10854400  total_loss: 5.303  time: 0.3346 s/iter  data_time: 0.2175 s/iter total_throughput: 3060.74 samples/s lr: 4.20e-04  
[09/22 04:17:43] lb.utils.events INFO:  eta: 16:00:07  iteration: 10699/375342  consumed_samples: 10956800  total_loss: 5.307  time: 0.3346 s/iter  data_time: 0.2026 s/iter total_throughput: 3060.66 samples/s lr: 4.24e-04  
[09/22 04:18:16] lb.utils.events INFO:  eta: 16:00:47  iteration: 10799/375342  consumed_samples: 11059200  total_loss: 5.281  time: 0.3346 s/iter  data_time: 0.2080 s/iter total_throughput: 3060.31 samples/s lr: 4.27e-04  
[09/22 04:18:50] lb.utils.events INFO:  eta: 16:04:37  iteration: 10899/375342  consumed_samples: 11161600  total_loss: 5.271  time: 0.3346 s/iter  data_time: 0.2107 s/iter total_throughput: 3059.95 samples/s lr: 4.31e-04  
[09/22 04:19:24] lb.utils.events INFO:  eta: 16:03:49  iteration: 10999/375342  consumed_samples: 11264000  total_loss: 5.275  time: 0.3347 s/iter  data_time: 0.2147 s/iter total_throughput: 3059.58 samples/s lr: 4.35e-04  
[09/22 04:19:58] lb.utils.events INFO:  eta: 16:02:14  iteration: 11099/375342  consumed_samples: 11366400  total_loss: 5.264  time: 0.3347 s/iter  data_time: 0.2206 s/iter total_throughput: 3059.42 samples/s lr: 4.39e-04  
[09/22 04:20:32] lb.utils.events INFO:  eta: 16:03:08  iteration: 11199/375342  consumed_samples: 11468800  total_loss: 5.246  time: 0.3347 s/iter  data_time: 0.2093 s/iter total_throughput: 3059.04 samples/s lr: 4.43e-04  
[09/22 04:21:06] lb.utils.events INFO:  eta: 16:04:39  iteration: 11299/375342  consumed_samples: 11571200  total_loss: 5.232  time: 0.3348 s/iter  data_time: 0.2094 s/iter total_throughput: 3058.58 samples/s lr: 4.47e-04  
[09/22 04:21:40] lb.utils.events INFO:  eta: 16:03:11  iteration: 11399/375342  consumed_samples: 11673600  total_loss: 5.225  time: 0.3348 s/iter  data_time: 0.2020 s/iter total_throughput: 3058.12 samples/s lr: 4.51e-04  
[09/22 04:22:14] lb.utils.events INFO:  eta: 16:02:31  iteration: 11499/375342  consumed_samples: 11776000  total_loss: 5.238  time: 0.3349 s/iter  data_time: 0.2057 s/iter total_throughput: 3057.75 samples/s lr: 4.55e-04  
[09/22 04:22:48] lb.utils.events INFO:  eta: 16:02:05  iteration: 11599/375342  consumed_samples: 11878400  total_loss: 5.23  time: 0.3349 s/iter  data_time: 0.2162 s/iter total_throughput: 3057.18 samples/s lr: 4.59e-04  
[09/22 04:23:22] lb.utils.events INFO:  eta: 16:00:11  iteration: 11699/375342  consumed_samples: 11980800  total_loss: 5.203  time: 0.3350 s/iter  data_time: 0.2126 s/iter total_throughput: 3056.59 samples/s lr: 4.63e-04  
[09/22 04:23:56] lb.utils.events INFO:  eta: 15:58:37  iteration: 11799/375342  consumed_samples: 12083200  total_loss: 5.188  time: 0.3350 s/iter  data_time: 0.2163 s/iter total_throughput: 3056.67 samples/s lr: 4.67e-04  
[09/22 04:24:30] lb.utils.events INFO:  eta: 15:57:44  iteration: 11899/375342  consumed_samples: 12185600  total_loss: 5.201  time: 0.3350 s/iter  data_time: 0.2219 s/iter total_throughput: 3056.27 samples/s lr: 4.71e-04  
[09/22 04:25:04] lb.utils.events INFO:  eta: 15:54:36  iteration: 11999/375342  consumed_samples: 12288000  total_loss: 5.197  time: 0.3351 s/iter  data_time: 0.2073 s/iter total_throughput: 3055.73 samples/s lr: 4.75e-04  
[09/22 04:25:38] lb.utils.events INFO:  eta: 15:53:42  iteration: 12099/375342  consumed_samples: 12390400  total_loss: 5.18  time: 0.3351 s/iter  data_time: 0.2171 s/iter total_throughput: 3055.38 samples/s lr: 4.79e-04  
[09/22 04:26:12] lb.utils.events INFO:  eta: 15:52:30  iteration: 12199/375342  consumed_samples: 12492800  total_loss: 5.182  time: 0.3352 s/iter  data_time: 0.2338 s/iter total_throughput: 3054.72 samples/s lr: 4.83e-04  
[09/22 04:26:47] lb.utils.events INFO:  eta: 15:51:44  iteration: 12299/375342  consumed_samples: 12595200  total_loss: 5.168  time: 0.3353 s/iter  data_time: 0.2181 s/iter total_throughput: 3054.25 samples/s lr: 4.87e-04  
[09/22 04:27:20] lb.utils.events INFO:  eta: 15:52:18  iteration: 12399/375342  consumed_samples: 12697600  total_loss: 5.162  time: 0.3353 s/iter  data_time: 0.2132 s/iter total_throughput: 3054.17 samples/s lr: 4.91e-04  
[09/22 04:27:54] lb.utils.events INFO:  eta: 15:51:13  iteration: 12499/375342  consumed_samples: 12800000  total_loss: 5.152  time: 0.3353 s/iter  data_time: 0.2154 s/iter total_throughput: 3053.94 samples/s lr: 4.95e-04  
[09/22 04:28:28] lb.utils.events INFO:  eta: 15:50:48  iteration: 12599/375342  consumed_samples: 12902400  total_loss: 5.148  time: 0.3354 s/iter  data_time: 0.2270 s/iter total_throughput: 3053.50 samples/s lr: 4.99e-04  
[09/22 04:29:03] lb.utils.events INFO:  eta: 15:52:15  iteration: 12699/375342  consumed_samples: 13004800  total_loss: 5.137  time: 0.3354 s/iter  data_time: 0.2193 s/iter total_throughput: 3052.99 samples/s lr: 5.02e-04  
[09/22 04:29:37] lb.utils.events INFO:  eta: 15:51:26  iteration: 12799/375342  consumed_samples: 13107200  total_loss: 5.121  time: 0.3355 s/iter  data_time: 0.2211 s/iter total_throughput: 3052.50 samples/s lr: 5.06e-04  
[09/22 04:30:11] lb.utils.events INFO:  eta: 15:50:24  iteration: 12899/375342  consumed_samples: 13209600  total_loss: 5.109  time: 0.3355 s/iter  data_time: 0.2050 s/iter total_throughput: 3052.14 samples/s lr: 5.10e-04  
[09/22 04:30:44] lb.utils.events INFO:  eta: 15:51:08  iteration: 12999/375342  consumed_samples: 13312000  total_loss: 5.1  time: 0.3355 s/iter  data_time: 0.2040 s/iter total_throughput: 3052.26 samples/s lr: 5.14e-04  
[09/22 04:31:19] lb.utils.events INFO:  eta: 15:50:22  iteration: 13099/375342  consumed_samples: 13414400  total_loss: 5.117  time: 0.3355 s/iter  data_time: 0.2224 s/iter total_throughput: 3051.74 samples/s lr: 5.18e-04  
[09/22 04:31:53] lb.utils.events INFO:  eta: 15:49:14  iteration: 13199/375342  consumed_samples: 13516800  total_loss: 5.117  time: 0.3356 s/iter  data_time: 0.2292 s/iter total_throughput: 3051.21 samples/s lr: 5.22e-04  
[09/22 04:32:27] lb.utils.events INFO:  eta: 15:48:33  iteration: 13299/375342  consumed_samples: 13619200  total_loss: 5.117  time: 0.3356 s/iter  data_time: 0.2070 s/iter total_throughput: 3051.06 samples/s lr: 5.26e-04  
[09/22 04:33:01] lb.utils.events INFO:  eta: 15:46:36  iteration: 13399/375342  consumed_samples: 13721600  total_loss: 5.109  time: 0.3357 s/iter  data_time: 0.2153 s/iter total_throughput: 3050.20 samples/s lr: 5.30e-04  
[09/22 04:33:36] lb.utils.events INFO:  eta: 15:47:48  iteration: 13499/375342  consumed_samples: 13824000  total_loss: 5.082  time: 0.3358 s/iter  data_time: 0.2041 s/iter total_throughput: 3049.87 samples/s lr: 5.34e-04  
[09/22 04:34:10] lb.utils.events INFO:  eta: 15:46:42  iteration: 13599/375342  consumed_samples: 13926400  total_loss: 5.072  time: 0.3358 s/iter  data_time: 0.2075 s/iter total_throughput: 3049.33 samples/s lr: 5.38e-04  
[09/22 04:34:44] lb.utils.events INFO:  eta: 15:47:18  iteration: 13699/375342  consumed_samples: 14028800  total_loss: 5.061  time: 0.3358 s/iter  data_time: 0.2128 s/iter total_throughput: 3049.16 samples/s lr: 5.42e-04  
[09/22 04:35:18] lb.utils.events INFO:  eta: 15:46:45  iteration: 13799/375342  consumed_samples: 14131200  total_loss: 5.053  time: 0.3358 s/iter  data_time: 0.2146 s/iter total_throughput: 3049.03 samples/s lr: 5.46e-04  
[09/22 04:35:52] lb.utils.events INFO:  eta: 15:46:24  iteration: 13899/375342  consumed_samples: 14233600  total_loss: 5.062  time: 0.3359 s/iter  data_time: 0.2201 s/iter total_throughput: 3048.65 samples/s lr: 5.50e-04  
[09/22 04:36:26] lb.utils.events INFO:  eta: 15:47:29  iteration: 13999/375342  consumed_samples: 14336000  total_loss: 5.051  time: 0.3359 s/iter  data_time: 0.2130 s/iter total_throughput: 3048.42 samples/s lr: 5.54e-04  
[09/22 04:37:00] lb.utils.events INFO:  eta: 15:47:14  iteration: 14099/375342  consumed_samples: 14438400  total_loss: 5.037  time: 0.3360 s/iter  data_time: 0.2127 s/iter total_throughput: 3047.84 samples/s lr: 5.58e-04  
[09/22 04:37:35] lb.utils.events INFO:  eta: 15:49:55  iteration: 14199/375342  consumed_samples: 14540800  total_loss: 5.039  time: 0.3360 s/iter  data_time: 0.2262 s/iter total_throughput: 3047.28 samples/s lr: 5.62e-04  
[09/22 04:38:10] lb.utils.events INFO:  eta: 15:49:07  iteration: 14299/375342  consumed_samples: 14643200  total_loss: 5.039  time: 0.3361 s/iter  data_time: 0.2204 s/iter total_throughput: 3046.47 samples/s lr: 5.66e-04  
[09/22 04:38:44] lb.utils.events INFO:  eta: 15:53:16  iteration: 14399/375342  consumed_samples: 14745600  total_loss: 5.055  time: 0.3362 s/iter  data_time: 0.2133 s/iter total_throughput: 3045.91 samples/s lr: 5.70e-04  
[09/22 04:39:19] lb.utils.events INFO:  eta: 15:52:41  iteration: 14499/375342  consumed_samples: 14848000  total_loss: 5.055  time: 0.3363 s/iter  data_time: 0.2217 s/iter total_throughput: 3045.31 samples/s lr: 5.74e-04  
[09/22 04:39:53] lb.utils.events INFO:  eta: 15:52:25  iteration: 14599/375342  consumed_samples: 14950400  total_loss: 5.008  time: 0.3363 s/iter  data_time: 0.2061 s/iter total_throughput: 3044.71 samples/s lr: 5.78e-04  
[09/22 04:40:28] lb.utils.events INFO:  eta: 15:49:27  iteration: 14699/375342  consumed_samples: 15052800  total_loss: 5.002  time: 0.3364 s/iter  data_time: 0.2223 s/iter total_throughput: 3043.88 samples/s lr: 5.81e-04  
[09/22 04:41:03] lb.utils.events INFO:  eta: 15:48:28  iteration: 14799/375342  consumed_samples: 15155200  total_loss: 5.004  time: 0.3365 s/iter  data_time: 0.2186 s/iter total_throughput: 3042.93 samples/s lr: 5.85e-04  
[09/22 04:41:38] lb.utils.events INFO:  eta: 15:49:55  iteration: 14899/375342  consumed_samples: 15257600  total_loss: 5.008  time: 0.3366 s/iter  data_time: 0.2394 s/iter total_throughput: 3042.28 samples/s lr: 5.89e-04  
[09/22 04:42:13] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0014999
[09/22 04:42:14] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/22 04:42:14] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/22 04:42:18] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0943 s/iter. Inference: 0.1554 s/iter. Eval: 0.0020 s/iter. Total: 0.2517 s/iter. ETA=0:00:09
[09/22 04:42:23] lb.evaluation.evaluator INFO: Inference done 29696/50000. Dataloading: 0.1193 s/iter. Inference: 0.1674 s/iter. Eval: 0.0020 s/iter. Total: 0.2888 s/iter. ETA=0:00:05
[09/22 04:42:28] lb.evaluation.evaluator INFO: Inference done 48128/50000. Dataloading: 0.0868 s/iter. Inference: 0.1972 s/iter. Eval: 0.0020 s/iter. Total: 0.2861 s/iter. ETA=0:00:00
[09/22 04:42:29] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/22 04:42:29] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.463154 (0.000249 s / iter per device, on 8 devices)
[09/22 04:42:29] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:08 (0.000174 s / iter per device, on 8 devices)
[09/22 04:42:29] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/22 04:42:29] lb.evaluation.utils INFO: copypaste: Acc@1=45.506
[09/22 04:42:29] lb.evaluation.utils INFO: copypaste: Acc@5=71.00800000000001
[09/22 04:42:29] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 45.50600, better than last best score 34.82000 @ iteration 9999.
[09/22 04:42:29] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/22 04:42:29] lb.utils.events INFO:  eta: 15:48:05  iteration: 14999/375342  consumed_samples: 15360000  total_loss: 5.02  time: 0.3367 s/iter  data_time: 0.2100 s/iter total_throughput: 3041.62 samples/s lr: 5.93e-04  
[09/22 04:43:02] lb.utils.events INFO:  eta: 15:52:36  iteration: 15099/375342  consumed_samples: 15462400  total_loss: 4.973  time: 0.3366 s/iter  data_time: 0.2416 s/iter total_throughput: 3042.27 samples/s lr: 5.97e-04  
[09/22 04:43:37] lb.utils.events INFO:  eta: 15:51:06  iteration: 15199/375342  consumed_samples: 15564800  total_loss: 4.961  time: 0.3367 s/iter  data_time: 0.2286 s/iter total_throughput: 3041.48 samples/s lr: 6.01e-04  
[09/22 04:44:12] lb.utils.events INFO:  eta: 15:51:03  iteration: 15299/375342  consumed_samples: 15667200  total_loss: 4.961  time: 0.3367 s/iter  data_time: 0.2200 s/iter total_throughput: 3040.88 samples/s lr: 6.05e-04  
[09/22 04:44:46] lb.utils.events INFO:  eta: 15:47:22  iteration: 15399/375342  consumed_samples: 15769600  total_loss: 4.977  time: 0.3368 s/iter  data_time: 0.2258 s/iter total_throughput: 3040.43 samples/s lr: 6.09e-04  
[09/22 04:45:21] lb.utils.events INFO:  eta: 15:47:27  iteration: 15499/375342  consumed_samples: 15872000  total_loss: 4.98  time: 0.3369 s/iter  data_time: 0.2311 s/iter total_throughput: 3039.89 samples/s lr: 6.13e-04  
[09/22 04:45:55] lb.utils.events INFO:  eta: 15:48:12  iteration: 15599/375342  consumed_samples: 15974400  total_loss: 4.961  time: 0.3369 s/iter  data_time: 0.2105 s/iter total_throughput: 3039.26 samples/s lr: 6.17e-04  
[09/22 04:46:30] lb.utils.events INFO:  eta: 15:47:22  iteration: 15699/375342  consumed_samples: 16076800  total_loss: 4.951  time: 0.3370 s/iter  data_time: 0.2304 s/iter total_throughput: 3038.66 samples/s lr: 6.21e-04  
[09/22 04:47:05] lb.utils.events INFO:  eta: 15:47:35  iteration: 15799/375342  consumed_samples: 16179200  total_loss: 4.941  time: 0.3371 s/iter  data_time: 0.2195 s/iter total_throughput: 3037.99 samples/s lr: 6.25e-04  
[09/22 04:47:40] lb.utils.events INFO:  eta: 15:46:50  iteration: 15899/375342  consumed_samples: 16281600  total_loss: 4.939  time: 0.3371 s/iter  data_time: 0.2346 s/iter total_throughput: 3037.23 samples/s lr: 6.29e-04  
[09/22 04:48:15] lb.utils.events INFO:  eta: 15:46:00  iteration: 15999/375342  consumed_samples: 16384000  total_loss: 4.953  time: 0.3372 s/iter  data_time: 0.2219 s/iter total_throughput: 3036.70 samples/s lr: 6.33e-04  
[09/22 04:48:50] lb.utils.events INFO:  eta: 15:38:55  iteration: 16099/375342  consumed_samples: 16486400  total_loss: 4.949  time: 0.3373 s/iter  data_time: 0.2097 s/iter total_throughput: 3035.91 samples/s lr: 6.37e-04  
[09/22 04:49:25] lb.utils.events INFO:  eta: 15:40:03  iteration: 16199/375342  consumed_samples: 16588800  total_loss: 4.945  time: 0.3374 s/iter  data_time: 0.2165 s/iter total_throughput: 3035.38 samples/s lr: 6.41e-04  
[09/22 04:49:59] lb.utils.events INFO:  eta: 15:41:47  iteration: 16299/375342  consumed_samples: 16691200  total_loss: 4.914  time: 0.3374 s/iter  data_time: 0.2145 s/iter total_throughput: 3034.82 samples/s lr: 6.45e-04  
[09/22 04:50:34] lb.utils.events INFO:  eta: 15:42:42  iteration: 16399/375342  consumed_samples: 16793600  total_loss: 4.869  time: 0.3375 s/iter  data_time: 0.2262 s/iter total_throughput: 3034.39 samples/s lr: 6.49e-04  
[09/22 04:51:09] lb.utils.events INFO:  eta: 15:39:22  iteration: 16499/375342  consumed_samples: 16896000  total_loss: 4.85  time: 0.3375 s/iter  data_time: 0.2298 s/iter total_throughput: 3033.76 samples/s lr: 6.53e-04  
[09/22 04:51:44] lb.utils.events INFO:  eta: 15:38:47  iteration: 16599/375342  consumed_samples: 16998400  total_loss: 4.883  time: 0.3376 s/iter  data_time: 0.2202 s/iter total_throughput: 3033.25 samples/s lr: 6.57e-04  
[09/22 04:52:18] lb.utils.events INFO:  eta: 15:40:44  iteration: 16699/375342  consumed_samples: 17100800  total_loss: 4.881  time: 0.3376 s/iter  data_time: 0.2084 s/iter total_throughput: 3032.89 samples/s lr: 6.60e-04  
[09/22 04:52:53] lb.utils.events INFO:  eta: 15:41:21  iteration: 16799/375342  consumed_samples: 17203200  total_loss: 4.883  time: 0.3377 s/iter  data_time: 0.2158 s/iter total_throughput: 3032.14 samples/s lr: 6.64e-04  
[09/22 04:53:28] lb.utils.events INFO:  eta: 15:41:23  iteration: 16899/375342  consumed_samples: 17305600  total_loss: 4.875  time: 0.3378 s/iter  data_time: 0.2296 s/iter total_throughput: 3031.66 samples/s lr: 6.68e-04  
[09/22 04:54:03] lb.utils.events INFO:  eta: 15:37:44  iteration: 16999/375342  consumed_samples: 17408000  total_loss: 4.859  time: 0.3378 s/iter  data_time: 0.2222 s/iter total_throughput: 3031.21 samples/s lr: 6.72e-04  
[09/22 04:54:37] lb.utils.events INFO:  eta: 15:37:22  iteration: 17099/375342  consumed_samples: 17510400  total_loss: 4.867  time: 0.3379 s/iter  data_time: 0.2177 s/iter total_throughput: 3030.69 samples/s lr: 6.76e-04  
[09/22 04:55:12] lb.utils.events INFO:  eta: 15:34:51  iteration: 17199/375342  consumed_samples: 17612800  total_loss: 4.861  time: 0.3380 s/iter  data_time: 0.2417 s/iter total_throughput: 3030.01 samples/s lr: 6.80e-04  
[09/22 04:55:47] lb.utils.events INFO:  eta: 15:33:37  iteration: 17299/375342  consumed_samples: 17715200  total_loss: 4.863  time: 0.3380 s/iter  data_time: 0.2074 s/iter total_throughput: 3029.59 samples/s lr: 6.84e-04  
[09/22 04:56:22] lb.utils.events INFO:  eta: 15:33:34  iteration: 17399/375342  consumed_samples: 17817600  total_loss: 4.848  time: 0.3381 s/iter  data_time: 0.2220 s/iter total_throughput: 3029.03 samples/s lr: 6.88e-04  
[09/22 04:56:57] lb.utils.events INFO:  eta: 15:33:20  iteration: 17499/375342  consumed_samples: 17920000  total_loss: 4.842  time: 0.3381 s/iter  data_time: 0.2255 s/iter total_throughput: 3028.49 samples/s lr: 6.92e-04  
[09/22 04:57:32] lb.utils.events INFO:  eta: 15:32:29  iteration: 17599/375342  consumed_samples: 18022400  total_loss: 4.828  time: 0.3382 s/iter  data_time: 0.2286 s/iter total_throughput: 3027.97 samples/s lr: 6.96e-04  
[09/22 04:58:07] lb.utils.events INFO:  eta: 15:31:23  iteration: 17699/375342  consumed_samples: 18124800  total_loss: 4.82  time: 0.3382 s/iter  data_time: 0.2046 s/iter total_throughput: 3027.36 samples/s lr: 7.00e-04  
[09/22 04:58:42] lb.utils.events INFO:  eta: 15:28:12  iteration: 17799/375342  consumed_samples: 18227200  total_loss: 4.822  time: 0.3383 s/iter  data_time: 0.2323 s/iter total_throughput: 3026.82 samples/s lr: 7.04e-04  
[09/22 04:59:17] lb.utils.events INFO:  eta: 15:25:20  iteration: 17899/375342  consumed_samples: 18329600  total_loss: 4.801  time: 0.3384 s/iter  data_time: 0.2405 s/iter total_throughput: 3026.19 samples/s lr: 7.08e-04  
[09/22 04:59:51] lb.utils.events INFO:  eta: 15:25:52  iteration: 17999/375342  consumed_samples: 18432000  total_loss: 4.807  time: 0.3384 s/iter  data_time: 0.2223 s/iter total_throughput: 3025.84 samples/s lr: 7.12e-04  
[09/22 05:00:26] lb.utils.events INFO:  eta: 15:26:49  iteration: 18099/375342  consumed_samples: 18534400  total_loss: 4.82  time: 0.3385 s/iter  data_time: 0.2125 s/iter total_throughput: 3025.54 samples/s lr: 7.16e-04  
[09/22 05:01:01] lb.utils.events INFO:  eta: 15:26:44  iteration: 18199/375342  consumed_samples: 18636800  total_loss: 4.811  time: 0.3385 s/iter  data_time: 0.2375 s/iter total_throughput: 3024.83 samples/s lr: 7.20e-04  
[09/22 05:01:35] lb.utils.events INFO:  eta: 15:27:02  iteration: 18299/375342  consumed_samples: 18739200  total_loss: 4.805  time: 0.3386 s/iter  data_time: 0.2107 s/iter total_throughput: 3024.62 samples/s lr: 7.24e-04  
[09/22 05:02:10] lb.utils.events INFO:  eta: 15:26:39  iteration: 18399/375342  consumed_samples: 18841600  total_loss: 4.787  time: 0.3386 s/iter  data_time: 0.2052 s/iter total_throughput: 3024.36 samples/s lr: 7.28e-04  
[09/22 05:02:44] lb.utils.events INFO:  eta: 15:26:05  iteration: 18499/375342  consumed_samples: 18944000  total_loss: 4.793  time: 0.3386 s/iter  data_time: 0.2178 s/iter total_throughput: 3024.01 samples/s lr: 7.32e-04  
[09/22 05:03:19] lb.utils.events INFO:  eta: 15:27:27  iteration: 18599/375342  consumed_samples: 19046400  total_loss: 4.801  time: 0.3387 s/iter  data_time: 0.2151 s/iter total_throughput: 3023.53 samples/s lr: 7.35e-04  
[09/22 05:03:54] lb.utils.events INFO:  eta: 15:27:44  iteration: 18699/375342  consumed_samples: 19148800  total_loss: 4.791  time: 0.3387 s/iter  data_time: 0.2169 s/iter total_throughput: 3023.27 samples/s lr: 7.39e-04  
[09/22 05:04:28] lb.utils.events INFO:  eta: 15:32:28  iteration: 18799/375342  consumed_samples: 19251200  total_loss: 4.781  time: 0.3387 s/iter  data_time: 0.2021 s/iter total_throughput: 3023.23 samples/s lr: 7.43e-04  
[09/22 05:05:03] lb.utils.events INFO:  eta: 15:34:40  iteration: 18899/375342  consumed_samples: 19353600  total_loss: 4.758  time: 0.3388 s/iter  data_time: 0.2269 s/iter total_throughput: 3022.63 samples/s lr: 7.47e-04  
[09/22 05:05:37] lb.utils.events INFO:  eta: 15:35:35  iteration: 18999/375342  consumed_samples: 19456000  total_loss: 4.746  time: 0.3388 s/iter  data_time: 0.2104 s/iter total_throughput: 3022.53 samples/s lr: 7.51e-04  
[09/22 05:06:11] lb.utils.events INFO:  eta: 15:34:18  iteration: 19099/375342  consumed_samples: 19558400  total_loss: 4.768  time: 0.3388 s/iter  data_time: 0.2264 s/iter total_throughput: 3022.24 samples/s lr: 7.55e-04  
[09/22 05:06:46] lb.utils.events INFO:  eta: 15:35:10  iteration: 19199/375342  consumed_samples: 19660800  total_loss: 4.766  time: 0.3388 s/iter  data_time: 0.2213 s/iter total_throughput: 3022.00 samples/s lr: 7.59e-04  
[09/22 05:07:20] lb.utils.events INFO:  eta: 15:36:07  iteration: 19299/375342  consumed_samples: 19763200  total_loss: 4.773  time: 0.3389 s/iter  data_time: 0.2182 s/iter total_throughput: 3021.64 samples/s lr: 7.63e-04  
[09/22 05:07:55] lb.utils.events INFO:  eta: 15:36:16  iteration: 19399/375342  consumed_samples: 19865600  total_loss: 4.783  time: 0.3389 s/iter  data_time: 0.2109 s/iter total_throughput: 3021.46 samples/s lr: 7.67e-04  
[09/22 05:08:29] lb.utils.events INFO:  eta: 15:37:38  iteration: 19499/375342  consumed_samples: 19968000  total_loss: 4.76  time: 0.3389 s/iter  data_time: 0.2177 s/iter total_throughput: 3021.42 samples/s lr: 7.71e-04  
[09/22 05:09:03] lb.utils.events INFO:  eta: 15:36:54  iteration: 19599/375342  consumed_samples: 20070400  total_loss: 4.742  time: 0.3389 s/iter  data_time: 0.2177 s/iter total_throughput: 3021.19 samples/s lr: 7.75e-04  
[09/22 05:09:37] lb.utils.events INFO:  eta: 15:37:07  iteration: 19699/375342  consumed_samples: 20172800  total_loss: 4.738  time: 0.3390 s/iter  data_time: 0.2194 s/iter total_throughput: 3021.01 samples/s lr: 7.79e-04  
[09/22 05:10:11] lb.utils.events INFO:  eta: 15:35:03  iteration: 19799/375342  consumed_samples: 20275200  total_loss: 4.744  time: 0.3390 s/iter  data_time: 0.2189 s/iter total_throughput: 3020.96 samples/s lr: 7.83e-04  
[09/22 05:10:46] lb.utils.events INFO:  eta: 15:33:27  iteration: 19899/375342  consumed_samples: 20377600  total_loss: 4.754  time: 0.3390 s/iter  data_time: 0.2270 s/iter total_throughput: 3020.82 samples/s lr: 7.87e-04  
[09/22 05:11:20] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0019999
[09/22 05:11:21] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/22 05:11:21] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/22 05:11:25] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0520 s/iter. Inference: 0.2040 s/iter. Eval: 0.0020 s/iter. Total: 0.2580 s/iter. ETA=0:00:09
[09/22 05:11:30] lb.evaluation.evaluator INFO: Inference done 28672/50000. Dataloading: 0.0361 s/iter. Inference: 0.2497 s/iter. Eval: 0.0020 s/iter. Total: 0.2878 s/iter. ETA=0:00:05
[09/22 05:11:35] lb.evaluation.evaluator INFO: Inference done 46080/50000. Dataloading: 0.0209 s/iter. Inference: 0.2716 s/iter. Eval: 0.0020 s/iter. Total: 0.2946 s/iter. ETA=0:00:00
[09/22 05:11:36] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/22 05:11:36] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.736557 (0.000255 s / iter per device, on 8 devices)
[09/22 05:11:36] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:11 (0.000236 s / iter per device, on 8 devices)
[09/22 05:11:36] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/22 05:11:36] lb.evaluation.utils INFO: copypaste: Acc@1=52.44799999999999
[09/22 05:11:36] lb.evaluation.utils INFO: copypaste: Acc@5=77.538
[09/22 05:11:36] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 52.44800, better than last best score 45.50600 @ iteration 14999.
[09/22 05:11:36] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/22 05:11:37] lb.utils.events INFO:  eta: 15:32:52  iteration: 19999/375342  consumed_samples: 20480000  total_loss: 4.729  time: 0.3390 s/iter  data_time: 0.2262 s/iter total_throughput: 3020.65 samples/s lr: 7.91e-04  
[09/22 05:12:09] lb.utils.events INFO:  eta: 15:38:00  iteration: 20099/375342  consumed_samples: 20582400  total_loss: 4.719  time: 0.3389 s/iter  data_time: 0.2057 s/iter total_throughput: 3021.47 samples/s lr: 7.95e-04  
[09/22 05:12:43] lb.utils.events INFO:  eta: 15:36:02  iteration: 20199/375342  consumed_samples: 20684800  total_loss: 4.727  time: 0.3389 s/iter  data_time: 0.2113 s/iter total_throughput: 3021.13 samples/s lr: 7.99e-04  
[09/22 05:13:18] lb.utils.events INFO:  eta: 15:37:15  iteration: 20299/375342  consumed_samples: 20787200  total_loss: 4.746  time: 0.3390 s/iter  data_time: 0.2150 s/iter total_throughput: 3020.88 samples/s lr: 8.03e-04  
[09/22 05:13:52] lb.utils.events INFO:  eta: 15:35:11  iteration: 20399/375342  consumed_samples: 20889600  total_loss: 4.73  time: 0.3390 s/iter  data_time: 0.2339 s/iter total_throughput: 3020.55 samples/s lr: 8.07e-04  
[09/22 05:14:27] lb.utils.events INFO:  eta: 15:32:20  iteration: 20499/375342  consumed_samples: 20992000  total_loss: 4.707  time: 0.3391 s/iter  data_time: 0.2415 s/iter total_throughput: 3020.08 samples/s lr: 8.11e-04  
[09/22 05:15:02] lb.utils.events INFO:  eta: 15:31:02  iteration: 20599/375342  consumed_samples: 21094400  total_loss: 4.717  time: 0.3391 s/iter  data_time: 0.2316 s/iter total_throughput: 3019.83 samples/s lr: 8.14e-04  
[09/22 05:15:36] lb.utils.events INFO:  eta: 15:30:25  iteration: 20699/375342  consumed_samples: 21196800  total_loss: 4.707  time: 0.3391 s/iter  data_time: 0.2038 s/iter total_throughput: 3019.77 samples/s lr: 8.18e-04  
[09/22 05:16:11] lb.utils.events INFO:  eta: 15:29:49  iteration: 20799/375342  consumed_samples: 21299200  total_loss: 4.703  time: 0.3391 s/iter  data_time: 0.2309 s/iter total_throughput: 3019.42 samples/s lr: 8.22e-04  
[09/22 05:16:45] lb.utils.events INFO:  eta: 15:29:33  iteration: 20899/375342  consumed_samples: 21401600  total_loss: 4.713  time: 0.3392 s/iter  data_time: 0.2033 s/iter total_throughput: 3019.28 samples/s lr: 8.26e-04  
[09/22 05:17:19] lb.utils.events INFO:  eta: 15:29:04  iteration: 20999/375342  consumed_samples: 21504000  total_loss: 4.719  time: 0.3392 s/iter  data_time: 0.2107 s/iter total_throughput: 3019.12 samples/s lr: 8.30e-04  
[09/22 05:17:54] lb.utils.events INFO:  eta: 15:25:20  iteration: 21099/375342  consumed_samples: 21606400  total_loss: 4.719  time: 0.3392 s/iter  data_time: 0.2254 s/iter total_throughput: 3018.95 samples/s lr: 8.34e-04  
[09/22 05:18:27] lb.utils.events INFO:  eta: 15:27:32  iteration: 21199/375342  consumed_samples: 21708800  total_loss: 4.705  time: 0.3392 s/iter  data_time: 0.2187 s/iter total_throughput: 3019.04 samples/s lr: 8.38e-04  
[09/22 05:19:02] lb.utils.events INFO:  eta: 15:26:08  iteration: 21299/375342  consumed_samples: 21811200  total_loss: 4.666  time: 0.3392 s/iter  data_time: 0.2197 s/iter total_throughput: 3018.85 samples/s lr: 8.42e-04  
[09/22 05:19:36] lb.utils.events INFO:  eta: 15:26:45  iteration: 21399/375342  consumed_samples: 21913600  total_loss: 4.664  time: 0.3392 s/iter  data_time: 0.2125 s/iter total_throughput: 3018.87 samples/s lr: 8.46e-04  
[09/22 05:20:10] lb.utils.events INFO:  eta: 15:27:45  iteration: 21499/375342  consumed_samples: 22016000  total_loss: 4.688  time: 0.3392 s/iter  data_time: 0.2244 s/iter total_throughput: 3018.63 samples/s lr: 8.50e-04  
[09/22 05:20:44] lb.utils.events INFO:  eta: 15:28:24  iteration: 21599/375342  consumed_samples: 22118400  total_loss: 4.672  time: 0.3392 s/iter  data_time: 0.2091 s/iter total_throughput: 3018.59 samples/s lr: 8.54e-04  
[09/22 05:21:19] lb.utils.events INFO:  eta: 15:27:14  iteration: 21699/375342  consumed_samples: 22220800  total_loss: 4.672  time: 0.3393 s/iter  data_time: 0.2050 s/iter total_throughput: 3018.37 samples/s lr: 8.58e-04  
[09/22 05:21:53] lb.utils.events INFO:  eta: 15:27:56  iteration: 21799/375342  consumed_samples: 22323200  total_loss: 4.697  time: 0.3393 s/iter  data_time: 0.2107 s/iter total_throughput: 3018.25 samples/s lr: 8.62e-04  
[09/22 05:22:28] lb.utils.events INFO:  eta: 15:28:45  iteration: 21899/375342  consumed_samples: 22425600  total_loss: 4.676  time: 0.3393 s/iter  data_time: 0.2231 s/iter total_throughput: 3017.95 samples/s lr: 8.66e-04  
[09/22 05:23:01] lb.utils.events INFO:  eta: 15:29:00  iteration: 21999/375342  consumed_samples: 22528000  total_loss: 4.686  time: 0.3393 s/iter  data_time: 0.2145 s/iter total_throughput: 3017.93 samples/s lr: 8.70e-04  
[09/22 05:23:36] lb.utils.events INFO:  eta: 15:28:52  iteration: 22099/375342  consumed_samples: 22630400  total_loss: 4.674  time: 0.3393 s/iter  data_time: 0.2148 s/iter total_throughput: 3017.78 samples/s lr: 8.74e-04  
[09/22 05:24:10] lb.utils.events INFO:  eta: 15:26:29  iteration: 22199/375342  consumed_samples: 22732800  total_loss: 4.652  time: 0.3393 s/iter  data_time: 0.2182 s/iter total_throughput: 3017.62 samples/s lr: 8.78e-04  
[09/22 05:24:44] lb.utils.events INFO:  eta: 15:28:30  iteration: 22299/375342  consumed_samples: 22835200  total_loss: 4.652  time: 0.3394 s/iter  data_time: 0.2047 s/iter total_throughput: 3017.51 samples/s lr: 8.82e-04  
[09/22 05:25:19] lb.utils.events INFO:  eta: 15:26:20  iteration: 22399/375342  consumed_samples: 22937600  total_loss: 4.652  time: 0.3394 s/iter  data_time: 0.2224 s/iter total_throughput: 3017.36 samples/s lr: 8.86e-04  
[09/22 05:25:53] lb.utils.events INFO:  eta: 15:25:24  iteration: 22499/375342  consumed_samples: 23040000  total_loss: 4.652  time: 0.3394 s/iter  data_time: 0.2073 s/iter total_throughput: 3017.07 samples/s lr: 8.90e-04  
[09/22 05:26:27] lb.utils.events INFO:  eta: 15:23:56  iteration: 22599/375342  consumed_samples: 23142400  total_loss: 4.637  time: 0.3394 s/iter  data_time: 0.2052 s/iter total_throughput: 3017.01 samples/s lr: 8.93e-04  
[09/22 05:27:01] lb.utils.events INFO:  eta: 15:27:20  iteration: 22699/375342  consumed_samples: 23244800  total_loss: 4.645  time: 0.3394 s/iter  data_time: 0.2094 s/iter total_throughput: 3017.10 samples/s lr: 8.97e-04  
[09/22 05:27:35] lb.utils.events INFO:  eta: 15:25:49  iteration: 22799/375342  consumed_samples: 23347200  total_loss: 4.641  time: 0.3394 s/iter  data_time: 0.2203 s/iter total_throughput: 3016.97 samples/s lr: 9.01e-04  
[09/22 05:28:10] lb.utils.events INFO:  eta: 15:25:26  iteration: 22899/375342  consumed_samples: 23449600  total_loss: 4.625  time: 0.3394 s/iter  data_time: 0.2141 s/iter total_throughput: 3016.92 samples/s lr: 9.05e-04  
[09/22 05:28:44] lb.utils.events INFO:  eta: 15:23:42  iteration: 22999/375342  consumed_samples: 23552000  total_loss: 4.625  time: 0.3394 s/iter  data_time: 0.2263 s/iter total_throughput: 3016.69 samples/s lr: 9.09e-04  
[09/22 05:29:18] lb.utils.events INFO:  eta: 15:23:02  iteration: 23099/375342  consumed_samples: 23654400  total_loss: 4.625  time: 0.3395 s/iter  data_time: 0.2208 s/iter total_throughput: 3016.54 samples/s lr: 9.13e-04  
[09/22 05:29:53] lb.utils.events INFO:  eta: 15:20:41  iteration: 23199/375342  consumed_samples: 23756800  total_loss: 4.623  time: 0.3395 s/iter  data_time: 0.2247 s/iter total_throughput: 3016.39 samples/s lr: 9.17e-04  
[09/22 05:30:27] lb.utils.events INFO:  eta: 15:20:43  iteration: 23299/375342  consumed_samples: 23859200  total_loss: 4.605  time: 0.3395 s/iter  data_time: 0.2137 s/iter total_throughput: 3016.38 samples/s lr: 9.21e-04  
[09/22 05:31:01] lb.utils.events INFO:  eta: 15:22:47  iteration: 23399/375342  consumed_samples: 23961600  total_loss: 4.605  time: 0.3395 s/iter  data_time: 0.2199 s/iter total_throughput: 3016.20 samples/s lr: 9.25e-04  
[09/22 05:31:36] lb.utils.events INFO:  eta: 15:23:46  iteration: 23499/375342  consumed_samples: 24064000  total_loss: 4.607  time: 0.3395 s/iter  data_time: 0.2151 s/iter total_throughput: 3015.99 samples/s lr: 9.29e-04  
[09/22 05:32:10] lb.utils.events INFO:  eta: 15:23:45  iteration: 23599/375342  consumed_samples: 24166400  total_loss: 4.611  time: 0.3395 s/iter  data_time: 0.2101 s/iter total_throughput: 3015.93 samples/s lr: 9.33e-04  
[09/22 05:32:44] lb.utils.events INFO:  eta: 15:23:35  iteration: 23699/375342  consumed_samples: 24268800  total_loss: 4.6  time: 0.3395 s/iter  data_time: 0.2168 s/iter total_throughput: 3015.98 samples/s lr: 9.37e-04  
[09/22 05:33:18] lb.utils.events INFO:  eta: 15:23:32  iteration: 23799/375342  consumed_samples: 24371200  total_loss: 4.602  time: 0.3395 s/iter  data_time: 0.2228 s/iter total_throughput: 3015.96 samples/s lr: 9.41e-04  
[09/22 05:33:51] lb.utils.events INFO:  eta: 15:24:28  iteration: 23899/375342  consumed_samples: 24473600  total_loss: 4.598  time: 0.3395 s/iter  data_time: 0.2042 s/iter total_throughput: 3016.06 samples/s lr: 9.45e-04  
[09/22 05:34:25] lb.utils.events INFO:  eta: 15:28:10  iteration: 23999/375342  consumed_samples: 24576000  total_loss: 4.59  time: 0.3395 s/iter  data_time: 0.2221 s/iter total_throughput: 3016.10 samples/s lr: 9.49e-04  
[09/22 05:34:59] lb.utils.events INFO:  eta: 15:26:16  iteration: 24099/375342  consumed_samples: 24678400  total_loss: 4.582  time: 0.3395 s/iter  data_time: 0.2153 s/iter total_throughput: 3015.98 samples/s lr: 9.53e-04  
[09/22 05:35:33] lb.utils.events INFO:  eta: 15:28:48  iteration: 24199/375342  consumed_samples: 24780800  total_loss: 4.572  time: 0.3395 s/iter  data_time: 0.2256 s/iter total_throughput: 3016.08 samples/s lr: 9.57e-04  
[09/22 05:36:07] lb.utils.events INFO:  eta: 15:28:11  iteration: 24299/375342  consumed_samples: 24883200  total_loss: 4.566  time: 0.3395 s/iter  data_time: 0.2141 s/iter total_throughput: 3016.16 samples/s lr: 9.61e-04  
[09/22 05:36:41] lb.utils.events INFO:  eta: 15:27:55  iteration: 24399/375342  consumed_samples: 24985600  total_loss: 4.586  time: 0.3395 s/iter  data_time: 0.2199 s/iter total_throughput: 3016.04 samples/s lr: 9.65e-04  
[09/22 05:37:15] lb.utils.events INFO:  eta: 15:26:34  iteration: 24499/375342  consumed_samples: 25088000  total_loss: 4.598  time: 0.3395 s/iter  data_time: 0.2102 s/iter total_throughput: 3015.95 samples/s lr: 9.68e-04  
[09/22 05:37:49] lb.utils.events INFO:  eta: 15:26:44  iteration: 24599/375342  consumed_samples: 25190400  total_loss: 4.578  time: 0.3395 s/iter  data_time: 0.2191 s/iter total_throughput: 3015.91 samples/s lr: 9.72e-04  
[09/22 05:38:24] lb.utils.events INFO:  eta: 15:25:20  iteration: 24699/375342  consumed_samples: 25292800  total_loss: 4.586  time: 0.3395 s/iter  data_time: 0.2159 s/iter total_throughput: 3015.79 samples/s lr: 9.76e-04  
[09/22 05:38:58] lb.utils.events INFO:  eta: 15:25:04  iteration: 24799/375342  consumed_samples: 25395200  total_loss: 4.592  time: 0.3395 s/iter  data_time: 0.2046 s/iter total_throughput: 3015.82 samples/s lr: 9.80e-04  
[09/22 05:39:32] lb.utils.events INFO:  eta: 15:23:32  iteration: 24899/375342  consumed_samples: 25497600  total_loss: 4.572  time: 0.3395 s/iter  data_time: 0.2144 s/iter total_throughput: 3015.79 samples/s lr: 9.84e-04  
[09/22 05:40:06] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0024999
[09/22 05:40:06] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/22 05:40:06] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/22 05:40:10] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0837 s/iter. Inference: 0.1679 s/iter. Eval: 0.0018 s/iter. Total: 0.2535 s/iter. ETA=0:00:09
[09/22 05:40:16] lb.evaluation.evaluator INFO: Inference done 28672/50000. Dataloading: 0.0677 s/iter. Inference: 0.2201 s/iter. Eval: 0.0019 s/iter. Total: 0.2899 s/iter. ETA=0:00:05
[09/22 05:40:21] lb.evaluation.evaluator INFO: Inference done 45056/50000. Dataloading: 0.0438 s/iter. Inference: 0.2568 s/iter. Eval: 0.0019 s/iter. Total: 0.3027 s/iter. ETA=0:00:01
[09/22 05:40:22] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/22 05:40:22] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.985298 (0.000260 s / iter per device, on 8 devices)
[09/22 05:40:22] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:11 (0.000224 s / iter per device, on 8 devices)
[09/22 05:40:22] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/22 05:40:22] lb.evaluation.utils INFO: copypaste: Acc@1=55.96
[09/22 05:40:22] lb.evaluation.utils INFO: copypaste: Acc@5=80.464
[09/22 05:40:22] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 55.96000, better than last best score 52.44800 @ iteration 19999.
[09/22 05:40:22] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/22 05:40:23] lb.utils.events INFO:  eta: 15:20:10  iteration: 24999/375342  consumed_samples: 25600000  total_loss: 4.566  time: 0.3395 s/iter  data_time: 0.2182 s/iter total_throughput: 3015.77 samples/s lr: 9.88e-04  
[09/22 05:40:55] lb.utils.events INFO:  eta: 15:25:30  iteration: 25099/375342  consumed_samples: 25702400  total_loss: 4.559  time: 0.3395 s/iter  data_time: 0.2196 s/iter total_throughput: 3016.43 samples/s lr: 9.89e-04  
[09/22 05:41:29] lb.utils.events INFO:  eta: 15:21:46  iteration: 25199/375342  consumed_samples: 25804800  total_loss: 4.543  time: 0.3395 s/iter  data_time: 0.2106 s/iter total_throughput: 3016.42 samples/s lr: 9.89e-04  
[09/22 05:42:03] lb.utils.events INFO:  eta: 15:20:04  iteration: 25299/375342  consumed_samples: 25907200  total_loss: 4.557  time: 0.3395 s/iter  data_time: 0.2170 s/iter total_throughput: 3016.40 samples/s lr: 9.89e-04  
[09/22 05:42:37] lb.utils.events INFO:  eta: 15:19:48  iteration: 25399/375342  consumed_samples: 26009600  total_loss: 4.539  time: 0.3395 s/iter  data_time: 0.2183 s/iter total_throughput: 3016.35 samples/s lr: 9.89e-04  
[09/22 05:43:11] lb.utils.events INFO:  eta: 15:20:05  iteration: 25499/375342  consumed_samples: 26112000  total_loss: 4.531  time: 0.3395 s/iter  data_time: 0.2227 s/iter total_throughput: 3016.31 samples/s lr: 9.89e-04  
[09/22 05:43:45] lb.utils.events INFO:  eta: 15:20:04  iteration: 25599/375342  consumed_samples: 26214400  total_loss: 4.531  time: 0.3395 s/iter  data_time: 0.2236 s/iter total_throughput: 3016.29 samples/s lr: 9.89e-04  
[09/22 05:44:19] lb.utils.events INFO:  eta: 15:20:53  iteration: 25699/375342  consumed_samples: 26316800  total_loss: 4.541  time: 0.3395 s/iter  data_time: 0.2148 s/iter total_throughput: 3016.25 samples/s lr: 9.89e-04  
[09/22 05:44:53] lb.utils.events INFO:  eta: 15:22:16  iteration: 25799/375342  consumed_samples: 26419200  total_loss: 4.539  time: 0.3395 s/iter  data_time: 0.2090 s/iter total_throughput: 3016.34 samples/s lr: 9.89e-04  
[09/22 05:45:27] lb.utils.events INFO:  eta: 15:21:13  iteration: 25899/375342  consumed_samples: 26521600  total_loss: 4.531  time: 0.3395 s/iter  data_time: 0.2189 s/iter total_throughput: 3016.32 samples/s lr: 9.88e-04  
[09/22 05:46:01] lb.utils.events INFO:  eta: 15:21:13  iteration: 25999/375342  consumed_samples: 26624000  total_loss: 4.523  time: 0.3395 s/iter  data_time: 0.2164 s/iter total_throughput: 3016.17 samples/s lr: 9.88e-04  
[09/22 05:46:35] lb.utils.events INFO:  eta: 15:17:40  iteration: 26099/375342  consumed_samples: 26726400  total_loss: 4.514  time: 0.3395 s/iter  data_time: 0.2102 s/iter total_throughput: 3016.22 samples/s lr: 9.88e-04  
[09/22 05:47:09] lb.utils.events INFO:  eta: 15:19:05  iteration: 26199/375342  consumed_samples: 26828800  total_loss: 4.514  time: 0.3395 s/iter  data_time: 0.2001 s/iter total_throughput: 3016.19 samples/s lr: 9.88e-04  
[09/22 05:47:43] lb.utils.events INFO:  eta: 15:20:06  iteration: 26299/375342  consumed_samples: 26931200  total_loss: 4.525  time: 0.3395 s/iter  data_time: 0.2174 s/iter total_throughput: 3016.04 samples/s lr: 9.88e-04  
[09/22 05:48:18] lb.utils.events INFO:  eta: 15:18:33  iteration: 26399/375342  consumed_samples: 27033600  total_loss: 4.516  time: 0.3395 s/iter  data_time: 0.2142 s/iter total_throughput: 3015.90 samples/s lr: 9.88e-04  
[09/22 05:48:52] lb.utils.events INFO:  eta: 15:18:56  iteration: 26499/375342  consumed_samples: 27136000  total_loss: 4.5  time: 0.3395 s/iter  data_time: 0.2227 s/iter total_throughput: 3015.91 samples/s lr: 9.88e-04  
[09/22 05:49:26] lb.utils.events INFO:  eta: 15:17:29  iteration: 26599/375342  consumed_samples: 27238400  total_loss: 4.504  time: 0.3395 s/iter  data_time: 0.2173 s/iter total_throughput: 3015.79 samples/s lr: 9.88e-04  
[09/22 05:50:00] lb.utils.events INFO:  eta: 15:17:03  iteration: 26699/375342  consumed_samples: 27340800  total_loss: 4.516  time: 0.3396 s/iter  data_time: 0.2142 s/iter total_throughput: 3015.70 samples/s lr: 9.88e-04  
[09/22 05:50:34] lb.utils.events INFO:  eta: 15:18:04  iteration: 26799/375342  consumed_samples: 27443200  total_loss: 4.518  time: 0.3395 s/iter  data_time: 0.2075 s/iter total_throughput: 3015.79 samples/s lr: 9.88e-04  
[09/22 05:51:08] lb.utils.events INFO:  eta: 15:16:44  iteration: 26899/375342  consumed_samples: 27545600  total_loss: 4.502  time: 0.3396 s/iter  data_time: 0.2210 s/iter total_throughput: 3015.68 samples/s lr: 9.88e-04  
[09/22 05:51:42] lb.utils.events INFO:  eta: 15:17:32  iteration: 26999/375342  consumed_samples: 27648000  total_loss: 4.5  time: 0.3395 s/iter  data_time: 0.1974 s/iter total_throughput: 3015.77 samples/s lr: 9.87e-04  
[09/22 05:52:16] lb.utils.events INFO:  eta: 15:19:18  iteration: 27099/375342  consumed_samples: 27750400  total_loss: 4.502  time: 0.3395 s/iter  data_time: 0.2094 s/iter total_throughput: 3015.91 samples/s lr: 9.87e-04  
[09/22 05:52:49] lb.utils.events INFO:  eta: 15:20:04  iteration: 27199/375342  consumed_samples: 27852800  total_loss: 4.496  time: 0.3395 s/iter  data_time: 0.2043 s/iter total_throughput: 3016.10 samples/s lr: 9.87e-04  
[09/22 05:53:22] lb.utils.events INFO:  eta: 15:21:01  iteration: 27299/375342  consumed_samples: 27955200  total_loss: 4.477  time: 0.3395 s/iter  data_time: 0.2189 s/iter total_throughput: 3016.23 samples/s lr: 9.87e-04  
[09/22 05:53:57] lb.utils.events INFO:  eta: 15:20:30  iteration: 27399/375342  consumed_samples: 28057600  total_loss: 4.469  time: 0.3395 s/iter  data_time: 0.2118 s/iter total_throughput: 3016.17 samples/s lr: 9.87e-04  
[09/22 05:54:30] lb.utils.events INFO:  eta: 15:20:01  iteration: 27499/375342  consumed_samples: 28160000  total_loss: 4.488  time: 0.3395 s/iter  data_time: 0.2101 s/iter total_throughput: 3016.22 samples/s lr: 9.87e-04  
[09/22 05:55:04] lb.utils.events INFO:  eta: 15:20:52  iteration: 27599/375342  consumed_samples: 28262400  total_loss: 4.453  time: 0.3395 s/iter  data_time: 0.2055 s/iter total_throughput: 3016.29 samples/s lr: 9.87e-04  
[09/22 05:55:38] lb.utils.events INFO:  eta: 15:20:53  iteration: 27699/375342  consumed_samples: 28364800  total_loss: 4.457  time: 0.3395 s/iter  data_time: 0.2019 s/iter total_throughput: 3016.41 samples/s lr: 9.87e-04  
[09/22 05:56:11] lb.utils.events INFO:  eta: 15:19:28  iteration: 27799/375342  consumed_samples: 28467200  total_loss: 4.471  time: 0.3395 s/iter  data_time: 0.2086 s/iter total_throughput: 3016.54 samples/s lr: 9.87e-04  
[09/22 05:56:45] lb.utils.events INFO:  eta: 15:21:37  iteration: 27899/375342  consumed_samples: 28569600  total_loss: 4.469  time: 0.3395 s/iter  data_time: 0.2030 s/iter total_throughput: 3016.58 samples/s lr: 9.87e-04  
[09/22 05:57:19] lb.utils.events INFO:  eta: 15:22:26  iteration: 27999/375342  consumed_samples: 28672000  total_loss: 4.449  time: 0.3395 s/iter  data_time: 0.2170 s/iter total_throughput: 3016.55 samples/s lr: 9.86e-04  
[09/22 05:57:54] lb.utils.events INFO:  eta: 15:20:41  iteration: 28099/375342  consumed_samples: 28774400  total_loss: 4.447  time: 0.3395 s/iter  data_time: 0.2097 s/iter total_throughput: 3016.19 samples/s lr: 9.86e-04  
[09/22 05:58:29] lb.utils.events INFO:  eta: 15:17:31  iteration: 28199/375342  consumed_samples: 28876800  total_loss: 4.463  time: 0.3395 s/iter  data_time: 0.2149 s/iter total_throughput: 3016.08 samples/s lr: 9.86e-04  
[09/22 05:59:03] lb.utils.events INFO:  eta: 15:17:09  iteration: 28299/375342  consumed_samples: 28979200  total_loss: 4.469  time: 0.3395 s/iter  data_time: 0.2034 s/iter total_throughput: 3016.08 samples/s lr: 9.86e-04  
[09/22 05:59:36] lb.utils.events INFO:  eta: 15:17:57  iteration: 28399/375342  consumed_samples: 29081600  total_loss: 4.455  time: 0.3395 s/iter  data_time: 0.2210 s/iter total_throughput: 3016.13 samples/s lr: 9.86e-04  
[09/22 06:00:10] lb.utils.events INFO:  eta: 15:19:51  iteration: 28499/375342  consumed_samples: 29184000  total_loss: 4.459  time: 0.3395 s/iter  data_time: 0.2089 s/iter total_throughput: 3016.20 samples/s lr: 9.86e-04  
[09/22 06:00:44] lb.utils.events INFO:  eta: 15:22:33  iteration: 28599/375342  consumed_samples: 29286400  total_loss: 4.439  time: 0.3395 s/iter  data_time: 0.2415 s/iter total_throughput: 3016.16 samples/s lr: 9.86e-04  
[09/22 06:01:19] lb.utils.events INFO:  eta: 15:22:51  iteration: 28699/375342  consumed_samples: 29388800  total_loss: 4.418  time: 0.3395 s/iter  data_time: 0.2286 s/iter total_throughput: 3016.01 samples/s lr: 9.86e-04  
[09/22 06:01:53] lb.utils.events INFO:  eta: 15:22:01  iteration: 28799/375342  consumed_samples: 29491200  total_loss: 4.424  time: 0.3395 s/iter  data_time: 0.2345 s/iter total_throughput: 3015.78 samples/s lr: 9.86e-04  
[09/22 06:02:27] lb.utils.events INFO:  eta: 15:21:14  iteration: 28899/375342  consumed_samples: 29593600  total_loss: 4.41  time: 0.3396 s/iter  data_time: 0.2161 s/iter total_throughput: 3015.72 samples/s lr: 9.86e-04  
[09/22 06:03:02] lb.utils.events INFO:  eta: 15:21:33  iteration: 28999/375342  consumed_samples: 29696000  total_loss: 4.414  time: 0.3396 s/iter  data_time: 0.2100 s/iter total_throughput: 3015.64 samples/s lr: 9.85e-04  
[09/22 06:03:36] lb.utils.events INFO:  eta: 15:21:41  iteration: 29099/375342  consumed_samples: 29798400  total_loss: 4.404  time: 0.3396 s/iter  data_time: 0.2102 s/iter total_throughput: 3015.66 samples/s lr: 9.85e-04  
[09/22 06:04:09] lb.utils.events INFO:  eta: 15:22:50  iteration: 29199/375342  consumed_samples: 29900800  total_loss: 4.402  time: 0.3396 s/iter  data_time: 0.2205 s/iter total_throughput: 3015.70 samples/s lr: 9.85e-04  
[09/22 06:04:43] lb.utils.events INFO:  eta: 15:21:01  iteration: 29299/375342  consumed_samples: 30003200  total_loss: 4.4  time: 0.3396 s/iter  data_time: 0.2076 s/iter total_throughput: 3015.73 samples/s lr: 9.85e-04  
[09/22 06:05:17] lb.utils.events INFO:  eta: 15:20:22  iteration: 29399/375342  consumed_samples: 30105600  total_loss: 4.424  time: 0.3396 s/iter  data_time: 0.2051 s/iter total_throughput: 3015.69 samples/s lr: 9.85e-04  
[09/22 06:05:51] lb.utils.events INFO:  eta: 15:22:50  iteration: 29499/375342  consumed_samples: 30208000  total_loss: 4.43  time: 0.3395 s/iter  data_time: 0.2116 s/iter total_throughput: 3015.76 samples/s lr: 9.85e-04  
[09/22 06:06:25] lb.utils.events INFO:  eta: 15:22:34  iteration: 29599/375342  consumed_samples: 30310400  total_loss: 4.424  time: 0.3395 s/iter  data_time: 0.2244 s/iter total_throughput: 3015.76 samples/s lr: 9.85e-04  
[09/22 06:06:59] lb.utils.events INFO:  eta: 15:20:44  iteration: 29699/375342  consumed_samples: 30412800  total_loss: 4.42  time: 0.3395 s/iter  data_time: 0.2070 s/iter total_throughput: 3015.80 samples/s lr: 9.85e-04  
[09/22 06:07:33] lb.utils.events INFO:  eta: 15:20:46  iteration: 29799/375342  consumed_samples: 30515200  total_loss: 4.42  time: 0.3396 s/iter  data_time: 0.2060 s/iter total_throughput: 3015.73 samples/s lr: 9.85e-04  
[09/22 06:08:07] lb.utils.events INFO:  eta: 15:21:31  iteration: 29899/375342  consumed_samples: 30617600  total_loss: 4.408  time: 0.3396 s/iter  data_time: 0.2174 s/iter total_throughput: 3015.75 samples/s lr: 9.85e-04  
[09/22 06:08:41] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0029999
[09/22 06:08:42] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/22 06:08:42] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/22 06:08:46] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0908 s/iter. Inference: 0.1659 s/iter. Eval: 0.0020 s/iter. Total: 0.2587 s/iter. ETA=0:00:09
[09/22 06:08:51] lb.evaluation.evaluator INFO: Inference done 29696/50000. Dataloading: 0.0981 s/iter. Inference: 0.1902 s/iter. Eval: 0.0021 s/iter. Total: 0.2905 s/iter. ETA=0:00:05
[09/22 06:08:56] lb.evaluation.evaluator INFO: Inference done 47104/50000. Dataloading: 0.0609 s/iter. Inference: 0.2313 s/iter. Eval: 0.0021 s/iter. Total: 0.2943 s/iter. ETA=0:00:00
[09/22 06:08:57] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/22 06:08:57] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.566647 (0.000251 s / iter per device, on 8 devices)
[09/22 06:08:57] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:09 (0.000199 s / iter per device, on 8 devices)
[09/22 06:08:57] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/22 06:08:57] lb.evaluation.utils INFO: copypaste: Acc@1=60.004000000000005
[09/22 06:08:57] lb.evaluation.utils INFO: copypaste: Acc@5=83.05799999999999
[09/22 06:08:57] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 60.00400, better than last best score 55.96000 @ iteration 24999.
[09/22 06:08:57] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/22 06:08:58] lb.utils.events INFO:  eta: 15:20:14  iteration: 29999/375342  consumed_samples: 30720000  total_loss: 4.412  time: 0.3396 s/iter  data_time: 0.2120 s/iter total_throughput: 3015.68 samples/s lr: 9.84e-04  
[09/22 06:09:30] lb.utils.events INFO:  eta: 15:20:59  iteration: 30099/375342  consumed_samples: 30822400  total_loss: 4.42  time: 0.3395 s/iter  data_time: 0.2495 s/iter total_throughput: 3016.29 samples/s lr: 9.84e-04  
[09/22 06:10:04] lb.utils.events INFO:  eta: 15:26:59  iteration: 30199/375342  consumed_samples: 30924800  total_loss: 4.402  time: 0.3395 s/iter  data_time: 0.2411 s/iter total_throughput: 3016.17 samples/s lr: 9.84e-04  
[09/22 06:10:38] lb.utils.events INFO:  eta: 15:26:13  iteration: 30299/375342  consumed_samples: 31027200  total_loss: 4.391  time: 0.3395 s/iter  data_time: 0.2158 s/iter total_throughput: 3016.06 samples/s lr: 9.84e-04  
[09/22 06:11:12] lb.utils.events INFO:  eta: 15:27:04  iteration: 30399/375342  consumed_samples: 31129600  total_loss: 4.365  time: 0.3395 s/iter  data_time: 0.1968 s/iter total_throughput: 3016.15 samples/s lr: 9.84e-04  
[09/22 06:11:46] lb.utils.events INFO:  eta: 15:25:03  iteration: 30499/375342  consumed_samples: 31232000  total_loss: 4.367  time: 0.3395 s/iter  data_time: 0.2106 s/iter total_throughput: 3016.08 samples/s lr: 9.84e-04  
[09/22 06:12:20] lb.utils.events INFO:  eta: 15:21:24  iteration: 30599/375342  consumed_samples: 31334400  total_loss: 4.389  time: 0.3395 s/iter  data_time: 0.2227 s/iter total_throughput: 3016.09 samples/s lr: 9.84e-04  
[09/22 06:12:54] lb.utils.events INFO:  eta: 15:19:44  iteration: 30699/375342  consumed_samples: 31436800  total_loss: 4.387  time: 0.3395 s/iter  data_time: 0.2203 s/iter total_throughput: 3016.05 samples/s lr: 9.84e-04  
[09/22 06:13:28] lb.utils.events INFO:  eta: 15:19:13  iteration: 30799/375342  consumed_samples: 31539200  total_loss: 4.359  time: 0.3395 s/iter  data_time: 0.2028 s/iter total_throughput: 3016.03 samples/s lr: 9.84e-04  
[09/22 06:14:02] lb.utils.events INFO:  eta: 15:20:14  iteration: 30899/375342  consumed_samples: 31641600  total_loss: 4.373  time: 0.3395 s/iter  data_time: 0.2077 s/iter total_throughput: 3016.09 samples/s lr: 9.84e-04  
[09/22 06:14:36] lb.utils.events INFO:  eta: 15:19:52  iteration: 30999/375342  consumed_samples: 31744000  total_loss: 4.367  time: 0.3395 s/iter  data_time: 0.2162 s/iter total_throughput: 3015.96 samples/s lr: 9.83e-04  
[09/22 06:15:11] lb.utils.events INFO:  eta: 15:16:25  iteration: 31099/375342  consumed_samples: 31846400  total_loss: 4.352  time: 0.3395 s/iter  data_time: 0.2068 s/iter total_throughput: 3015.83 samples/s lr: 9.83e-04  
[09/22 06:15:45] lb.utils.events INFO:  eta: 15:07:49  iteration: 31199/375342  consumed_samples: 31948800  total_loss: 4.375  time: 0.3396 s/iter  data_time: 0.2049 s/iter total_throughput: 3015.76 samples/s lr: 9.83e-04  
[09/22 06:16:19] lb.utils.events INFO:  eta: 15:08:03  iteration: 31299/375342  consumed_samples: 32051200  total_loss: 4.375  time: 0.3396 s/iter  data_time: 0.2096 s/iter total_throughput: 3015.74 samples/s lr: 9.83e-04  
[09/22 06:16:53] lb.utils.events INFO:  eta: 15:07:33  iteration: 31399/375342  consumed_samples: 32153600  total_loss: 4.363  time: 0.3395 s/iter  data_time: 0.2149 s/iter total_throughput: 3015.78 samples/s lr: 9.83e-04  
[09/22 06:17:27] lb.utils.events INFO:  eta: 15:07:31  iteration: 31499/375342  consumed_samples: 32256000  total_loss: 4.348  time: 0.3395 s/iter  data_time: 0.2099 s/iter total_throughput: 3015.77 samples/s lr: 9.83e-04  
[09/22 06:18:01] lb.utils.events INFO:  eta: 15:07:10  iteration: 31599/375342  consumed_samples: 32358400  total_loss: 4.344  time: 0.3396 s/iter  data_time: 0.2096 s/iter total_throughput: 3015.72 samples/s lr: 9.83e-04  
[09/22 06:18:35] lb.utils.events INFO:  eta: 15:07:22  iteration: 31699/375342  consumed_samples: 32460800  total_loss: 4.34  time: 0.3395 s/iter  data_time: 0.1937 s/iter total_throughput: 3015.82 samples/s lr: 9.83e-04  
[09/22 06:19:09] lb.utils.events INFO:  eta: 15:09:25  iteration: 31799/375342  consumed_samples: 32563200  total_loss: 4.359  time: 0.3395 s/iter  data_time: 0.2095 s/iter total_throughput: 3015.83 samples/s lr: 9.83e-04  
[09/22 06:19:42] lb.utils.events INFO:  eta: 15:07:42  iteration: 31899/375342  consumed_samples: 32665600  total_loss: 4.359  time: 0.3395 s/iter  data_time: 0.2161 s/iter total_throughput: 3015.88 samples/s lr: 9.82e-04  
[09/22 06:20:16] lb.utils.events INFO:  eta: 15:08:07  iteration: 31999/375342  consumed_samples: 32768000  total_loss: 4.344  time: 0.3395 s/iter  data_time: 0.2093 s/iter total_throughput: 3015.87 samples/s lr: 9.82e-04  
[09/22 06:20:51] lb.utils.events INFO:  eta: 15:06:35  iteration: 32099/375342  consumed_samples: 32870400  total_loss: 4.352  time: 0.3396 s/iter  data_time: 0.2173 s/iter total_throughput: 3015.71 samples/s lr: 9.82e-04  
[09/22 06:21:26] lb.utils.events INFO:  eta: 15:06:55  iteration: 32199/375342  consumed_samples: 32972800  total_loss: 4.354  time: 0.3396 s/iter  data_time: 0.2198 s/iter total_throughput: 3015.52 samples/s lr: 9.82e-04  
[09/22 06:22:00] lb.utils.events INFO:  eta: 15:05:55  iteration: 32299/375342  consumed_samples: 33075200  total_loss: 4.346  time: 0.3396 s/iter  data_time: 0.2257 s/iter total_throughput: 3015.41 samples/s lr: 9.82e-04  
[09/22 06:22:34] lb.utils.events INFO:  eta: 15:05:39  iteration: 32399/375342  consumed_samples: 33177600  total_loss: 4.32  time: 0.3396 s/iter  data_time: 0.2238 s/iter total_throughput: 3015.39 samples/s lr: 9.82e-04  
[09/22 06:23:08] lb.utils.events INFO:  eta: 15:04:02  iteration: 32499/375342  consumed_samples: 33280000  total_loss: 4.324  time: 0.3396 s/iter  data_time: 0.2094 s/iter total_throughput: 3015.40 samples/s lr: 9.82e-04  
[09/22 06:23:42] lb.utils.events INFO:  eta: 15:03:19  iteration: 32599/375342  consumed_samples: 33382400  total_loss: 4.324  time: 0.3396 s/iter  data_time: 0.2064 s/iter total_throughput: 3015.31 samples/s lr: 9.82e-04  
[09/22 06:24:17] lb.utils.events INFO:  eta: 15:01:52  iteration: 32699/375342  consumed_samples: 33484800  total_loss: 4.312  time: 0.3396 s/iter  data_time: 0.2025 s/iter total_throughput: 3015.16 samples/s lr: 9.82e-04  
[09/22 06:24:51] lb.utils.events INFO:  eta: 15:01:49  iteration: 32799/375342  consumed_samples: 33587200  total_loss: 4.334  time: 0.3396 s/iter  data_time: 0.2115 s/iter total_throughput: 3015.18 samples/s lr: 9.81e-04  
[09/22 06:25:25] lb.utils.events INFO:  eta: 15:00:59  iteration: 32899/375342  consumed_samples: 33689600  total_loss: 4.328  time: 0.3396 s/iter  data_time: 0.2122 s/iter total_throughput: 3015.16 samples/s lr: 9.81e-04  
[09/22 06:25:59] lb.utils.events INFO:  eta: 15:01:31  iteration: 32999/375342  consumed_samples: 33792000  total_loss: 4.309  time: 0.3396 s/iter  data_time: 0.2182 s/iter total_throughput: 3015.11 samples/s lr: 9.81e-04  
[09/22 06:26:33] lb.utils.events INFO:  eta: 15:01:23  iteration: 33099/375342  consumed_samples: 33894400  total_loss: 4.328  time: 0.3396 s/iter  data_time: 0.2111 s/iter total_throughput: 3015.04 samples/s lr: 9.81e-04  
[09/22 06:27:07] lb.utils.events INFO:  eta: 15:01:41  iteration: 33199/375342  consumed_samples: 33996800  total_loss: 4.311  time: 0.3396 s/iter  data_time: 0.2090 s/iter total_throughput: 3015.04 samples/s lr: 9.81e-04  
[09/22 06:27:41] lb.utils.events INFO:  eta: 15:01:59  iteration: 33299/375342  consumed_samples: 34099200  total_loss: 4.305  time: 0.3396 s/iter  data_time: 0.2144 s/iter total_throughput: 3014.95 samples/s lr: 9.81e-04  
[09/22 06:28:16] lb.utils.events INFO:  eta: 15:00:42  iteration: 33399/375342  consumed_samples: 34201600  total_loss: 4.303  time: 0.3397 s/iter  data_time: 0.2137 s/iter total_throughput: 3014.79 samples/s lr: 9.81e-04  
[09/22 06:28:50] lb.utils.events INFO:  eta: 15:00:20  iteration: 33499/375342  consumed_samples: 34304000  total_loss: 4.285  time: 0.3397 s/iter  data_time: 0.2138 s/iter total_throughput: 3014.75 samples/s lr: 9.81e-04  
[09/22 06:29:24] lb.utils.events INFO:  eta: 15:02:15  iteration: 33599/375342  consumed_samples: 34406400  total_loss: 4.301  time: 0.3397 s/iter  data_time: 0.2177 s/iter total_throughput: 3014.65 samples/s lr: 9.81e-04  
[09/22 06:29:58] lb.utils.events INFO:  eta: 15:01:19  iteration: 33699/375342  consumed_samples: 34508800  total_loss: 4.297  time: 0.3397 s/iter  data_time: 0.2038 s/iter total_throughput: 3014.66 samples/s lr: 9.80e-04  
[09/22 06:30:32] lb.utils.events INFO:  eta: 14:59:21  iteration: 33799/375342  consumed_samples: 34611200  total_loss: 4.275  time: 0.3397 s/iter  data_time: 0.2137 s/iter total_throughput: 3014.61 samples/s lr: 9.80e-04  
[09/22 06:31:07] lb.utils.events INFO:  eta: 14:59:02  iteration: 33899/375342  consumed_samples: 34713600  total_loss: 4.287  time: 0.3397 s/iter  data_time: 0.2154 s/iter total_throughput: 3014.46 samples/s lr: 9.80e-04  
[09/22 06:31:41] lb.utils.events INFO:  eta: 14:58:32  iteration: 33999/375342  consumed_samples: 34816000  total_loss: 4.273  time: 0.3397 s/iter  data_time: 0.2137 s/iter total_throughput: 3014.39 samples/s lr: 9.80e-04  
[09/22 06:32:16] lb.utils.events INFO:  eta: 15:00:53  iteration: 34099/375342  consumed_samples: 34918400  total_loss: 4.273  time: 0.3397 s/iter  data_time: 0.2179 s/iter total_throughput: 3014.28 samples/s lr: 9.80e-04  
[09/22 06:32:50] lb.utils.events INFO:  eta: 15:05:50  iteration: 34199/375342  consumed_samples: 35020800  total_loss: 4.268  time: 0.3397 s/iter  data_time: 0.2061 s/iter total_throughput: 3014.25 samples/s lr: 9.80e-04  
[09/22 06:33:24] lb.utils.events INFO:  eta: 15:04:42  iteration: 34299/375342  consumed_samples: 35123200  total_loss: 4.297  time: 0.3397 s/iter  data_time: 0.2050 s/iter total_throughput: 3014.15 samples/s lr: 9.80e-04  
[09/22 06:33:58] lb.utils.events INFO:  eta: 15:05:55  iteration: 34399/375342  consumed_samples: 35225600  total_loss: 4.309  time: 0.3397 s/iter  data_time: 0.2023 s/iter total_throughput: 3014.18 samples/s lr: 9.80e-04  
[09/22 06:34:32] lb.utils.events INFO:  eta: 15:07:14  iteration: 34499/375342  consumed_samples: 35328000  total_loss: 4.285  time: 0.3397 s/iter  data_time: 0.2130 s/iter total_throughput: 3014.23 samples/s lr: 9.80e-04  
[09/22 06:35:06] lb.utils.events INFO:  eta: 15:06:54  iteration: 34599/375342  consumed_samples: 35430400  total_loss: 4.285  time: 0.3397 s/iter  data_time: 0.2067 s/iter total_throughput: 3014.20 samples/s lr: 9.79e-04  
[09/22 06:35:40] lb.utils.events INFO:  eta: 15:07:57  iteration: 34699/375342  consumed_samples: 35532800  total_loss: 4.285  time: 0.3397 s/iter  data_time: 0.2163 s/iter total_throughput: 3014.10 samples/s lr: 9.79e-04  
[09/22 06:36:14] lb.utils.events INFO:  eta: 15:08:57  iteration: 34799/375342  consumed_samples: 35635200  total_loss: 4.283  time: 0.3397 s/iter  data_time: 0.2211 s/iter total_throughput: 3014.11 samples/s lr: 9.79e-04  
[09/22 06:36:49] lb.utils.events INFO:  eta: 15:08:41  iteration: 34899/375342  consumed_samples: 35737600  total_loss: 4.268  time: 0.3397 s/iter  data_time: 0.2150 s/iter total_throughput: 3013.99 samples/s lr: 9.79e-04  
[09/22 06:37:23] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0034999
[09/22 06:37:24] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/22 06:37:24] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/22 06:37:28] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0508 s/iter. Inference: 0.1902 s/iter. Eval: 0.0020 s/iter. Total: 0.2430 s/iter. ETA=0:00:08
[09/22 06:37:33] lb.evaluation.evaluator INFO: Inference done 29696/50000. Dataloading: 0.0981 s/iter. Inference: 0.1865 s/iter. Eval: 0.0020 s/iter. Total: 0.2866 s/iter. ETA=0:00:05
[09/22 06:37:38] lb.evaluation.evaluator INFO: Inference done 48128/50000. Dataloading: 0.1023 s/iter. Inference: 0.1812 s/iter. Eval: 0.0020 s/iter. Total: 0.2856 s/iter. ETA=0:00:00
[09/22 06:37:39] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/22 06:37:39] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.341234 (0.000247 s / iter per device, on 8 devices)
[09/22 06:37:39] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000159 s / iter per device, on 8 devices)
[09/22 06:37:39] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/22 06:37:39] lb.evaluation.utils INFO: copypaste: Acc@1=62.980000000000004
[09/22 06:37:39] lb.evaluation.utils INFO: copypaste: Acc@5=85.548
[09/22 06:37:39] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 62.98000, better than last best score 60.00400 @ iteration 29999.
[09/22 06:37:39] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/22 06:37:40] lb.utils.events INFO:  eta: 15:07:30  iteration: 34999/375342  consumed_samples: 35840000  total_loss: 4.266  time: 0.3398 s/iter  data_time: 0.2169 s/iter total_throughput: 3013.84 samples/s lr: 9.79e-04  
[09/22 06:38:11] lb.utils.events INFO:  eta: 15:11:03  iteration: 35099/375342  consumed_samples: 35942400  total_loss: 4.264  time: 0.3397 s/iter  data_time: 0.2248 s/iter total_throughput: 3014.44 samples/s lr: 9.79e-04  
[09/22 06:38:46] lb.utils.events INFO:  eta: 15:10:03  iteration: 35199/375342  consumed_samples: 36044800  total_loss: 4.252  time: 0.3397 s/iter  data_time: 0.2499 s/iter total_throughput: 3014.33 samples/s lr: 9.79e-04  
[09/22 06:39:20] lb.utils.events INFO:  eta: 15:09:32  iteration: 35299/375342  consumed_samples: 36147200  total_loss: 4.25  time: 0.3397 s/iter  data_time: 0.2074 s/iter total_throughput: 3014.25 samples/s lr: 9.79e-04  
[09/22 06:39:54] lb.utils.events INFO:  eta: 15:07:21  iteration: 35399/375342  consumed_samples: 36249600  total_loss: 4.25  time: 0.3397 s/iter  data_time: 0.2073 s/iter total_throughput: 3014.32 samples/s lr: 9.78e-04  
[09/22 06:40:27] lb.utils.events INFO:  eta: 15:06:04  iteration: 35499/375342  consumed_samples: 36352000  total_loss: 4.24  time: 0.3397 s/iter  data_time: 0.2090 s/iter total_throughput: 3014.35 samples/s lr: 9.78e-04  
[09/22 06:41:01] lb.utils.events INFO:  eta: 15:03:59  iteration: 35599/375342  consumed_samples: 36454400  total_loss: 4.246  time: 0.3397 s/iter  data_time: 0.2042 s/iter total_throughput: 3014.41 samples/s lr: 9.78e-04  
[09/22 06:41:35] lb.utils.events INFO:  eta: 15:03:01  iteration: 35699/375342  consumed_samples: 36556800  total_loss: 4.266  time: 0.3397 s/iter  data_time: 0.2074 s/iter total_throughput: 3014.47 samples/s lr: 9.78e-04  
[09/22 06:42:09] lb.utils.events INFO:  eta: 15:00:37  iteration: 35799/375342  consumed_samples: 36659200  total_loss: 4.24  time: 0.3397 s/iter  data_time: 0.2284 s/iter total_throughput: 3014.45 samples/s lr: 9.78e-04  
[09/22 06:42:43] lb.utils.events INFO:  eta: 15:02:45  iteration: 35899/375342  consumed_samples: 36761600  total_loss: 4.236  time: 0.3397 s/iter  data_time: 0.2103 s/iter total_throughput: 3014.53 samples/s lr: 9.78e-04  
[09/22 06:43:17] lb.utils.events INFO:  eta: 15:02:52  iteration: 35999/375342  consumed_samples: 36864000  total_loss: 4.254  time: 0.3397 s/iter  data_time: 0.2084 s/iter total_throughput: 3014.47 samples/s lr: 9.78e-04  
[09/22 06:43:51] lb.utils.events INFO:  eta: 14:58:36  iteration: 36099/375342  consumed_samples: 36966400  total_loss: 4.254  time: 0.3397 s/iter  data_time: 0.2213 s/iter total_throughput: 3014.47 samples/s lr: 9.78e-04  
[09/22 06:44:25] lb.utils.events INFO:  eta: 14:56:39  iteration: 36199/375342  consumed_samples: 37068800  total_loss: 4.223  time: 0.3397 s/iter  data_time: 0.2115 s/iter total_throughput: 3014.45 samples/s lr: 9.77e-04  
[09/22 06:44:59] lb.utils.events INFO:  eta: 14:55:34  iteration: 36299/375342  consumed_samples: 37171200  total_loss: 4.23  time: 0.3397 s/iter  data_time: 0.2198 s/iter total_throughput: 3014.46 samples/s lr: 9.77e-04  
[09/22 06:45:33] lb.utils.events INFO:  eta: 14:54:55  iteration: 36399/375342  consumed_samples: 37273600  total_loss: 4.242  time: 0.3397 s/iter  data_time: 0.2175 s/iter total_throughput: 3014.42 samples/s lr: 9.77e-04  
[09/22 06:46:07] lb.utils.events INFO:  eta: 14:55:12  iteration: 36499/375342  consumed_samples: 37376000  total_loss: 4.238  time: 0.3397 s/iter  data_time: 0.2132 s/iter total_throughput: 3014.42 samples/s lr: 9.77e-04  
[09/22 06:46:41] lb.utils.events INFO:  eta: 14:55:52  iteration: 36599/375342  consumed_samples: 37478400  total_loss: 4.221  time: 0.3397 s/iter  data_time: 0.2048 s/iter total_throughput: 3014.34 samples/s lr: 9.77e-04  
[09/22 06:47:15] lb.utils.events INFO:  eta: 14:57:09  iteration: 36699/375342  consumed_samples: 37580800  total_loss: 4.209  time: 0.3397 s/iter  data_time: 0.2185 s/iter total_throughput: 3014.52 samples/s lr: 9.77e-04  
[09/22 06:47:49] lb.utils.events INFO:  eta: 14:55:56  iteration: 36799/375342  consumed_samples: 37683200  total_loss: 4.232  time: 0.3397 s/iter  data_time: 0.2122 s/iter total_throughput: 3014.45 samples/s lr: 9.77e-04  
[09/22 06:48:23] lb.utils.events INFO:  eta: 14:54:25  iteration: 36899/375342  consumed_samples: 37785600  total_loss: 4.25  time: 0.3397 s/iter  data_time: 0.2204 s/iter total_throughput: 3014.37 samples/s lr: 9.77e-04  
[09/22 06:48:57] lb.utils.events INFO:  eta: 14:54:09  iteration: 36999/375342  consumed_samples: 37888000  total_loss: 4.236  time: 0.3397 s/iter  data_time: 0.2132 s/iter total_throughput: 3014.38 samples/s lr: 9.76e-04  
[09/22 06:49:30] lb.utils.events INFO:  eta: 14:52:13  iteration: 37099/375342  consumed_samples: 37990400  total_loss: 4.221  time: 0.3397 s/iter  data_time: 0.2104 s/iter total_throughput: 3014.51 samples/s lr: 9.76e-04  
[09/22 06:50:04] lb.utils.events INFO:  eta: 14:51:36  iteration: 37199/375342  consumed_samples: 38092800  total_loss: 4.232  time: 0.3397 s/iter  data_time: 0.2115 s/iter total_throughput: 3014.52 samples/s lr: 9.76e-04  
[09/22 06:50:38] lb.utils.events INFO:  eta: 14:51:21  iteration: 37299/375342  consumed_samples: 38195200  total_loss: 4.234  time: 0.3397 s/iter  data_time: 0.2113 s/iter total_throughput: 3014.50 samples/s lr: 9.76e-04  
[09/22 06:51:12] lb.utils.events INFO:  eta: 14:51:16  iteration: 37399/375342  consumed_samples: 38297600  total_loss: 4.234  time: 0.3397 s/iter  data_time: 0.1979 s/iter total_throughput: 3014.64 samples/s lr: 9.76e-04  
[09/22 06:51:46] lb.utils.events INFO:  eta: 14:50:37  iteration: 37499/375342  consumed_samples: 38400000  total_loss: 4.219  time: 0.3397 s/iter  data_time: 0.2056 s/iter total_throughput: 3014.72 samples/s lr: 9.76e-04  
[09/22 06:52:20] lb.utils.events INFO:  eta: 14:48:37  iteration: 37599/375342  consumed_samples: 38502400  total_loss: 4.217  time: 0.3397 s/iter  data_time: 0.2218 s/iter total_throughput: 3014.68 samples/s lr: 9.76e-04  
[09/22 06:52:54] lb.utils.events INFO:  eta: 14:46:02  iteration: 37699/375342  consumed_samples: 38604800  total_loss: 4.203  time: 0.3397 s/iter  data_time: 0.2188 s/iter total_throughput: 3014.65 samples/s lr: 9.76e-04  
[09/22 06:53:28] lb.utils.events INFO:  eta: 14:45:07  iteration: 37799/375342  consumed_samples: 38707200  total_loss: 4.195  time: 0.3397 s/iter  data_time: 0.2221 s/iter total_throughput: 3014.54 samples/s lr: 9.75e-04  
[09/22 06:54:02] lb.utils.events INFO:  eta: 14:44:48  iteration: 37899/375342  consumed_samples: 38809600  total_loss: 4.217  time: 0.3397 s/iter  data_time: 0.1978 s/iter total_throughput: 3014.49 samples/s lr: 9.75e-04  
[09/22 06:54:36] lb.utils.events INFO:  eta: 14:44:36  iteration: 37999/375342  consumed_samples: 38912000  total_loss: 4.221  time: 0.3397 s/iter  data_time: 0.2295 s/iter total_throughput: 3014.49 samples/s lr: 9.75e-04  
[09/22 06:55:10] lb.utils.events INFO:  eta: 14:43:07  iteration: 38099/375342  consumed_samples: 39014400  total_loss: 4.207  time: 0.3397 s/iter  data_time: 0.2118 s/iter total_throughput: 3014.59 samples/s lr: 9.75e-04  
[09/22 06:55:44] lb.utils.events INFO:  eta: 14:41:21  iteration: 38199/375342  consumed_samples: 39116800  total_loss: 4.193  time: 0.3397 s/iter  data_time: 0.2079 s/iter total_throughput: 3014.61 samples/s lr: 9.75e-04  
[09/22 06:56:17] lb.utils.events INFO:  eta: 14:43:42  iteration: 38299/375342  consumed_samples: 39219200  total_loss: 4.201  time: 0.3397 s/iter  data_time: 0.2064 s/iter total_throughput: 3014.77 samples/s lr: 9.75e-04  
[09/22 06:56:51] lb.utils.events INFO:  eta: 14:42:02  iteration: 38399/375342  consumed_samples: 39321600  total_loss: 4.215  time: 0.3397 s/iter  data_time: 0.2067 s/iter total_throughput: 3014.77 samples/s lr: 9.75e-04  
[09/22 06:57:25] lb.utils.events INFO:  eta: 14:40:53  iteration: 38499/375342  consumed_samples: 39424000  total_loss: 4.205  time: 0.3397 s/iter  data_time: 0.2018 s/iter total_throughput: 3014.69 samples/s lr: 9.75e-04  
[09/22 06:57:59] lb.utils.events INFO:  eta: 14:43:33  iteration: 38599/375342  consumed_samples: 39526400  total_loss: 4.197  time: 0.3397 s/iter  data_time: 0.2177 s/iter total_throughput: 3014.76 samples/s lr: 9.74e-04  
[09/22 06:58:33] lb.utils.events INFO:  eta: 14:43:47  iteration: 38699/375342  consumed_samples: 39628800  total_loss: 4.201  time: 0.3397 s/iter  data_time: 0.2127 s/iter total_throughput: 3014.84 samples/s lr: 9.74e-04  
[09/22 06:59:06] lb.utils.events INFO:  eta: 14:44:21  iteration: 38799/375342  consumed_samples: 39731200  total_loss: 4.219  time: 0.3396 s/iter  data_time: 0.2087 s/iter total_throughput: 3014.91 samples/s lr: 9.74e-04  
[09/22 06:59:41] lb.utils.events INFO:  eta: 14:40:53  iteration: 38899/375342  consumed_samples: 39833600  total_loss: 4.207  time: 0.3397 s/iter  data_time: 0.2211 s/iter total_throughput: 3014.79 samples/s lr: 9.74e-04  
[09/22 07:00:15] lb.utils.events INFO:  eta: 14:42:26  iteration: 38999/375342  consumed_samples: 39936000  total_loss: 4.195  time: 0.3397 s/iter  data_time: 0.2106 s/iter total_throughput: 3014.86 samples/s lr: 9.74e-04  
[09/22 07:00:48] lb.utils.events INFO:  eta: 14:42:25  iteration: 39099/375342  consumed_samples: 40038400  total_loss: 4.182  time: 0.3396 s/iter  data_time: 0.2086 s/iter total_throughput: 3014.89 samples/s lr: 9.74e-04  
[09/22 07:01:22] lb.utils.events INFO:  eta: 14:39:57  iteration: 39199/375342  consumed_samples: 40140800  total_loss: 4.188  time: 0.3397 s/iter  data_time: 0.2230 s/iter total_throughput: 3014.86 samples/s lr: 9.74e-04  
[09/22 07:01:56] lb.utils.events INFO:  eta: 14:42:09  iteration: 39299/375342  consumed_samples: 40243200  total_loss: 4.211  time: 0.3396 s/iter  data_time: 0.2135 s/iter total_throughput: 3014.96 samples/s lr: 9.73e-04  
[09/22 07:02:30] lb.utils.events INFO:  eta: 14:41:53  iteration: 39399/375342  consumed_samples: 40345600  total_loss: 4.211  time: 0.3396 s/iter  data_time: 0.2055 s/iter total_throughput: 3015.01 samples/s lr: 9.73e-04  
[09/22 07:03:04] lb.utils.events INFO:  eta: 14:39:48  iteration: 39499/375342  consumed_samples: 40448000  total_loss: 4.211  time: 0.3396 s/iter  data_time: 0.2258 s/iter total_throughput: 3015.04 samples/s lr: 9.73e-04  
[09/22 07:03:38] lb.utils.events INFO:  eta: 14:38:30  iteration: 39599/375342  consumed_samples: 40550400  total_loss: 4.182  time: 0.3396 s/iter  data_time: 0.2116 s/iter total_throughput: 3014.90 samples/s lr: 9.73e-04  
[09/22 07:04:12] lb.utils.events INFO:  eta: 14:39:17  iteration: 39699/375342  consumed_samples: 40652800  total_loss: 4.189  time: 0.3396 s/iter  data_time: 0.1986 s/iter total_throughput: 3014.94 samples/s lr: 9.73e-04  
[09/22 07:04:46] lb.utils.events INFO:  eta: 14:37:29  iteration: 39799/375342  consumed_samples: 40755200  total_loss: 4.191  time: 0.3396 s/iter  data_time: 0.2041 s/iter total_throughput: 3014.95 samples/s lr: 9.73e-04  
[09/22 07:05:20] lb.utils.events INFO:  eta: 14:42:39  iteration: 39899/375342  consumed_samples: 40857600  total_loss: 4.172  time: 0.3396 s/iter  data_time: 0.2145 s/iter total_throughput: 3014.93 samples/s lr: 9.73e-04  
[09/22 07:05:55] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0039999
[09/22 07:05:55] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/22 07:05:55] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/22 07:06:00] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0971 s/iter. Inference: 0.1608 s/iter. Eval: 0.0020 s/iter. Total: 0.2599 s/iter. ETA=0:00:09
[09/22 07:06:05] lb.evaluation.evaluator INFO: Inference done 28672/50000. Dataloading: 0.0724 s/iter. Inference: 0.2114 s/iter. Eval: 0.0020 s/iter. Total: 0.2859 s/iter. ETA=0:00:05
[09/22 07:06:10] lb.evaluation.evaluator INFO: Inference done 46080/50000. Dataloading: 0.0654 s/iter. Inference: 0.2242 s/iter. Eval: 0.0020 s/iter. Total: 0.2916 s/iter. ETA=0:00:00
[09/22 07:06:11] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/22 07:06:11] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.607516 (0.000252 s / iter per device, on 8 devices)
[09/22 07:06:11] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:09 (0.000197 s / iter per device, on 8 devices)
[09/22 07:06:11] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/22 07:06:11] lb.evaluation.utils INFO: copypaste: Acc@1=64.67
[09/22 07:06:11] lb.evaluation.utils INFO: copypaste: Acc@5=86.424
[09/22 07:06:11] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 64.67000, better than last best score 62.98000 @ iteration 34999.
[09/22 07:06:11] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/22 07:06:11] lb.utils.events INFO:  eta: 14:38:34  iteration: 39999/375342  consumed_samples: 40960000  total_loss: 4.195  time: 0.3397 s/iter  data_time: 0.2063 s/iter total_throughput: 3014.75 samples/s lr: 9.73e-04  
[09/22 07:06:43] lb.utils.events INFO:  eta: 14:41:58  iteration: 40099/375342  consumed_samples: 41062400  total_loss: 4.188  time: 0.3396 s/iter  data_time: 0.2302 s/iter total_throughput: 3015.31 samples/s lr: 9.72e-04  
[09/22 07:07:17] lb.utils.events INFO:  eta: 14:42:48  iteration: 40199/375342  consumed_samples: 41164800  total_loss: 4.193  time: 0.3396 s/iter  data_time: 0.2245 s/iter total_throughput: 3015.30 samples/s lr: 9.72e-04  
[09/22 07:07:51] lb.utils.events INFO:  eta: 14:42:26  iteration: 40299/375342  consumed_samples: 41267200  total_loss: 4.195  time: 0.3396 s/iter  data_time: 0.2180 s/iter total_throughput: 3015.36 samples/s lr: 9.72e-04  
[09/22 07:08:24] lb.utils.events INFO:  eta: 14:41:58  iteration: 40399/375342  consumed_samples: 41369600  total_loss: 4.178  time: 0.3396 s/iter  data_time: 0.1996 s/iter total_throughput: 3015.41 samples/s lr: 9.72e-04  
[09/22 07:08:58] lb.utils.events INFO:  eta: 14:42:52  iteration: 40499/375342  consumed_samples: 41472000  total_loss: 4.18  time: 0.3396 s/iter  data_time: 0.2116 s/iter total_throughput: 3015.49 samples/s lr: 9.72e-04  
[09/22 07:09:32] lb.utils.events INFO:  eta: 14:43:48  iteration: 40599/375342  consumed_samples: 41574400  total_loss: 4.176  time: 0.3396 s/iter  data_time: 0.2199 s/iter total_throughput: 3015.49 samples/s lr: 9.72e-04  
[09/22 07:10:06] lb.utils.events INFO:  eta: 14:40:21  iteration: 40699/375342  consumed_samples: 41676800  total_loss: 4.164  time: 0.3396 s/iter  data_time: 0.2135 s/iter total_throughput: 3015.46 samples/s lr: 9.72e-04  
[09/22 07:10:40] lb.utils.events INFO:  eta: 14:40:37  iteration: 40799/375342  consumed_samples: 41779200  total_loss: 4.141  time: 0.3396 s/iter  data_time: 0.2217 s/iter total_throughput: 3015.46 samples/s lr: 9.71e-04  
[09/22 07:11:14] lb.utils.events INFO:  eta: 14:39:14  iteration: 40899/375342  consumed_samples: 41881600  total_loss: 4.141  time: 0.3396 s/iter  data_time: 0.2115 s/iter total_throughput: 3015.43 samples/s lr: 9.71e-04  
[09/22 07:11:48] lb.utils.events INFO:  eta: 14:39:48  iteration: 40999/375342  consumed_samples: 41984000  total_loss: 4.15  time: 0.3396 s/iter  data_time: 0.1979 s/iter total_throughput: 3015.50 samples/s lr: 9.71e-04  
[09/22 07:12:21] lb.utils.events INFO:  eta: 14:38:17  iteration: 41099/375342  consumed_samples: 42086400  total_loss: 4.162  time: 0.3396 s/iter  data_time: 0.2206 s/iter total_throughput: 3015.57 samples/s lr: 9.71e-04  
[09/22 07:12:55] lb.utils.events INFO:  eta: 14:37:03  iteration: 41199/375342  consumed_samples: 42188800  total_loss: 4.186  time: 0.3396 s/iter  data_time: 0.2168 s/iter total_throughput: 3015.59 samples/s lr: 9.71e-04  
[09/22 07:13:29] lb.utils.events INFO:  eta: 14:34:41  iteration: 41299/375342  consumed_samples: 42291200  total_loss: 4.186  time: 0.3396 s/iter  data_time: 0.2183 s/iter total_throughput: 3015.73 samples/s lr: 9.71e-04  
[09/22 07:14:03] lb.utils.events INFO:  eta: 14:32:38  iteration: 41399/375342  consumed_samples: 42393600  total_loss: 4.156  time: 0.3396 s/iter  data_time: 0.2267 s/iter total_throughput: 3015.70 samples/s lr: 9.71e-04  
[09/22 07:14:36] lb.utils.events INFO:  eta: 14:30:45  iteration: 41499/375342  consumed_samples: 42496000  total_loss: 4.143  time: 0.3396 s/iter  data_time: 0.2179 s/iter total_throughput: 3015.75 samples/s lr: 9.70e-04  
[09/22 07:15:10] lb.utils.events INFO:  eta: 14:32:38  iteration: 41599/375342  consumed_samples: 42598400  total_loss: 4.162  time: 0.3395 s/iter  data_time: 0.1921 s/iter total_throughput: 3015.86 samples/s lr: 9.70e-04  
[09/22 07:15:43] lb.utils.events INFO:  eta: 14:32:59  iteration: 41699/375342  consumed_samples: 42700800  total_loss: 4.148  time: 0.3395 s/iter  data_time: 0.2080 s/iter total_throughput: 3015.92 samples/s lr: 9.70e-04  
[09/22 07:16:17] lb.utils.events INFO:  eta: 14:32:22  iteration: 41799/375342  consumed_samples: 42803200  total_loss: 4.145  time: 0.3395 s/iter  data_time: 0.1947 s/iter total_throughput: 3016.04 samples/s lr: 9.70e-04  
[09/22 07:16:51] lb.utils.events INFO:  eta: 14:30:35  iteration: 41899/375342  consumed_samples: 42905600  total_loss: 4.156  time: 0.3395 s/iter  data_time: 0.2065 s/iter total_throughput: 3016.11 samples/s lr: 9.70e-04  
[09/22 07:17:25] lb.utils.events INFO:  eta: 14:30:31  iteration: 41999/375342  consumed_samples: 43008000  total_loss: 4.15  time: 0.3395 s/iter  data_time: 0.2251 s/iter total_throughput: 3016.01 samples/s lr: 9.70e-04  
[09/22 07:17:59] lb.utils.events INFO:  eta: 14:30:18  iteration: 42099/375342  consumed_samples: 43110400  total_loss: 4.156  time: 0.3395 s/iter  data_time: 0.2011 s/iter total_throughput: 3016.06 samples/s lr: 9.70e-04  
[09/22 07:18:33] lb.utils.events INFO:  eta: 14:30:02  iteration: 42199/375342  consumed_samples: 43212800  total_loss: 4.176  time: 0.3395 s/iter  data_time: 0.2260 s/iter total_throughput: 3015.99 samples/s lr: 9.69e-04  
[09/22 07:19:07] lb.utils.events INFO:  eta: 14:30:11  iteration: 42299/375342  consumed_samples: 43315200  total_loss: 4.172  time: 0.3395 s/iter  data_time: 0.2162 s/iter total_throughput: 3015.92 samples/s lr: 9.69e-04  
[09/22 07:19:41] lb.utils.events INFO:  eta: 14:31:02  iteration: 42399/375342  consumed_samples: 43417600  total_loss: 4.164  time: 0.3395 s/iter  data_time: 0.2106 s/iter total_throughput: 3015.90 samples/s lr: 9.69e-04  
[09/22 07:20:16] lb.utils.events INFO:  eta: 14:30:46  iteration: 42499/375342  consumed_samples: 43520000  total_loss: 4.141  time: 0.3395 s/iter  data_time: 0.2328 s/iter total_throughput: 3015.81 samples/s lr: 9.69e-04  
[09/22 07:20:50] lb.utils.events INFO:  eta: 14:30:25  iteration: 42599/375342  consumed_samples: 43622400  total_loss: 4.133  time: 0.3396 s/iter  data_time: 0.2179 s/iter total_throughput: 3015.69 samples/s lr: 9.69e-04  
[09/22 07:21:25] lb.utils.events INFO:  eta: 14:30:40  iteration: 42699/375342  consumed_samples: 43724800  total_loss: 4.166  time: 0.3396 s/iter  data_time: 0.2256 s/iter total_throughput: 3015.62 samples/s lr: 9.69e-04  
[09/22 07:21:59] lb.utils.events INFO:  eta: 14:31:55  iteration: 42799/375342  consumed_samples: 43827200  total_loss: 4.156  time: 0.3396 s/iter  data_time: 0.2227 s/iter total_throughput: 3015.50 samples/s lr: 9.69e-04  
[09/22 07:22:34] lb.utils.events INFO:  eta: 14:32:12  iteration: 42899/375342  consumed_samples: 43929600  total_loss: 4.135  time: 0.3396 s/iter  data_time: 0.2184 s/iter total_throughput: 3015.39 samples/s lr: 9.68e-04  
[09/22 07:23:08] lb.utils.events INFO:  eta: 14:32:21  iteration: 42999/375342  consumed_samples: 44032000  total_loss: 4.143  time: 0.3396 s/iter  data_time: 0.2184 s/iter total_throughput: 3015.34 samples/s lr: 9.68e-04  
[09/22 07:23:42] lb.utils.events INFO:  eta: 14:32:25  iteration: 43099/375342  consumed_samples: 44134400  total_loss: 4.152  time: 0.3396 s/iter  data_time: 0.2094 s/iter total_throughput: 3015.35 samples/s lr: 9.68e-04  
[09/22 07:24:16] lb.utils.events INFO:  eta: 14:32:01  iteration: 43199/375342  consumed_samples: 44236800  total_loss: 4.145  time: 0.3396 s/iter  data_time: 0.2201 s/iter total_throughput: 3015.31 samples/s lr: 9.68e-04  
[09/22 07:24:50] lb.utils.events INFO:  eta: 14:30:36  iteration: 43299/375342  consumed_samples: 44339200  total_loss: 4.127  time: 0.3396 s/iter  data_time: 0.2166 s/iter total_throughput: 3015.21 samples/s lr: 9.68e-04  
[09/22 07:25:25] lb.utils.events INFO:  eta: 14:29:57  iteration: 43399/375342  consumed_samples: 44441600  total_loss: 4.113  time: 0.3396 s/iter  data_time: 0.2180 s/iter total_throughput: 3015.05 samples/s lr: 9.68e-04  
[09/22 07:25:59] lb.utils.events INFO:  eta: 14:30:51  iteration: 43499/375342  consumed_samples: 44544000  total_loss: 4.139  time: 0.3396 s/iter  data_time: 0.2161 s/iter total_throughput: 3015.09 samples/s lr: 9.68e-04  
[09/22 07:26:33] lb.utils.events INFO:  eta: 14:30:40  iteration: 43599/375342  consumed_samples: 44646400  total_loss: 4.143  time: 0.3396 s/iter  data_time: 0.2169 s/iter total_throughput: 3015.02 samples/s lr: 9.67e-04  
[09/22 07:27:07] lb.utils.events INFO:  eta: 14:30:32  iteration: 43699/375342  consumed_samples: 44748800  total_loss: 4.137  time: 0.3396 s/iter  data_time: 0.2205 s/iter total_throughput: 3014.96 samples/s lr: 9.67e-04  
[09/22 07:27:42] lb.utils.events INFO:  eta: 14:30:08  iteration: 43799/375342  consumed_samples: 44851200  total_loss: 4.139  time: 0.3396 s/iter  data_time: 0.1977 s/iter total_throughput: 3014.93 samples/s lr: 9.67e-04  
[09/22 07:28:16] lb.utils.events INFO:  eta: 14:30:00  iteration: 43899/375342  consumed_samples: 44953600  total_loss: 4.113  time: 0.3396 s/iter  data_time: 0.2078 s/iter total_throughput: 3014.91 samples/s lr: 9.67e-04  
[09/22 07:28:50] lb.utils.events INFO:  eta: 14:26:46  iteration: 43999/375342  consumed_samples: 45056000  total_loss: 4.105  time: 0.3397 s/iter  data_time: 0.2243 s/iter total_throughput: 3014.77 samples/s lr: 9.67e-04  
[09/22 07:29:25] lb.utils.events INFO:  eta: 14:25:46  iteration: 44099/375342  consumed_samples: 45158400  total_loss: 4.109  time: 0.3397 s/iter  data_time: 0.2117 s/iter total_throughput: 3014.70 samples/s lr: 9.67e-04  
[09/22 07:29:59] lb.utils.events INFO:  eta: 14:23:39  iteration: 44199/375342  consumed_samples: 45260800  total_loss: 4.107  time: 0.3397 s/iter  data_time: 0.2277 s/iter total_throughput: 3014.53 samples/s lr: 9.67e-04  
[09/22 07:30:34] lb.utils.events INFO:  eta: 14:25:43  iteration: 44299/375342  consumed_samples: 45363200  total_loss: 4.115  time: 0.3397 s/iter  data_time: 0.2134 s/iter total_throughput: 3014.47 samples/s lr: 9.66e-04  
[09/22 07:31:08] lb.utils.events INFO:  eta: 14:26:45  iteration: 44399/375342  consumed_samples: 45465600  total_loss: 4.113  time: 0.3397 s/iter  data_time: 0.2100 s/iter total_throughput: 3014.44 samples/s lr: 9.66e-04  
[09/22 07:31:43] lb.utils.events INFO:  eta: 14:26:30  iteration: 44499/375342  consumed_samples: 45568000  total_loss: 4.111  time: 0.3397 s/iter  data_time: 0.2150 s/iter total_throughput: 3014.31 samples/s lr: 9.66e-04  
[09/22 07:32:17] lb.utils.events INFO:  eta: 14:24:47  iteration: 44599/375342  consumed_samples: 45670400  total_loss: 4.109  time: 0.3397 s/iter  data_time: 0.2344 s/iter total_throughput: 3014.21 samples/s lr: 9.66e-04  
[09/22 07:32:50] lb.utils.events INFO:  eta: 14:23:55  iteration: 44699/375342  consumed_samples: 45772800  total_loss: 4.154  time: 0.3397 s/iter  data_time: 0.2169 s/iter total_throughput: 3014.31 samples/s lr: 9.66e-04  
[09/22 07:33:25] lb.utils.events INFO:  eta: 14:23:45  iteration: 44799/375342  consumed_samples: 45875200  total_loss: 4.133  time: 0.3397 s/iter  data_time: 0.2097 s/iter total_throughput: 3014.22 samples/s lr: 9.66e-04  
[09/22 07:33:59] lb.utils.events INFO:  eta: 14:23:11  iteration: 44899/375342  consumed_samples: 45977600  total_loss: 4.127  time: 0.3397 s/iter  data_time: 0.2206 s/iter total_throughput: 3014.15 samples/s lr: 9.65e-04  
[09/22 07:34:33] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0044999
[09/22 07:34:34] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/22 07:34:34] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/22 07:34:38] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0943 s/iter. Inference: 0.1630 s/iter. Eval: 0.0021 s/iter. Total: 0.2593 s/iter. ETA=0:00:09
[09/22 07:34:43] lb.evaluation.evaluator INFO: Inference done 28672/50000. Dataloading: 0.0949 s/iter. Inference: 0.1888 s/iter. Eval: 0.0021 s/iter. Total: 0.2858 s/iter. ETA=0:00:05
[09/22 07:34:48] lb.evaluation.evaluator INFO: Inference done 46080/50000. Dataloading: 0.0947 s/iter. Inference: 0.1958 s/iter. Eval: 0.0020 s/iter. Total: 0.2925 s/iter. ETA=0:00:00
[09/22 07:34:49] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/22 07:34:49] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.632699 (0.000253 s / iter per device, on 8 devices)
[09/22 07:34:49] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:08 (0.000173 s / iter per device, on 8 devices)
[09/22 07:34:49] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/22 07:34:49] lb.evaluation.utils INFO: copypaste: Acc@1=65.848
[09/22 07:34:49] lb.evaluation.utils INFO: copypaste: Acc@5=87.354
[09/22 07:34:49] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 65.84800, better than last best score 64.67000 @ iteration 39999.
[09/22 07:34:49] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/22 07:34:50] lb.utils.events INFO:  eta: 14:24:03  iteration: 44999/375342  consumed_samples: 46080000  total_loss: 4.139  time: 0.3397 s/iter  data_time: 0.2185 s/iter total_throughput: 3014.13 samples/s lr: 9.65e-04  
[09/22 07:35:22] lb.utils.events INFO:  eta: 14:26:16  iteration: 45099/375342  consumed_samples: 46182400  total_loss: 4.113  time: 0.3397 s/iter  data_time: 0.2475 s/iter total_throughput: 3014.47 samples/s lr: 9.65e-04  
[09/22 07:35:56] lb.utils.events INFO:  eta: 14:28:58  iteration: 45199/375342  consumed_samples: 46284800  total_loss: 4.117  time: 0.3397 s/iter  data_time: 0.2032 s/iter total_throughput: 3014.51 samples/s lr: 9.65e-04  
[09/22 07:36:30] lb.utils.events INFO:  eta: 14:27:27  iteration: 45299/375342  consumed_samples: 46387200  total_loss: 4.117  time: 0.3397 s/iter  data_time: 0.2034 s/iter total_throughput: 3014.53 samples/s lr: 9.65e-04  
[09/22 07:37:04] lb.utils.events INFO:  eta: 14:27:58  iteration: 45399/375342  consumed_samples: 46489600  total_loss: 4.092  time: 0.3397 s/iter  data_time: 0.2070 s/iter total_throughput: 3014.46 samples/s lr: 9.65e-04  
[09/22 07:37:38] lb.utils.events INFO:  eta: 14:27:43  iteration: 45499/375342  consumed_samples: 46592000  total_loss: 4.098  time: 0.3397 s/iter  data_time: 0.2078 s/iter total_throughput: 3014.42 samples/s lr: 9.65e-04  
[09/22 07:38:13] lb.utils.events INFO:  eta: 14:28:00  iteration: 45599/375342  consumed_samples: 46694400  total_loss: 4.102  time: 0.3397 s/iter  data_time: 0.2224 s/iter total_throughput: 3014.35 samples/s lr: 9.64e-04  
[09/22 07:38:47] lb.utils.events INFO:  eta: 14:26:55  iteration: 45699/375342  consumed_samples: 46796800  total_loss: 4.109  time: 0.3397 s/iter  data_time: 0.2061 s/iter total_throughput: 3014.37 samples/s lr: 9.64e-04  
[09/22 07:39:21] lb.utils.events INFO:  eta: 14:27:01  iteration: 45799/375342  consumed_samples: 46899200  total_loss: 4.115  time: 0.3397 s/iter  data_time: 0.2083 s/iter total_throughput: 3014.38 samples/s lr: 9.64e-04  
[09/22 07:39:54] lb.utils.events INFO:  eta: 14:27:42  iteration: 45899/375342  consumed_samples: 47001600  total_loss: 4.121  time: 0.3397 s/iter  data_time: 0.2099 s/iter total_throughput: 3014.41 samples/s lr: 9.64e-04  
[09/22 07:40:29] lb.utils.events INFO:  eta: 14:26:40  iteration: 45999/375342  consumed_samples: 47104000  total_loss: 4.123  time: 0.3397 s/iter  data_time: 0.2257 s/iter total_throughput: 3014.24 samples/s lr: 9.64e-04  
[09/22 07:41:03] lb.utils.events INFO:  eta: 14:22:49  iteration: 46099/375342  consumed_samples: 47206400  total_loss: 4.125  time: 0.3397 s/iter  data_time: 0.2102 s/iter total_throughput: 3014.27 samples/s lr: 9.64e-04  
[09/22 07:41:37] lb.utils.events INFO:  eta: 14:20:17  iteration: 46199/375342  consumed_samples: 47308800  total_loss: 4.109  time: 0.3397 s/iter  data_time: 0.2034 s/iter total_throughput: 3014.23 samples/s lr: 9.63e-04  
[09/22 07:42:12] lb.utils.events INFO:  eta: 14:18:49  iteration: 46299/375342  consumed_samples: 47411200  total_loss: 4.09  time: 0.3397 s/iter  data_time: 0.2267 s/iter total_throughput: 3014.05 samples/s lr: 9.63e-04  
[09/22 07:42:46] lb.utils.events INFO:  eta: 14:18:01  iteration: 46399/375342  consumed_samples: 47513600  total_loss: 4.084  time: 0.3397 s/iter  data_time: 0.2058 s/iter total_throughput: 3014.06 samples/s lr: 9.63e-04  
[09/22 07:43:20] lb.utils.events INFO:  eta: 14:16:38  iteration: 46499/375342  consumed_samples: 47616000  total_loss: 4.098  time: 0.3397 s/iter  data_time: 0.2032 s/iter total_throughput: 3014.12 samples/s lr: 9.63e-04  
[09/22 07:43:54] lb.utils.events INFO:  eta: 14:17:03  iteration: 46599/375342  consumed_samples: 47718400  total_loss: 4.098  time: 0.3397 s/iter  data_time: 0.2071 s/iter total_throughput: 3014.13 samples/s lr: 9.63e-04  
[09/22 07:44:28] lb.utils.events INFO:  eta: 14:17:38  iteration: 46699/375342  consumed_samples: 47820800  total_loss: 4.094  time: 0.3397 s/iter  data_time: 0.2172 s/iter total_throughput: 3014.01 samples/s lr: 9.63e-04  
[09/22 07:45:03] lb.utils.events INFO:  eta: 14:15:44  iteration: 46799/375342  consumed_samples: 47923200  total_loss: 4.086  time: 0.3398 s/iter  data_time: 0.2218 s/iter total_throughput: 3013.80 samples/s lr: 9.63e-04  
[09/22 07:45:38] lb.utils.events INFO:  eta: 14:15:23  iteration: 46899/375342  consumed_samples: 48025600  total_loss: 4.086  time: 0.3398 s/iter  data_time: 0.2101 s/iter total_throughput: 3013.77 samples/s lr: 9.62e-04  
[09/22 07:46:11] lb.utils.events INFO:  eta: 14:16:43  iteration: 46999/375342  consumed_samples: 48128000  total_loss: 4.102  time: 0.3398 s/iter  data_time: 0.2137 s/iter total_throughput: 3013.79 samples/s lr: 9.62e-04  
[09/22 07:46:46] lb.utils.events INFO:  eta: 14:16:28  iteration: 47099/375342  consumed_samples: 48230400  total_loss: 4.117  time: 0.3398 s/iter  data_time: 0.2264 s/iter total_throughput: 3013.67 samples/s lr: 9.62e-04  
[09/22 07:47:21] lb.utils.events INFO:  eta: 14:15:25  iteration: 47199/375342  consumed_samples: 48332800  total_loss: 4.117  time: 0.3398 s/iter  data_time: 0.2483 s/iter total_throughput: 3013.48 samples/s lr: 9.62e-04  
[09/22 07:47:55] lb.utils.events INFO:  eta: 14:17:43  iteration: 47299/375342  consumed_samples: 48435200  total_loss: 4.113  time: 0.3398 s/iter  data_time: 0.2207 s/iter total_throughput: 3013.53 samples/s lr: 9.62e-04  
[09/22 07:48:29] lb.utils.events INFO:  eta: 14:16:33  iteration: 47399/375342  consumed_samples: 48537600  total_loss: 4.094  time: 0.3398 s/iter  data_time: 0.2087 s/iter total_throughput: 3013.45 samples/s lr: 9.62e-04  
[09/22 07:49:03] lb.utils.events INFO:  eta: 14:15:46  iteration: 47499/375342  consumed_samples: 48640000  total_loss: 4.098  time: 0.3398 s/iter  data_time: 0.2156 s/iter total_throughput: 3013.39 samples/s lr: 9.61e-04  
[09/22 07:49:37] lb.utils.events INFO:  eta: 14:17:08  iteration: 47599/375342  consumed_samples: 48742400  total_loss: 4.109  time: 0.3398 s/iter  data_time: 0.2176 s/iter total_throughput: 3013.42 samples/s lr: 9.61e-04  
[09/22 07:50:11] lb.utils.events INFO:  eta: 14:17:50  iteration: 47699/375342  consumed_samples: 48844800  total_loss: 4.094  time: 0.3398 s/iter  data_time: 0.2002 s/iter total_throughput: 3013.52 samples/s lr: 9.61e-04  
[09/22 07:50:44] lb.utils.events INFO:  eta: 14:20:13  iteration: 47799/375342  consumed_samples: 48947200  total_loss: 4.082  time: 0.3398 s/iter  data_time: 0.2089 s/iter total_throughput: 3013.60 samples/s lr: 9.61e-04  
[09/22 07:51:19] lb.utils.events INFO:  eta: 14:18:23  iteration: 47899/375342  consumed_samples: 49049600  total_loss: 4.09  time: 0.3398 s/iter  data_time: 0.2222 s/iter total_throughput: 3013.53 samples/s lr: 9.61e-04  
[09/22 07:51:53] lb.utils.events INFO:  eta: 14:17:36  iteration: 47999/375342  consumed_samples: 49152000  total_loss: 4.07  time: 0.3398 s/iter  data_time: 0.2137 s/iter total_throughput: 3013.48 samples/s lr: 9.61e-04  
[09/22 07:52:27] lb.utils.events INFO:  eta: 14:17:17  iteration: 48099/375342  consumed_samples: 49254400  total_loss: 4.068  time: 0.3398 s/iter  data_time: 0.2171 s/iter total_throughput: 3013.40 samples/s lr: 9.60e-04  
[09/22 07:53:01] lb.utils.events INFO:  eta: 14:19:49  iteration: 48199/375342  consumed_samples: 49356800  total_loss: 4.09  time: 0.3398 s/iter  data_time: 0.2135 s/iter total_throughput: 3013.39 samples/s lr: 9.60e-04  
[09/22 07:53:35] lb.utils.events INFO:  eta: 14:19:33  iteration: 48299/375342  consumed_samples: 49459200  total_loss: 4.08  time: 0.3398 s/iter  data_time: 0.2092 s/iter total_throughput: 3013.41 samples/s lr: 9.60e-04  
[09/22 07:54:09] lb.utils.events INFO:  eta: 14:21:36  iteration: 48399/375342  consumed_samples: 49561600  total_loss: 4.09  time: 0.3398 s/iter  data_time: 0.2025 s/iter total_throughput: 3013.40 samples/s lr: 9.60e-04  
[09/22 07:54:43] lb.utils.events INFO:  eta: 14:22:57  iteration: 48499/375342  consumed_samples: 49664000  total_loss: 4.102  time: 0.3398 s/iter  data_time: 0.2135 s/iter total_throughput: 3013.45 samples/s lr: 9.60e-04  
[09/22 07:55:17] lb.utils.events INFO:  eta: 14:22:51  iteration: 48599/375342  consumed_samples: 49766400  total_loss: 4.092  time: 0.3398 s/iter  data_time: 0.2232 s/iter total_throughput: 3013.43 samples/s lr: 9.60e-04  
[09/22 07:55:51] lb.utils.events INFO:  eta: 14:22:26  iteration: 48699/375342  consumed_samples: 49868800  total_loss: 4.082  time: 0.3398 s/iter  data_time: 0.2015 s/iter total_throughput: 3013.52 samples/s lr: 9.59e-04  
[09/22 07:56:25] lb.utils.events INFO:  eta: 14:20:01  iteration: 48799/375342  consumed_samples: 49971200  total_loss: 4.074  time: 0.3398 s/iter  data_time: 0.2260 s/iter total_throughput: 3013.44 samples/s lr: 9.59e-04  
[09/22 07:57:00] lb.utils.events INFO:  eta: 14:21:40  iteration: 48899/375342  consumed_samples: 50073600  total_loss: 4.041  time: 0.3398 s/iter  data_time: 0.2268 s/iter total_throughput: 3013.29 samples/s lr: 9.59e-04  
[09/22 07:57:34] lb.utils.events INFO:  eta: 14:20:21  iteration: 48999/375342  consumed_samples: 50176000  total_loss: 4.039  time: 0.3398 s/iter  data_time: 0.2246 s/iter total_throughput: 3013.20 samples/s lr: 9.59e-04  
[09/22 07:58:09] lb.utils.events INFO:  eta: 14:19:13  iteration: 49099/375342  consumed_samples: 50278400  total_loss: 4.064  time: 0.3398 s/iter  data_time: 0.2087 s/iter total_throughput: 3013.12 samples/s lr: 9.59e-04  
[09/22 07:58:43] lb.utils.events INFO:  eta: 14:17:21  iteration: 49199/375342  consumed_samples: 50380800  total_loss: 4.072  time: 0.3398 s/iter  data_time: 0.2206 s/iter total_throughput: 3013.14 samples/s lr: 9.59e-04  
[09/22 07:59:16] lb.utils.events INFO:  eta: 14:15:49  iteration: 49299/375342  consumed_samples: 50483200  total_loss: 4.055  time: 0.3398 s/iter  data_time: 0.2013 s/iter total_throughput: 3013.21 samples/s lr: 9.58e-04  
[09/22 07:59:50] lb.utils.events INFO:  eta: 14:16:14  iteration: 49399/375342  consumed_samples: 50585600  total_loss: 4.055  time: 0.3398 s/iter  data_time: 0.2009 s/iter total_throughput: 3013.24 samples/s lr: 9.58e-04  
[09/22 08:00:24] lb.utils.events INFO:  eta: 14:15:16  iteration: 49499/375342  consumed_samples: 50688000  total_loss: 4.07  time: 0.3398 s/iter  data_time: 0.2136 s/iter total_throughput: 3013.17 samples/s lr: 9.58e-04  
[09/22 08:00:59] lb.utils.events INFO:  eta: 14:13:49  iteration: 49599/375342  consumed_samples: 50790400  total_loss: 4.082  time: 0.3398 s/iter  data_time: 0.2212 s/iter total_throughput: 3013.17 samples/s lr: 9.58e-04  
[09/22 08:01:33] lb.utils.events INFO:  eta: 14:14:28  iteration: 49699/375342  consumed_samples: 50892800  total_loss: 4.072  time: 0.3398 s/iter  data_time: 0.2249 s/iter total_throughput: 3013.16 samples/s lr: 9.58e-04  
[09/22 08:02:06] lb.utils.events INFO:  eta: 14:14:12  iteration: 49799/375342  consumed_samples: 50995200  total_loss: 4.072  time: 0.3398 s/iter  data_time: 0.2056 s/iter total_throughput: 3013.21 samples/s lr: 9.58e-04  
[09/22 08:02:40] lb.utils.events INFO:  eta: 14:15:03  iteration: 49899/375342  consumed_samples: 51097600  total_loss: 4.072  time: 0.3398 s/iter  data_time: 0.2094 s/iter total_throughput: 3013.23 samples/s lr: 9.57e-04  
[09/22 08:03:14] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0049999
[09/22 08:03:15] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/22 08:03:15] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/22 08:03:19] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0960 s/iter. Inference: 0.1589 s/iter. Eval: 0.0020 s/iter. Total: 0.2569 s/iter. ETA=0:00:09
[09/22 08:03:24] lb.evaluation.evaluator INFO: Inference done 29696/50000. Dataloading: 0.1316 s/iter. Inference: 0.1677 s/iter. Eval: 0.0020 s/iter. Total: 0.3014 s/iter. ETA=0:00:05
[09/22 08:03:30] lb.evaluation.evaluator INFO: Inference done 50000/50000. Dataloading: 0.1130 s/iter. Inference: 0.1726 s/iter. Eval: 0.0020 s/iter. Total: 0.2876 s/iter. ETA=0:00:00
[09/22 08:03:30] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/22 08:03:30] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.660346 (0.000253 s / iter per device, on 8 devices)
[09/22 08:03:30] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000152 s / iter per device, on 8 devices)
[09/22 08:03:30] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/22 08:03:30] lb.evaluation.utils INFO: copypaste: Acc@1=66.72200000000001
[09/22 08:03:30] lb.evaluation.utils INFO: copypaste: Acc@5=87.968
[09/22 08:03:30] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 66.72200, better than last best score 65.84800 @ iteration 44999.
[09/22 08:03:30] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/22 08:03:31] lb.utils.events INFO:  eta: 14:14:23  iteration: 49999/375342  consumed_samples: 51200000  total_loss: 4.078  time: 0.3398 s/iter  data_time: 0.2118 s/iter total_throughput: 3013.28 samples/s lr: 9.57e-04  
[09/22 08:04:02] lb.utils.events INFO:  eta: 14:17:47  iteration: 50099/375342  consumed_samples: 51302400  total_loss: 4.09  time: 0.3398 s/iter  data_time: 0.2289 s/iter total_throughput: 3013.66 samples/s lr: 9.57e-04  
[09/22 08:04:37] lb.utils.events INFO:  eta: 14:23:36  iteration: 50199/375342  consumed_samples: 51404800  total_loss: 4.086  time: 0.3398 s/iter  data_time: 0.2156 s/iter total_throughput: 3013.62 samples/s lr: 9.57e-04  
[09/22 08:05:11] lb.utils.events INFO:  eta: 14:22:40  iteration: 50299/375342  consumed_samples: 51507200  total_loss: 4.07  time: 0.3398 s/iter  data_time: 0.2166 s/iter total_throughput: 3013.50 samples/s lr: 9.57e-04  
[09/22 08:05:45] lb.utils.events INFO:  eta: 14:20:06  iteration: 50399/375342  consumed_samples: 51609600  total_loss: 4.031  time: 0.3398 s/iter  data_time: 0.2105 s/iter total_throughput: 3013.54 samples/s lr: 9.57e-04  
[09/22 08:06:19] lb.utils.events INFO:  eta: 14:20:06  iteration: 50499/375342  consumed_samples: 51712000  total_loss: 4.064  time: 0.3398 s/iter  data_time: 0.2159 s/iter total_throughput: 3013.52 samples/s lr: 9.56e-04  
[09/22 08:06:54] lb.utils.events INFO:  eta: 14:19:34  iteration: 50599/375342  consumed_samples: 51814400  total_loss: 4.076  time: 0.3398 s/iter  data_time: 0.2167 s/iter total_throughput: 3013.42 samples/s lr: 9.56e-04  
[09/22 08:07:28] lb.utils.events INFO:  eta: 14:16:55  iteration: 50699/375342  consumed_samples: 51916800  total_loss: 4.043  time: 0.3398 s/iter  data_time: 0.2147 s/iter total_throughput: 3013.43 samples/s lr: 9.56e-04  
[09/22 08:08:01] lb.utils.events INFO:  eta: 14:16:13  iteration: 50799/375342  consumed_samples: 52019200  total_loss: 4.037  time: 0.3398 s/iter  data_time: 0.2051 s/iter total_throughput: 3013.46 samples/s lr: 9.56e-04  
[09/22 08:08:36] lb.utils.events INFO:  eta: 14:13:26  iteration: 50899/375342  consumed_samples: 52121600  total_loss: 4.055  time: 0.3398 s/iter  data_time: 0.1998 s/iter total_throughput: 3013.42 samples/s lr: 9.56e-04  
[09/22 08:09:10] lb.utils.events INFO:  eta: 14:12:14  iteration: 50999/375342  consumed_samples: 52224000  total_loss: 4.059  time: 0.3398 s/iter  data_time: 0.2371 s/iter total_throughput: 3013.34 samples/s lr: 9.56e-04  
[09/22 08:09:45] lb.utils.events INFO:  eta: 14:08:01  iteration: 51099/375342  consumed_samples: 52326400  total_loss: 4.07  time: 0.3398 s/iter  data_time: 0.2122 s/iter total_throughput: 3013.26 samples/s lr: 9.55e-04  
[09/22 08:10:19] lb.utils.events INFO:  eta: 14:04:03  iteration: 51199/375342  consumed_samples: 52428800  total_loss: 4.074  time: 0.3398 s/iter  data_time: 0.2091 s/iter total_throughput: 3013.24 samples/s lr: 9.55e-04  
[09/22 08:10:52] lb.utils.events INFO:  eta: 14:06:07  iteration: 51299/375342  consumed_samples: 52531200  total_loss: 4.068  time: 0.3398 s/iter  data_time: 0.2053 s/iter total_throughput: 3013.34 samples/s lr: 9.55e-04  
[09/22 08:11:26] lb.utils.events INFO:  eta: 14:07:14  iteration: 51399/375342  consumed_samples: 52633600  total_loss: 4.062  time: 0.3398 s/iter  data_time: 0.2094 s/iter total_throughput: 3013.44 samples/s lr: 9.55e-04  
[09/22 08:12:00] lb.utils.events INFO:  eta: 14:07:00  iteration: 51499/375342  consumed_samples: 52736000  total_loss: 4.057  time: 0.3398 s/iter  data_time: 0.2155 s/iter total_throughput: 3013.40 samples/s lr: 9.55e-04  
[09/22 08:12:34] lb.utils.events INFO:  eta: 14:06:46  iteration: 51599/375342  consumed_samples: 52838400  total_loss: 4.039  time: 0.3398 s/iter  data_time: 0.2124 s/iter total_throughput: 3013.40 samples/s lr: 9.55e-04  
[09/22 08:13:07] lb.utils.events INFO:  eta: 14:07:56  iteration: 51699/375342  consumed_samples: 52940800  total_loss: 4.047  time: 0.3398 s/iter  data_time: 0.2066 s/iter total_throughput: 3013.52 samples/s lr: 9.54e-04  
[09/22 08:13:41] lb.utils.events INFO:  eta: 14:06:13  iteration: 51799/375342  consumed_samples: 53043200  total_loss: 4.066  time: 0.3398 s/iter  data_time: 0.2091 s/iter total_throughput: 3013.49 samples/s lr: 9.54e-04  
[09/22 08:14:15] lb.utils.events INFO:  eta: 14:08:50  iteration: 51899/375342  consumed_samples: 53145600  total_loss: 4.049  time: 0.3398 s/iter  data_time: 0.2063 s/iter total_throughput: 3013.51 samples/s lr: 9.54e-04  
[09/22 08:14:49] lb.utils.events INFO:  eta: 14:09:45  iteration: 51999/375342  consumed_samples: 53248000  total_loss: 4.039  time: 0.3398 s/iter  data_time: 0.2290 s/iter total_throughput: 3013.51 samples/s lr: 9.54e-04  
[09/22 08:15:23] lb.utils.events INFO:  eta: 14:11:45  iteration: 52099/375342  consumed_samples: 53350400  total_loss: 4.051  time: 0.3398 s/iter  data_time: 0.2240 s/iter total_throughput: 3013.54 samples/s lr: 9.54e-04  
[09/22 08:15:57] lb.utils.events INFO:  eta: 14:11:21  iteration: 52199/375342  consumed_samples: 53452800  total_loss: 4.066  time: 0.3398 s/iter  data_time: 0.2100 s/iter total_throughput: 3013.48 samples/s lr: 9.54e-04  
[09/22 08:16:31] lb.utils.events INFO:  eta: 14:08:38  iteration: 52299/375342  consumed_samples: 53555200  total_loss: 4.084  time: 0.3398 s/iter  data_time: 0.2085 s/iter total_throughput: 3013.49 samples/s lr: 9.53e-04  
[09/22 08:17:05] lb.utils.events INFO:  eta: 14:07:22  iteration: 52399/375342  consumed_samples: 53657600  total_loss: 4.074  time: 0.3398 s/iter  data_time: 0.2086 s/iter total_throughput: 3013.53 samples/s lr: 9.53e-04  
[09/22 08:17:39] lb.utils.events INFO:  eta: 14:06:14  iteration: 52499/375342  consumed_samples: 53760000  total_loss: 4.068  time: 0.3398 s/iter  data_time: 0.2046 s/iter total_throughput: 3013.49 samples/s lr: 9.53e-04  
[09/22 08:18:13] lb.utils.events INFO:  eta: 14:06:00  iteration: 52599/375342  consumed_samples: 53862400  total_loss: 4.049  time: 0.3398 s/iter  data_time: 0.2183 s/iter total_throughput: 3013.48 samples/s lr: 9.53e-04  
[09/22 08:18:47] lb.utils.events INFO:  eta: 14:04:09  iteration: 52699/375342  consumed_samples: 53964800  total_loss: 4.035  time: 0.3398 s/iter  data_time: 0.2213 s/iter total_throughput: 3013.48 samples/s lr: 9.53e-04  
[09/22 08:19:21] lb.utils.events INFO:  eta: 14:04:49  iteration: 52799/375342  consumed_samples: 54067200  total_loss: 4.047  time: 0.3398 s/iter  data_time: 0.2168 s/iter total_throughput: 3013.54 samples/s lr: 9.52e-04  
[09/22 08:19:55] lb.utils.events INFO:  eta: 14:03:11  iteration: 52899/375342  consumed_samples: 54169600  total_loss: 4.047  time: 0.3398 s/iter  data_time: 0.2244 s/iter total_throughput: 3013.56 samples/s lr: 9.52e-04  
[09/22 08:20:29] lb.utils.events INFO:  eta: 14:01:34  iteration: 52999/375342  consumed_samples: 54272000  total_loss: 4.062  time: 0.3398 s/iter  data_time: 0.2103 s/iter total_throughput: 3013.56 samples/s lr: 9.52e-04  
[09/22 08:21:03] lb.utils.events INFO:  eta: 14:00:06  iteration: 53099/375342  consumed_samples: 54374400  total_loss: 4.066  time: 0.3398 s/iter  data_time: 0.2119 s/iter total_throughput: 3013.50 samples/s lr: 9.52e-04  
[09/22 08:21:37] lb.utils.events INFO:  eta: 13:58:02  iteration: 53199/375342  consumed_samples: 54476800  total_loss: 4.035  time: 0.3398 s/iter  data_time: 0.2236 s/iter total_throughput: 3013.51 samples/s lr: 9.52e-04  
[09/22 08:22:11] lb.utils.events INFO:  eta: 14:00:18  iteration: 53299/375342  consumed_samples: 54579200  total_loss: 4.023  time: 0.3398 s/iter  data_time: 0.2043 s/iter total_throughput: 3013.52 samples/s lr: 9.52e-04  
[09/22 08:22:45] lb.utils.events INFO:  eta: 13:59:44  iteration: 53399/375342  consumed_samples: 54681600  total_loss: 4.037  time: 0.3398 s/iter  data_time: 0.2033 s/iter total_throughput: 3013.55 samples/s lr: 9.51e-04  
[09/22 08:23:19] lb.utils.events INFO:  eta: 13:59:28  iteration: 53499/375342  consumed_samples: 54784000  total_loss: 4.057  time: 0.3398 s/iter  data_time: 0.2194 s/iter total_throughput: 3013.46 samples/s lr: 9.51e-04  
[09/22 08:23:53] lb.utils.events INFO:  eta: 13:59:12  iteration: 53599/375342  consumed_samples: 54886400  total_loss: 4.047  time: 0.3398 s/iter  data_time: 0.2229 s/iter total_throughput: 3013.46 samples/s lr: 9.51e-04  
[09/22 08:24:27] lb.utils.events INFO:  eta: 13:59:15  iteration: 53699/375342  consumed_samples: 54988800  total_loss: 4.037  time: 0.3398 s/iter  data_time: 0.2024 s/iter total_throughput: 3013.56 samples/s lr: 9.51e-04  
[09/22 08:25:00] lb.utils.events INFO:  eta: 13:59:31  iteration: 53799/375342  consumed_samples: 55091200  total_loss: 4.045  time: 0.3398 s/iter  data_time: 0.2012 s/iter total_throughput: 3013.62 samples/s lr: 9.51e-04  
[09/22 08:25:35] lb.utils.events INFO:  eta: 13:59:16  iteration: 53899/375342  consumed_samples: 55193600  total_loss: 4.039  time: 0.3398 s/iter  data_time: 0.2301 s/iter total_throughput: 3013.57 samples/s lr: 9.50e-04  
[09/22 08:26:08] lb.utils.events INFO:  eta: 13:59:21  iteration: 53999/375342  consumed_samples: 55296000  total_loss: 4.025  time: 0.3398 s/iter  data_time: 0.2092 s/iter total_throughput: 3013.60 samples/s lr: 9.50e-04  
[09/22 08:26:43] lb.utils.events INFO:  eta: 13:58:42  iteration: 54099/375342  consumed_samples: 55398400  total_loss: 4.012  time: 0.3398 s/iter  data_time: 0.2377 s/iter total_throughput: 3013.51 samples/s lr: 9.50e-04  
[09/22 08:27:17] lb.utils.events INFO:  eta: 14:00:17  iteration: 54199/375342  consumed_samples: 55500800  total_loss: 4.02  time: 0.3398 s/iter  data_time: 0.2181 s/iter total_throughput: 3013.53 samples/s lr: 9.50e-04  
[09/22 08:27:51] lb.utils.events INFO:  eta: 13:58:34  iteration: 54299/375342  consumed_samples: 55603200  total_loss: 4.039  time: 0.3398 s/iter  data_time: 0.2221 s/iter total_throughput: 3013.55 samples/s lr: 9.50e-04  
[09/22 08:28:24] lb.utils.events INFO:  eta: 13:58:47  iteration: 54399/375342  consumed_samples: 55705600  total_loss: 4.027  time: 0.3398 s/iter  data_time: 0.2199 s/iter total_throughput: 3013.61 samples/s lr: 9.50e-04  
[09/22 08:28:58] lb.utils.events INFO:  eta: 13:58:20  iteration: 54499/375342  consumed_samples: 55808000  total_loss: 4.006  time: 0.3398 s/iter  data_time: 0.2070 s/iter total_throughput: 3013.61 samples/s lr: 9.49e-04  
[09/22 08:29:32] lb.utils.events INFO:  eta: 13:57:17  iteration: 54599/375342  consumed_samples: 55910400  total_loss: 4.018  time: 0.3398 s/iter  data_time: 0.2105 s/iter total_throughput: 3013.57 samples/s lr: 9.49e-04  
[09/22 08:30:06] lb.utils.events INFO:  eta: 13:58:22  iteration: 54699/375342  consumed_samples: 56012800  total_loss: 4.02  time: 0.3398 s/iter  data_time: 0.2046 s/iter total_throughput: 3013.67 samples/s lr: 9.49e-04  
[09/22 08:30:40] lb.utils.events INFO:  eta: 13:56:25  iteration: 54799/375342  consumed_samples: 56115200  total_loss: 4.033  time: 0.3398 s/iter  data_time: 0.2145 s/iter total_throughput: 3013.64 samples/s lr: 9.49e-04  
[09/22 08:31:14] lb.utils.events INFO:  eta: 13:56:38  iteration: 54899/375342  consumed_samples: 56217600  total_loss: 4.055  time: 0.3398 s/iter  data_time: 0.2318 s/iter total_throughput: 3013.67 samples/s lr: 9.49e-04  
[09/22 08:31:48] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0054999
[09/22 08:31:48] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/22 08:31:48] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/22 08:31:53] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0949 s/iter. Inference: 0.1676 s/iter. Eval: 0.0022 s/iter. Total: 0.2646 s/iter. ETA=0:00:09
[09/22 08:31:58] lb.evaluation.evaluator INFO: Inference done 29696/50000. Dataloading: 0.1190 s/iter. Inference: 0.1755 s/iter. Eval: 0.0021 s/iter. Total: 0.2967 s/iter. ETA=0:00:05
[09/22 08:32:03] lb.evaluation.evaluator INFO: Inference done 49152/50000. Dataloading: 0.0972 s/iter. Inference: 0.1828 s/iter. Eval: 0.0020 s/iter. Total: 0.2821 s/iter. ETA=0:00:00
[09/22 08:32:03] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/22 08:32:03] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.568164 (0.000251 s / iter per device, on 8 devices)
[09/22 08:32:03] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:08 (0.000161 s / iter per device, on 8 devices)
[09/22 08:32:03] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/22 08:32:03] lb.evaluation.utils INFO: copypaste: Acc@1=67.42399999999999
[09/22 08:32:03] lb.evaluation.utils INFO: copypaste: Acc@5=88.188
[09/22 08:32:03] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 67.42400, better than last best score 66.72200 @ iteration 49999.
[09/22 08:32:04] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/22 08:32:04] lb.utils.events INFO:  eta: 13:55:30  iteration: 54999/375342  consumed_samples: 56320000  total_loss: 4.053  time: 0.3398 s/iter  data_time: 0.2081 s/iter total_throughput: 3013.67 samples/s lr: 9.48e-04  
[09/22 08:32:36] lb.utils.events INFO:  eta: 13:58:40  iteration: 55099/375342  consumed_samples: 56422400  total_loss: 4.023  time: 0.3397 s/iter  data_time: 0.2138 s/iter total_throughput: 3014.03 samples/s lr: 9.48e-04  
[09/22 08:33:09] lb.utils.events INFO:  eta: 13:58:40  iteration: 55199/375342  consumed_samples: 56524800  total_loss: 4.02  time: 0.3397 s/iter  data_time: 0.1977 s/iter total_throughput: 3014.13 samples/s lr: 9.48e-04  
[09/22 08:33:43] lb.utils.events INFO:  eta: 13:58:31  iteration: 55299/375342  consumed_samples: 56627200  total_loss: 4.016  time: 0.3397 s/iter  data_time: 0.2131 s/iter total_throughput: 3014.14 samples/s lr: 9.48e-04  
[09/22 08:34:17] lb.utils.events INFO:  eta: 13:57:04  iteration: 55399/375342  consumed_samples: 56729600  total_loss: 4.016  time: 0.3397 s/iter  data_time: 0.2090 s/iter total_throughput: 3014.14 samples/s lr: 9.48e-04  
[09/22 08:34:51] lb.utils.events INFO:  eta: 13:57:26  iteration: 55499/375342  consumed_samples: 56832000  total_loss: 4.031  time: 0.3397 s/iter  data_time: 0.2000 s/iter total_throughput: 3014.25 samples/s lr: 9.48e-04  
[09/22 08:35:24] lb.utils.events INFO:  eta: 13:57:33  iteration: 55599/375342  consumed_samples: 56934400  total_loss: 4.049  time: 0.3397 s/iter  data_time: 0.2147 s/iter total_throughput: 3014.34 samples/s lr: 9.47e-04  
[09/22 08:35:57] lb.utils.events INFO:  eta: 13:57:12  iteration: 55699/375342  consumed_samples: 57036800  total_loss: 4.02  time: 0.3397 s/iter  data_time: 0.2026 s/iter total_throughput: 3014.43 samples/s lr: 9.47e-04  
[09/22 08:36:31] lb.utils.events INFO:  eta: 13:58:46  iteration: 55799/375342  consumed_samples: 57139200  total_loss: 4.001  time: 0.3397 s/iter  data_time: 0.2020 s/iter total_throughput: 3014.54 samples/s lr: 9.47e-04  
[09/22 08:37:04] lb.utils.events INFO:  eta: 14:00:31  iteration: 55899/375342  consumed_samples: 57241600  total_loss: 4.016  time: 0.3397 s/iter  data_time: 0.2048 s/iter total_throughput: 3014.63 samples/s lr: 9.47e-04  
[09/22 08:37:38] lb.utils.events INFO:  eta: 14:01:25  iteration: 55999/375342  consumed_samples: 57344000  total_loss: 4.02  time: 0.3397 s/iter  data_time: 0.2176 s/iter total_throughput: 3014.68 samples/s lr: 9.47e-04  
[09/22 08:38:12] lb.utils.events INFO:  eta: 13:59:16  iteration: 56099/375342  consumed_samples: 57446400  total_loss: 4.035  time: 0.3397 s/iter  data_time: 0.2114 s/iter total_throughput: 3014.66 samples/s lr: 9.46e-04  
[09/22 08:38:46] lb.utils.events INFO:  eta: 13:58:09  iteration: 56199/375342  consumed_samples: 57548800  total_loss: 4.059  time: 0.3397 s/iter  data_time: 0.2141 s/iter total_throughput: 3014.60 samples/s lr: 9.46e-04  
[09/22 08:39:20] lb.utils.events INFO:  eta: 13:59:28  iteration: 56299/375342  consumed_samples: 57651200  total_loss: 4.041  time: 0.3397 s/iter  data_time: 0.2071 s/iter total_throughput: 3014.63 samples/s lr: 9.46e-04  
[09/22 08:39:54] lb.utils.events INFO:  eta: 14:02:07  iteration: 56399/375342  consumed_samples: 57753600  total_loss: 4.004  time: 0.3397 s/iter  data_time: 0.2122 s/iter total_throughput: 3014.61 samples/s lr: 9.46e-04  
[09/22 08:40:28] lb.utils.events INFO:  eta: 14:02:23  iteration: 56499/375342  consumed_samples: 57856000  total_loss: 3.999  time: 0.3397 s/iter  data_time: 0.2242 s/iter total_throughput: 3014.56 samples/s lr: 9.46e-04  
[09/22 08:41:03] lb.utils.events INFO:  eta: 14:02:27  iteration: 56599/375342  consumed_samples: 57958400  total_loss: 4.012  time: 0.3397 s/iter  data_time: 0.2213 s/iter total_throughput: 3014.46 samples/s lr: 9.45e-04  
[09/22 08:41:38] lb.utils.events INFO:  eta: 14:01:19  iteration: 56699/375342  consumed_samples: 58060800  total_loss: 4.027  time: 0.3397 s/iter  data_time: 0.2324 s/iter total_throughput: 3014.36 samples/s lr: 9.45e-04  
[09/22 08:42:11] lb.utils.events INFO:  eta: 14:00:56  iteration: 56799/375342  consumed_samples: 58163200  total_loss: 4.01  time: 0.3397 s/iter  data_time: 0.2082 s/iter total_throughput: 3014.39 samples/s lr: 9.45e-04  
[09/22 08:42:45] lb.utils.events INFO:  eta: 14:00:47  iteration: 56899/375342  consumed_samples: 58265600  total_loss: 4.008  time: 0.3397 s/iter  data_time: 0.2171 s/iter total_throughput: 3014.41 samples/s lr: 9.45e-04  
[09/22 08:43:19] lb.utils.events INFO:  eta: 14:00:31  iteration: 56999/375342  consumed_samples: 58368000  total_loss: 4.023  time: 0.3397 s/iter  data_time: 0.2123 s/iter total_throughput: 3014.44 samples/s lr: 9.45e-04  
[09/22 08:43:53] lb.utils.events INFO:  eta: 13:59:31  iteration: 57099/375342  consumed_samples: 58470400  total_loss: 4.029  time: 0.3397 s/iter  data_time: 0.2111 s/iter total_throughput: 3014.47 samples/s lr: 9.45e-04  
[09/22 08:44:27] lb.utils.events INFO:  eta: 13:59:15  iteration: 57199/375342  consumed_samples: 58572800  total_loss: 4.025  time: 0.3397 s/iter  data_time: 0.1960 s/iter total_throughput: 3014.48 samples/s lr: 9.44e-04  
[09/22 08:45:01] lb.utils.events INFO:  eta: 13:57:56  iteration: 57299/375342  consumed_samples: 58675200  total_loss: 4.012  time: 0.3397 s/iter  data_time: 0.2239 s/iter total_throughput: 3014.48 samples/s lr: 9.44e-04  
[09/22 08:45:36] lb.utils.events INFO:  eta: 13:55:34  iteration: 57399/375342  consumed_samples: 58777600  total_loss: 4.01  time: 0.3397 s/iter  data_time: 0.2190 s/iter total_throughput: 3014.35 samples/s lr: 9.44e-04  
[09/22 08:46:10] lb.utils.events INFO:  eta: 13:56:42  iteration: 57499/375342  consumed_samples: 58880000  total_loss: 4.02  time: 0.3397 s/iter  data_time: 0.2094 s/iter total_throughput: 3014.31 samples/s lr: 9.44e-04  
[09/22 08:46:44] lb.utils.events INFO:  eta: 13:54:59  iteration: 57599/375342  consumed_samples: 58982400  total_loss: 4.025  time: 0.3397 s/iter  data_time: 0.2254 s/iter total_throughput: 3014.24 samples/s lr: 9.44e-04  
[09/22 08:47:18] lb.utils.events INFO:  eta: 13:54:37  iteration: 57699/375342  consumed_samples: 59084800  total_loss: 4.016  time: 0.3397 s/iter  data_time: 0.2258 s/iter total_throughput: 3014.25 samples/s lr: 9.43e-04  
[09/22 08:47:52] lb.utils.events INFO:  eta: 13:56:07  iteration: 57799/375342  consumed_samples: 59187200  total_loss: 4.014  time: 0.3397 s/iter  data_time: 0.2186 s/iter total_throughput: 3014.30 samples/s lr: 9.43e-04  
[09/22 08:48:25] lb.utils.events INFO:  eta: 13:56:19  iteration: 57899/375342  consumed_samples: 59289600  total_loss: 4.037  time: 0.3397 s/iter  data_time: 0.2070 s/iter total_throughput: 3014.40 samples/s lr: 9.43e-04  
[09/22 08:48:59] lb.utils.events INFO:  eta: 13:55:50  iteration: 57999/375342  consumed_samples: 59392000  total_loss: 4.027  time: 0.3397 s/iter  data_time: 0.2033 s/iter total_throughput: 3014.44 samples/s lr: 9.43e-04  
[09/22 08:49:33] lb.utils.events INFO:  eta: 13:55:48  iteration: 58099/375342  consumed_samples: 59494400  total_loss: 4.004  time: 0.3397 s/iter  data_time: 0.2267 s/iter total_throughput: 3014.44 samples/s lr: 9.43e-04  
[09/22 08:50:07] lb.utils.events INFO:  eta: 13:55:01  iteration: 58199/375342  consumed_samples: 59596800  total_loss: 3.999  time: 0.3397 s/iter  data_time: 0.2147 s/iter total_throughput: 3014.46 samples/s lr: 9.42e-04  
[09/22 08:50:40] lb.utils.events INFO:  eta: 13:55:02  iteration: 58299/375342  consumed_samples: 59699200  total_loss: 4.004  time: 0.3397 s/iter  data_time: 0.2063 s/iter total_throughput: 3014.53 samples/s lr: 9.42e-04  
[09/22 08:51:14] lb.utils.events INFO:  eta: 13:57:06  iteration: 58399/375342  consumed_samples: 59801600  total_loss: 4  time: 0.3397 s/iter  data_time: 0.2129 s/iter total_throughput: 3014.54 samples/s lr: 9.42e-04  
[09/22 08:51:48] lb.utils.events INFO:  eta: 13:55:21  iteration: 58499/375342  consumed_samples: 59904000  total_loss: 3.986  time: 0.3397 s/iter  data_time: 0.2086 s/iter total_throughput: 3014.51 samples/s lr: 9.42e-04  
[09/22 08:52:23] lb.utils.events INFO:  eta: 13:56:40  iteration: 58599/375342  consumed_samples: 60006400  total_loss: 3.981  time: 0.3397 s/iter  data_time: 0.2101 s/iter total_throughput: 3014.48 samples/s lr: 9.42e-04  
[09/22 08:52:57] lb.utils.events INFO:  eta: 13:55:56  iteration: 58699/375342  consumed_samples: 60108800  total_loss: 3.993  time: 0.3397 s/iter  data_time: 0.2199 s/iter total_throughput: 3014.45 samples/s lr: 9.41e-04  
[09/22 08:53:31] lb.utils.events INFO:  eta: 13:52:42  iteration: 58799/375342  consumed_samples: 60211200  total_loss: 4.016  time: 0.3397 s/iter  data_time: 0.2142 s/iter total_throughput: 3014.45 samples/s lr: 9.41e-04  
[09/22 08:54:04] lb.utils.events INFO:  eta: 13:51:44  iteration: 58899/375342  consumed_samples: 60313600  total_loss: 3.997  time: 0.3397 s/iter  data_time: 0.2036 s/iter total_throughput: 3014.49 samples/s lr: 9.41e-04  
[09/22 08:54:38] lb.utils.events INFO:  eta: 13:52:10  iteration: 58999/375342  consumed_samples: 60416000  total_loss: 3.982  time: 0.3397 s/iter  data_time: 0.2120 s/iter total_throughput: 3014.53 samples/s lr: 9.41e-04  
[09/22 08:55:12] lb.utils.events INFO:  eta: 13:50:26  iteration: 59099/375342  consumed_samples: 60518400  total_loss: 3.983  time: 0.3397 s/iter  data_time: 0.2246 s/iter total_throughput: 3014.51 samples/s lr: 9.41e-04  
[09/22 08:55:47] lb.utils.events INFO:  eta: 13:51:24  iteration: 59199/375342  consumed_samples: 60620800  total_loss: 3.991  time: 0.3397 s/iter  data_time: 0.2331 s/iter total_throughput: 3014.43 samples/s lr: 9.40e-04  
[09/22 08:56:21] lb.utils.events INFO:  eta: 13:49:57  iteration: 59299/375342  consumed_samples: 60723200  total_loss: 3.985  time: 0.3397 s/iter  data_time: 0.2084 s/iter total_throughput: 3014.44 samples/s lr: 9.40e-04  
[09/22 08:56:55] lb.utils.events INFO:  eta: 13:49:29  iteration: 59399/375342  consumed_samples: 60825600  total_loss: 3.984  time: 0.3397 s/iter  data_time: 0.2206 s/iter total_throughput: 3014.44 samples/s lr: 9.40e-04  
[09/22 08:57:29] lb.utils.events INFO:  eta: 13:49:25  iteration: 59499/375342  consumed_samples: 60928000  total_loss: 3.99  time: 0.3397 s/iter  data_time: 0.2140 s/iter total_throughput: 3014.44 samples/s lr: 9.40e-04  
[09/22 08:58:03] lb.utils.events INFO:  eta: 13:48:19  iteration: 59599/375342  consumed_samples: 61030400  total_loss: 4  time: 0.3397 s/iter  data_time: 0.2061 s/iter total_throughput: 3014.44 samples/s lr: 9.40e-04  
[09/22 08:58:37] lb.utils.events INFO:  eta: 13:46:39  iteration: 59699/375342  consumed_samples: 61132800  total_loss: 3.993  time: 0.3397 s/iter  data_time: 0.2151 s/iter total_throughput: 3014.39 samples/s lr: 9.39e-04  
[09/22 08:59:11] lb.utils.events INFO:  eta: 13:48:51  iteration: 59799/375342  consumed_samples: 61235200  total_loss: 3.984  time: 0.3397 s/iter  data_time: 0.2085 s/iter total_throughput: 3014.41 samples/s lr: 9.39e-04  
[09/22 08:59:45] lb.utils.events INFO:  eta: 13:48:40  iteration: 59899/375342  consumed_samples: 61337600  total_loss: 4.004  time: 0.3397 s/iter  data_time: 0.2152 s/iter total_throughput: 3014.41 samples/s lr: 9.39e-04  
[09/22 09:00:19] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0059999
[09/22 09:00:19] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/22 09:00:19] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/22 09:00:23] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0824 s/iter. Inference: 0.1728 s/iter. Eval: 0.0021 s/iter. Total: 0.2573 s/iter. ETA=0:00:09
[09/22 09:00:28] lb.evaluation.evaluator INFO: Inference done 28672/50000. Dataloading: 0.0797 s/iter. Inference: 0.2049 s/iter. Eval: 0.0019 s/iter. Total: 0.2866 s/iter. ETA=0:00:05
[09/22 09:00:34] lb.evaluation.evaluator INFO: Inference done 46080/50000. Dataloading: 0.0752 s/iter. Inference: 0.2140 s/iter. Eval: 0.0020 s/iter. Total: 0.2912 s/iter. ETA=0:00:00
[09/22 09:00:34] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/22 09:00:34] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.597567 (0.000252 s / iter per device, on 8 devices)
[09/22 09:00:34] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:09 (0.000190 s / iter per device, on 8 devices)
[09/22 09:00:34] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/22 09:00:34] lb.evaluation.utils INFO: copypaste: Acc@1=68.438
[09/22 09:00:34] lb.evaluation.utils INFO: copypaste: Acc@5=88.804
[09/22 09:00:34] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 68.43800, better than last best score 67.42400 @ iteration 54999.
[09/22 09:00:34] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/22 09:00:35] lb.utils.events INFO:  eta: 13:48:41  iteration: 59999/375342  consumed_samples: 61440000  total_loss: 4.004  time: 0.3397 s/iter  data_time: 0.2129 s/iter total_throughput: 3014.40 samples/s lr: 9.39e-04  
[09/22 09:01:07] lb.utils.events INFO:  eta: 13:49:24  iteration: 60099/375342  consumed_samples: 61542400  total_loss: 4.014  time: 0.3397 s/iter  data_time: 0.2051 s/iter total_throughput: 3014.75 samples/s lr: 9.39e-04  
[09/22 09:01:40] lb.utils.events INFO:  eta: 13:49:31  iteration: 60199/375342  consumed_samples: 61644800  total_loss: 3.999  time: 0.3397 s/iter  data_time: 0.2233 s/iter total_throughput: 3014.82 samples/s lr: 9.38e-04  
[09/22 09:02:14] lb.utils.events INFO:  eta: 13:52:02  iteration: 60299/375342  consumed_samples: 61747200  total_loss: 3.991  time: 0.3397 s/iter  data_time: 0.2105 s/iter total_throughput: 3014.82 samples/s lr: 9.38e-04  
[09/22 09:02:48] lb.utils.events INFO:  eta: 13:54:02  iteration: 60399/375342  consumed_samples: 61849600  total_loss: 3.993  time: 0.3397 s/iter  data_time: 0.2131 s/iter total_throughput: 3014.81 samples/s lr: 9.38e-04  
[09/22 09:03:22] lb.utils.events INFO:  eta: 13:55:24  iteration: 60499/375342  consumed_samples: 61952000  total_loss: 3.995  time: 0.3397 s/iter  data_time: 0.1997 s/iter total_throughput: 3014.81 samples/s lr: 9.38e-04  
[09/22 09:03:56] lb.utils.events INFO:  eta: 13:55:49  iteration: 60599/375342  consumed_samples: 62054400  total_loss: 3.997  time: 0.3397 s/iter  data_time: 0.2080 s/iter total_throughput: 3014.81 samples/s lr: 9.38e-04  
[09/22 09:04:30] lb.utils.events INFO:  eta: 13:58:21  iteration: 60699/375342  consumed_samples: 62156800  total_loss: 4.008  time: 0.3397 s/iter  data_time: 0.2019 s/iter total_throughput: 3014.81 samples/s lr: 9.37e-04  
[09/22 09:05:05] lb.utils.events INFO:  eta: 13:56:51  iteration: 60799/375342  consumed_samples: 62259200  total_loss: 4.016  time: 0.3397 s/iter  data_time: 0.2103 s/iter total_throughput: 3014.77 samples/s lr: 9.37e-04  
[09/22 09:05:38] lb.utils.events INFO:  eta: 13:55:56  iteration: 60899/375342  consumed_samples: 62361600  total_loss: 3.995  time: 0.3397 s/iter  data_time: 0.2128 s/iter total_throughput: 3014.78 samples/s lr: 9.37e-04  
[09/22 09:06:12] lb.utils.events INFO:  eta: 13:54:51  iteration: 60999/375342  consumed_samples: 62464000  total_loss: 3.994  time: 0.3397 s/iter  data_time: 0.2143 s/iter total_throughput: 3014.81 samples/s lr: 9.37e-04  
[09/22 09:06:46] lb.utils.events INFO:  eta: 13:52:41  iteration: 61099/375342  consumed_samples: 62566400  total_loss: 3.99  time: 0.3397 s/iter  data_time: 0.2125 s/iter total_throughput: 3014.85 samples/s lr: 9.37e-04  
[09/22 09:07:20] lb.utils.events INFO:  eta: 13:49:15  iteration: 61199/375342  consumed_samples: 62668800  total_loss: 3.976  time: 0.3397 s/iter  data_time: 0.2264 s/iter total_throughput: 3014.77 samples/s lr: 9.36e-04  
[09/22 09:07:54] lb.utils.events INFO:  eta: 13:47:37  iteration: 61299/375342  consumed_samples: 62771200  total_loss: 3.976  time: 0.3397 s/iter  data_time: 0.2110 s/iter total_throughput: 3014.81 samples/s lr: 9.36e-04  
[09/22 09:08:28] lb.utils.events INFO:  eta: 13:44:59  iteration: 61399/375342  consumed_samples: 62873600  total_loss: 3.963  time: 0.3397 s/iter  data_time: 0.2102 s/iter total_throughput: 3014.76 samples/s lr: 9.36e-04  
[09/22 09:09:02] lb.utils.events INFO:  eta: 13:44:39  iteration: 61499/375342  consumed_samples: 62976000  total_loss: 3.976  time: 0.3397 s/iter  data_time: 0.2191 s/iter total_throughput: 3014.77 samples/s lr: 9.36e-04  
[09/22 09:09:37] lb.utils.events INFO:  eta: 13:44:14  iteration: 61599/375342  consumed_samples: 63078400  total_loss: 3.994  time: 0.3397 s/iter  data_time: 0.2135 s/iter total_throughput: 3014.74 samples/s lr: 9.36e-04  
[09/22 09:10:11] lb.utils.events INFO:  eta: 13:43:44  iteration: 61699/375342  consumed_samples: 63180800  total_loss: 3.979  time: 0.3397 s/iter  data_time: 0.2159 s/iter total_throughput: 3014.72 samples/s lr: 9.35e-04  
[09/22 09:10:45] lb.utils.events INFO:  eta: 13:44:32  iteration: 61799/375342  consumed_samples: 63283200  total_loss: 3.975  time: 0.3397 s/iter  data_time: 0.2224 s/iter total_throughput: 3014.72 samples/s lr: 9.35e-04  
[09/22 09:11:18] lb.utils.events INFO:  eta: 13:44:02  iteration: 61899/375342  consumed_samples: 63385600  total_loss: 3.978  time: 0.3397 s/iter  data_time: 0.2067 s/iter total_throughput: 3014.78 samples/s lr: 9.35e-04  
[09/22 09:11:52] lb.utils.events INFO:  eta: 13:46:24  iteration: 61999/375342  consumed_samples: 63488000  total_loss: 3.984  time: 0.3397 s/iter  data_time: 0.2088 s/iter total_throughput: 3014.84 samples/s lr: 9.35e-04  
[09/22 09:12:26] lb.utils.events INFO:  eta: 13:45:53  iteration: 62099/375342  consumed_samples: 63590400  total_loss: 3.99  time: 0.3397 s/iter  data_time: 0.2397 s/iter total_throughput: 3014.82 samples/s lr: 9.35e-04  
[09/22 09:13:00] lb.utils.events INFO:  eta: 13:45:23  iteration: 62199/375342  consumed_samples: 63692800  total_loss: 3.973  time: 0.3397 s/iter  data_time: 0.2137 s/iter total_throughput: 3014.82 samples/s lr: 9.34e-04  
[09/22 09:13:34] lb.utils.events INFO:  eta: 13:44:48  iteration: 62299/375342  consumed_samples: 63795200  total_loss: 3.973  time: 0.3397 s/iter  data_time: 0.2121 s/iter total_throughput: 3014.87 samples/s lr: 9.34e-04  
[09/22 09:14:07] lb.utils.events INFO:  eta: 13:44:42  iteration: 62399/375342  consumed_samples: 63897600  total_loss: 3.986  time: 0.3396 s/iter  data_time: 0.2214 s/iter total_throughput: 3014.89 samples/s lr: 9.34e-04  
[09/22 09:14:42] lb.utils.events INFO:  eta: 13:43:10  iteration: 62499/375342  consumed_samples: 64000000  total_loss: 3.983  time: 0.3397 s/iter  data_time: 0.2043 s/iter total_throughput: 3014.83 samples/s lr: 9.34e-04  
[09/22 09:15:16] lb.utils.events INFO:  eta: 13:42:54  iteration: 62599/375342  consumed_samples: 64102400  total_loss: 3.983  time: 0.3397 s/iter  data_time: 0.2153 s/iter total_throughput: 3014.81 samples/s lr: 9.34e-04  
[09/22 09:15:50] lb.utils.events INFO:  eta: 13:42:09  iteration: 62699/375342  consumed_samples: 64204800  total_loss: 3.973  time: 0.3397 s/iter  data_time: 0.2190 s/iter total_throughput: 3014.83 samples/s lr: 9.33e-04  
[09/22 09:16:23] lb.utils.events INFO:  eta: 13:41:40  iteration: 62799/375342  consumed_samples: 64307200  total_loss: 3.967  time: 0.3397 s/iter  data_time: 0.2110 s/iter total_throughput: 3014.86 samples/s lr: 9.33e-04  
[09/22 09:16:57] lb.utils.events INFO:  eta: 13:42:48  iteration: 62899/375342  consumed_samples: 64409600  total_loss: 3.961  time: 0.3396 s/iter  data_time: 0.2086 s/iter total_throughput: 3014.92 samples/s lr: 9.33e-04  
[09/22 09:17:31] lb.utils.events INFO:  eta: 13:40:58  iteration: 62999/375342  consumed_samples: 64512000  total_loss: 3.947  time: 0.3396 s/iter  data_time: 0.2088 s/iter total_throughput: 3014.94 samples/s lr: 9.33e-04  
[09/22 09:18:04] lb.utils.events INFO:  eta: 13:41:17  iteration: 63099/375342  consumed_samples: 64614400  total_loss: 3.965  time: 0.3396 s/iter  data_time: 0.2043 s/iter total_throughput: 3014.99 samples/s lr: 9.33e-04  
[09/22 09:18:39] lb.utils.events INFO:  eta: 13:41:50  iteration: 63199/375342  consumed_samples: 64716800  total_loss: 3.977  time: 0.3396 s/iter  data_time: 0.2092 s/iter total_throughput: 3014.94 samples/s lr: 9.32e-04  
[09/22 09:19:13] lb.utils.events INFO:  eta: 13:40:35  iteration: 63299/375342  consumed_samples: 64819200  total_loss: 3.983  time: 0.3396 s/iter  data_time: 0.2109 s/iter total_throughput: 3014.94 samples/s lr: 9.32e-04  
[09/22 09:19:47] lb.utils.events INFO:  eta: 13:40:29  iteration: 63399/375342  consumed_samples: 64921600  total_loss: 3.984  time: 0.3396 s/iter  data_time: 0.2132 s/iter total_throughput: 3014.93 samples/s lr: 9.32e-04  
[09/22 09:20:21] lb.utils.events INFO:  eta: 13:40:14  iteration: 63499/375342  consumed_samples: 65024000  total_loss: 3.974  time: 0.3396 s/iter  data_time: 0.2054 s/iter total_throughput: 3014.93 samples/s lr: 9.32e-04  
[09/22 09:20:54] lb.utils.events INFO:  eta: 13:41:29  iteration: 63599/375342  consumed_samples: 65126400  total_loss: 3.979  time: 0.3396 s/iter  data_time: 0.2076 s/iter total_throughput: 3014.99 samples/s lr: 9.32e-04  
[09/22 09:21:28] lb.utils.events INFO:  eta: 13:41:13  iteration: 63699/375342  consumed_samples: 65228800  total_loss: 3.987  time: 0.3396 s/iter  data_time: 0.2155 s/iter total_throughput: 3015.06 samples/s lr: 9.31e-04  
[09/22 09:22:02] lb.utils.events INFO:  eta: 13:40:21  iteration: 63799/375342  consumed_samples: 65331200  total_loss: 3.979  time: 0.3396 s/iter  data_time: 0.2106 s/iter total_throughput: 3015.04 samples/s lr: 9.31e-04  
[09/22 09:22:36] lb.utils.events INFO:  eta: 13:40:04  iteration: 63899/375342  consumed_samples: 65433600  total_loss: 3.958  time: 0.3396 s/iter  data_time: 0.2190 s/iter total_throughput: 3015.02 samples/s lr: 9.31e-04  
[09/22 09:23:10] lb.utils.events INFO:  eta: 13:40:45  iteration: 63999/375342  consumed_samples: 65536000  total_loss: 3.957  time: 0.3396 s/iter  data_time: 0.2041 s/iter total_throughput: 3015.02 samples/s lr: 9.31e-04  
[09/22 09:23:44] lb.utils.events INFO:  eta: 13:39:14  iteration: 64099/375342  consumed_samples: 65638400  total_loss: 3.974  time: 0.3396 s/iter  data_time: 0.2256 s/iter total_throughput: 3014.96 samples/s lr: 9.30e-04  
[09/22 09:24:18] lb.utils.events INFO:  eta: 13:41:04  iteration: 64199/375342  consumed_samples: 65740800  total_loss: 3.98  time: 0.3396 s/iter  data_time: 0.2080 s/iter total_throughput: 3014.96 samples/s lr: 9.30e-04  
[09/22 09:24:52] lb.utils.events INFO:  eta: 13:41:26  iteration: 64299/375342  consumed_samples: 65843200  total_loss: 3.975  time: 0.3396 s/iter  data_time: 0.2129 s/iter total_throughput: 3014.98 samples/s lr: 9.30e-04  
[09/22 09:25:26] lb.utils.events INFO:  eta: 13:40:42  iteration: 64399/375342  consumed_samples: 65945600  total_loss: 3.982  time: 0.3396 s/iter  data_time: 0.2087 s/iter total_throughput: 3014.95 samples/s lr: 9.30e-04  
[09/22 09:26:01] lb.utils.events INFO:  eta: 13:41:07  iteration: 64499/375342  consumed_samples: 66048000  total_loss: 3.994  time: 0.3396 s/iter  data_time: 0.2193 s/iter total_throughput: 3014.90 samples/s lr: 9.30e-04  
[09/22 09:26:34] lb.utils.events INFO:  eta: 13:40:36  iteration: 64599/375342  consumed_samples: 66150400  total_loss: 3.979  time: 0.3396 s/iter  data_time: 0.2062 s/iter total_throughput: 3015.01 samples/s lr: 9.29e-04  
[09/22 09:27:09] lb.utils.events INFO:  eta: 13:39:01  iteration: 64699/375342  consumed_samples: 66252800  total_loss: 3.979  time: 0.3396 s/iter  data_time: 0.2269 s/iter total_throughput: 3014.92 samples/s lr: 9.29e-04  
[09/22 09:27:42] lb.utils.events INFO:  eta: 13:39:35  iteration: 64799/375342  consumed_samples: 66355200  total_loss: 3.973  time: 0.3396 s/iter  data_time: 0.2107 s/iter total_throughput: 3014.94 samples/s lr: 9.29e-04  
[09/22 09:28:16] lb.utils.events INFO:  eta: 13:39:19  iteration: 64899/375342  consumed_samples: 66457600  total_loss: 3.979  time: 0.3396 s/iter  data_time: 0.2174 s/iter total_throughput: 3014.98 samples/s lr: 9.29e-04  
[09/22 09:28:50] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0064999
[09/22 09:28:50] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/22 09:28:50] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/22 09:28:54] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0930 s/iter. Inference: 0.1624 s/iter. Eval: 0.0019 s/iter. Total: 0.2574 s/iter. ETA=0:00:09
[09/22 09:29:00] lb.evaluation.evaluator INFO: Inference done 28672/50000. Dataloading: 0.0829 s/iter. Inference: 0.2003 s/iter. Eval: 0.0019 s/iter. Total: 0.2853 s/iter. ETA=0:00:05
[09/22 09:29:05] lb.evaluation.evaluator INFO: Inference done 46080/50000. Dataloading: 0.0817 s/iter. Inference: 0.2074 s/iter. Eval: 0.0019 s/iter. Total: 0.2911 s/iter. ETA=0:00:00
[09/22 09:29:06] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/22 09:29:06] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.579963 (0.000252 s / iter per device, on 8 devices)
[09/22 09:29:06] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:09 (0.000182 s / iter per device, on 8 devices)
[09/22 09:29:06] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/22 09:29:06] lb.evaluation.utils INFO: copypaste: Acc@1=68.80199999999999
[09/22 09:29:06] lb.evaluation.utils INFO: copypaste: Acc@5=89.038
[09/22 09:29:06] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 68.80200, better than last best score 68.43800 @ iteration 59999.
[09/22 09:29:06] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/22 09:29:06] lb.utils.events INFO:  eta: 13:38:50  iteration: 64999/375342  consumed_samples: 66560000  total_loss: 3.986  time: 0.3396 s/iter  data_time: 0.2114 s/iter total_throughput: 3015.01 samples/s lr: 9.29e-04  
[09/22 09:29:38] lb.utils.events INFO:  eta: 13:43:34  iteration: 65099/375342  consumed_samples: 66662400  total_loss: 3.961  time: 0.3396 s/iter  data_time: 0.2089 s/iter total_throughput: 3015.33 samples/s lr: 9.28e-04  
[09/22 09:30:11] lb.utils.events INFO:  eta: 13:43:14  iteration: 65199/375342  consumed_samples: 66764800  total_loss: 3.956  time: 0.3396 s/iter  data_time: 0.1992 s/iter total_throughput: 3015.41 samples/s lr: 9.28e-04  
[09/22 09:30:45] lb.utils.events INFO:  eta: 13:45:41  iteration: 65299/375342  consumed_samples: 66867200  total_loss: 3.967  time: 0.3396 s/iter  data_time: 0.2318 s/iter total_throughput: 3015.40 samples/s lr: 9.28e-04  
[09/22 09:31:19] lb.utils.events INFO:  eta: 13:47:03  iteration: 65399/375342  consumed_samples: 66969600  total_loss: 3.944  time: 0.3396 s/iter  data_time: 0.2044 s/iter total_throughput: 3015.47 samples/s lr: 9.28e-04  
[09/22 09:31:53] lb.utils.events INFO:  eta: 13:44:36  iteration: 65499/375342  consumed_samples: 67072000  total_loss: 3.946  time: 0.3396 s/iter  data_time: 0.2242 s/iter total_throughput: 3015.45 samples/s lr: 9.27e-04  
[09/22 09:32:27] lb.utils.events INFO:  eta: 13:44:07  iteration: 65599/375342  consumed_samples: 67174400  total_loss: 3.958  time: 0.3396 s/iter  data_time: 0.2105 s/iter total_throughput: 3015.45 samples/s lr: 9.27e-04  
[09/22 09:33:00] lb.utils.events INFO:  eta: 13:44:27  iteration: 65699/375342  consumed_samples: 67276800  total_loss: 3.949  time: 0.3396 s/iter  data_time: 0.2027 s/iter total_throughput: 3015.51 samples/s lr: 9.27e-04  
[09/22 09:33:34] lb.utils.events INFO:  eta: 13:43:48  iteration: 65799/375342  consumed_samples: 67379200  total_loss: 3.974  time: 0.3396 s/iter  data_time: 0.2011 s/iter total_throughput: 3015.52 samples/s lr: 9.27e-04  
[09/22 09:34:08] lb.utils.events INFO:  eta: 13:43:32  iteration: 65899/375342  consumed_samples: 67481600  total_loss: 3.981  time: 0.3396 s/iter  data_time: 0.2057 s/iter total_throughput: 3015.58 samples/s lr: 9.27e-04  
[09/22 09:34:41] lb.utils.events INFO:  eta: 13:43:46  iteration: 65999/375342  consumed_samples: 67584000  total_loss: 3.943  time: 0.3396 s/iter  data_time: 0.2025 s/iter total_throughput: 3015.66 samples/s lr: 9.26e-04  
[09/22 09:35:16] lb.utils.events INFO:  eta: 13:39:50  iteration: 66099/375342  consumed_samples: 67686400  total_loss: 3.944  time: 0.3396 s/iter  data_time: 0.2016 s/iter total_throughput: 3015.62 samples/s lr: 9.26e-04  
[09/22 09:35:50] lb.utils.events INFO:  eta: 13:37:35  iteration: 66199/375342  consumed_samples: 67788800  total_loss: 3.98  time: 0.3396 s/iter  data_time: 0.2150 s/iter total_throughput: 3015.53 samples/s lr: 9.26e-04  
[09/22 09:36:24] lb.utils.events INFO:  eta: 13:34:04  iteration: 66299/375342  consumed_samples: 67891200  total_loss: 3.979  time: 0.3396 s/iter  data_time: 0.2081 s/iter total_throughput: 3015.53 samples/s lr: 9.26e-04  
[09/22 09:36:58] lb.utils.events INFO:  eta: 13:31:35  iteration: 66399/375342  consumed_samples: 67993600  total_loss: 3.93  time: 0.3396 s/iter  data_time: 0.2265 s/iter total_throughput: 3015.54 samples/s lr: 9.26e-04  
[09/22 09:37:32] lb.utils.events INFO:  eta: 13:31:10  iteration: 66499/375342  consumed_samples: 68096000  total_loss: 3.944  time: 0.3396 s/iter  data_time: 0.2170 s/iter total_throughput: 3015.53 samples/s lr: 9.25e-04  
[09/22 09:38:06] lb.utils.events INFO:  eta: 13:30:48  iteration: 66599/375342  consumed_samples: 68198400  total_loss: 3.955  time: 0.3396 s/iter  data_time: 0.2093 s/iter total_throughput: 3015.59 samples/s lr: 9.25e-04  
[09/22 09:38:39] lb.utils.events INFO:  eta: 13:30:17  iteration: 66699/375342  consumed_samples: 68300800  total_loss: 3.946  time: 0.3396 s/iter  data_time: 0.2037 s/iter total_throughput: 3015.60 samples/s lr: 9.25e-04  
[09/22 09:39:14] lb.utils.events INFO:  eta: 13:27:24  iteration: 66799/375342  consumed_samples: 68403200  total_loss: 3.946  time: 0.3396 s/iter  data_time: 0.2103 s/iter total_throughput: 3015.54 samples/s lr: 9.25e-04  
[09/22 09:39:48] lb.utils.events INFO:  eta: 13:26:26  iteration: 66899/375342  consumed_samples: 68505600  total_loss: 3.954  time: 0.3396 s/iter  data_time: 0.2111 s/iter total_throughput: 3015.55 samples/s lr: 9.24e-04  
[09/22 09:40:21] lb.utils.events INFO:  eta: 13:25:49  iteration: 66999/375342  consumed_samples: 68608000  total_loss: 3.956  time: 0.3396 s/iter  data_time: 0.2160 s/iter total_throughput: 3015.62 samples/s lr: 9.24e-04  
[09/22 09:40:55] lb.utils.events INFO:  eta: 13:23:50  iteration: 67099/375342  consumed_samples: 68710400  total_loss: 3.939  time: 0.3396 s/iter  data_time: 0.2199 s/iter total_throughput: 3015.62 samples/s lr: 9.24e-04  
[09/22 09:41:29] lb.utils.events INFO:  eta: 13:24:37  iteration: 67199/375342  consumed_samples: 68812800  total_loss: 3.959  time: 0.3396 s/iter  data_time: 0.2115 s/iter total_throughput: 3015.58 samples/s lr: 9.24e-04  
[09/22 09:42:03] lb.utils.events INFO:  eta: 13:24:57  iteration: 67299/375342  consumed_samples: 68915200  total_loss: 3.948  time: 0.3396 s/iter  data_time: 0.2000 s/iter total_throughput: 3015.63 samples/s lr: 9.24e-04  
[09/22 09:42:37] lb.utils.events INFO:  eta: 13:24:31  iteration: 67399/375342  consumed_samples: 69017600  total_loss: 3.938  time: 0.3396 s/iter  data_time: 0.2151 s/iter total_throughput: 3015.68 samples/s lr: 9.23e-04  
[09/22 09:43:10] lb.utils.events INFO:  eta: 13:25:50  iteration: 67499/375342  consumed_samples: 69120000  total_loss: 3.952  time: 0.3395 s/iter  data_time: 0.1987 s/iter total_throughput: 3015.81 samples/s lr: 9.23e-04  
[09/22 09:43:43] lb.utils.events INFO:  eta: 13:26:45  iteration: 67599/375342  consumed_samples: 69222400  total_loss: 3.952  time: 0.3395 s/iter  data_time: 0.2051 s/iter total_throughput: 3015.82 samples/s lr: 9.23e-04  
[09/22 09:44:17] lb.utils.events INFO:  eta: 13:26:15  iteration: 67699/375342  consumed_samples: 69324800  total_loss: 3.939  time: 0.3395 s/iter  data_time: 0.2058 s/iter total_throughput: 3015.90 samples/s lr: 9.23e-04  
[09/22 09:44:51] lb.utils.events INFO:  eta: 13:25:59  iteration: 67799/375342  consumed_samples: 69427200  total_loss: 3.944  time: 0.3395 s/iter  data_time: 0.1990 s/iter total_throughput: 3015.86 samples/s lr: 9.22e-04  
[09/22 09:45:24] lb.utils.events INFO:  eta: 13:27:22  iteration: 67899/375342  consumed_samples: 69529600  total_loss: 3.963  time: 0.3395 s/iter  data_time: 0.2055 s/iter total_throughput: 3015.95 samples/s lr: 9.22e-04  
[09/22 09:45:58] lb.utils.events INFO:  eta: 13:25:48  iteration: 67999/375342  consumed_samples: 69632000  total_loss: 3.977  time: 0.3395 s/iter  data_time: 0.2110 s/iter total_throughput: 3015.94 samples/s lr: 9.22e-04  
[09/22 09:46:32] lb.utils.events INFO:  eta: 13:28:05  iteration: 68099/375342  consumed_samples: 69734400  total_loss: 3.958  time: 0.3395 s/iter  data_time: 0.2204 s/iter total_throughput: 3015.96 samples/s lr: 9.22e-04  
[09/22 09:47:06] lb.utils.events INFO:  eta: 13:28:36  iteration: 68199/375342  consumed_samples: 69836800  total_loss: 3.952  time: 0.3395 s/iter  data_time: 0.2177 s/iter total_throughput: 3015.97 samples/s lr: 9.22e-04  
[09/22 09:47:40] lb.utils.events INFO:  eta: 13:27:24  iteration: 68299/375342  consumed_samples: 69939200  total_loss: 3.958  time: 0.3395 s/iter  data_time: 0.2017 s/iter total_throughput: 3016.01 samples/s lr: 9.21e-04  
[09/22 09:48:14] lb.utils.events INFO:  eta: 13:26:28  iteration: 68399/375342  consumed_samples: 70041600  total_loss: 3.971  time: 0.3395 s/iter  data_time: 0.2196 s/iter total_throughput: 3016.03 samples/s lr: 9.21e-04  
[09/22 09:48:48] lb.utils.events INFO:  eta: 13:24:35  iteration: 68499/375342  consumed_samples: 70144000  total_loss: 3.968  time: 0.3395 s/iter  data_time: 0.2118 s/iter total_throughput: 3016.01 samples/s lr: 9.21e-04  
[09/22 09:49:21] lb.utils.events INFO:  eta: 13:23:32  iteration: 68599/375342  consumed_samples: 70246400  total_loss: 3.953  time: 0.3395 s/iter  data_time: 0.2005 s/iter total_throughput: 3016.08 samples/s lr: 9.21e-04  
[09/22 09:49:54] lb.utils.events INFO:  eta: 13:23:13  iteration: 68699/375342  consumed_samples: 70348800  total_loss: 3.938  time: 0.3395 s/iter  data_time: 0.1928 s/iter total_throughput: 3016.18 samples/s lr: 9.20e-04  
[09/22 09:50:27] lb.utils.events INFO:  eta: 13:24:37  iteration: 68799/375342  consumed_samples: 70451200  total_loss: 3.946  time: 0.3395 s/iter  data_time: 0.2025 s/iter total_throughput: 3016.30 samples/s lr: 9.20e-04  
[09/22 09:51:01] lb.utils.events INFO:  eta: 13:23:58  iteration: 68899/375342  consumed_samples: 70553600  total_loss: 3.952  time: 0.3395 s/iter  data_time: 0.1969 s/iter total_throughput: 3016.35 samples/s lr: 9.20e-04  
[09/22 09:51:35] lb.utils.events INFO:  eta: 13:23:22  iteration: 68999/375342  consumed_samples: 70656000  total_loss: 3.96  time: 0.3395 s/iter  data_time: 0.2087 s/iter total_throughput: 3016.35 samples/s lr: 9.20e-04  
[09/22 09:52:08] lb.utils.events INFO:  eta: 13:22:21  iteration: 69099/375342  consumed_samples: 70758400  total_loss: 3.937  time: 0.3395 s/iter  data_time: 0.2084 s/iter total_throughput: 3016.49 samples/s lr: 9.19e-04  
[09/22 09:52:41] lb.utils.events INFO:  eta: 13:22:43  iteration: 69199/375342  consumed_samples: 70860800  total_loss: 3.925  time: 0.3395 s/iter  data_time: 0.2144 s/iter total_throughput: 3016.51 samples/s lr: 9.19e-04  
[09/22 09:53:15] lb.utils.events INFO:  eta: 13:25:34  iteration: 69299/375342  consumed_samples: 70963200  total_loss: 3.937  time: 0.3395 s/iter  data_time: 0.1999 s/iter total_throughput: 3016.63 samples/s lr: 9.19e-04  
[09/22 09:53:48] lb.utils.events INFO:  eta: 13:26:15  iteration: 69399/375342  consumed_samples: 71065600  total_loss: 3.918  time: 0.3394 s/iter  data_time: 0.2178 s/iter total_throughput: 3016.72 samples/s lr: 9.19e-04  
[09/22 09:54:21] lb.utils.events INFO:  eta: 13:27:30  iteration: 69499/375342  consumed_samples: 71168000  total_loss: 3.933  time: 0.3394 s/iter  data_time: 0.2077 s/iter total_throughput: 3016.80 samples/s lr: 9.19e-04  
[09/22 09:54:54] lb.utils.events INFO:  eta: 13:27:38  iteration: 69599/375342  consumed_samples: 71270400  total_loss: 3.951  time: 0.3394 s/iter  data_time: 0.2107 s/iter total_throughput: 3016.87 samples/s lr: 9.18e-04  
[09/22 09:55:28] lb.utils.events INFO:  eta: 13:27:23  iteration: 69699/375342  consumed_samples: 71372800  total_loss: 3.948  time: 0.3394 s/iter  data_time: 0.1997 s/iter total_throughput: 3016.95 samples/s lr: 9.18e-04  
[09/22 09:56:02] lb.utils.events INFO:  eta: 13:26:05  iteration: 69799/375342  consumed_samples: 71475200  total_loss: 3.942  time: 0.3394 s/iter  data_time: 0.1957 s/iter total_throughput: 3016.97 samples/s lr: 9.18e-04  
[09/22 09:56:35] lb.utils.events INFO:  eta: 13:25:12  iteration: 69899/375342  consumed_samples: 71577600  total_loss: 3.95  time: 0.3394 s/iter  data_time: 0.1949 s/iter total_throughput: 3017.07 samples/s lr: 9.18e-04  
[09/22 09:57:08] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0069999
[09/22 09:57:08] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/22 09:57:08] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/22 09:57:12] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0975 s/iter. Inference: 0.1580 s/iter. Eval: 0.0023 s/iter. Total: 0.2578 s/iter. ETA=0:00:09
[09/22 09:57:18] lb.evaluation.evaluator INFO: Inference done 29696/50000. Dataloading: 0.1142 s/iter. Inference: 0.1796 s/iter. Eval: 0.0020 s/iter. Total: 0.2958 s/iter. ETA=0:00:05
[09/22 09:57:23] lb.evaluation.evaluator INFO: Inference done 49152/50000. Dataloading: 0.0966 s/iter. Inference: 0.1852 s/iter. Eval: 0.0020 s/iter. Total: 0.2840 s/iter. ETA=0:00:00
[09/22 09:57:23] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/22 09:57:23] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.694773 (0.000254 s / iter per device, on 8 devices)
[09/22 09:57:23] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:08 (0.000169 s / iter per device, on 8 devices)
[09/22 09:57:23] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/22 09:57:23] lb.evaluation.utils INFO: copypaste: Acc@1=69.328
[09/22 09:57:23] lb.evaluation.utils INFO: copypaste: Acc@5=89.41799999999999
[09/22 09:57:23] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 69.32800, better than last best score 68.80200 @ iteration 64999.
[09/22 09:57:23] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/22 09:57:24] lb.utils.events INFO:  eta: 13:24:56  iteration: 69999/375342  consumed_samples: 71680000  total_loss: 3.926  time: 0.3394 s/iter  data_time: 0.2034 s/iter total_throughput: 3017.22 samples/s lr: 9.17e-04  
[09/22 09:57:56] lb.utils.events INFO:  eta: 13:29:02  iteration: 70099/375342  consumed_samples: 71782400  total_loss: 3.911  time: 0.3393 s/iter  data_time: 0.2456 s/iter total_throughput: 3017.54 samples/s lr: 9.17e-04  
[09/22 09:58:30] lb.utils.events INFO:  eta: 13:30:23  iteration: 70199/375342  consumed_samples: 71884800  total_loss: 3.892  time: 0.3393 s/iter  data_time: 0.2099 s/iter total_throughput: 3017.54 samples/s lr: 9.17e-04  
[09/22 09:59:04] lb.utils.events INFO:  eta: 13:29:04  iteration: 70299/375342  consumed_samples: 71987200  total_loss: 3.88  time: 0.3394 s/iter  data_time: 0.2020 s/iter total_throughput: 3017.51 samples/s lr: 9.17e-04  
[09/22 09:59:38] lb.utils.events INFO:  eta: 13:28:36  iteration: 70399/375342  consumed_samples: 72089600  total_loss: 3.889  time: 0.3394 s/iter  data_time: 0.2233 s/iter total_throughput: 3017.48 samples/s lr: 9.17e-04  
[09/22 10:00:12] lb.utils.events INFO:  eta: 13:27:22  iteration: 70499/375342  consumed_samples: 72192000  total_loss: 3.913  time: 0.3394 s/iter  data_time: 0.2136 s/iter total_throughput: 3017.42 samples/s lr: 9.16e-04  
[09/22 10:00:47] lb.utils.events INFO:  eta: 13:26:15  iteration: 70599/375342  consumed_samples: 72294400  total_loss: 3.934  time: 0.3394 s/iter  data_time: 0.2100 s/iter total_throughput: 3017.37 samples/s lr: 9.16e-04  
[09/22 10:01:21] lb.utils.events INFO:  eta: 13:27:55  iteration: 70699/375342  consumed_samples: 72396800  total_loss: 3.927  time: 0.3394 s/iter  data_time: 0.2156 s/iter total_throughput: 3017.30 samples/s lr: 9.16e-04  
[09/22 10:01:55] lb.utils.events INFO:  eta: 13:25:16  iteration: 70799/375342  consumed_samples: 72499200  total_loss: 3.945  time: 0.3394 s/iter  data_time: 0.2134 s/iter total_throughput: 3017.26 samples/s lr: 9.16e-04  
[09/22 10:02:30] lb.utils.events INFO:  eta: 13:24:20  iteration: 70899/375342  consumed_samples: 72601600  total_loss: 3.94  time: 0.3394 s/iter  data_time: 0.2126 s/iter total_throughput: 3017.23 samples/s lr: 9.15e-04  
[09/22 10:03:04] lb.utils.events INFO:  eta: 13:23:33  iteration: 70999/375342  consumed_samples: 72704000  total_loss: 3.911  time: 0.3394 s/iter  data_time: 0.2087 s/iter total_throughput: 3017.16 samples/s lr: 9.15e-04  
[09/22 10:03:38] lb.utils.events INFO:  eta: 13:19:31  iteration: 71099/375342  consumed_samples: 72806400  total_loss: 3.896  time: 0.3394 s/iter  data_time: 0.2113 s/iter total_throughput: 3017.16 samples/s lr: 9.15e-04  
[09/22 10:04:12] lb.utils.events INFO:  eta: 13:17:59  iteration: 71199/375342  consumed_samples: 72908800  total_loss: 3.925  time: 0.3394 s/iter  data_time: 0.2104 s/iter total_throughput: 3017.13 samples/s lr: 9.15e-04  
[09/22 10:04:46] lb.utils.events INFO:  eta: 13:19:00  iteration: 71299/375342  consumed_samples: 73011200  total_loss: 3.948  time: 0.3394 s/iter  data_time: 0.2156 s/iter total_throughput: 3017.16 samples/s lr: 9.14e-04  
[09/22 10:05:20] lb.utils.events INFO:  eta: 13:19:49  iteration: 71399/375342  consumed_samples: 73113600  total_loss: 3.968  time: 0.3394 s/iter  data_time: 0.2202 s/iter total_throughput: 3017.16 samples/s lr: 9.14e-04  
[09/22 10:05:54] lb.utils.events INFO:  eta: 13:17:17  iteration: 71499/375342  consumed_samples: 73216000  total_loss: 3.951  time: 0.3394 s/iter  data_time: 0.2116 s/iter total_throughput: 3017.10 samples/s lr: 9.14e-04  
[09/22 10:06:29] lb.utils.events INFO:  eta: 13:18:16  iteration: 71599/375342  consumed_samples: 73318400  total_loss: 3.926  time: 0.3394 s/iter  data_time: 0.2159 s/iter total_throughput: 3017.01 samples/s lr: 9.14e-04  
[09/22 10:07:03] lb.utils.events INFO:  eta: 13:16:44  iteration: 71699/375342  consumed_samples: 73420800  total_loss: 3.918  time: 0.3394 s/iter  data_time: 0.2310 s/iter total_throughput: 3016.96 samples/s lr: 9.14e-04  
[09/22 10:07:37] lb.utils.events INFO:  eta: 13:18:03  iteration: 71799/375342  consumed_samples: 73523200  total_loss: 3.918  time: 0.3394 s/iter  data_time: 0.2161 s/iter total_throughput: 3017.00 samples/s lr: 9.13e-04  
[09/22 10:08:11] lb.utils.events INFO:  eta: 13:18:22  iteration: 71899/375342  consumed_samples: 73625600  total_loss: 3.923  time: 0.3394 s/iter  data_time: 0.2081 s/iter total_throughput: 3016.99 samples/s lr: 9.13e-04  
[09/22 10:08:45] lb.utils.events INFO:  eta: 13:18:43  iteration: 71999/375342  consumed_samples: 73728000  total_loss: 3.916  time: 0.3394 s/iter  data_time: 0.2161 s/iter total_throughput: 3016.98 samples/s lr: 9.13e-04  
[09/22 10:09:20] lb.utils.events INFO:  eta: 13:15:33  iteration: 72099/375342  consumed_samples: 73830400  total_loss: 3.913  time: 0.3394 s/iter  data_time: 0.2105 s/iter total_throughput: 3016.92 samples/s lr: 9.13e-04  
[09/22 10:09:54] lb.utils.events INFO:  eta: 13:14:34  iteration: 72199/375342  consumed_samples: 73932800  total_loss: 3.924  time: 0.3394 s/iter  data_time: 0.2076 s/iter total_throughput: 3016.90 samples/s lr: 9.12e-04  
[09/22 10:10:28] lb.utils.events INFO:  eta: 13:14:06  iteration: 72299/375342  consumed_samples: 74035200  total_loss: 3.941  time: 0.3394 s/iter  data_time: 0.2169 s/iter total_throughput: 3016.88 samples/s lr: 9.12e-04  
[09/22 10:11:02] lb.utils.events INFO:  eta: 13:13:53  iteration: 72399/375342  consumed_samples: 74137600  total_loss: 3.949  time: 0.3394 s/iter  data_time: 0.2312 s/iter total_throughput: 3016.87 samples/s lr: 9.12e-04  
[09/22 10:11:36] lb.utils.events INFO:  eta: 13:14:54  iteration: 72499/375342  consumed_samples: 74240000  total_loss: 3.93  time: 0.3394 s/iter  data_time: 0.2182 s/iter total_throughput: 3016.80 samples/s lr: 9.12e-04  
[09/22 10:12:10] lb.utils.events INFO:  eta: 13:14:44  iteration: 72599/375342  consumed_samples: 74342400  total_loss: 3.926  time: 0.3394 s/iter  data_time: 0.2243 s/iter total_throughput: 3016.77 samples/s lr: 9.11e-04  
[09/22 10:12:45] lb.utils.events INFO:  eta: 13:15:20  iteration: 72699/375342  consumed_samples: 74444800  total_loss: 3.898  time: 0.3394 s/iter  data_time: 0.2179 s/iter total_throughput: 3016.76 samples/s lr: 9.11e-04  
[09/22 10:13:18] lb.utils.events INFO:  eta: 13:15:14  iteration: 72799/375342  consumed_samples: 74547200  total_loss: 3.892  time: 0.3394 s/iter  data_time: 0.2172 s/iter total_throughput: 3016.77 samples/s lr: 9.11e-04  
[09/22 10:13:52] lb.utils.events INFO:  eta: 13:15:05  iteration: 72899/375342  consumed_samples: 74649600  total_loss: 3.902  time: 0.3394 s/iter  data_time: 0.2119 s/iter total_throughput: 3016.79 samples/s lr: 9.11e-04  
[09/22 10:14:26] lb.utils.events INFO:  eta: 13:14:44  iteration: 72999/375342  consumed_samples: 74752000  total_loss: 3.911  time: 0.3394 s/iter  data_time: 0.2103 s/iter total_throughput: 3016.79 samples/s lr: 9.10e-04  
[09/22 10:15:00] lb.utils.events INFO:  eta: 13:15:52  iteration: 73099/375342  consumed_samples: 74854400  total_loss: 3.904  time: 0.3394 s/iter  data_time: 0.2184 s/iter total_throughput: 3016.75 samples/s lr: 9.10e-04  
[09/22 10:15:35] lb.utils.events INFO:  eta: 13:15:49  iteration: 73199/375342  consumed_samples: 74956800  total_loss: 3.917  time: 0.3394 s/iter  data_time: 0.2100 s/iter total_throughput: 3016.73 samples/s lr: 9.10e-04  
[09/22 10:16:08] lb.utils.events INFO:  eta: 13:16:28  iteration: 73299/375342  consumed_samples: 75059200  total_loss: 3.945  time: 0.3394 s/iter  data_time: 0.2202 s/iter total_throughput: 3016.77 samples/s lr: 9.10e-04  
[09/22 10:16:42] lb.utils.events INFO:  eta: 13:16:06  iteration: 73399/375342  consumed_samples: 75161600  total_loss: 3.933  time: 0.3394 s/iter  data_time: 0.2094 s/iter total_throughput: 3016.77 samples/s lr: 9.09e-04  
[09/22 10:17:16] lb.utils.events INFO:  eta: 13:15:50  iteration: 73499/375342  consumed_samples: 75264000  total_loss: 3.913  time: 0.3394 s/iter  data_time: 0.2225 s/iter total_throughput: 3016.77 samples/s lr: 9.09e-04  
[09/22 10:17:50] lb.utils.events INFO:  eta: 13:16:18  iteration: 73599/375342  consumed_samples: 75366400  total_loss: 3.911  time: 0.3394 s/iter  data_time: 0.2123 s/iter total_throughput: 3016.80 samples/s lr: 9.09e-04  
[09/22 10:18:24] lb.utils.events INFO:  eta: 13:16:43  iteration: 73699/375342  consumed_samples: 75468800  total_loss: 3.93  time: 0.3394 s/iter  data_time: 0.2088 s/iter total_throughput: 3016.82 samples/s lr: 9.09e-04  
[09/22 10:18:58] lb.utils.events INFO:  eta: 13:16:58  iteration: 73799/375342  consumed_samples: 75571200  total_loss: 3.937  time: 0.3394 s/iter  data_time: 0.2235 s/iter total_throughput: 3016.76 samples/s lr: 9.09e-04  
[09/22 10:19:32] lb.utils.events INFO:  eta: 13:17:44  iteration: 73899/375342  consumed_samples: 75673600  total_loss: 3.893  time: 0.3394 s/iter  data_time: 0.2246 s/iter total_throughput: 3016.79 samples/s lr: 9.08e-04  
[09/22 10:20:06] lb.utils.events INFO:  eta: 13:17:44  iteration: 73999/375342  consumed_samples: 75776000  total_loss: 3.879  time: 0.3394 s/iter  data_time: 0.2174 s/iter total_throughput: 3016.75 samples/s lr: 9.08e-04  
[09/22 10:20:40] lb.utils.events INFO:  eta: 13:18:03  iteration: 74099/375342  consumed_samples: 75878400  total_loss: 3.901  time: 0.3394 s/iter  data_time: 0.2026 s/iter total_throughput: 3016.77 samples/s lr: 9.08e-04  
[09/22 10:21:14] lb.utils.events INFO:  eta: 13:19:18  iteration: 74199/375342  consumed_samples: 75980800  total_loss: 3.925  time: 0.3394 s/iter  data_time: 0.2260 s/iter total_throughput: 3016.73 samples/s lr: 9.08e-04  
[09/22 10:21:48] lb.utils.events INFO:  eta: 13:17:32  iteration: 74299/375342  consumed_samples: 76083200  total_loss: 3.915  time: 0.3394 s/iter  data_time: 0.2164 s/iter total_throughput: 3016.70 samples/s lr: 9.07e-04  
[09/22 10:22:23] lb.utils.events INFO:  eta: 13:16:34  iteration: 74399/375342  consumed_samples: 76185600  total_loss: 3.903  time: 0.3395 s/iter  data_time: 0.2234 s/iter total_throughput: 3016.62 samples/s lr: 9.07e-04  
[09/22 10:22:57] lb.utils.events INFO:  eta: 13:15:43  iteration: 74499/375342  consumed_samples: 76288000  total_loss: 3.888  time: 0.3395 s/iter  data_time: 0.2072 s/iter total_throughput: 3016.57 samples/s lr: 9.07e-04  
[09/22 10:23:31] lb.utils.events INFO:  eta: 13:14:48  iteration: 74599/375342  consumed_samples: 76390400  total_loss: 3.902  time: 0.3395 s/iter  data_time: 0.2084 s/iter total_throughput: 3016.61 samples/s lr: 9.07e-04  
[09/22 10:24:04] lb.utils.events INFO:  eta: 13:15:44  iteration: 74699/375342  consumed_samples: 76492800  total_loss: 3.925  time: 0.3394 s/iter  data_time: 0.2166 s/iter total_throughput: 3016.66 samples/s lr: 9.06e-04  
[09/22 10:24:38] lb.utils.events INFO:  eta: 13:14:44  iteration: 74799/375342  consumed_samples: 76595200  total_loss: 3.92  time: 0.3394 s/iter  data_time: 0.2112 s/iter total_throughput: 3016.69 samples/s lr: 9.06e-04  
[09/22 10:25:12] lb.utils.events INFO:  eta: 13:13:49  iteration: 74899/375342  consumed_samples: 76697600  total_loss: 3.919  time: 0.3394 s/iter  data_time: 0.2092 s/iter total_throughput: 3016.68 samples/s lr: 9.06e-04  
[09/22 10:25:46] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0074999
[09/22 10:25:47] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/22 10:25:47] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/22 10:25:51] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0995 s/iter. Inference: 0.1619 s/iter. Eval: 0.0021 s/iter. Total: 0.2636 s/iter. ETA=0:00:09
[09/22 10:25:56] lb.evaluation.evaluator INFO: Inference done 29696/50000. Dataloading: 0.1186 s/iter. Inference: 0.1712 s/iter. Eval: 0.0020 s/iter. Total: 0.2920 s/iter. ETA=0:00:05
[09/22 10:26:02] lb.evaluation.evaluator INFO: Inference done 48128/50000. Dataloading: 0.1112 s/iter. Inference: 0.1745 s/iter. Eval: 0.0020 s/iter. Total: 0.2877 s/iter. ETA=0:00:00
[09/22 10:26:02] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/22 10:26:02] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.437035 (0.000249 s / iter per device, on 8 devices)
[09/22 10:26:02] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000153 s / iter per device, on 8 devices)
[09/22 10:26:02] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/22 10:26:02] lb.evaluation.utils INFO: copypaste: Acc@1=69.482
[09/22 10:26:02] lb.evaluation.utils INFO: copypaste: Acc@5=89.622
[09/22 10:26:02] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 69.48200, better than last best score 69.32800 @ iteration 69999.
[09/22 10:26:02] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/22 10:26:03] lb.utils.events INFO:  eta: 13:13:24  iteration: 74999/375342  consumed_samples: 76800000  total_loss: 3.94  time: 0.3394 s/iter  data_time: 0.2227 s/iter total_throughput: 3016.67 samples/s lr: 9.06e-04  
[09/22 10:26:35] lb.utils.events INFO:  eta: 13:16:06  iteration: 75099/375342  consumed_samples: 76902400  total_loss: 3.938  time: 0.3394 s/iter  data_time: 0.2418 s/iter total_throughput: 3016.89 samples/s lr: 9.05e-04  
[09/22 10:27:09] lb.utils.events INFO:  eta: 13:15:55  iteration: 75199/375342  consumed_samples: 77004800  total_loss: 3.893  time: 0.3394 s/iter  data_time: 0.2066 s/iter total_throughput: 3016.87 samples/s lr: 9.05e-04  
[09/22 10:27:43] lb.utils.events INFO:  eta: 13:16:47  iteration: 75299/375342  consumed_samples: 77107200  total_loss: 3.898  time: 0.3394 s/iter  data_time: 0.2268 s/iter total_throughput: 3016.90 samples/s lr: 9.05e-04  
[09/22 10:28:17] lb.utils.events INFO:  eta: 13:17:16  iteration: 75399/375342  consumed_samples: 77209600  total_loss: 3.912  time: 0.3394 s/iter  data_time: 0.2168 s/iter total_throughput: 3016.89 samples/s lr: 9.05e-04  
[09/22 10:28:51] lb.utils.events INFO:  eta: 13:19:23  iteration: 75499/375342  consumed_samples: 77312000  total_loss: 3.902  time: 0.3394 s/iter  data_time: 0.2297 s/iter total_throughput: 3016.89 samples/s lr: 9.04e-04  
[09/22 10:29:25] lb.utils.events INFO:  eta: 13:17:47  iteration: 75599/375342  consumed_samples: 77414400  total_loss: 3.906  time: 0.3394 s/iter  data_time: 0.2181 s/iter total_throughput: 3016.83 samples/s lr: 9.04e-04  
[09/22 10:29:59] lb.utils.events INFO:  eta: 13:15:37  iteration: 75699/375342  consumed_samples: 77516800  total_loss: 3.914  time: 0.3394 s/iter  data_time: 0.2290 s/iter total_throughput: 3016.78 samples/s lr: 9.04e-04  
[09/22 10:30:33] lb.utils.events INFO:  eta: 13:17:16  iteration: 75799/375342  consumed_samples: 77619200  total_loss: 3.894  time: 0.3394 s/iter  data_time: 0.2032 s/iter total_throughput: 3016.79 samples/s lr: 9.04e-04  
[09/22 10:31:07] lb.utils.events INFO:  eta: 13:16:30  iteration: 75899/375342  consumed_samples: 77721600  total_loss: 3.896  time: 0.3394 s/iter  data_time: 0.2112 s/iter total_throughput: 3016.78 samples/s lr: 9.03e-04  
[09/22 10:31:41] lb.utils.events INFO:  eta: 13:17:16  iteration: 75999/375342  consumed_samples: 77824000  total_loss: 3.912  time: 0.3394 s/iter  data_time: 0.2007 s/iter total_throughput: 3016.78 samples/s lr: 9.03e-04  
[09/22 10:32:16] lb.utils.events INFO:  eta: 13:12:34  iteration: 76099/375342  consumed_samples: 77926400  total_loss: 3.919  time: 0.3394 s/iter  data_time: 0.2171 s/iter total_throughput: 3016.74 samples/s lr: 9.03e-04  
[09/22 10:32:50] lb.utils.events INFO:  eta: 13:09:42  iteration: 76199/375342  consumed_samples: 78028800  total_loss: 3.931  time: 0.3394 s/iter  data_time: 0.2106 s/iter total_throughput: 3016.75 samples/s lr: 9.03e-04  
[09/22 10:33:23] lb.utils.events INFO:  eta: 13:09:38  iteration: 76299/375342  consumed_samples: 78131200  total_loss: 3.93  time: 0.3394 s/iter  data_time: 0.2267 s/iter total_throughput: 3016.75 samples/s lr: 9.02e-04  
[09/22 10:33:57] lb.utils.events INFO:  eta: 13:08:46  iteration: 76399/375342  consumed_samples: 78233600  total_loss: 3.925  time: 0.3394 s/iter  data_time: 0.2095 s/iter total_throughput: 3016.77 samples/s lr: 9.02e-04  
[09/22 10:34:32] lb.utils.events INFO:  eta: 13:07:09  iteration: 76499/375342  consumed_samples: 78336000  total_loss: 3.927  time: 0.3394 s/iter  data_time: 0.2088 s/iter total_throughput: 3016.73 samples/s lr: 9.02e-04  
[09/22 10:35:06] lb.utils.events INFO:  eta: 13:06:53  iteration: 76599/375342  consumed_samples: 78438400  total_loss: 3.93  time: 0.3394 s/iter  data_time: 0.2197 s/iter total_throughput: 3016.68 samples/s lr: 9.02e-04  
[09/22 10:35:40] lb.utils.events INFO:  eta: 13:07:39  iteration: 76699/375342  consumed_samples: 78540800  total_loss: 3.917  time: 0.3395 s/iter  data_time: 0.2313 s/iter total_throughput: 3016.62 samples/s lr: 9.01e-04  
[09/22 10:36:15] lb.utils.events INFO:  eta: 13:05:39  iteration: 76799/375342  consumed_samples: 78643200  total_loss: 3.893  time: 0.3395 s/iter  data_time: 0.2266 s/iter total_throughput: 3016.56 samples/s lr: 9.01e-04  
[09/22 10:36:49] lb.utils.events INFO:  eta: 13:03:48  iteration: 76899/375342  consumed_samples: 78745600  total_loss: 3.898  time: 0.3395 s/iter  data_time: 0.2159 s/iter total_throughput: 3016.48 samples/s lr: 9.01e-04  
[09/22 10:37:24] lb.utils.events INFO:  eta: 13:00:24  iteration: 76999/375342  consumed_samples: 78848000  total_loss: 3.907  time: 0.3395 s/iter  data_time: 0.2175 s/iter total_throughput: 3016.46 samples/s lr: 9.01e-04  
[09/22 10:37:58] lb.utils.events INFO:  eta: 12:59:55  iteration: 77099/375342  consumed_samples: 78950400  total_loss: 3.882  time: 0.3395 s/iter  data_time: 0.2216 s/iter total_throughput: 3016.45 samples/s lr: 9.00e-04  
[09/22 10:38:32] lb.utils.events INFO:  eta: 12:58:35  iteration: 77199/375342  consumed_samples: 79052800  total_loss: 3.899  time: 0.3395 s/iter  data_time: 0.2185 s/iter total_throughput: 3016.35 samples/s lr: 9.00e-04  
[09/22 10:39:06] lb.utils.events INFO:  eta: 12:58:43  iteration: 77299/375342  consumed_samples: 79155200  total_loss: 3.907  time: 0.3395 s/iter  data_time: 0.2030 s/iter total_throughput: 3016.35 samples/s lr: 9.00e-04  
[09/22 10:39:41] lb.utils.events INFO:  eta: 12:57:02  iteration: 77399/375342  consumed_samples: 79257600  total_loss: 3.907  time: 0.3395 s/iter  data_time: 0.2199 s/iter total_throughput: 3016.32 samples/s lr: 9.00e-04  
[09/22 10:40:16] lb.utils.events INFO:  eta: 12:56:46  iteration: 77499/375342  consumed_samples: 79360000  total_loss: 3.908  time: 0.3395 s/iter  data_time: 0.2371 s/iter total_throughput: 3016.21 samples/s lr: 8.99e-04  
[09/22 10:40:50] lb.utils.events INFO:  eta: 12:57:12  iteration: 77599/375342  consumed_samples: 79462400  total_loss: 3.898  time: 0.3395 s/iter  data_time: 0.2222 s/iter total_throughput: 3016.19 samples/s lr: 8.99e-04  
[09/22 10:41:24] lb.utils.events INFO:  eta: 12:57:18  iteration: 77699/375342  consumed_samples: 79564800  total_loss: 3.902  time: 0.3395 s/iter  data_time: 0.2125 s/iter total_throughput: 3016.20 samples/s lr: 8.99e-04  
[09/22 10:41:58] lb.utils.events INFO:  eta: 12:56:22  iteration: 77799/375342  consumed_samples: 79667200  total_loss: 3.912  time: 0.3395 s/iter  data_time: 0.2095 s/iter total_throughput: 3016.16 samples/s lr: 8.99e-04  
[09/22 10:42:31] lb.utils.events INFO:  eta: 12:59:20  iteration: 77899/375342  consumed_samples: 79769600  total_loss: 3.891  time: 0.3395 s/iter  data_time: 0.1979 s/iter total_throughput: 3016.20 samples/s lr: 8.98e-04  
[09/22 10:43:06] lb.utils.events INFO:  eta: 13:00:33  iteration: 77999/375342  consumed_samples: 79872000  total_loss: 3.887  time: 0.3395 s/iter  data_time: 0.2082 s/iter total_throughput: 3016.18 samples/s lr: 8.98e-04  
[09/22 10:43:40] lb.utils.events INFO:  eta: 13:00:31  iteration: 78099/375342  consumed_samples: 79974400  total_loss: 3.913  time: 0.3395 s/iter  data_time: 0.2171 s/iter total_throughput: 3016.16 samples/s lr: 8.98e-04  
[09/22 10:44:14] lb.utils.events INFO:  eta: 13:00:37  iteration: 78199/375342  consumed_samples: 80076800  total_loss: 3.915  time: 0.3395 s/iter  data_time: 0.2220 s/iter total_throughput: 3016.12 samples/s lr: 8.98e-04  
[09/22 10:44:48] lb.utils.events INFO:  eta: 12:59:05  iteration: 78299/375342  consumed_samples: 80179200  total_loss: 3.915  time: 0.3395 s/iter  data_time: 0.2134 s/iter total_throughput: 3016.09 samples/s lr: 8.97e-04  
[09/22 10:45:22] lb.utils.events INFO:  eta: 12:59:25  iteration: 78399/375342  consumed_samples: 80281600  total_loss: 3.9  time: 0.3395 s/iter  data_time: 0.2063 s/iter total_throughput: 3016.08 samples/s lr: 8.97e-04  
[09/22 10:45:56] lb.utils.events INFO:  eta: 12:58:33  iteration: 78499/375342  consumed_samples: 80384000  total_loss: 3.886  time: 0.3395 s/iter  data_time: 0.2168 s/iter total_throughput: 3016.07 samples/s lr: 8.97e-04  
[09/22 10:46:31] lb.utils.events INFO:  eta: 12:58:18  iteration: 78599/375342  consumed_samples: 80486400  total_loss: 3.881  time: 0.3395 s/iter  data_time: 0.2194 s/iter total_throughput: 3016.03 samples/s lr: 8.97e-04  
[09/22 10:47:04] lb.utils.events INFO:  eta: 12:58:10  iteration: 78699/375342  consumed_samples: 80588800  total_loss: 3.878  time: 0.3395 s/iter  data_time: 0.2043 s/iter total_throughput: 3016.05 samples/s lr: 8.96e-04  
[09/22 10:47:39] lb.utils.events INFO:  eta: 12:57:55  iteration: 78799/375342  consumed_samples: 80691200  total_loss: 3.883  time: 0.3395 s/iter  data_time: 0.2118 s/iter total_throughput: 3016.04 samples/s lr: 8.96e-04  
[09/22 10:48:12] lb.utils.events INFO:  eta: 12:56:47  iteration: 78899/375342  consumed_samples: 80793600  total_loss: 3.875  time: 0.3395 s/iter  data_time: 0.2046 s/iter total_throughput: 3016.06 samples/s lr: 8.96e-04  
[09/22 10:48:46] lb.utils.events INFO:  eta: 12:56:42  iteration: 78999/375342  consumed_samples: 80896000  total_loss: 3.866  time: 0.3395 s/iter  data_time: 0.2127 s/iter total_throughput: 3016.07 samples/s lr: 8.96e-04  
[09/22 10:49:20] lb.utils.events INFO:  eta: 12:56:45  iteration: 79099/375342  consumed_samples: 80998400  total_loss: 3.862  time: 0.3395 s/iter  data_time: 0.2147 s/iter total_throughput: 3016.07 samples/s lr: 8.95e-04  
[09/22 10:49:54] lb.utils.events INFO:  eta: 12:55:53  iteration: 79199/375342  consumed_samples: 81100800  total_loss: 3.879  time: 0.3395 s/iter  data_time: 0.2215 s/iter total_throughput: 3016.08 samples/s lr: 8.95e-04  
[09/22 10:50:28] lb.utils.events INFO:  eta: 12:56:58  iteration: 79299/375342  consumed_samples: 81203200  total_loss: 3.897  time: 0.3395 s/iter  data_time: 0.2148 s/iter total_throughput: 3016.12 samples/s lr: 8.95e-04  
[09/22 10:51:02] lb.utils.events INFO:  eta: 12:56:23  iteration: 79399/375342  consumed_samples: 81305600  total_loss: 3.888  time: 0.3395 s/iter  data_time: 0.2200 s/iter total_throughput: 3016.06 samples/s lr: 8.95e-04  
[09/22 10:51:36] lb.utils.events INFO:  eta: 12:56:54  iteration: 79499/375342  consumed_samples: 81408000  total_loss: 3.881  time: 0.3395 s/iter  data_time: 0.2037 s/iter total_throughput: 3016.09 samples/s lr: 8.94e-04  
[09/22 10:52:10] lb.utils.events INFO:  eta: 12:56:38  iteration: 79599/375342  consumed_samples: 81510400  total_loss: 3.889  time: 0.3395 s/iter  data_time: 0.2165 s/iter total_throughput: 3016.04 samples/s lr: 8.94e-04  
[09/22 10:52:44] lb.utils.events INFO:  eta: 12:56:46  iteration: 79699/375342  consumed_samples: 81612800  total_loss: 3.89  time: 0.3395 s/iter  data_time: 0.2234 s/iter total_throughput: 3016.07 samples/s lr: 8.94e-04  
[09/22 10:53:18] lb.utils.events INFO:  eta: 12:55:38  iteration: 79799/375342  consumed_samples: 81715200  total_loss: 3.886  time: 0.3395 s/iter  data_time: 0.2167 s/iter total_throughput: 3016.03 samples/s lr: 8.94e-04  
[09/22 10:53:52] lb.utils.events INFO:  eta: 12:54:55  iteration: 79899/375342  consumed_samples: 81817600  total_loss: 3.87  time: 0.3395 s/iter  data_time: 0.2225 s/iter total_throughput: 3016.01 samples/s lr: 8.93e-04  
[09/22 10:54:27] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0079999
[09/22 10:54:27] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/22 10:54:27] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/22 10:54:32] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0988 s/iter. Inference: 0.1626 s/iter. Eval: 0.0020 s/iter. Total: 0.2634 s/iter. ETA=0:00:09
[09/22 10:54:37] lb.evaluation.evaluator INFO: Inference done 29696/50000. Dataloading: 0.0848 s/iter. Inference: 0.2122 s/iter. Eval: 0.0020 s/iter. Total: 0.2991 s/iter. ETA=0:00:05
[09/22 10:54:42] lb.evaluation.evaluator INFO: Inference done 49152/50000. Dataloading: 0.0745 s/iter. Inference: 0.2072 s/iter. Eval: 0.0020 s/iter. Total: 0.2839 s/iter. ETA=0:00:00
[09/22 10:54:43] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/22 10:54:43] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.570490 (0.000251 s / iter per device, on 8 devices)
[09/22 10:54:43] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:09 (0.000185 s / iter per device, on 8 devices)
[09/22 10:54:43] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/22 10:54:43] lb.evaluation.utils INFO: copypaste: Acc@1=70.336
[09/22 10:54:43] lb.evaluation.utils INFO: copypaste: Acc@5=90.104
[09/22 10:54:43] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 70.33600, better than last best score 69.48200 @ iteration 74999.
[09/22 10:54:43] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/22 10:54:43] lb.utils.events INFO:  eta: 12:54:53  iteration: 79999/375342  consumed_samples: 81920000  total_loss: 3.895  time: 0.3395 s/iter  data_time: 0.2279 s/iter total_throughput: 3015.97 samples/s lr: 8.93e-04  
[09/22 10:55:15] lb.utils.events INFO:  eta: 12:57:21  iteration: 80099/375342  consumed_samples: 82022400  total_loss: 3.91  time: 0.3395 s/iter  data_time: 0.2571 s/iter total_throughput: 3016.20 samples/s lr: 8.93e-04  
[09/22 10:55:49] lb.utils.events INFO:  eta: 12:57:37  iteration: 80199/375342  consumed_samples: 82124800  total_loss: 3.881  time: 0.3395 s/iter  data_time: 0.2194 s/iter total_throughput: 3016.17 samples/s lr: 8.93e-04  
[09/22 10:56:23] lb.utils.events INFO:  eta: 12:55:55  iteration: 80299/375342  consumed_samples: 82227200  total_loss: 3.865  time: 0.3395 s/iter  data_time: 0.2122 s/iter total_throughput: 3016.19 samples/s lr: 8.92e-04  
[09/22 10:56:57] lb.utils.events INFO:  eta: 12:56:13  iteration: 80399/375342  consumed_samples: 82329600  total_loss: 3.855  time: 0.3395 s/iter  data_time: 0.2115 s/iter total_throughput: 3016.18 samples/s lr: 8.92e-04  
[09/22 10:57:31] lb.utils.events INFO:  eta: 12:56:32  iteration: 80499/375342  consumed_samples: 82432000  total_loss: 3.889  time: 0.3395 s/iter  data_time: 0.2076 s/iter total_throughput: 3016.20 samples/s lr: 8.92e-04  
[09/22 10:58:05] lb.utils.events INFO:  eta: 12:56:45  iteration: 80599/375342  consumed_samples: 82534400  total_loss: 3.89  time: 0.3395 s/iter  data_time: 0.2123 s/iter total_throughput: 3016.17 samples/s lr: 8.92e-04  
[09/22 10:58:39] lb.utils.events INFO:  eta: 12:56:54  iteration: 80699/375342  consumed_samples: 82636800  total_loss: 3.892  time: 0.3395 s/iter  data_time: 0.2220 s/iter total_throughput: 3016.18 samples/s lr: 8.91e-04  
[09/22 10:59:13] lb.utils.events INFO:  eta: 12:57:14  iteration: 80799/375342  consumed_samples: 82739200  total_loss: 3.893  time: 0.3395 s/iter  data_time: 0.2084 s/iter total_throughput: 3016.17 samples/s lr: 8.91e-04  
[09/22 10:59:47] lb.utils.events INFO:  eta: 12:57:55  iteration: 80899/375342  consumed_samples: 82841600  total_loss: 3.886  time: 0.3395 s/iter  data_time: 0.2071 s/iter total_throughput: 3016.20 samples/s lr: 8.91e-04  
[09/22 11:00:21] lb.utils.events INFO:  eta: 12:56:42  iteration: 80999/375342  consumed_samples: 82944000  total_loss: 3.888  time: 0.3395 s/iter  data_time: 0.2120 s/iter total_throughput: 3016.18 samples/s lr: 8.91e-04  
[09/22 11:00:55] lb.utils.events INFO:  eta: 12:52:32  iteration: 81099/375342  consumed_samples: 83046400  total_loss: 3.896  time: 0.3395 s/iter  data_time: 0.2116 s/iter total_throughput: 3016.16 samples/s lr: 8.90e-04  
[09/22 11:01:30] lb.utils.events INFO:  eta: 12:52:47  iteration: 81199/375342  consumed_samples: 83148800  total_loss: 3.896  time: 0.3395 s/iter  data_time: 0.2180 s/iter total_throughput: 3016.11 samples/s lr: 8.90e-04  
[09/22 11:02:03] lb.utils.events INFO:  eta: 12:53:03  iteration: 81299/375342  consumed_samples: 83251200  total_loss: 3.896  time: 0.3395 s/iter  data_time: 0.2082 s/iter total_throughput: 3016.16 samples/s lr: 8.90e-04  
[09/22 11:02:37] lb.utils.events INFO:  eta: 12:53:43  iteration: 81399/375342  consumed_samples: 83353600  total_loss: 3.897  time: 0.3395 s/iter  data_time: 0.2195 s/iter total_throughput: 3016.12 samples/s lr: 8.89e-04  
[09/22 11:03:11] lb.utils.events INFO:  eta: 12:51:46  iteration: 81499/375342  consumed_samples: 83456000  total_loss: 3.888  time: 0.3395 s/iter  data_time: 0.2151 s/iter total_throughput: 3016.14 samples/s lr: 8.89e-04  
[09/22 11:03:45] lb.utils.events INFO:  eta: 12:51:42  iteration: 81599/375342  consumed_samples: 83558400  total_loss: 3.871  time: 0.3395 s/iter  data_time: 0.2093 s/iter total_throughput: 3016.17 samples/s lr: 8.89e-04  
[09/22 11:04:18] lb.utils.events INFO:  eta: 12:50:58  iteration: 81699/375342  consumed_samples: 83660800  total_loss: 3.873  time: 0.3395 s/iter  data_time: 0.2083 s/iter total_throughput: 3016.25 samples/s lr: 8.89e-04  
[09/22 11:04:52] lb.utils.events INFO:  eta: 12:49:12  iteration: 81799/375342  consumed_samples: 83763200  total_loss: 3.874  time: 0.3395 s/iter  data_time: 0.2117 s/iter total_throughput: 3016.24 samples/s lr: 8.88e-04  
[09/22 11:05:26] lb.utils.events INFO:  eta: 12:48:34  iteration: 81899/375342  consumed_samples: 83865600  total_loss: 3.885  time: 0.3395 s/iter  data_time: 0.2169 s/iter total_throughput: 3016.22 samples/s lr: 8.88e-04  
[09/22 11:06:01] lb.utils.events INFO:  eta: 12:47:35  iteration: 81999/375342  consumed_samples: 83968000  total_loss: 3.907  time: 0.3395 s/iter  data_time: 0.2126 s/iter total_throughput: 3016.17 samples/s lr: 8.88e-04  
[09/22 11:06:36] lb.utils.events INFO:  eta: 12:47:32  iteration: 82099/375342  consumed_samples: 84070400  total_loss: 3.887  time: 0.3395 s/iter  data_time: 0.2320 s/iter total_throughput: 3016.06 samples/s lr: 8.88e-04  
[09/22 11:07:10] lb.utils.events INFO:  eta: 12:47:56  iteration: 82199/375342  consumed_samples: 84172800  total_loss: 3.883  time: 0.3395 s/iter  data_time: 0.2165 s/iter total_throughput: 3016.04 samples/s lr: 8.87e-04  
[09/22 11:07:44] lb.utils.events INFO:  eta: 12:46:31  iteration: 82299/375342  consumed_samples: 84275200  total_loss: 3.894  time: 0.3395 s/iter  data_time: 0.2145 s/iter total_throughput: 3016.05 samples/s lr: 8.87e-04  
[09/22 11:08:17] lb.utils.events INFO:  eta: 12:46:39  iteration: 82399/375342  consumed_samples: 84377600  total_loss: 3.886  time: 0.3395 s/iter  data_time: 0.2124 s/iter total_throughput: 3016.08 samples/s lr: 8.87e-04  
[09/22 11:08:52] lb.utils.events INFO:  eta: 12:46:29  iteration: 82499/375342  consumed_samples: 84480000  total_loss: 3.896  time: 0.3395 s/iter  data_time: 0.2053 s/iter total_throughput: 3016.06 samples/s lr: 8.87e-04  
[09/22 11:09:26] lb.utils.events INFO:  eta: 12:45:47  iteration: 82599/375342  consumed_samples: 84582400  total_loss: 3.89  time: 0.3395 s/iter  data_time: 0.2132 s/iter total_throughput: 3016.02 samples/s lr: 8.86e-04  
[09/22 11:10:00] lb.utils.events INFO:  eta: 12:43:05  iteration: 82699/375342  consumed_samples: 84684800  total_loss: 3.883  time: 0.3395 s/iter  data_time: 0.2108 s/iter total_throughput: 3016.02 samples/s lr: 8.86e-04  
[09/22 11:10:34] lb.utils.events INFO:  eta: 12:43:42  iteration: 82799/375342  consumed_samples: 84787200  total_loss: 3.899  time: 0.3395 s/iter  data_time: 0.2177 s/iter total_throughput: 3016.04 samples/s lr: 8.86e-04  
[09/22 11:11:07] lb.utils.events INFO:  eta: 12:44:39  iteration: 82899/375342  consumed_samples: 84889600  total_loss: 3.883  time: 0.3395 s/iter  data_time: 0.2091 s/iter total_throughput: 3016.09 samples/s lr: 8.86e-04  
[09/22 11:11:41] lb.utils.events INFO:  eta: 12:45:41  iteration: 82999/375342  consumed_samples: 84992000  total_loss: 3.898  time: 0.3395 s/iter  data_time: 0.2211 s/iter total_throughput: 3016.15 samples/s lr: 8.85e-04  
[09/22 11:12:15] lb.utils.events INFO:  eta: 12:45:30  iteration: 83099/375342  consumed_samples: 85094400  total_loss: 3.908  time: 0.3395 s/iter  data_time: 0.2114 s/iter total_throughput: 3016.14 samples/s lr: 8.85e-04  
[09/22 11:12:48] lb.utils.events INFO:  eta: 12:45:14  iteration: 83199/375342  consumed_samples: 85196800  total_loss: 3.896  time: 0.3395 s/iter  data_time: 0.2015 s/iter total_throughput: 3016.15 samples/s lr: 8.85e-04  
[09/22 11:13:23] lb.utils.events INFO:  eta: 12:44:58  iteration: 83299/375342  consumed_samples: 85299200  total_loss: 3.89  time: 0.3395 s/iter  data_time: 0.2139 s/iter total_throughput: 3016.13 samples/s lr: 8.84e-04  
[09/22 11:13:56] lb.utils.events INFO:  eta: 12:45:00  iteration: 83399/375342  consumed_samples: 85401600  total_loss: 3.908  time: 0.3395 s/iter  data_time: 0.2136 s/iter total_throughput: 3016.23 samples/s lr: 8.84e-04  
[09/22 11:14:29] lb.utils.events INFO:  eta: 12:45:03  iteration: 83499/375342  consumed_samples: 85504000  total_loss: 3.914  time: 0.3395 s/iter  data_time: 0.2041 s/iter total_throughput: 3016.28 samples/s lr: 8.84e-04  
[09/22 11:15:03] lb.utils.events INFO:  eta: 12:44:11  iteration: 83599/375342  consumed_samples: 85606400  total_loss: 3.902  time: 0.3395 s/iter  data_time: 0.2284 s/iter total_throughput: 3016.31 samples/s lr: 8.84e-04  
[09/22 11:15:36] lb.utils.events INFO:  eta: 12:45:33  iteration: 83699/375342  consumed_samples: 85708800  total_loss: 3.884  time: 0.3395 s/iter  data_time: 0.1992 s/iter total_throughput: 3016.34 samples/s lr: 8.83e-04  
[09/22 11:16:10] lb.utils.events INFO:  eta: 12:46:27  iteration: 83799/375342  consumed_samples: 85811200  total_loss: 3.877  time: 0.3395 s/iter  data_time: 0.2158 s/iter total_throughput: 3016.37 samples/s lr: 8.83e-04  
[09/22 11:16:44] lb.utils.events INFO:  eta: 12:46:11  iteration: 83899/375342  consumed_samples: 85913600  total_loss: 3.86  time: 0.3395 s/iter  data_time: 0.2083 s/iter total_throughput: 3016.39 samples/s lr: 8.83e-04  
[09/22 11:17:18] lb.utils.events INFO:  eta: 12:45:00  iteration: 83999/375342  consumed_samples: 86016000  total_loss: 3.852  time: 0.3395 s/iter  data_time: 0.2067 s/iter total_throughput: 3016.42 samples/s lr: 8.83e-04  
[09/22 11:17:51] lb.utils.events INFO:  eta: 12:45:44  iteration: 84099/375342  consumed_samples: 86118400  total_loss: 3.867  time: 0.3395 s/iter  data_time: 0.2204 s/iter total_throughput: 3016.45 samples/s lr: 8.82e-04  
[09/22 11:18:26] lb.utils.events INFO:  eta: 12:44:18  iteration: 84199/375342  consumed_samples: 86220800  total_loss: 3.879  time: 0.3395 s/iter  data_time: 0.2419 s/iter total_throughput: 3016.32 samples/s lr: 8.82e-04  
[09/22 11:19:01] lb.utils.events INFO:  eta: 12:44:00  iteration: 84299/375342  consumed_samples: 86323200  total_loss: 3.868  time: 0.3395 s/iter  data_time: 0.2150 s/iter total_throughput: 3016.27 samples/s lr: 8.82e-04  
[09/22 11:19:35] lb.utils.events INFO:  eta: 12:44:16  iteration: 84399/375342  consumed_samples: 86425600  total_loss: 3.886  time: 0.3395 s/iter  data_time: 0.2152 s/iter total_throughput: 3016.26 samples/s lr: 8.82e-04  
[09/22 11:20:10] lb.utils.events INFO:  eta: 12:43:32  iteration: 84499/375342  consumed_samples: 86528000  total_loss: 3.875  time: 0.3395 s/iter  data_time: 0.2152 s/iter total_throughput: 3016.19 samples/s lr: 8.81e-04  
[09/22 11:20:46] lb.utils.events INFO:  eta: 12:42:22  iteration: 84599/375342  consumed_samples: 86630400  total_loss: 3.863  time: 0.3395 s/iter  data_time: 0.2394 s/iter total_throughput: 3015.96 samples/s lr: 8.81e-04  
[09/22 11:21:21] lb.utils.events INFO:  eta: 12:41:30  iteration: 84699/375342  consumed_samples: 86732800  total_loss: 3.888  time: 0.3395 s/iter  data_time: 0.2195 s/iter total_throughput: 3015.85 samples/s lr: 8.81e-04  
[09/22 11:21:56] lb.utils.events INFO:  eta: 12:37:22  iteration: 84799/375342  consumed_samples: 86835200  total_loss: 3.868  time: 0.3396 s/iter  data_time: 0.2306 s/iter total_throughput: 3015.71 samples/s lr: 8.80e-04  
[09/22 11:22:31] lb.utils.events INFO:  eta: 12:34:44  iteration: 84899/375342  consumed_samples: 86937600  total_loss: 3.842  time: 0.3396 s/iter  data_time: 0.2375 s/iter total_throughput: 3015.59 samples/s lr: 8.80e-04  
[09/22 11:23:06] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0084999
[09/22 11:23:07] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/22 11:23:07] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/22 11:23:11] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0899 s/iter. Inference: 0.1656 s/iter. Eval: 0.0021 s/iter. Total: 0.2576 s/iter. ETA=0:00:09
[09/22 11:23:16] lb.evaluation.evaluator INFO: Inference done 29696/50000. Dataloading: 0.1102 s/iter. Inference: 0.1836 s/iter. Eval: 0.0021 s/iter. Total: 0.2960 s/iter. ETA=0:00:05
[09/22 11:23:22] lb.evaluation.evaluator INFO: Inference done 50000/50000. Dataloading: 0.1051 s/iter. Inference: 0.1760 s/iter. Eval: 0.0021 s/iter. Total: 0.2833 s/iter. ETA=0:00:00
[09/22 11:23:22] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/22 11:23:22] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.467986 (0.000249 s / iter per device, on 8 devices)
[09/22 11:23:22] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000155 s / iter per device, on 8 devices)
[09/22 11:23:22] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/22 11:23:22] lb.evaluation.utils INFO: copypaste: Acc@1=69.91000000000001
[09/22 11:23:22] lb.evaluation.utils INFO: copypaste: Acc@5=89.786
[09/22 11:23:22] lb.engine.hooks INFO: Not saving as latest eval score for Acc@1 is 69.91000, not better than best score 70.33600 @ iteration 79999.
[09/22 11:23:22] lb.utils.events INFO:  eta: 12:33:58  iteration: 84999/375342  consumed_samples: 87040000  total_loss: 3.866  time: 0.3396 s/iter  data_time: 0.2247 s/iter total_throughput: 3015.51 samples/s lr: 8.80e-04  
[09/22 11:23:53] lb.utils.events INFO:  eta: 12:35:37  iteration: 85099/375342  consumed_samples: 87142400  total_loss: 3.876  time: 0.3395 s/iter  data_time: 0.2458 s/iter total_throughput: 3015.76 samples/s lr: 8.80e-04  
[09/22 11:24:27] lb.utils.events INFO:  eta: 12:46:10  iteration: 85199/375342  consumed_samples: 87244800  total_loss: 3.849  time: 0.3395 s/iter  data_time: 0.2337 s/iter total_throughput: 3015.77 samples/s lr: 8.79e-04  
[09/22 11:25:01] lb.utils.events INFO:  eta: 12:46:54  iteration: 85299/375342  consumed_samples: 87347200  total_loss: 3.848  time: 0.3395 s/iter  data_time: 0.2069 s/iter total_throughput: 3015.80 samples/s lr: 8.79e-04  
[09/22 11:25:36] lb.utils.events INFO:  eta: 12:45:24  iteration: 85399/375342  consumed_samples: 87449600  total_loss: 3.863  time: 0.3396 s/iter  data_time: 0.2304 s/iter total_throughput: 3015.65 samples/s lr: 8.79e-04  
[09/22 11:26:11] lb.utils.events INFO:  eta: 12:44:13  iteration: 85499/375342  consumed_samples: 87552000  total_loss: 3.864  time: 0.3396 s/iter  data_time: 0.2183 s/iter total_throughput: 3015.57 samples/s lr: 8.79e-04  
[09/22 11:26:45] lb.utils.events INFO:  eta: 12:44:53  iteration: 85599/375342  consumed_samples: 87654400  total_loss: 3.875  time: 0.3396 s/iter  data_time: 0.2134 s/iter total_throughput: 3015.53 samples/s lr: 8.78e-04  
[09/22 11:27:19] lb.utils.events INFO:  eta: 12:44:53  iteration: 85699/375342  consumed_samples: 87756800  total_loss: 3.903  time: 0.3396 s/iter  data_time: 0.2133 s/iter total_throughput: 3015.50 samples/s lr: 8.78e-04  
[09/22 11:27:54] lb.utils.events INFO:  eta: 12:44:41  iteration: 85799/375342  consumed_samples: 87859200  total_loss: 3.885  time: 0.3396 s/iter  data_time: 0.2154 s/iter total_throughput: 3015.40 samples/s lr: 8.78e-04  
[09/22 11:28:29] lb.utils.events INFO:  eta: 12:44:41  iteration: 85899/375342  consumed_samples: 87961600  total_loss: 3.861  time: 0.3396 s/iter  data_time: 0.2200 s/iter total_throughput: 3015.32 samples/s lr: 8.77e-04  
[09/22 11:29:04] lb.utils.events INFO:  eta: 12:43:54  iteration: 85999/375342  consumed_samples: 88064000  total_loss: 3.859  time: 0.3396 s/iter  data_time: 0.2257 s/iter total_throughput: 3015.18 samples/s lr: 8.77e-04  
[09/22 11:29:39] lb.utils.events INFO:  eta: 12:41:42  iteration: 86099/375342  consumed_samples: 88166400  total_loss: 3.845  time: 0.3396 s/iter  data_time: 0.2076 s/iter total_throughput: 3015.14 samples/s lr: 8.77e-04  
[09/22 11:30:13] lb.utils.events INFO:  eta: 12:34:13  iteration: 86199/375342  consumed_samples: 88268800  total_loss: 3.854  time: 0.3396 s/iter  data_time: 0.2172 s/iter total_throughput: 3015.12 samples/s lr: 8.77e-04  
[09/22 11:30:47] lb.utils.events INFO:  eta: 12:32:33  iteration: 86299/375342  consumed_samples: 88371200  total_loss: 3.865  time: 0.3396 s/iter  data_time: 0.2216 s/iter total_throughput: 3015.07 samples/s lr: 8.76e-04  
[09/22 11:31:22] lb.utils.events INFO:  eta: 12:32:48  iteration: 86399/375342  consumed_samples: 88473600  total_loss: 3.866  time: 0.3396 s/iter  data_time: 0.2129 s/iter total_throughput: 3015.01 samples/s lr: 8.76e-04  
[09/22 11:31:57] lb.utils.events INFO:  eta: 12:32:32  iteration: 86499/375342  consumed_samples: 88576000  total_loss: 3.846  time: 0.3396 s/iter  data_time: 0.2327 s/iter total_throughput: 3014.90 samples/s lr: 8.76e-04  
[09/22 11:32:32] lb.utils.events INFO:  eta: 12:32:31  iteration: 86599/375342  consumed_samples: 88678400  total_loss: 3.846  time: 0.3397 s/iter  data_time: 0.2336 s/iter total_throughput: 3014.83 samples/s lr: 8.76e-04  
[09/22 11:33:06] lb.utils.events INFO:  eta: 12:31:21  iteration: 86699/375342  consumed_samples: 88780800  total_loss: 3.868  time: 0.3397 s/iter  data_time: 0.2256 s/iter total_throughput: 3014.77 samples/s lr: 8.75e-04  
[09/22 11:33:41] lb.utils.events INFO:  eta: 12:31:47  iteration: 86799/375342  consumed_samples: 88883200  total_loss: 3.871  time: 0.3397 s/iter  data_time: 0.2264 s/iter total_throughput: 3014.70 samples/s lr: 8.75e-04  
[09/22 11:34:15] lb.utils.events INFO:  eta: 12:31:36  iteration: 86899/375342  consumed_samples: 88985600  total_loss: 3.846  time: 0.3397 s/iter  data_time: 0.2120 s/iter total_throughput: 3014.65 samples/s lr: 8.75e-04  
[09/22 11:34:50] lb.utils.events INFO:  eta: 12:32:09  iteration: 86999/375342  consumed_samples: 89088000  total_loss: 3.858  time: 0.3397 s/iter  data_time: 0.2372 s/iter total_throughput: 3014.59 samples/s lr: 8.74e-04  
[09/22 11:35:24] lb.utils.events INFO:  eta: 12:33:14  iteration: 87099/375342  consumed_samples: 89190400  total_loss: 3.871  time: 0.3397 s/iter  data_time: 0.2098 s/iter total_throughput: 3014.55 samples/s lr: 8.74e-04  
[09/22 11:35:59] lb.utils.events INFO:  eta: 12:32:28  iteration: 87199/375342  consumed_samples: 89292800  total_loss: 3.846  time: 0.3397 s/iter  data_time: 0.2314 s/iter total_throughput: 3014.47 samples/s lr: 8.74e-04  
[09/22 11:36:34] lb.utils.events INFO:  eta: 12:31:18  iteration: 87299/375342  consumed_samples: 89395200  total_loss: 3.854  time: 0.3397 s/iter  data_time: 0.2273 s/iter total_throughput: 3014.40 samples/s lr: 8.74e-04  
[09/22 11:37:08] lb.utils.events INFO:  eta: 12:30:33  iteration: 87399/375342  consumed_samples: 89497600  total_loss: 3.864  time: 0.3397 s/iter  data_time: 0.2175 s/iter total_throughput: 3014.33 samples/s lr: 8.73e-04  
[09/22 11:37:44] lb.utils.events INFO:  eta: 12:30:25  iteration: 87499/375342  consumed_samples: 89600000  total_loss: 3.866  time: 0.3397 s/iter  data_time: 0.2350 s/iter total_throughput: 3014.20 samples/s lr: 8.73e-04  
[09/22 11:38:18] lb.utils.events INFO:  eta: 12:30:07  iteration: 87599/375342  consumed_samples: 89702400  total_loss: 3.87  time: 0.3397 s/iter  data_time: 0.2264 s/iter total_throughput: 3014.14 samples/s lr: 8.73e-04  
[09/22 11:38:53] lb.utils.events INFO:  eta: 12:29:22  iteration: 87699/375342  consumed_samples: 89804800  total_loss: 3.832  time: 0.3397 s/iter  data_time: 0.2257 s/iter total_throughput: 3014.02 samples/s lr: 8.73e-04  
[09/22 11:39:28] lb.utils.events INFO:  eta: 12:29:26  iteration: 87799/375342  consumed_samples: 89907200  total_loss: 3.832  time: 0.3398 s/iter  data_time: 0.2145 s/iter total_throughput: 3013.97 samples/s lr: 8.72e-04  
[09/22 11:40:02] lb.utils.events INFO:  eta: 12:29:07  iteration: 87899/375342  consumed_samples: 90009600  total_loss: 3.861  time: 0.3398 s/iter  data_time: 0.2131 s/iter total_throughput: 3013.91 samples/s lr: 8.72e-04  
[09/22 11:40:37] lb.utils.events INFO:  eta: 12:28:04  iteration: 87999/375342  consumed_samples: 90112000  total_loss: 3.864  time: 0.3398 s/iter  data_time: 0.2082 s/iter total_throughput: 3013.84 samples/s lr: 8.72e-04  
[09/22 11:41:12] lb.utils.events INFO:  eta: 12:24:03  iteration: 88099/375342  consumed_samples: 90214400  total_loss: 3.855  time: 0.3398 s/iter  data_time: 0.2194 s/iter total_throughput: 3013.75 samples/s lr: 8.71e-04  
[09/22 11:41:46] lb.utils.events INFO:  eta: 12:25:07  iteration: 88199/375342  consumed_samples: 90316800  total_loss: 3.85  time: 0.3398 s/iter  data_time: 0.1968 s/iter total_throughput: 3013.73 samples/s lr: 8.71e-04  
[09/22 11:42:21] lb.utils.events INFO:  eta: 12:26:11  iteration: 88299/375342  consumed_samples: 90419200  total_loss: 3.878  time: 0.3398 s/iter  data_time: 0.2112 s/iter total_throughput: 3013.67 samples/s lr: 8.71e-04  
[09/22 11:42:55] lb.utils.events INFO:  eta: 12:26:32  iteration: 88399/375342  consumed_samples: 90521600  total_loss: 3.874  time: 0.3398 s/iter  data_time: 0.2248 s/iter total_throughput: 3013.63 samples/s lr: 8.71e-04  
[09/22 11:43:30] lb.utils.events INFO:  eta: 12:25:52  iteration: 88499/375342  consumed_samples: 90624000  total_loss: 3.843  time: 0.3398 s/iter  data_time: 0.2116 s/iter total_throughput: 3013.58 samples/s lr: 8.70e-04  
[09/22 11:44:04] lb.utils.events INFO:  eta: 12:25:27  iteration: 88599/375342  consumed_samples: 90726400  total_loss: 3.864  time: 0.3398 s/iter  data_time: 0.2238 s/iter total_throughput: 3013.53 samples/s lr: 8.70e-04  
[09/22 11:44:39] lb.utils.events INFO:  eta: 12:26:24  iteration: 88699/375342  consumed_samples: 90828800  total_loss: 3.869  time: 0.3398 s/iter  data_time: 0.2281 s/iter total_throughput: 3013.45 samples/s lr: 8.70e-04  
[09/22 11:45:13] lb.utils.events INFO:  eta: 12:25:17  iteration: 88799/375342  consumed_samples: 90931200  total_loss: 3.835  time: 0.3398 s/iter  data_time: 0.2174 s/iter total_throughput: 3013.45 samples/s lr: 8.69e-04  
[09/22 11:45:47] lb.utils.events INFO:  eta: 12:26:45  iteration: 88899/375342  consumed_samples: 91033600  total_loss: 3.82  time: 0.3398 s/iter  data_time: 0.2301 s/iter total_throughput: 3013.43 samples/s lr: 8.69e-04  
[09/22 11:46:22] lb.utils.events INFO:  eta: 12:26:00  iteration: 88999/375342  consumed_samples: 91136000  total_loss: 3.835  time: 0.3398 s/iter  data_time: 0.2066 s/iter total_throughput: 3013.39 samples/s lr: 8.69e-04  
[09/22 11:46:56] lb.utils.events INFO:  eta: 12:32:18  iteration: 89099/375342  consumed_samples: 91238400  total_loss: 3.831  time: 0.3398 s/iter  data_time: 0.2191 s/iter total_throughput: 3013.35 samples/s lr: 8.69e-04  
[09/22 11:47:30] lb.utils.events INFO:  eta: 12:26:38  iteration: 89199/375342  consumed_samples: 91340800  total_loss: 3.827  time: 0.3398 s/iter  data_time: 0.2192 s/iter total_throughput: 3013.29 samples/s lr: 8.68e-04  
[09/22 11:48:05] lb.utils.events INFO:  eta: 12:29:03  iteration: 89299/375342  consumed_samples: 91443200  total_loss: 3.842  time: 0.3398 s/iter  data_time: 0.2107 s/iter total_throughput: 3013.25 samples/s lr: 8.68e-04  
[09/22 11:48:39] lb.utils.events INFO:  eta: 12:27:20  iteration: 89399/375342  consumed_samples: 91545600  total_loss: 3.854  time: 0.3398 s/iter  data_time: 0.2239 s/iter total_throughput: 3013.19 samples/s lr: 8.68e-04  
[09/22 11:49:14] lb.utils.events INFO:  eta: 12:25:46  iteration: 89499/375342  consumed_samples: 91648000  total_loss: 3.859  time: 0.3398 s/iter  data_time: 0.2166 s/iter total_throughput: 3013.15 samples/s lr: 8.67e-04  
[09/22 11:49:48] lb.utils.events INFO:  eta: 12:25:50  iteration: 89599/375342  consumed_samples: 91750400  total_loss: 3.88  time: 0.3398 s/iter  data_time: 0.2083 s/iter total_throughput: 3013.12 samples/s lr: 8.67e-04  
[09/22 11:50:22] lb.utils.events INFO:  eta: 12:25:36  iteration: 89699/375342  consumed_samples: 91852800  total_loss: 3.861  time: 0.3398 s/iter  data_time: 0.2189 s/iter total_throughput: 3013.12 samples/s lr: 8.67e-04  
[09/22 11:50:56] lb.utils.events INFO:  eta: 12:26:30  iteration: 89799/375342  consumed_samples: 91955200  total_loss: 3.854  time: 0.3398 s/iter  data_time: 0.2145 s/iter total_throughput: 3013.11 samples/s lr: 8.67e-04  
[09/22 11:51:30] lb.utils.events INFO:  eta: 12:25:35  iteration: 89899/375342  consumed_samples: 92057600  total_loss: 3.857  time: 0.3398 s/iter  data_time: 0.2162 s/iter total_throughput: 3013.15 samples/s lr: 8.66e-04  
[09/22 11:52:04] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0089999
[09/22 11:52:05] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/22 11:52:05] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/22 11:52:09] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0915 s/iter. Inference: 0.1582 s/iter. Eval: 0.0021 s/iter. Total: 0.2518 s/iter. ETA=0:00:09
[09/22 11:52:14] lb.evaluation.evaluator INFO: Inference done 29696/50000. Dataloading: 0.1090 s/iter. Inference: 0.1841 s/iter. Eval: 0.0019 s/iter. Total: 0.2951 s/iter. ETA=0:00:05
[09/22 11:52:19] lb.evaluation.evaluator INFO: Inference done 49152/50000. Dataloading: 0.0912 s/iter. Inference: 0.1880 s/iter. Eval: 0.0020 s/iter. Total: 0.2813 s/iter. ETA=0:00:00
[09/22 11:52:20] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/22 11:52:20] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.557328 (0.000251 s / iter per device, on 8 devices)
[09/22 11:52:20] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:08 (0.000169 s / iter per device, on 8 devices)
[09/22 11:52:20] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/22 11:52:20] lb.evaluation.utils INFO: copypaste: Acc@1=70.77799999999999
[09/22 11:52:20] lb.evaluation.utils INFO: copypaste: Acc@5=90.18599999999999
[09/22 11:52:20] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 70.77800, better than last best score 70.33600 @ iteration 79999.
[09/22 11:52:20] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/22 11:52:21] lb.utils.events INFO:  eta: 12:27:02  iteration: 89999/375342  consumed_samples: 92160000  total_loss: 3.874  time: 0.3398 s/iter  data_time: 0.2244 s/iter total_throughput: 3013.14 samples/s lr: 8.66e-04  
[09/22 11:52:53] lb.utils.events INFO:  eta: 12:28:36  iteration: 90099/375342  consumed_samples: 92262400  total_loss: 3.864  time: 0.3398 s/iter  data_time: 0.2372 s/iter total_throughput: 3013.32 samples/s lr: 8.66e-04  
[09/22 11:53:27] lb.utils.events INFO:  eta: 12:29:10  iteration: 90199/375342  consumed_samples: 92364800  total_loss: 3.833  time: 0.3398 s/iter  data_time: 0.2125 s/iter total_throughput: 3013.27 samples/s lr: 8.66e-04  
[09/22 11:54:02] lb.utils.events INFO:  eta: 12:26:25  iteration: 90299/375342  consumed_samples: 92467200  total_loss: 3.842  time: 0.3398 s/iter  data_time: 0.2147 s/iter total_throughput: 3013.22 samples/s lr: 8.65e-04  
[09/22 11:54:36] lb.utils.events INFO:  eta: 12:26:40  iteration: 90399/375342  consumed_samples: 92569600  total_loss: 3.84  time: 0.3398 s/iter  data_time: 0.2234 s/iter total_throughput: 3013.17 samples/s lr: 8.65e-04  
[09/22 11:55:10] lb.utils.events INFO:  eta: 12:30:38  iteration: 90499/375342  consumed_samples: 92672000  total_loss: 3.832  time: 0.3398 s/iter  data_time: 0.2048 s/iter total_throughput: 3013.14 samples/s lr: 8.65e-04  
[09/22 11:55:45] lb.utils.events INFO:  eta: 12:30:11  iteration: 90599/375342  consumed_samples: 92774400  total_loss: 3.829  time: 0.3399 s/iter  data_time: 0.2268 s/iter total_throughput: 3013.08 samples/s lr: 8.64e-04  
[09/22 11:56:19] lb.utils.events INFO:  eta: 12:29:35  iteration: 90699/375342  consumed_samples: 92876800  total_loss: 3.832  time: 0.3399 s/iter  data_time: 0.2087 s/iter total_throughput: 3013.06 samples/s lr: 8.64e-04  
[09/22 11:56:54] lb.utils.events INFO:  eta: 12:29:31  iteration: 90799/375342  consumed_samples: 92979200  total_loss: 3.863  time: 0.3399 s/iter  data_time: 0.2165 s/iter total_throughput: 3013.01 samples/s lr: 8.64e-04  
[09/22 11:57:28] lb.utils.events INFO:  eta: 12:30:03  iteration: 90899/375342  consumed_samples: 93081600  total_loss: 3.859  time: 0.3399 s/iter  data_time: 0.2176 s/iter total_throughput: 3013.01 samples/s lr: 8.64e-04  
[09/22 11:58:02] lb.utils.events INFO:  eta: 12:31:03  iteration: 90999/375342  consumed_samples: 93184000  total_loss: 3.845  time: 0.3399 s/iter  data_time: 0.2205 s/iter total_throughput: 3013.00 samples/s lr: 8.63e-04  
[09/22 11:58:37] lb.utils.events INFO:  eta: 12:27:56  iteration: 91099/375342  consumed_samples: 93286400  total_loss: 3.857  time: 0.3399 s/iter  data_time: 0.2174 s/iter total_throughput: 3012.94 samples/s lr: 8.63e-04  
[09/22 11:59:11] lb.utils.events INFO:  eta: 12:25:31  iteration: 91199/375342  consumed_samples: 93388800  total_loss: 3.865  time: 0.3399 s/iter  data_time: 0.2181 s/iter total_throughput: 3012.92 samples/s lr: 8.63e-04  
[09/22 11:59:45] lb.utils.events INFO:  eta: 12:26:22  iteration: 91299/375342  consumed_samples: 93491200  total_loss: 3.86  time: 0.3399 s/iter  data_time: 0.2110 s/iter total_throughput: 3012.86 samples/s lr: 8.62e-04  
[09/22 12:00:20] lb.utils.events INFO:  eta: 12:25:25  iteration: 91399/375342  consumed_samples: 93593600  total_loss: 3.84  time: 0.3399 s/iter  data_time: 0.2163 s/iter total_throughput: 3012.81 samples/s lr: 8.62e-04  
[09/22 12:00:54] lb.utils.events INFO:  eta: 12:22:39  iteration: 91499/375342  consumed_samples: 93696000  total_loss: 3.855  time: 0.3399 s/iter  data_time: 0.2168 s/iter total_throughput: 3012.75 samples/s lr: 8.62e-04  
[09/22 12:01:29] lb.utils.events INFO:  eta: 12:20:58  iteration: 91599/375342  consumed_samples: 93798400  total_loss: 3.855  time: 0.3399 s/iter  data_time: 0.2183 s/iter total_throughput: 3012.74 samples/s lr: 8.62e-04  
[09/22 12:02:03] lb.utils.events INFO:  eta: 12:21:42  iteration: 91699/375342  consumed_samples: 93900800  total_loss: 3.833  time: 0.3399 s/iter  data_time: 0.2264 s/iter total_throughput: 3012.72 samples/s lr: 8.61e-04  
[09/22 12:02:37] lb.utils.events INFO:  eta: 12:20:11  iteration: 91799/375342  consumed_samples: 94003200  total_loss: 3.838  time: 0.3399 s/iter  data_time: 0.2233 s/iter total_throughput: 3012.69 samples/s lr: 8.61e-04  
[09/22 12:03:11] lb.utils.events INFO:  eta: 12:19:55  iteration: 91899/375342  consumed_samples: 94105600  total_loss: 3.848  time: 0.3399 s/iter  data_time: 0.2067 s/iter total_throughput: 3012.72 samples/s lr: 8.61e-04  
[09/22 12:03:45] lb.utils.events INFO:  eta: 12:18:50  iteration: 91999/375342  consumed_samples: 94208000  total_loss: 3.848  time: 0.3399 s/iter  data_time: 0.2144 s/iter total_throughput: 3012.71 samples/s lr: 8.60e-04  
[09/22 12:04:19] lb.utils.events INFO:  eta: 12:20:19  iteration: 92099/375342  consumed_samples: 94310400  total_loss: 3.852  time: 0.3399 s/iter  data_time: 0.2160 s/iter total_throughput: 3012.74 samples/s lr: 8.60e-04  
[09/22 12:04:53] lb.utils.events INFO:  eta: 12:19:22  iteration: 92199/375342  consumed_samples: 94412800  total_loss: 3.859  time: 0.3399 s/iter  data_time: 0.2037 s/iter total_throughput: 3012.74 samples/s lr: 8.60e-04  
[09/22 12:05:27] lb.utils.events INFO:  eta: 12:19:57  iteration: 92299/375342  consumed_samples: 94515200  total_loss: 3.848  time: 0.3399 s/iter  data_time: 0.2253 s/iter total_throughput: 3012.74 samples/s lr: 8.59e-04  
[09/22 12:06:01] lb.utils.events INFO:  eta: 12:20:32  iteration: 92399/375342  consumed_samples: 94617600  total_loss: 3.841  time: 0.3399 s/iter  data_time: 0.2106 s/iter total_throughput: 3012.72 samples/s lr: 8.59e-04  
[09/22 12:06:35] lb.utils.events INFO:  eta: 12:20:53  iteration: 92499/375342  consumed_samples: 94720000  total_loss: 3.849  time: 0.3399 s/iter  data_time: 0.2123 s/iter total_throughput: 3012.69 samples/s lr: 8.59e-04  
[09/22 12:07:10] lb.utils.events INFO:  eta: 12:21:07  iteration: 92599/375342  consumed_samples: 94822400  total_loss: 3.836  time: 0.3399 s/iter  data_time: 0.2098 s/iter total_throughput: 3012.65 samples/s lr: 8.59e-04  
[09/22 12:07:44] lb.utils.events INFO:  eta: 12:21:02  iteration: 92699/375342  consumed_samples: 94924800  total_loss: 3.82  time: 0.3399 s/iter  data_time: 0.2152 s/iter total_throughput: 3012.60 samples/s lr: 8.58e-04  
[09/22 12:08:18] lb.utils.events INFO:  eta: 12:22:47  iteration: 92799/375342  consumed_samples: 95027200  total_loss: 3.844  time: 0.3399 s/iter  data_time: 0.2076 s/iter total_throughput: 3012.61 samples/s lr: 8.58e-04  
[09/22 12:08:52] lb.utils.events INFO:  eta: 12:21:38  iteration: 92899/375342  consumed_samples: 95129600  total_loss: 3.861  time: 0.3399 s/iter  data_time: 0.2195 s/iter total_throughput: 3012.58 samples/s lr: 8.58e-04  
[09/22 12:09:26] lb.utils.events INFO:  eta: 12:20:23  iteration: 92999/375342  consumed_samples: 95232000  total_loss: 3.855  time: 0.3399 s/iter  data_time: 0.2073 s/iter total_throughput: 3012.57 samples/s lr: 8.57e-04  
[09/22 12:10:00] lb.utils.events INFO:  eta: 12:18:07  iteration: 93099/375342  consumed_samples: 95334400  total_loss: 3.83  time: 0.3399 s/iter  data_time: 0.2334 s/iter total_throughput: 3012.56 samples/s lr: 8.57e-04  
[09/22 12:10:35] lb.utils.events INFO:  eta: 12:18:29  iteration: 93199/375342  consumed_samples: 95436800  total_loss: 3.824  time: 0.3399 s/iter  data_time: 0.2094 s/iter total_throughput: 3012.54 samples/s lr: 8.57e-04  
[09/22 12:11:09] lb.utils.events INFO:  eta: 12:18:14  iteration: 93299/375342  consumed_samples: 95539200  total_loss: 3.845  time: 0.3399 s/iter  data_time: 0.2201 s/iter total_throughput: 3012.52 samples/s lr: 8.57e-04  
[09/22 12:11:43] lb.utils.events INFO:  eta: 12:17:42  iteration: 93399/375342  consumed_samples: 95641600  total_loss: 3.854  time: 0.3399 s/iter  data_time: 0.2172 s/iter total_throughput: 3012.50 samples/s lr: 8.56e-04  
[09/22 12:12:18] lb.utils.events INFO:  eta: 12:16:58  iteration: 93499/375342  consumed_samples: 95744000  total_loss: 3.856  time: 0.3399 s/iter  data_time: 0.2286 s/iter total_throughput: 3012.43 samples/s lr: 8.56e-04  
[09/22 12:12:52] lb.utils.events INFO:  eta: 12:14:38  iteration: 93599/375342  consumed_samples: 95846400  total_loss: 3.851  time: 0.3399 s/iter  data_time: 0.2143 s/iter total_throughput: 3012.40 samples/s lr: 8.56e-04  
[09/22 12:13:26] lb.utils.events INFO:  eta: 12:14:30  iteration: 93699/375342  consumed_samples: 95948800  total_loss: 3.842  time: 0.3399 s/iter  data_time: 0.2205 s/iter total_throughput: 3012.38 samples/s lr: 8.55e-04  
[09/22 12:14:01] lb.utils.events INFO:  eta: 12:11:36  iteration: 93799/375342  consumed_samples: 96051200  total_loss: 3.846  time: 0.3399 s/iter  data_time: 0.2180 s/iter total_throughput: 3012.32 samples/s lr: 8.55e-04  
[09/22 12:14:35] lb.utils.events INFO:  eta: 12:13:53  iteration: 93899/375342  consumed_samples: 96153600  total_loss: 3.848  time: 0.3399 s/iter  data_time: 0.2106 s/iter total_throughput: 3012.32 samples/s lr: 8.55e-04  
[09/22 12:15:09] lb.utils.events INFO:  eta: 12:15:51  iteration: 93999/375342  consumed_samples: 96256000  total_loss: 3.841  time: 0.3399 s/iter  data_time: 0.2241 s/iter total_throughput: 3012.30 samples/s lr: 8.55e-04  
[09/22 12:15:43] lb.utils.events INFO:  eta: 12:15:49  iteration: 94099/375342  consumed_samples: 96358400  total_loss: 3.847  time: 0.3399 s/iter  data_time: 0.2154 s/iter total_throughput: 3012.30 samples/s lr: 8.54e-04  
[09/22 12:16:17] lb.utils.events INFO:  eta: 12:15:45  iteration: 94199/375342  consumed_samples: 96460800  total_loss: 3.85  time: 0.3399 s/iter  data_time: 0.2120 s/iter total_throughput: 3012.33 samples/s lr: 8.54e-04  
[09/22 12:16:51] lb.utils.events INFO:  eta: 12:15:04  iteration: 94299/375342  consumed_samples: 96563200  total_loss: 3.822  time: 0.3399 s/iter  data_time: 0.2136 s/iter total_throughput: 3012.34 samples/s lr: 8.54e-04  
[09/22 12:17:25] lb.utils.events INFO:  eta: 12:15:01  iteration: 94399/375342  consumed_samples: 96665600  total_loss: 3.829  time: 0.3399 s/iter  data_time: 0.2084 s/iter total_throughput: 3012.32 samples/s lr: 8.53e-04  
[09/22 12:17:58] lb.utils.events INFO:  eta: 12:17:11  iteration: 94499/375342  consumed_samples: 96768000  total_loss: 3.844  time: 0.3399 s/iter  data_time: 0.1992 s/iter total_throughput: 3012.37 samples/s lr: 8.53e-04  
[09/22 12:18:33] lb.utils.events INFO:  eta: 12:16:46  iteration: 94599/375342  consumed_samples: 96870400  total_loss: 3.827  time: 0.3399 s/iter  data_time: 0.2139 s/iter total_throughput: 3012.35 samples/s lr: 8.53e-04  
[09/22 12:19:06] lb.utils.events INFO:  eta: 12:16:01  iteration: 94699/375342  consumed_samples: 96972800  total_loss: 3.832  time: 0.3399 s/iter  data_time: 0.2132 s/iter total_throughput: 3012.38 samples/s lr: 8.52e-04  
[09/22 12:19:40] lb.utils.events INFO:  eta: 12:16:47  iteration: 94799/375342  consumed_samples: 97075200  total_loss: 3.844  time: 0.3399 s/iter  data_time: 0.2121 s/iter total_throughput: 3012.43 samples/s lr: 8.52e-04  
[09/22 12:20:14] lb.utils.events INFO:  eta: 12:15:29  iteration: 94899/375342  consumed_samples: 97177600  total_loss: 3.864  time: 0.3399 s/iter  data_time: 0.2043 s/iter total_throughput: 3012.43 samples/s lr: 8.52e-04  
[09/22 12:20:48] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0094999
[09/22 12:20:49] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/22 12:20:49] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/22 12:20:53] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0911 s/iter. Inference: 0.1641 s/iter. Eval: 0.0022 s/iter. Total: 0.2575 s/iter. ETA=0:00:09
[09/22 12:20:59] lb.evaluation.evaluator INFO: Inference done 29696/50000. Dataloading: 0.1227 s/iter. Inference: 0.1702 s/iter. Eval: 0.0020 s/iter. Total: 0.2949 s/iter. ETA=0:00:05
[09/22 12:21:04] lb.evaluation.evaluator INFO: Inference done 50000/50000. Dataloading: 0.1153 s/iter. Inference: 0.1666 s/iter. Eval: 0.0019 s/iter. Total: 0.2838 s/iter. ETA=0:00:00
[09/22 12:21:04] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/22 12:21:04] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.494068 (0.000250 s / iter per device, on 8 devices)
[09/22 12:21:04] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000147 s / iter per device, on 8 devices)
[09/22 12:21:04] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/22 12:21:04] lb.evaluation.utils INFO: copypaste: Acc@1=70.532
[09/22 12:21:04] lb.evaluation.utils INFO: copypaste: Acc@5=89.962
[09/22 12:21:04] lb.engine.hooks INFO: Not saving as latest eval score for Acc@1 is 70.53200, not better than best score 70.77800 @ iteration 89999.
[09/22 12:21:04] lb.utils.events INFO:  eta: 12:14:42  iteration: 94999/375342  consumed_samples: 97280000  total_loss: 3.86  time: 0.3399 s/iter  data_time: 0.2354 s/iter total_throughput: 3012.39 samples/s lr: 8.52e-04  
[09/22 12:21:36] lb.utils.events INFO:  eta: 12:17:02  iteration: 95099/375342  consumed_samples: 97382400  total_loss: 3.827  time: 0.3399 s/iter  data_time: 0.2332 s/iter total_throughput: 3012.60 samples/s lr: 8.51e-04  
[09/22 12:22:10] lb.utils.events INFO:  eta: 12:18:08  iteration: 95199/375342  consumed_samples: 97484800  total_loss: 3.815  time: 0.3399 s/iter  data_time: 0.1981 s/iter total_throughput: 3012.54 samples/s lr: 8.51e-04  
[09/22 12:22:44] lb.utils.events INFO:  eta: 12:19:52  iteration: 95299/375342  consumed_samples: 97587200  total_loss: 3.814  time: 0.3399 s/iter  data_time: 0.2213 s/iter total_throughput: 3012.59 samples/s lr: 8.51e-04  
[09/22 12:23:17] lb.utils.events INFO:  eta: 12:19:51  iteration: 95399/375342  consumed_samples: 97689600  total_loss: 3.807  time: 0.3399 s/iter  data_time: 0.2016 s/iter total_throughput: 3012.64 samples/s lr: 8.50e-04  
[09/22 12:23:52] lb.utils.events INFO:  eta: 12:18:14  iteration: 95499/375342  consumed_samples: 97792000  total_loss: 3.832  time: 0.3399 s/iter  data_time: 0.2148 s/iter total_throughput: 3012.61 samples/s lr: 8.50e-04  
[09/22 12:24:25] lb.utils.events INFO:  eta: 12:18:51  iteration: 95599/375342  consumed_samples: 97894400  total_loss: 3.854  time: 0.3399 s/iter  data_time: 0.2096 s/iter total_throughput: 3012.64 samples/s lr: 8.50e-04  
[09/22 12:24:59] lb.utils.events INFO:  eta: 12:19:05  iteration: 95699/375342  consumed_samples: 97996800  total_loss: 3.84  time: 0.3399 s/iter  data_time: 0.2223 s/iter total_throughput: 3012.63 samples/s lr: 8.50e-04  
[09/22 12:25:33] lb.utils.events INFO:  eta: 12:17:35  iteration: 95799/375342  consumed_samples: 98099200  total_loss: 3.82  time: 0.3399 s/iter  data_time: 0.2147 s/iter total_throughput: 3012.67 samples/s lr: 8.49e-04  
[09/22 12:26:07] lb.utils.events INFO:  eta: 12:15:21  iteration: 95899/375342  consumed_samples: 98201600  total_loss: 3.819  time: 0.3399 s/iter  data_time: 0.2133 s/iter total_throughput: 3012.69 samples/s lr: 8.49e-04  
[09/22 12:26:41] lb.utils.events INFO:  eta: 12:14:29  iteration: 95999/375342  consumed_samples: 98304000  total_loss: 3.817  time: 0.3399 s/iter  data_time: 0.2258 s/iter total_throughput: 3012.65 samples/s lr: 8.49e-04  
[09/22 12:27:15] lb.utils.events INFO:  eta: 12:11:58  iteration: 96099/375342  consumed_samples: 98406400  total_loss: 3.824  time: 0.3399 s/iter  data_time: 0.2322 s/iter total_throughput: 3012.63 samples/s lr: 8.48e-04  
[09/22 12:27:49] lb.utils.events INFO:  eta: 12:11:33  iteration: 96199/375342  consumed_samples: 98508800  total_loss: 3.83  time: 0.3399 s/iter  data_time: 0.2058 s/iter total_throughput: 3012.67 samples/s lr: 8.48e-04  
[09/22 12:28:23] lb.utils.events INFO:  eta: 12:09:00  iteration: 96299/375342  consumed_samples: 98611200  total_loss: 3.821  time: 0.3399 s/iter  data_time: 0.2117 s/iter total_throughput: 3012.65 samples/s lr: 8.48e-04  
[09/22 12:28:57] lb.utils.events INFO:  eta: 12:07:36  iteration: 96399/375342  consumed_samples: 98713600  total_loss: 3.827  time: 0.3399 s/iter  data_time: 0.2129 s/iter total_throughput: 3012.69 samples/s lr: 8.47e-04  
[09/22 12:29:30] lb.utils.events INFO:  eta: 12:08:07  iteration: 96499/375342  consumed_samples: 98816000  total_loss: 3.828  time: 0.3399 s/iter  data_time: 0.2198 s/iter total_throughput: 3012.72 samples/s lr: 8.47e-04  
[09/22 12:30:05] lb.utils.events INFO:  eta: 12:07:09  iteration: 96599/375342  consumed_samples: 98918400  total_loss: 3.826  time: 0.3399 s/iter  data_time: 0.2185 s/iter total_throughput: 3012.67 samples/s lr: 8.47e-04  
[09/22 12:30:39] lb.utils.events INFO:  eta: 12:06:13  iteration: 96699/375342  consumed_samples: 99020800  total_loss: 3.833  time: 0.3399 s/iter  data_time: 0.2162 s/iter total_throughput: 3012.68 samples/s lr: 8.47e-04  
[09/22 12:31:13] lb.utils.events INFO:  eta: 12:05:43  iteration: 96799/375342  consumed_samples: 99123200  total_loss: 3.819  time: 0.3399 s/iter  data_time: 0.2215 s/iter total_throughput: 3012.67 samples/s lr: 8.46e-04  
[09/22 12:31:47] lb.utils.events INFO:  eta: 12:04:23  iteration: 96899/375342  consumed_samples: 99225600  total_loss: 3.797  time: 0.3399 s/iter  data_time: 0.2197 s/iter total_throughput: 3012.66 samples/s lr: 8.46e-04  
[09/22 12:32:21] lb.utils.events INFO:  eta: 12:05:37  iteration: 96999/375342  consumed_samples: 99328000  total_loss: 3.824  time: 0.3399 s/iter  data_time: 0.2069 s/iter total_throughput: 3012.68 samples/s lr: 8.46e-04  
[09/22 12:32:54] lb.utils.events INFO:  eta: 12:06:14  iteration: 97099/375342  consumed_samples: 99430400  total_loss: 3.839  time: 0.3399 s/iter  data_time: 0.2082 s/iter total_throughput: 3012.72 samples/s lr: 8.45e-04  
[09/22 12:33:28] lb.utils.events INFO:  eta: 12:05:48  iteration: 97199/375342  consumed_samples: 99532800  total_loss: 3.813  time: 0.3399 s/iter  data_time: 0.2083 s/iter total_throughput: 3012.74 samples/s lr: 8.45e-04  
[09/22 12:34:02] lb.utils.events INFO:  eta: 12:05:42  iteration: 97299/375342  consumed_samples: 99635200  total_loss: 3.82  time: 0.3399 s/iter  data_time: 0.2116 s/iter total_throughput: 3012.77 samples/s lr: 8.45e-04  
[09/22 12:34:36] lb.utils.events INFO:  eta: 12:04:51  iteration: 97399/375342  consumed_samples: 99737600  total_loss: 3.82  time: 0.3399 s/iter  data_time: 0.2180 s/iter total_throughput: 3012.77 samples/s lr: 8.44e-04  
[09/22 12:35:09] lb.utils.events INFO:  eta: 12:04:23  iteration: 97499/375342  consumed_samples: 99840000  total_loss: 3.809  time: 0.3399 s/iter  data_time: 0.2039 s/iter total_throughput: 3012.83 samples/s lr: 8.44e-04  
[09/22 12:35:43] lb.utils.events INFO:  eta: 12:01:55  iteration: 97599/375342  consumed_samples: 99942400  total_loss: 3.812  time: 0.3399 s/iter  data_time: 0.2090 s/iter total_throughput: 3012.84 samples/s lr: 8.44e-04  
[09/22 12:36:16] lb.utils.events INFO:  eta: 12:04:30  iteration: 97699/375342  consumed_samples: 100044800  total_loss: 3.832  time: 0.3399 s/iter  data_time: 0.2000 s/iter total_throughput: 3012.92 samples/s lr: 8.44e-04  
[09/22 12:36:49] lb.utils.events INFO:  eta: 12:04:21  iteration: 97799/375342  consumed_samples: 100147200  total_loss: 3.808  time: 0.3399 s/iter  data_time: 0.2070 s/iter total_throughput: 3013.00 samples/s lr: 8.43e-04  
[09/22 12:37:22] lb.utils.events INFO:  eta: 12:04:56  iteration: 97899/375342  consumed_samples: 100249600  total_loss: 3.796  time: 0.3399 s/iter  data_time: 0.2117 s/iter total_throughput: 3013.08 samples/s lr: 8.43e-04  
[09/22 12:37:56] lb.utils.events INFO:  eta: 12:05:55  iteration: 97999/375342  consumed_samples: 100352000  total_loss: 3.805  time: 0.3398 s/iter  data_time: 0.2174 s/iter total_throughput: 3013.15 samples/s lr: 8.43e-04  
[09/22 12:38:29] lb.utils.events INFO:  eta: 12:05:58  iteration: 98099/375342  consumed_samples: 100454400  total_loss: 3.806  time: 0.3398 s/iter  data_time: 0.2158 s/iter total_throughput: 3013.19 samples/s lr: 8.42e-04  
[09/22 12:39:03] lb.utils.events INFO:  eta: 12:05:42  iteration: 98199/375342  consumed_samples: 100556800  total_loss: 3.847  time: 0.3398 s/iter  data_time: 0.2132 s/iter total_throughput: 3013.21 samples/s lr: 8.42e-04  
[09/22 12:39:37] lb.utils.events INFO:  eta: 12:07:36  iteration: 98299/375342  consumed_samples: 100659200  total_loss: 3.841  time: 0.3398 s/iter  data_time: 0.2081 s/iter total_throughput: 3013.22 samples/s lr: 8.42e-04  
[09/22 12:40:11] lb.utils.events INFO:  eta: 12:08:27  iteration: 98399/375342  consumed_samples: 100761600  total_loss: 3.814  time: 0.3398 s/iter  data_time: 0.2078 s/iter total_throughput: 3013.21 samples/s lr: 8.41e-04  
[09/22 12:40:45] lb.utils.events INFO:  eta: 12:07:44  iteration: 98499/375342  consumed_samples: 100864000  total_loss: 3.81  time: 0.3398 s/iter  data_time: 0.2050 s/iter total_throughput: 3013.22 samples/s lr: 8.41e-04  
[09/22 12:41:19] lb.utils.events INFO:  eta: 12:09:12  iteration: 98599/375342  consumed_samples: 100966400  total_loss: 3.844  time: 0.3398 s/iter  data_time: 0.2072 s/iter total_throughput: 3013.21 samples/s lr: 8.41e-04  
[09/22 12:41:53] lb.utils.events INFO:  eta: 12:09:07  iteration: 98699/375342  consumed_samples: 101068800  total_loss: 3.852  time: 0.3398 s/iter  data_time: 0.2167 s/iter total_throughput: 3013.17 samples/s lr: 8.40e-04  
[09/22 12:42:27] lb.utils.events INFO:  eta: 12:08:12  iteration: 98799/375342  consumed_samples: 101171200  total_loss: 3.838  time: 0.3398 s/iter  data_time: 0.2139 s/iter total_throughput: 3013.16 samples/s lr: 8.40e-04  
[09/22 12:43:02] lb.utils.events INFO:  eta: 12:07:33  iteration: 98899/375342  consumed_samples: 101273600  total_loss: 3.811  time: 0.3398 s/iter  data_time: 0.2152 s/iter total_throughput: 3013.12 samples/s lr: 8.40e-04  
[09/22 12:43:36] lb.utils.events INFO:  eta: 12:06:26  iteration: 98999/375342  consumed_samples: 101376000  total_loss: 3.799  time: 0.3398 s/iter  data_time: 0.2106 s/iter total_throughput: 3013.14 samples/s lr: 8.40e-04  
[09/22 12:44:10] lb.utils.events INFO:  eta: 12:07:01  iteration: 99099/375342  consumed_samples: 101478400  total_loss: 3.805  time: 0.3398 s/iter  data_time: 0.2166 s/iter total_throughput: 3013.11 samples/s lr: 8.39e-04  
[09/22 12:44:44] lb.utils.events INFO:  eta: 12:05:54  iteration: 99199/375342  consumed_samples: 101580800  total_loss: 3.81  time: 0.3399 s/iter  data_time: 0.2142 s/iter total_throughput: 3013.08 samples/s lr: 8.39e-04  
[09/22 12:45:18] lb.utils.events INFO:  eta: 12:05:22  iteration: 99299/375342  consumed_samples: 101683200  total_loss: 3.815  time: 0.3398 s/iter  data_time: 0.2142 s/iter total_throughput: 3013.14 samples/s lr: 8.39e-04  
[09/22 12:45:52] lb.utils.events INFO:  eta: 12:05:23  iteration: 99399/375342  consumed_samples: 101785600  total_loss: 3.813  time: 0.3398 s/iter  data_time: 0.2147 s/iter total_throughput: 3013.13 samples/s lr: 8.38e-04  
[09/22 12:46:26] lb.utils.events INFO:  eta: 12:05:23  iteration: 99499/375342  consumed_samples: 101888000  total_loss: 3.804  time: 0.3398 s/iter  data_time: 0.2108 s/iter total_throughput: 3013.10 samples/s lr: 8.38e-04  
[09/22 12:47:01] lb.utils.events INFO:  eta: 12:03:04  iteration: 99599/375342  consumed_samples: 101990400  total_loss: 3.819  time: 0.3399 s/iter  data_time: 0.2253 s/iter total_throughput: 3013.03 samples/s lr: 8.38e-04  
[09/22 12:47:35] lb.utils.events INFO:  eta: 12:01:56  iteration: 99699/375342  consumed_samples: 102092800  total_loss: 3.836  time: 0.3399 s/iter  data_time: 0.2173 s/iter total_throughput: 3013.01 samples/s lr: 8.37e-04  
[09/22 12:48:09] lb.utils.events INFO:  eta: 12:02:50  iteration: 99799/375342  consumed_samples: 102195200  total_loss: 3.824  time: 0.3399 s/iter  data_time: 0.2150 s/iter total_throughput: 3012.99 samples/s lr: 8.37e-04  
[09/22 12:48:44] lb.utils.events INFO:  eta: 12:03:06  iteration: 99899/375342  consumed_samples: 102297600  total_loss: 3.846  time: 0.3399 s/iter  data_time: 0.2394 s/iter total_throughput: 3012.92 samples/s lr: 8.37e-04  
[09/22 12:49:18] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0099999
[09/22 12:49:19] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/22 12:49:19] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/22 12:49:23] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0992 s/iter. Inference: 0.1644 s/iter. Eval: 0.0021 s/iter. Total: 0.2657 s/iter. ETA=0:00:09
[09/22 12:49:29] lb.evaluation.evaluator INFO: Inference done 29696/50000. Dataloading: 0.0948 s/iter. Inference: 0.2011 s/iter. Eval: 0.0021 s/iter. Total: 0.2981 s/iter. ETA=0:00:05
[09/22 12:49:34] lb.evaluation.evaluator INFO: Inference done 49152/50000. Dataloading: 0.0737 s/iter. Inference: 0.2071 s/iter. Eval: 0.0020 s/iter. Total: 0.2829 s/iter. ETA=0:00:00
[09/22 12:49:34] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/22 12:49:34] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.522067 (0.000250 s / iter per device, on 8 devices)
[09/22 12:49:34] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:09 (0.000185 s / iter per device, on 8 devices)
[09/22 12:49:34] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/22 12:49:34] lb.evaluation.utils INFO: copypaste: Acc@1=71.44
[09/22 12:49:34] lb.evaluation.utils INFO: copypaste: Acc@5=90.498
[09/22 12:49:34] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 71.44000, better than last best score 70.77800 @ iteration 89999.
[09/22 12:49:34] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/22 12:49:35] lb.utils.events INFO:  eta: 12:03:17  iteration: 99999/375342  consumed_samples: 102400000  total_loss: 3.843  time: 0.3399 s/iter  data_time: 0.2060 s/iter total_throughput: 3012.91 samples/s lr: 8.37e-04  
[09/22 12:50:06] lb.utils.events INFO:  eta: 12:07:34  iteration: 100099/375342  consumed_samples: 102502400  total_loss: 3.817  time: 0.3398 s/iter  data_time: 0.2450 s/iter total_throughput: 3013.10 samples/s lr: 8.36e-04  
[09/22 12:50:41] lb.utils.events INFO:  eta: 12:07:25  iteration: 100199/375342  consumed_samples: 102604800  total_loss: 3.815  time: 0.3399 s/iter  data_time: 0.2107 s/iter total_throughput: 3013.03 samples/s lr: 8.36e-04  
[09/22 12:51:15] lb.utils.events INFO:  eta: 12:05:35  iteration: 100299/375342  consumed_samples: 102707200  total_loss: 3.804  time: 0.3399 s/iter  data_time: 0.2197 s/iter total_throughput: 3013.03 samples/s lr: 8.36e-04  
[09/22 12:51:49] lb.utils.events INFO:  eta: 12:04:37  iteration: 100399/375342  consumed_samples: 102809600  total_loss: 3.801  time: 0.3399 s/iter  data_time: 0.2208 s/iter total_throughput: 3013.01 samples/s lr: 8.35e-04  
[09/22 12:52:24] lb.utils.events INFO:  eta: 12:03:52  iteration: 100499/375342  consumed_samples: 102912000  total_loss: 3.814  time: 0.3399 s/iter  data_time: 0.2165 s/iter total_throughput: 3013.00 samples/s lr: 8.35e-04  
[09/22 12:52:58] lb.utils.events INFO:  eta: 12:04:11  iteration: 100599/375342  consumed_samples: 103014400  total_loss: 3.805  time: 0.3399 s/iter  data_time: 0.2103 s/iter total_throughput: 3012.98 samples/s lr: 8.35e-04  
[09/22 12:53:32] lb.utils.events INFO:  eta: 12:03:55  iteration: 100699/375342  consumed_samples: 103116800  total_loss: 3.796  time: 0.3399 s/iter  data_time: 0.2150 s/iter total_throughput: 3012.97 samples/s lr: 8.34e-04  
[09/22 12:54:06] lb.utils.events INFO:  eta: 12:04:03  iteration: 100799/375342  consumed_samples: 103219200  total_loss: 3.789  time: 0.3399 s/iter  data_time: 0.2107 s/iter total_throughput: 3012.94 samples/s lr: 8.34e-04  
[09/22 12:54:40] lb.utils.events INFO:  eta: 12:03:47  iteration: 100899/375342  consumed_samples: 103321600  total_loss: 3.809  time: 0.3399 s/iter  data_time: 0.2167 s/iter total_throughput: 3012.95 samples/s lr: 8.34e-04  
[09/22 12:55:14] lb.utils.events INFO:  eta: 12:02:38  iteration: 100999/375342  consumed_samples: 103424000  total_loss: 3.814  time: 0.3399 s/iter  data_time: 0.2114 s/iter total_throughput: 3012.97 samples/s lr: 8.33e-04  
[09/22 12:55:48] lb.utils.events INFO:  eta: 11:58:50  iteration: 101099/375342  consumed_samples: 103526400  total_loss: 3.818  time: 0.3399 s/iter  data_time: 0.2113 s/iter total_throughput: 3012.99 samples/s lr: 8.33e-04  
[09/22 12:56:22] lb.utils.events INFO:  eta: 11:58:31  iteration: 101199/375342  consumed_samples: 103628800  total_loss: 3.795  time: 0.3399 s/iter  data_time: 0.2251 s/iter total_throughput: 3012.96 samples/s lr: 8.33e-04  
[09/22 12:56:56] lb.utils.events INFO:  eta: 11:57:50  iteration: 101299/375342  consumed_samples: 103731200  total_loss: 3.788  time: 0.3399 s/iter  data_time: 0.2229 s/iter total_throughput: 3012.95 samples/s lr: 8.32e-04  
[09/22 12:57:30] lb.utils.events INFO:  eta: 11:56:55  iteration: 101399/375342  consumed_samples: 103833600  total_loss: 3.785  time: 0.3399 s/iter  data_time: 0.2218 s/iter total_throughput: 3012.94 samples/s lr: 8.32e-04  
[09/22 12:58:05] lb.utils.events INFO:  eta: 11:55:53  iteration: 101499/375342  consumed_samples: 103936000  total_loss: 3.78  time: 0.3399 s/iter  data_time: 0.2193 s/iter total_throughput: 3012.89 samples/s lr: 8.32e-04  
[09/22 12:58:39] lb.utils.events INFO:  eta: 11:55:31  iteration: 101599/375342  consumed_samples: 104038400  total_loss: 3.809  time: 0.3399 s/iter  data_time: 0.2086 s/iter total_throughput: 3012.86 samples/s lr: 8.32e-04  
[09/22 12:59:13] lb.utils.events INFO:  eta: 11:55:19  iteration: 101699/375342  consumed_samples: 104140800  total_loss: 3.813  time: 0.3399 s/iter  data_time: 0.2125 s/iter total_throughput: 3012.84 samples/s lr: 8.31e-04  
[09/22 12:59:47] lb.utils.events INFO:  eta: 11:56:13  iteration: 101799/375342  consumed_samples: 104243200  total_loss: 3.798  time: 0.3399 s/iter  data_time: 0.2185 s/iter total_throughput: 3012.83 samples/s lr: 8.31e-04  
[09/22 13:00:22] lb.utils.events INFO:  eta: 11:55:57  iteration: 101899/375342  consumed_samples: 104345600  total_loss: 3.809  time: 0.3399 s/iter  data_time: 0.2237 s/iter total_throughput: 3012.81 samples/s lr: 8.31e-04  
[09/22 13:00:56] lb.utils.events INFO:  eta: 11:55:47  iteration: 101999/375342  consumed_samples: 104448000  total_loss: 3.816  time: 0.3399 s/iter  data_time: 0.2157 s/iter total_throughput: 3012.82 samples/s lr: 8.30e-04  
[09/22 13:01:29] lb.utils.events INFO:  eta: 11:55:32  iteration: 102099/375342  consumed_samples: 104550400  total_loss: 3.814  time: 0.3399 s/iter  data_time: 0.2028 s/iter total_throughput: 3012.83 samples/s lr: 8.30e-04  
[09/22 13:02:03] lb.utils.events INFO:  eta: 11:56:03  iteration: 102199/375342  consumed_samples: 104652800  total_loss: 3.809  time: 0.3399 s/iter  data_time: 0.2117 s/iter total_throughput: 3012.84 samples/s lr: 8.30e-04  
[09/22 13:02:37] lb.utils.events INFO:  eta: 11:57:23  iteration: 102299/375342  consumed_samples: 104755200  total_loss: 3.818  time: 0.3399 s/iter  data_time: 0.2187 s/iter total_throughput: 3012.85 samples/s lr: 8.29e-04  
[09/22 13:03:11] lb.utils.events INFO:  eta: 11:58:35  iteration: 102399/375342  consumed_samples: 104857600  total_loss: 3.837  time: 0.3399 s/iter  data_time: 0.2196 s/iter total_throughput: 3012.83 samples/s lr: 8.29e-04  
[09/22 13:03:45] lb.utils.events INFO:  eta: 11:58:26  iteration: 102499/375342  consumed_samples: 104960000  total_loss: 3.832  time: 0.3399 s/iter  data_time: 0.2010 s/iter total_throughput: 3012.86 samples/s lr: 8.29e-04  
[09/22 13:04:19] lb.utils.events INFO:  eta: 11:58:39  iteration: 102599/375342  consumed_samples: 105062400  total_loss: 3.821  time: 0.3399 s/iter  data_time: 0.2080 s/iter total_throughput: 3012.83 samples/s lr: 8.28e-04  
[09/22 13:04:54] lb.utils.events INFO:  eta: 11:57:53  iteration: 102699/375342  consumed_samples: 105164800  total_loss: 3.809  time: 0.3399 s/iter  data_time: 0.2042 s/iter total_throughput: 3012.81 samples/s lr: 8.28e-04  
[09/22 13:05:28] lb.utils.events INFO:  eta: 11:56:06  iteration: 102799/375342  consumed_samples: 105267200  total_loss: 3.808  time: 0.3399 s/iter  data_time: 0.2131 s/iter total_throughput: 3012.78 samples/s lr: 8.28e-04  
[09/22 13:06:02] lb.utils.events INFO:  eta: 11:56:15  iteration: 102899/375342  consumed_samples: 105369600  total_loss: 3.801  time: 0.3399 s/iter  data_time: 0.2118 s/iter total_throughput: 3012.77 samples/s lr: 8.27e-04  
[09/22 13:06:36] lb.utils.events INFO:  eta: 11:55:47  iteration: 102999/375342  consumed_samples: 105472000  total_loss: 3.802  time: 0.3399 s/iter  data_time: 0.2128 s/iter total_throughput: 3012.78 samples/s lr: 8.27e-04  
[09/22 13:07:10] lb.utils.events INFO:  eta: 11:56:57  iteration: 103099/375342  consumed_samples: 105574400  total_loss: 3.797  time: 0.3399 s/iter  data_time: 0.2136 s/iter total_throughput: 3012.79 samples/s lr: 8.27e-04  
[09/22 13:07:43] lb.utils.events INFO:  eta: 11:56:13  iteration: 103199/375342  consumed_samples: 105676800  total_loss: 3.797  time: 0.3399 s/iter  data_time: 0.2193 s/iter total_throughput: 3012.82 samples/s lr: 8.27e-04  
[09/22 13:08:17] lb.utils.events INFO:  eta: 11:55:57  iteration: 103299/375342  consumed_samples: 105779200  total_loss: 3.819  time: 0.3399 s/iter  data_time: 0.2087 s/iter total_throughput: 3012.85 samples/s lr: 8.26e-04  
[09/22 13:08:52] lb.utils.events INFO:  eta: 11:55:30  iteration: 103399/375342  consumed_samples: 105881600  total_loss: 3.819  time: 0.3399 s/iter  data_time: 0.2146 s/iter total_throughput: 3012.81 samples/s lr: 8.26e-04  
[09/22 13:09:26] lb.utils.events INFO:  eta: 11:56:15  iteration: 103499/375342  consumed_samples: 105984000  total_loss: 3.814  time: 0.3399 s/iter  data_time: 0.2062 s/iter total_throughput: 3012.81 samples/s lr: 8.26e-04  
[09/22 13:10:00] lb.utils.events INFO:  eta: 11:56:13  iteration: 103599/375342  consumed_samples: 106086400  total_loss: 3.82  time: 0.3399 s/iter  data_time: 0.2241 s/iter total_throughput: 3012.77 samples/s lr: 8.25e-04  
[09/22 13:10:34] lb.utils.events INFO:  eta: 11:56:32  iteration: 103699/375342  consumed_samples: 106188800  total_loss: 3.82  time: 0.3399 s/iter  data_time: 0.2119 s/iter total_throughput: 3012.78 samples/s lr: 8.25e-04  
[09/22 13:11:08] lb.utils.events INFO:  eta: 11:58:01  iteration: 103799/375342  consumed_samples: 106291200  total_loss: 3.8  time: 0.3399 s/iter  data_time: 0.2222 s/iter total_throughput: 3012.79 samples/s lr: 8.25e-04  
[09/22 13:11:42] lb.utils.events INFO:  eta: 11:59:21  iteration: 103899/375342  consumed_samples: 106393600  total_loss: 3.787  time: 0.3399 s/iter  data_time: 0.2108 s/iter total_throughput: 3012.79 samples/s lr: 8.24e-04  
[09/22 13:12:16] lb.utils.events INFO:  eta: 11:58:07  iteration: 103999/375342  consumed_samples: 106496000  total_loss: 3.793  time: 0.3399 s/iter  data_time: 0.2190 s/iter total_throughput: 3012.78 samples/s lr: 8.24e-04  
[09/22 13:12:50] lb.utils.events INFO:  eta: 11:57:06  iteration: 104099/375342  consumed_samples: 106598400  total_loss: 3.801  time: 0.3399 s/iter  data_time: 0.2050 s/iter total_throughput: 3012.76 samples/s lr: 8.24e-04  
[09/22 13:13:25] lb.utils.events INFO:  eta: 11:55:48  iteration: 104199/375342  consumed_samples: 106700800  total_loss: 3.798  time: 0.3399 s/iter  data_time: 0.2222 s/iter total_throughput: 3012.70 samples/s lr: 8.23e-04  
[09/22 13:13:59] lb.utils.events INFO:  eta: 11:56:11  iteration: 104299/375342  consumed_samples: 106803200  total_loss: 3.797  time: 0.3399 s/iter  data_time: 0.2099 s/iter total_throughput: 3012.72 samples/s lr: 8.23e-04  
[09/22 13:14:33] lb.utils.events INFO:  eta: 11:56:02  iteration: 104399/375342  consumed_samples: 106905600  total_loss: 3.797  time: 0.3399 s/iter  data_time: 0.2206 s/iter total_throughput: 3012.69 samples/s lr: 8.23e-04  
[09/22 13:15:07] lb.utils.events INFO:  eta: 11:55:23  iteration: 104499/375342  consumed_samples: 107008000  total_loss: 3.801  time: 0.3399 s/iter  data_time: 0.2109 s/iter total_throughput: 3012.68 samples/s lr: 8.22e-04  
[09/22 13:15:41] lb.utils.events INFO:  eta: 11:54:33  iteration: 104599/375342  consumed_samples: 107110400  total_loss: 3.801  time: 0.3399 s/iter  data_time: 0.2184 s/iter total_throughput: 3012.67 samples/s lr: 8.22e-04  
[09/22 13:16:15] lb.utils.events INFO:  eta: 11:53:22  iteration: 104699/375342  consumed_samples: 107212800  total_loss: 3.793  time: 0.3399 s/iter  data_time: 0.2182 s/iter total_throughput: 3012.65 samples/s lr: 8.22e-04  
[09/22 13:16:49] lb.utils.events INFO:  eta: 11:52:39  iteration: 104799/375342  consumed_samples: 107315200  total_loss: 3.789  time: 0.3399 s/iter  data_time: 0.2112 s/iter total_throughput: 3012.66 samples/s lr: 8.21e-04  
[09/22 13:17:23] lb.utils.events INFO:  eta: 11:51:16  iteration: 104899/375342  consumed_samples: 107417600  total_loss: 3.804  time: 0.3399 s/iter  data_time: 0.2200 s/iter total_throughput: 3012.66 samples/s lr: 8.21e-04  
[09/22 13:17:57] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0104999
[09/22 13:17:58] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/22 13:17:58] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/22 13:18:02] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0883 s/iter. Inference: 0.1620 s/iter. Eval: 0.0021 s/iter. Total: 0.2525 s/iter. ETA=0:00:09
[09/22 13:18:08] lb.evaluation.evaluator INFO: Inference done 29696/50000. Dataloading: 0.1122 s/iter. Inference: 0.1807 s/iter. Eval: 0.0020 s/iter. Total: 0.2950 s/iter. ETA=0:00:05
[09/22 13:18:13] lb.evaluation.evaluator INFO: Inference done 50000/50000. Dataloading: 0.1049 s/iter. Inference: 0.1761 s/iter. Eval: 0.0020 s/iter. Total: 0.2831 s/iter. ETA=0:00:00
[09/22 13:18:13] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/22 13:18:13] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.458616 (0.000249 s / iter per device, on 8 devices)
[09/22 13:18:13] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000155 s / iter per device, on 8 devices)
[09/22 13:18:13] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/22 13:18:13] lb.evaluation.utils INFO: copypaste: Acc@1=71.624
[09/22 13:18:13] lb.evaluation.utils INFO: copypaste: Acc@5=90.656
[09/22 13:18:13] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 71.62400, better than last best score 71.44000 @ iteration 99999.
[09/22 13:18:13] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/22 13:18:14] lb.utils.events INFO:  eta: 11:52:11  iteration: 104999/375342  consumed_samples: 107520000  total_loss: 3.824  time: 0.3399 s/iter  data_time: 0.2162 s/iter total_throughput: 3012.65 samples/s lr: 8.21e-04  
[09/22 13:18:45] lb.utils.events INFO:  eta: 11:52:24  iteration: 105099/375342  consumed_samples: 107622400  total_loss: 3.807  time: 0.3399 s/iter  data_time: 0.2318 s/iter total_throughput: 3012.88 samples/s lr: 8.21e-04  
[09/22 13:19:19] lb.utils.events INFO:  eta: 11:56:55  iteration: 105199/375342  consumed_samples: 107724800  total_loss: 3.79  time: 0.3399 s/iter  data_time: 0.2155 s/iter total_throughput: 3012.86 samples/s lr: 8.20e-04  
[09/22 13:19:53] lb.utils.events INFO:  eta: 11:54:48  iteration: 105299/375342  consumed_samples: 107827200  total_loss: 3.789  time: 0.3399 s/iter  data_time: 0.2115 s/iter total_throughput: 3012.88 samples/s lr: 8.20e-04  
[09/22 13:20:28] lb.utils.events INFO:  eta: 11:52:27  iteration: 105399/375342  consumed_samples: 107929600  total_loss: 3.797  time: 0.3399 s/iter  data_time: 0.2183 s/iter total_throughput: 3012.84 samples/s lr: 8.20e-04  
[09/22 13:21:01] lb.utils.events INFO:  eta: 11:51:50  iteration: 105499/375342  consumed_samples: 108032000  total_loss: 3.802  time: 0.3399 s/iter  data_time: 0.2038 s/iter total_throughput: 3012.87 samples/s lr: 8.19e-04  
[09/22 13:21:35] lb.utils.events INFO:  eta: 11:52:22  iteration: 105599/375342  consumed_samples: 108134400  total_loss: 3.799  time: 0.3399 s/iter  data_time: 0.2111 s/iter total_throughput: 3012.89 samples/s lr: 8.19e-04  
[09/22 13:22:09] lb.utils.events INFO:  eta: 11:51:07  iteration: 105699/375342  consumed_samples: 108236800  total_loss: 3.784  time: 0.3399 s/iter  data_time: 0.2122 s/iter total_throughput: 3012.89 samples/s lr: 8.19e-04  
[09/22 13:22:43] lb.utils.events INFO:  eta: 11:50:15  iteration: 105799/375342  consumed_samples: 108339200  total_loss: 3.771  time: 0.3399 s/iter  data_time: 0.2140 s/iter total_throughput: 3012.88 samples/s lr: 8.18e-04  
[09/22 13:23:18] lb.utils.events INFO:  eta: 11:48:15  iteration: 105899/375342  consumed_samples: 108441600  total_loss: 3.788  time: 0.3399 s/iter  data_time: 0.2155 s/iter total_throughput: 3012.83 samples/s lr: 8.18e-04  
[09/22 13:23:52] lb.utils.events INFO:  eta: 11:47:42  iteration: 105999/375342  consumed_samples: 108544000  total_loss: 3.802  time: 0.3399 s/iter  data_time: 0.2068 s/iter total_throughput: 3012.84 samples/s lr: 8.18e-04  
[09/22 13:24:26] lb.utils.events INFO:  eta: 11:46:23  iteration: 106099/375342  consumed_samples: 108646400  total_loss: 3.789  time: 0.3399 s/iter  data_time: 0.2251 s/iter total_throughput: 3012.80 samples/s lr: 8.17e-04  
[09/22 13:25:00] lb.utils.events INFO:  eta: 11:44:27  iteration: 106199/375342  consumed_samples: 108748800  total_loss: 3.79  time: 0.3399 s/iter  data_time: 0.2040 s/iter total_throughput: 3012.80 samples/s lr: 8.17e-04  
[09/22 13:25:34] lb.utils.events INFO:  eta: 11:42:59  iteration: 106299/375342  consumed_samples: 108851200  total_loss: 3.798  time: 0.3399 s/iter  data_time: 0.2178 s/iter total_throughput: 3012.78 samples/s lr: 8.17e-04  
[09/22 13:26:08] lb.utils.events INFO:  eta: 11:44:00  iteration: 106399/375342  consumed_samples: 108953600  total_loss: 3.793  time: 0.3399 s/iter  data_time: 0.2061 s/iter total_throughput: 3012.79 samples/s lr: 8.16e-04  
[09/22 13:26:43] lb.utils.events INFO:  eta: 11:43:57  iteration: 106499/375342  consumed_samples: 109056000  total_loss: 3.787  time: 0.3399 s/iter  data_time: 0.2102 s/iter total_throughput: 3012.75 samples/s lr: 8.16e-04  
[09/22 13:27:17] lb.utils.events INFO:  eta: 11:43:24  iteration: 106599/375342  consumed_samples: 109158400  total_loss: 3.793  time: 0.3399 s/iter  data_time: 0.2140 s/iter total_throughput: 3012.74 samples/s lr: 8.16e-04  
[09/22 13:27:50] lb.utils.events INFO:  eta: 11:44:18  iteration: 106699/375342  consumed_samples: 109260800  total_loss: 3.793  time: 0.3399 s/iter  data_time: 0.2167 s/iter total_throughput: 3012.77 samples/s lr: 8.15e-04  
[09/22 13:28:24] lb.utils.events INFO:  eta: 11:42:53  iteration: 106799/375342  consumed_samples: 109363200  total_loss: 3.81  time: 0.3399 s/iter  data_time: 0.2077 s/iter total_throughput: 3012.80 samples/s lr: 8.15e-04  
[09/22 13:28:58] lb.utils.events INFO:  eta: 11:42:17  iteration: 106899/375342  consumed_samples: 109465600  total_loss: 3.812  time: 0.3399 s/iter  data_time: 0.2113 s/iter total_throughput: 3012.79 samples/s lr: 8.15e-04  
[09/22 13:29:33] lb.utils.events INFO:  eta: 11:40:22  iteration: 106999/375342  consumed_samples: 109568000  total_loss: 3.805  time: 0.3399 s/iter  data_time: 0.2216 s/iter total_throughput: 3012.75 samples/s lr: 8.14e-04  
[09/22 13:30:07] lb.utils.events INFO:  eta: 11:41:13  iteration: 107099/375342  consumed_samples: 109670400  total_loss: 3.803  time: 0.3399 s/iter  data_time: 0.2239 s/iter total_throughput: 3012.76 samples/s lr: 8.14e-04  
[09/22 13:30:40] lb.utils.events INFO:  eta: 11:40:05  iteration: 107199/375342  consumed_samples: 109772800  total_loss: 3.801  time: 0.3399 s/iter  data_time: 0.2200 s/iter total_throughput: 3012.77 samples/s lr: 8.14e-04  
[09/22 13:31:15] lb.utils.events INFO:  eta: 11:39:49  iteration: 107299/375342  consumed_samples: 109875200  total_loss: 3.802  time: 0.3399 s/iter  data_time: 0.2144 s/iter total_throughput: 3012.76 samples/s lr: 8.13e-04  
[09/22 13:31:49] lb.utils.events INFO:  eta: 11:39:21  iteration: 107399/375342  consumed_samples: 109977600  total_loss: 3.803  time: 0.3399 s/iter  data_time: 0.2111 s/iter total_throughput: 3012.76 samples/s lr: 8.13e-04  
[09/22 13:32:23] lb.utils.events INFO:  eta: 11:38:07  iteration: 107499/375342  consumed_samples: 110080000  total_loss: 3.777  time: 0.3399 s/iter  data_time: 0.2145 s/iter total_throughput: 3012.75 samples/s lr: 8.13e-04  
[09/22 13:32:57] lb.utils.events INFO:  eta: 11:36:16  iteration: 107599/375342  consumed_samples: 110182400  total_loss: 3.787  time: 0.3399 s/iter  data_time: 0.2158 s/iter total_throughput: 3012.73 samples/s lr: 8.12e-04  
[09/22 13:33:31] lb.utils.events INFO:  eta: 11:35:01  iteration: 107699/375342  consumed_samples: 110284800  total_loss: 3.799  time: 0.3399 s/iter  data_time: 0.2153 s/iter total_throughput: 3012.72 samples/s lr: 8.12e-04  
[09/22 13:34:05] lb.utils.events INFO:  eta: 11:36:39  iteration: 107799/375342  consumed_samples: 110387200  total_loss: 3.795  time: 0.3399 s/iter  data_time: 0.2128 s/iter total_throughput: 3012.75 samples/s lr: 8.12e-04  
[09/22 13:34:39] lb.utils.events INFO:  eta: 11:38:29  iteration: 107899/375342  consumed_samples: 110489600  total_loss: 3.796  time: 0.3399 s/iter  data_time: 0.2134 s/iter total_throughput: 3012.72 samples/s lr: 8.11e-04  
[09/22 13:35:13] lb.utils.events INFO:  eta: 11:41:03  iteration: 107999/375342  consumed_samples: 110592000  total_loss: 3.785  time: 0.3399 s/iter  data_time: 0.2319 s/iter total_throughput: 3012.74 samples/s lr: 8.11e-04  
[09/22 13:35:47] lb.utils.events INFO:  eta: 11:38:36  iteration: 108099/375342  consumed_samples: 110694400  total_loss: 3.784  time: 0.3399 s/iter  data_time: 0.2092 s/iter total_throughput: 3012.75 samples/s lr: 8.11e-04  
[09/22 13:36:20] lb.utils.events INFO:  eta: 11:38:26  iteration: 108199/375342  consumed_samples: 110796800  total_loss: 3.776  time: 0.3399 s/iter  data_time: 0.2209 s/iter total_throughput: 3012.79 samples/s lr: 8.11e-04  
[09/22 13:36:54] lb.utils.events INFO:  eta: 11:38:06  iteration: 108299/375342  consumed_samples: 110899200  total_loss: 3.779  time: 0.3399 s/iter  data_time: 0.2205 s/iter total_throughput: 3012.76 samples/s lr: 8.10e-04  
[09/22 13:37:29] lb.utils.events INFO:  eta: 11:37:39  iteration: 108399/375342  consumed_samples: 111001600  total_loss: 3.804  time: 0.3399 s/iter  data_time: 0.2205 s/iter total_throughput: 3012.75 samples/s lr: 8.10e-04  
[09/22 13:38:02] lb.utils.events INFO:  eta: 11:39:45  iteration: 108499/375342  consumed_samples: 111104000  total_loss: 3.808  time: 0.3399 s/iter  data_time: 0.2033 s/iter total_throughput: 3012.80 samples/s lr: 8.10e-04  
[09/22 13:38:35] lb.utils.events INFO:  eta: 11:42:50  iteration: 108599/375342  consumed_samples: 111206400  total_loss: 3.824  time: 0.3399 s/iter  data_time: 0.2119 s/iter total_throughput: 3012.85 samples/s lr: 8.09e-04  
[09/22 13:39:09] lb.utils.events INFO:  eta: 11:42:59  iteration: 108699/375342  consumed_samples: 111308800  total_loss: 3.812  time: 0.3399 s/iter  data_time: 0.2076 s/iter total_throughput: 3012.87 samples/s lr: 8.09e-04  
[09/22 13:39:43] lb.utils.events INFO:  eta: 11:41:36  iteration: 108799/375342  consumed_samples: 111411200  total_loss: 3.796  time: 0.3399 s/iter  data_time: 0.2058 s/iter total_throughput: 3012.90 samples/s lr: 8.09e-04  
[09/22 13:40:17] lb.utils.events INFO:  eta: 11:39:37  iteration: 108899/375342  consumed_samples: 111513600  total_loss: 3.792  time: 0.3399 s/iter  data_time: 0.2146 s/iter total_throughput: 3012.91 samples/s lr: 8.08e-04  
[09/22 13:40:51] lb.utils.events INFO:  eta: 11:37:37  iteration: 108999/375342  consumed_samples: 111616000  total_loss: 3.797  time: 0.3399 s/iter  data_time: 0.2068 s/iter total_throughput: 3012.90 samples/s lr: 8.08e-04  
[09/22 13:41:25] lb.utils.events INFO:  eta: 11:39:31  iteration: 109099/375342  consumed_samples: 111718400  total_loss: 3.792  time: 0.3399 s/iter  data_time: 0.2127 s/iter total_throughput: 3012.92 samples/s lr: 8.08e-04  
[09/22 13:41:59] lb.utils.events INFO:  eta: 11:40:01  iteration: 109199/375342  consumed_samples: 111820800  total_loss: 3.781  time: 0.3399 s/iter  data_time: 0.2219 s/iter total_throughput: 3012.92 samples/s lr: 8.07e-04  
[09/22 13:42:33] lb.utils.events INFO:  eta: 11:39:16  iteration: 109299/375342  consumed_samples: 111923200  total_loss: 3.79  time: 0.3399 s/iter  data_time: 0.2077 s/iter total_throughput: 3012.92 samples/s lr: 8.07e-04  
[09/22 13:43:07] lb.utils.events INFO:  eta: 11:39:00  iteration: 109399/375342  consumed_samples: 112025600  total_loss: 3.784  time: 0.3399 s/iter  data_time: 0.2024 s/iter total_throughput: 3012.91 samples/s lr: 8.07e-04  
[09/22 13:43:40] lb.utils.events INFO:  eta: 11:38:08  iteration: 109499/375342  consumed_samples: 112128000  total_loss: 3.797  time: 0.3399 s/iter  data_time: 0.2189 s/iter total_throughput: 3012.96 samples/s lr: 8.06e-04  
[09/22 13:44:13] lb.utils.events INFO:  eta: 11:37:46  iteration: 109599/375342  consumed_samples: 112230400  total_loss: 3.796  time: 0.3399 s/iter  data_time: 0.1948 s/iter total_throughput: 3013.01 samples/s lr: 8.06e-04  
[09/22 13:44:47] lb.utils.events INFO:  eta: 11:36:56  iteration: 109699/375342  consumed_samples: 112332800  total_loss: 3.792  time: 0.3399 s/iter  data_time: 0.2186 s/iter total_throughput: 3013.02 samples/s lr: 8.06e-04  
[09/22 13:45:21] lb.utils.events INFO:  eta: 11:36:33  iteration: 109799/375342  consumed_samples: 112435200  total_loss: 3.795  time: 0.3399 s/iter  data_time: 0.2159 s/iter total_throughput: 3013.03 samples/s lr: 8.05e-04  
[09/22 13:45:55] lb.utils.events INFO:  eta: 11:36:42  iteration: 109899/375342  consumed_samples: 112537600  total_loss: 3.776  time: 0.3399 s/iter  data_time: 0.2148 s/iter total_throughput: 3013.04 samples/s lr: 8.05e-04  
[09/22 13:46:29] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0109999
[09/22 13:46:29] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/22 13:46:29] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/22 13:46:33] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0943 s/iter. Inference: 0.1628 s/iter. Eval: 0.0019 s/iter. Total: 0.2589 s/iter. ETA=0:00:09
[09/22 13:46:38] lb.evaluation.evaluator INFO: Inference done 28672/50000. Dataloading: 0.0836 s/iter. Inference: 0.2004 s/iter. Eval: 0.0019 s/iter. Total: 0.2860 s/iter. ETA=0:00:05
[09/22 13:46:44] lb.evaluation.evaluator INFO: Inference done 46080/50000. Dataloading: 0.0653 s/iter. Inference: 0.2304 s/iter. Eval: 0.0019 s/iter. Total: 0.2977 s/iter. ETA=0:00:00
[09/22 13:46:44] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/22 13:46:44] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.791427 (0.000256 s / iter per device, on 8 devices)
[09/22 13:46:44] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:10 (0.000202 s / iter per device, on 8 devices)
[09/22 13:46:44] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/22 13:46:44] lb.evaluation.utils INFO: copypaste: Acc@1=71.468
[09/22 13:46:44] lb.evaluation.utils INFO: copypaste: Acc@5=90.598
[09/22 13:46:44] lb.engine.hooks INFO: Not saving as latest eval score for Acc@1 is 71.46800, not better than best score 71.62400 @ iteration 104999.
[09/22 13:46:44] lb.utils.events INFO:  eta: 11:38:14  iteration: 109999/375342  consumed_samples: 112640000  total_loss: 3.779  time: 0.3399 s/iter  data_time: 0.2026 s/iter total_throughput: 3013.09 samples/s lr: 8.05e-04  
[09/22 13:47:17] lb.utils.events INFO:  eta: 11:39:03  iteration: 110099/375342  consumed_samples: 112742400  total_loss: 3.803  time: 0.3398 s/iter  data_time: 0.2043 s/iter total_throughput: 3013.22 samples/s lr: 8.04e-04  
[09/22 13:47:50] lb.utils.events INFO:  eta: 11:38:42  iteration: 110199/375342  consumed_samples: 112844800  total_loss: 3.812  time: 0.3398 s/iter  data_time: 0.1987 s/iter total_throughput: 3013.24 samples/s lr: 8.04e-04  
[09/22 13:48:24] lb.utils.events INFO:  eta: 11:39:39  iteration: 110299/375342  consumed_samples: 112947200  total_loss: 3.812  time: 0.3398 s/iter  data_time: 0.2187 s/iter total_throughput: 3013.26 samples/s lr: 8.04e-04  
[09/22 13:48:58] lb.utils.events INFO:  eta: 11:39:07  iteration: 110399/375342  consumed_samples: 113049600  total_loss: 3.797  time: 0.3398 s/iter  data_time: 0.1952 s/iter total_throughput: 3013.30 samples/s lr: 8.03e-04  
[09/22 13:49:32] lb.utils.events INFO:  eta: 11:37:31  iteration: 110499/375342  consumed_samples: 113152000  total_loss: 3.776  time: 0.3398 s/iter  data_time: 0.2185 s/iter total_throughput: 3013.27 samples/s lr: 8.03e-04  
[09/22 13:50:06] lb.utils.events INFO:  eta: 11:35:46  iteration: 110599/375342  consumed_samples: 113254400  total_loss: 3.773  time: 0.3398 s/iter  data_time: 0.2254 s/iter total_throughput: 3013.30 samples/s lr: 8.03e-04  
[09/22 13:50:39] lb.utils.events INFO:  eta: 11:35:19  iteration: 110699/375342  consumed_samples: 113356800  total_loss: 3.794  time: 0.3398 s/iter  data_time: 0.2161 s/iter total_throughput: 3013.33 samples/s lr: 8.02e-04  
[09/22 13:51:13] lb.utils.events INFO:  eta: 11:34:41  iteration: 110799/375342  consumed_samples: 113459200  total_loss: 3.794  time: 0.3398 s/iter  data_time: 0.2042 s/iter total_throughput: 3013.36 samples/s lr: 8.02e-04  
[09/22 13:51:46] lb.utils.events INFO:  eta: 11:34:25  iteration: 110899/375342  consumed_samples: 113561600  total_loss: 3.796  time: 0.3398 s/iter  data_time: 0.2051 s/iter total_throughput: 3013.41 samples/s lr: 8.02e-04  
[09/22 13:52:20] lb.utils.events INFO:  eta: 11:32:08  iteration: 110999/375342  consumed_samples: 113664000  total_loss: 3.787  time: 0.3398 s/iter  data_time: 0.2124 s/iter total_throughput: 3013.47 samples/s lr: 8.01e-04  
[09/22 13:52:53] lb.utils.events INFO:  eta: 11:28:53  iteration: 111099/375342  consumed_samples: 113766400  total_loss: 3.771  time: 0.3398 s/iter  data_time: 0.2073 s/iter total_throughput: 3013.50 samples/s lr: 8.01e-04  
[09/22 13:53:27] lb.utils.events INFO:  eta: 11:28:37  iteration: 111199/375342  consumed_samples: 113868800  total_loss: 3.795  time: 0.3398 s/iter  data_time: 0.2135 s/iter total_throughput: 3013.53 samples/s lr: 8.01e-04  
[09/22 13:54:00] lb.utils.events INFO:  eta: 11:27:55  iteration: 111299/375342  consumed_samples: 113971200  total_loss: 3.801  time: 0.3398 s/iter  data_time: 0.1992 s/iter total_throughput: 3013.57 samples/s lr: 8.00e-04  
[09/22 13:54:33] lb.utils.events INFO:  eta: 11:28:12  iteration: 111399/375342  consumed_samples: 114073600  total_loss: 3.774  time: 0.3398 s/iter  data_time: 0.1989 s/iter total_throughput: 3013.65 samples/s lr: 8.00e-04  
[09/22 13:55:06] lb.utils.events INFO:  eta: 11:29:49  iteration: 111499/375342  consumed_samples: 114176000  total_loss: 3.771  time: 0.3398 s/iter  data_time: 0.2019 s/iter total_throughput: 3013.72 samples/s lr: 8.00e-04  
[09/22 13:55:40] lb.utils.events INFO:  eta: 11:30:11  iteration: 111599/375342  consumed_samples: 114278400  total_loss: 3.78  time: 0.3398 s/iter  data_time: 0.2082 s/iter total_throughput: 3013.75 samples/s lr: 7.99e-04  
[09/22 13:56:14] lb.utils.events INFO:  eta: 11:29:18  iteration: 111699/375342  consumed_samples: 114380800  total_loss: 3.773  time: 0.3398 s/iter  data_time: 0.2129 s/iter total_throughput: 3013.76 samples/s lr: 7.99e-04  
[09/22 13:56:47] lb.utils.events INFO:  eta: 11:29:13  iteration: 111799/375342  consumed_samples: 114483200  total_loss: 3.769  time: 0.3398 s/iter  data_time: 0.2105 s/iter total_throughput: 3013.80 samples/s lr: 7.99e-04  
[09/22 13:57:21] lb.utils.events INFO:  eta: 11:28:57  iteration: 111899/375342  consumed_samples: 114585600  total_loss: 3.76  time: 0.3398 s/iter  data_time: 0.2022 s/iter total_throughput: 3013.84 samples/s lr: 7.98e-04  
[09/22 13:57:54] lb.utils.events INFO:  eta: 11:28:49  iteration: 111999/375342  consumed_samples: 114688000  total_loss: 3.778  time: 0.3398 s/iter  data_time: 0.2150 s/iter total_throughput: 3013.88 samples/s lr: 7.98e-04  
[09/22 13:58:27] lb.utils.events INFO:  eta: 11:28:36  iteration: 112099/375342  consumed_samples: 114790400  total_loss: 3.778  time: 0.3398 s/iter  data_time: 0.2035 s/iter total_throughput: 3013.95 samples/s lr: 7.98e-04  
[09/22 13:59:02] lb.utils.events INFO:  eta: 11:27:19  iteration: 112199/375342  consumed_samples: 114892800  total_loss: 3.764  time: 0.3398 s/iter  data_time: 0.2174 s/iter total_throughput: 3013.91 samples/s lr: 7.97e-04  
[09/22 13:59:35] lb.utils.events INFO:  eta: 11:27:44  iteration: 112299/375342  consumed_samples: 114995200  total_loss: 3.785  time: 0.3398 s/iter  data_time: 0.2042 s/iter total_throughput: 3013.97 samples/s lr: 7.97e-04  
[09/22 14:00:09] lb.utils.events INFO:  eta: 11:27:25  iteration: 112399/375342  consumed_samples: 115097600  total_loss: 3.782  time: 0.3398 s/iter  data_time: 0.2083 s/iter total_throughput: 3013.95 samples/s lr: 7.97e-04  
[09/22 14:00:44] lb.utils.events INFO:  eta: 11:26:24  iteration: 112499/375342  consumed_samples: 115200000  total_loss: 3.777  time: 0.3398 s/iter  data_time: 0.2117 s/iter total_throughput: 3013.92 samples/s lr: 7.96e-04  
[09/22 14:01:19] lb.utils.events INFO:  eta: 11:25:22  iteration: 112599/375342  consumed_samples: 115302400  total_loss: 3.779  time: 0.3398 s/iter  data_time: 0.2141 s/iter total_throughput: 3013.84 samples/s lr: 7.96e-04  
[09/22 14:01:53] lb.utils.events INFO:  eta: 11:25:09  iteration: 112699/375342  consumed_samples: 115404800  total_loss: 3.78  time: 0.3398 s/iter  data_time: 0.2179 s/iter total_throughput: 3013.79 samples/s lr: 7.96e-04  
[09/22 14:02:28] lb.utils.events INFO:  eta: 11:24:51  iteration: 112799/375342  consumed_samples: 115507200  total_loss: 3.773  time: 0.3398 s/iter  data_time: 0.2108 s/iter total_throughput: 3013.74 samples/s lr: 7.95e-04  
[09/22 14:03:02] lb.utils.events INFO:  eta: 11:24:24  iteration: 112899/375342  consumed_samples: 115609600  total_loss: 3.773  time: 0.3398 s/iter  data_time: 0.2097 s/iter total_throughput: 3013.70 samples/s lr: 7.95e-04  
[09/22 14:03:37] lb.utils.events INFO:  eta: 11:24:15  iteration: 112999/375342  consumed_samples: 115712000  total_loss: 3.771  time: 0.3398 s/iter  data_time: 0.2108 s/iter total_throughput: 3013.65 samples/s lr: 7.95e-04  
[09/22 14:04:11] lb.utils.events INFO:  eta: 11:23:47  iteration: 113099/375342  consumed_samples: 115814400  total_loss: 3.777  time: 0.3398 s/iter  data_time: 0.2127 s/iter total_throughput: 3013.63 samples/s lr: 7.94e-04  
[09/22 14:04:45] lb.utils.events INFO:  eta: 11:24:53  iteration: 113199/375342  consumed_samples: 115916800  total_loss: 3.777  time: 0.3398 s/iter  data_time: 0.2260 s/iter total_throughput: 3013.63 samples/s lr: 7.94e-04  
[09/22 14:05:20] lb.utils.events INFO:  eta: 11:21:16  iteration: 113299/375342  consumed_samples: 116019200  total_loss: 3.77  time: 0.3398 s/iter  data_time: 0.2363 s/iter total_throughput: 3013.55 samples/s lr: 7.94e-04  
[09/22 14:05:55] lb.utils.events INFO:  eta: 11:18:07  iteration: 113399/375342  consumed_samples: 116121600  total_loss: 3.78  time: 0.3398 s/iter  data_time: 0.2210 s/iter total_throughput: 3013.47 samples/s lr: 7.93e-04  
[09/22 14:06:30] lb.utils.events INFO:  eta: 11:19:09  iteration: 113499/375342  consumed_samples: 116224000  total_loss: 3.788  time: 0.3398 s/iter  data_time: 0.2239 s/iter total_throughput: 3013.44 samples/s lr: 7.93e-04  
[09/22 14:07:04] lb.utils.events INFO:  eta: 11:21:41  iteration: 113599/375342  consumed_samples: 116326400  total_loss: 3.773  time: 0.3398 s/iter  data_time: 0.2148 s/iter total_throughput: 3013.42 samples/s lr: 7.93e-04  
[09/22 14:07:38] lb.utils.events INFO:  eta: 11:21:26  iteration: 113699/375342  consumed_samples: 116428800  total_loss: 3.781  time: 0.3398 s/iter  data_time: 0.2185 s/iter total_throughput: 3013.40 samples/s lr: 7.92e-04  
[09/22 14:08:13] lb.utils.events INFO:  eta: 11:19:43  iteration: 113799/375342  consumed_samples: 116531200  total_loss: 3.789  time: 0.3398 s/iter  data_time: 0.2106 s/iter total_throughput: 3013.36 samples/s lr: 7.92e-04  
[09/22 14:08:46] lb.utils.events INFO:  eta: 11:21:34  iteration: 113899/375342  consumed_samples: 116633600  total_loss: 3.781  time: 0.3398 s/iter  data_time: 0.2110 s/iter total_throughput: 3013.40 samples/s lr: 7.92e-04  
[09/22 14:09:20] lb.utils.events INFO:  eta: 11:22:01  iteration: 113999/375342  consumed_samples: 116736000  total_loss: 3.77  time: 0.3398 s/iter  data_time: 0.2156 s/iter total_throughput: 3013.41 samples/s lr: 7.91e-04  
[09/22 14:09:54] lb.utils.events INFO:  eta: 11:23:12  iteration: 114099/375342  consumed_samples: 116838400  total_loss: 3.747  time: 0.3398 s/iter  data_time: 0.2054 s/iter total_throughput: 3013.45 samples/s lr: 7.91e-04  
[09/22 14:10:27] lb.utils.events INFO:  eta: 11:23:08  iteration: 114199/375342  consumed_samples: 116940800  total_loss: 3.758  time: 0.3398 s/iter  data_time: 0.2153 s/iter total_throughput: 3013.46 samples/s lr: 7.91e-04  
[09/22 14:11:02] lb.utils.events INFO:  eta: 11:23:24  iteration: 114299/375342  consumed_samples: 117043200  total_loss: 3.774  time: 0.3398 s/iter  data_time: 0.2160 s/iter total_throughput: 3013.43 samples/s lr: 7.90e-04  
[09/22 14:11:36] lb.utils.events INFO:  eta: 11:26:12  iteration: 114399/375342  consumed_samples: 117145600  total_loss: 3.766  time: 0.3398 s/iter  data_time: 0.2122 s/iter total_throughput: 3013.44 samples/s lr: 7.90e-04  
[09/22 14:12:10] lb.utils.events INFO:  eta: 11:25:32  iteration: 114499/375342  consumed_samples: 117248000  total_loss: 3.746  time: 0.3398 s/iter  data_time: 0.2283 s/iter total_throughput: 3013.44 samples/s lr: 7.90e-04  
[09/22 14:12:44] lb.utils.events INFO:  eta: 11:23:01  iteration: 114599/375342  consumed_samples: 117350400  total_loss: 3.769  time: 0.3398 s/iter  data_time: 0.2088 s/iter total_throughput: 3013.43 samples/s lr: 7.89e-04  
[09/22 14:13:18] lb.utils.events INFO:  eta: 11:25:37  iteration: 114699/375342  consumed_samples: 117452800  total_loss: 3.779  time: 0.3398 s/iter  data_time: 0.2029 s/iter total_throughput: 3013.44 samples/s lr: 7.89e-04  
[09/22 14:13:52] lb.utils.events INFO:  eta: 11:25:31  iteration: 114799/375342  consumed_samples: 117555200  total_loss: 3.776  time: 0.3398 s/iter  data_time: 0.2237 s/iter total_throughput: 3013.42 samples/s lr: 7.89e-04  
[09/22 14:14:26] lb.utils.events INFO:  eta: 11:23:57  iteration: 114899/375342  consumed_samples: 117657600  total_loss: 3.779  time: 0.3398 s/iter  data_time: 0.2209 s/iter total_throughput: 3013.44 samples/s lr: 7.88e-04  
[09/22 14:15:00] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0114999
[09/22 14:15:01] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/22 14:15:01] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/22 14:15:05] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.1009 s/iter. Inference: 0.1587 s/iter. Eval: 0.0021 s/iter. Total: 0.2617 s/iter. ETA=0:00:09
[09/22 14:15:10] lb.evaluation.evaluator INFO: Inference done 29696/50000. Dataloading: 0.1187 s/iter. Inference: 0.1740 s/iter. Eval: 0.0020 s/iter. Total: 0.2948 s/iter. ETA=0:00:05
[09/22 14:15:15] lb.evaluation.evaluator INFO: Inference done 48128/50000. Dataloading: 0.1201 s/iter. Inference: 0.1677 s/iter. Eval: 0.0021 s/iter. Total: 0.2899 s/iter. ETA=0:00:00
[09/22 14:15:16] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/22 14:15:16] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.530676 (0.000251 s / iter per device, on 8 devices)
[09/22 14:15:16] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000148 s / iter per device, on 8 devices)
[09/22 14:15:16] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/22 14:15:16] lb.evaluation.utils INFO: copypaste: Acc@1=71.92399999999999
[09/22 14:15:16] lb.evaluation.utils INFO: copypaste: Acc@5=90.84400000000001
[09/22 14:15:16] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 71.92400, better than last best score 71.62400 @ iteration 104999.
[09/22 14:15:16] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/22 14:15:16] lb.utils.events INFO:  eta: 11:22:14  iteration: 114999/375342  consumed_samples: 117760000  total_loss: 3.765  time: 0.3398 s/iter  data_time: 0.2138 s/iter total_throughput: 3013.41 samples/s lr: 7.88e-04  
[09/22 14:15:48] lb.utils.events INFO:  eta: 11:26:23  iteration: 115099/375342  consumed_samples: 117862400  total_loss: 3.766  time: 0.3398 s/iter  data_time: 0.2448 s/iter total_throughput: 3013.58 samples/s lr: 7.88e-04  
[09/22 14:16:22] lb.utils.events INFO:  eta: 11:25:53  iteration: 115199/375342  consumed_samples: 117964800  total_loss: 3.767  time: 0.3398 s/iter  data_time: 0.2161 s/iter total_throughput: 3013.55 samples/s lr: 7.87e-04  
[09/22 14:16:57] lb.utils.events INFO:  eta: 11:25:51  iteration: 115299/375342  consumed_samples: 118067200  total_loss: 3.773  time: 0.3398 s/iter  data_time: 0.2173 s/iter total_throughput: 3013.52 samples/s lr: 7.87e-04  
[09/22 14:17:31] lb.utils.events INFO:  eta: 11:25:49  iteration: 115399/375342  consumed_samples: 118169600  total_loss: 3.778  time: 0.3398 s/iter  data_time: 0.2059 s/iter total_throughput: 3013.54 samples/s lr: 7.87e-04  
[09/22 14:18:05] lb.utils.events INFO:  eta: 11:26:03  iteration: 115499/375342  consumed_samples: 118272000  total_loss: 3.783  time: 0.3398 s/iter  data_time: 0.2108 s/iter total_throughput: 3013.55 samples/s lr: 7.86e-04  
[09/22 14:18:39] lb.utils.events INFO:  eta: 11:25:31  iteration: 115599/375342  consumed_samples: 118374400  total_loss: 3.781  time: 0.3398 s/iter  data_time: 0.2158 s/iter total_throughput: 3013.51 samples/s lr: 7.86e-04  
[09/22 14:19:13] lb.utils.events INFO:  eta: 11:24:51  iteration: 115699/375342  consumed_samples: 118476800  total_loss: 3.778  time: 0.3398 s/iter  data_time: 0.2111 s/iter total_throughput: 3013.53 samples/s lr: 7.85e-04  
[09/22 14:19:47] lb.utils.events INFO:  eta: 11:24:35  iteration: 115799/375342  consumed_samples: 118579200  total_loss: 3.775  time: 0.3398 s/iter  data_time: 0.2135 s/iter total_throughput: 3013.51 samples/s lr: 7.85e-04  
[09/22 14:20:22] lb.utils.events INFO:  eta: 11:24:52  iteration: 115899/375342  consumed_samples: 118681600  total_loss: 3.759  time: 0.3398 s/iter  data_time: 0.2209 s/iter total_throughput: 3013.46 samples/s lr: 7.85e-04  
[09/22 14:20:56] lb.utils.events INFO:  eta: 11:26:06  iteration: 115999/375342  consumed_samples: 118784000  total_loss: 3.753  time: 0.3398 s/iter  data_time: 0.2134 s/iter total_throughput: 3013.45 samples/s lr: 7.84e-04  
[09/22 14:21:30] lb.utils.events INFO:  eta: 11:19:57  iteration: 116099/375342  consumed_samples: 118886400  total_loss: 3.753  time: 0.3398 s/iter  data_time: 0.2068 s/iter total_throughput: 3013.44 samples/s lr: 7.84e-04  
[09/22 14:22:04] lb.utils.events INFO:  eta: 11:19:39  iteration: 116199/375342  consumed_samples: 118988800  total_loss: 3.754  time: 0.3398 s/iter  data_time: 0.2026 s/iter total_throughput: 3013.46 samples/s lr: 7.84e-04  
[09/22 14:22:37] lb.utils.events INFO:  eta: 11:19:43  iteration: 116299/375342  consumed_samples: 119091200  total_loss: 3.783  time: 0.3398 s/iter  data_time: 0.2184 s/iter total_throughput: 3013.48 samples/s lr: 7.83e-04  
[09/22 14:23:12] lb.utils.events INFO:  eta: 11:19:21  iteration: 116399/375342  consumed_samples: 119193600  total_loss: 3.77  time: 0.3398 s/iter  data_time: 0.2147 s/iter total_throughput: 3013.44 samples/s lr: 7.83e-04  
[09/22 14:23:47] lb.utils.events INFO:  eta: 11:18:18  iteration: 116499/375342  consumed_samples: 119296000  total_loss: 3.752  time: 0.3398 s/iter  data_time: 0.2334 s/iter total_throughput: 3013.36 samples/s lr: 7.83e-04  
[09/22 14:24:21] lb.utils.events INFO:  eta: 11:17:58  iteration: 116599/375342  consumed_samples: 119398400  total_loss: 3.745  time: 0.3398 s/iter  data_time: 0.2100 s/iter total_throughput: 3013.36 samples/s lr: 7.82e-04  
[09/22 14:24:55] lb.utils.events INFO:  eta: 11:17:05  iteration: 116699/375342  consumed_samples: 119500800  total_loss: 3.731  time: 0.3398 s/iter  data_time: 0.2048 s/iter total_throughput: 3013.36 samples/s lr: 7.82e-04  
[09/22 14:25:29] lb.utils.events INFO:  eta: 11:17:08  iteration: 116799/375342  consumed_samples: 119603200  total_loss: 3.735  time: 0.3398 s/iter  data_time: 0.2123 s/iter total_throughput: 3013.36 samples/s lr: 7.82e-04  
[09/22 14:26:03] lb.utils.events INFO:  eta: 11:18:02  iteration: 116899/375342  consumed_samples: 119705600  total_loss: 3.777  time: 0.3398 s/iter  data_time: 0.2047 s/iter total_throughput: 3013.37 samples/s lr: 7.81e-04  
[09/22 14:26:37] lb.utils.events INFO:  eta: 11:16:58  iteration: 116999/375342  consumed_samples: 119808000  total_loss: 3.775  time: 0.3398 s/iter  data_time: 0.2037 s/iter total_throughput: 3013.38 samples/s lr: 7.81e-04  
[09/22 14:27:10] lb.utils.events INFO:  eta: 11:17:02  iteration: 117099/375342  consumed_samples: 119910400  total_loss: 3.765  time: 0.3398 s/iter  data_time: 0.2088 s/iter total_throughput: 3013.41 samples/s lr: 7.81e-04  
[09/22 14:27:44] lb.utils.events INFO:  eta: 11:16:16  iteration: 117199/375342  consumed_samples: 120012800  total_loss: 3.77  time: 0.3398 s/iter  data_time: 0.2097 s/iter total_throughput: 3013.42 samples/s lr: 7.80e-04  
[09/22 14:28:17] lb.utils.events INFO:  eta: 11:17:38  iteration: 117299/375342  consumed_samples: 120115200  total_loss: 3.764  time: 0.3398 s/iter  data_time: 0.2017 s/iter total_throughput: 3013.47 samples/s lr: 7.80e-04  
[09/22 14:28:52] lb.utils.events INFO:  eta: 11:16:16  iteration: 117399/375342  consumed_samples: 120217600  total_loss: 3.754  time: 0.3398 s/iter  data_time: 0.2219 s/iter total_throughput: 3013.45 samples/s lr: 7.80e-04  
[09/22 14:29:26] lb.utils.events INFO:  eta: 11:17:21  iteration: 117499/375342  consumed_samples: 120320000  total_loss: 3.762  time: 0.3398 s/iter  data_time: 0.2022 s/iter total_throughput: 3013.45 samples/s lr: 7.79e-04  
[09/22 14:30:00] lb.utils.events INFO:  eta: 11:17:16  iteration: 117599/375342  consumed_samples: 120422400  total_loss: 3.762  time: 0.3398 s/iter  data_time: 0.2231 s/iter total_throughput: 3013.44 samples/s lr: 7.79e-04  
[09/22 14:30:34] lb.utils.events INFO:  eta: 11:16:51  iteration: 117699/375342  consumed_samples: 120524800  total_loss: 3.747  time: 0.3398 s/iter  data_time: 0.2089 s/iter total_throughput: 3013.45 samples/s lr: 7.79e-04  
[09/22 14:31:08] lb.utils.events INFO:  eta: 11:16:43  iteration: 117799/375342  consumed_samples: 120627200  total_loss: 3.75  time: 0.3398 s/iter  data_time: 0.2226 s/iter total_throughput: 3013.41 samples/s lr: 7.78e-04  
[09/22 14:31:42] lb.utils.events INFO:  eta: 11:14:22  iteration: 117899/375342  consumed_samples: 120729600  total_loss: 3.759  time: 0.3398 s/iter  data_time: 0.2167 s/iter total_throughput: 3013.42 samples/s lr: 7.78e-04  
[09/22 14:32:16] lb.utils.events INFO:  eta: 11:13:24  iteration: 117999/375342  consumed_samples: 120832000  total_loss: 3.751  time: 0.3398 s/iter  data_time: 0.2190 s/iter total_throughput: 3013.41 samples/s lr: 7.78e-04  
[09/22 14:32:50] lb.utils.events INFO:  eta: 11:12:37  iteration: 118099/375342  consumed_samples: 120934400  total_loss: 3.743  time: 0.3398 s/iter  data_time: 0.2005 s/iter total_throughput: 3013.42 samples/s lr: 7.77e-04  
[09/22 14:33:25] lb.utils.events INFO:  eta: 11:12:21  iteration: 118199/375342  consumed_samples: 121036800  total_loss: 3.756  time: 0.3398 s/iter  data_time: 0.2348 s/iter total_throughput: 3013.37 samples/s lr: 7.77e-04  
[09/22 14:33:58] lb.utils.events INFO:  eta: 11:09:03  iteration: 118299/375342  consumed_samples: 121139200  total_loss: 3.758  time: 0.3398 s/iter  data_time: 0.2118 s/iter total_throughput: 3013.38 samples/s lr: 7.77e-04  
[09/22 14:34:33] lb.utils.events INFO:  eta: 11:09:01  iteration: 118399/375342  consumed_samples: 121241600  total_loss: 3.764  time: 0.3398 s/iter  data_time: 0.2116 s/iter total_throughput: 3013.36 samples/s lr: 7.76e-04  
[09/22 14:35:07] lb.utils.events INFO:  eta: 11:10:02  iteration: 118499/375342  consumed_samples: 121344000  total_loss: 3.775  time: 0.3398 s/iter  data_time: 0.2216 s/iter total_throughput: 3013.37 samples/s lr: 7.76e-04  
[09/22 14:35:41] lb.utils.events INFO:  eta: 11:10:14  iteration: 118599/375342  consumed_samples: 121446400  total_loss: 3.771  time: 0.3398 s/iter  data_time: 0.2052 s/iter total_throughput: 3013.36 samples/s lr: 7.75e-04  
[09/22 14:36:14] lb.utils.events INFO:  eta: 11:10:35  iteration: 118699/375342  consumed_samples: 121548800  total_loss: 3.751  time: 0.3398 s/iter  data_time: 0.2141 s/iter total_throughput: 3013.39 samples/s lr: 7.75e-04  
[09/22 14:36:48] lb.utils.events INFO:  eta: 11:10:16  iteration: 118799/375342  consumed_samples: 121651200  total_loss: 3.769  time: 0.3398 s/iter  data_time: 0.2150 s/iter total_throughput: 3013.42 samples/s lr: 7.75e-04  
[09/22 14:37:22] lb.utils.events INFO:  eta: 11:10:30  iteration: 118899/375342  consumed_samples: 121753600  total_loss: 3.76  time: 0.3398 s/iter  data_time: 0.2068 s/iter total_throughput: 3013.40 samples/s lr: 7.74e-04  
[09/22 14:37:56] lb.utils.events INFO:  eta: 11:11:24  iteration: 118999/375342  consumed_samples: 121856000  total_loss: 3.74  time: 0.3398 s/iter  data_time: 0.1968 s/iter total_throughput: 3013.44 samples/s lr: 7.74e-04  
[09/22 14:38:30] lb.utils.events INFO:  eta: 11:11:12  iteration: 119099/375342  consumed_samples: 121958400  total_loss: 3.771  time: 0.3398 s/iter  data_time: 0.2219 s/iter total_throughput: 3013.40 samples/s lr: 7.74e-04  
[09/22 14:39:04] lb.utils.events INFO:  eta: 11:10:40  iteration: 119199/375342  consumed_samples: 122060800  total_loss: 3.77  time: 0.3398 s/iter  data_time: 0.2290 s/iter total_throughput: 3013.38 samples/s lr: 7.73e-04  
[09/22 14:39:38] lb.utils.events INFO:  eta: 11:10:22  iteration: 119299/375342  consumed_samples: 122163200  total_loss: 3.744  time: 0.3398 s/iter  data_time: 0.2189 s/iter total_throughput: 3013.40 samples/s lr: 7.73e-04  
[09/22 14:40:12] lb.utils.events INFO:  eta: 11:10:06  iteration: 119399/375342  consumed_samples: 122265600  total_loss: 3.735  time: 0.3398 s/iter  data_time: 0.2139 s/iter total_throughput: 3013.41 samples/s lr: 7.73e-04  
[09/22 14:40:46] lb.utils.events INFO:  eta: 11:08:58  iteration: 119499/375342  consumed_samples: 122368000  total_loss: 3.749  time: 0.3398 s/iter  data_time: 0.2169 s/iter total_throughput: 3013.41 samples/s lr: 7.72e-04  
[09/22 14:41:20] lb.utils.events INFO:  eta: 11:08:28  iteration: 119599/375342  consumed_samples: 122470400  total_loss: 3.762  time: 0.3398 s/iter  data_time: 0.2177 s/iter total_throughput: 3013.43 samples/s lr: 7.72e-04  
[09/22 14:41:54] lb.utils.events INFO:  eta: 11:07:36  iteration: 119699/375342  consumed_samples: 122572800  total_loss: 3.774  time: 0.3398 s/iter  data_time: 0.2128 s/iter total_throughput: 3013.41 samples/s lr: 7.72e-04  
[09/22 14:42:28] lb.utils.events INFO:  eta: 11:06:54  iteration: 119799/375342  consumed_samples: 122675200  total_loss: 3.775  time: 0.3398 s/iter  data_time: 0.2145 s/iter total_throughput: 3013.41 samples/s lr: 7.71e-04  
[09/22 14:43:02] lb.utils.events INFO:  eta: 11:06:01  iteration: 119899/375342  consumed_samples: 122777600  total_loss: 3.764  time: 0.3398 s/iter  data_time: 0.2295 s/iter total_throughput: 3013.39 samples/s lr: 7.71e-04  
[09/22 14:43:36] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0119999
[09/22 14:43:37] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/22 14:43:37] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/22 14:43:41] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0966 s/iter. Inference: 0.1621 s/iter. Eval: 0.0020 s/iter. Total: 0.2607 s/iter. ETA=0:00:09
[09/22 14:43:46] lb.evaluation.evaluator INFO: Inference done 28672/50000. Dataloading: 0.1080 s/iter. Inference: 0.1759 s/iter. Eval: 0.0022 s/iter. Total: 0.2861 s/iter. ETA=0:00:05
[09/22 14:43:51] lb.evaluation.evaluator INFO: Inference done 47104/50000. Dataloading: 0.1211 s/iter. Inference: 0.1686 s/iter. Eval: 0.0020 s/iter. Total: 0.2919 s/iter. ETA=0:00:00
[09/22 14:43:52] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/22 14:43:52] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.596377 (0.000252 s / iter per device, on 8 devices)
[09/22 14:43:52] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000148 s / iter per device, on 8 devices)
[09/22 14:43:52] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/22 14:43:52] lb.evaluation.utils INFO: copypaste: Acc@1=72.166
[09/22 14:43:52] lb.evaluation.utils INFO: copypaste: Acc@5=91.122
[09/22 14:43:52] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 72.16600, better than last best score 71.92400 @ iteration 114999.
[09/22 14:43:52] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/22 14:43:53] lb.utils.events INFO:  eta: 11:04:39  iteration: 119999/375342  consumed_samples: 122880000  total_loss: 3.764  time: 0.3398 s/iter  data_time: 0.2147 s/iter total_throughput: 3013.39 samples/s lr: 7.71e-04  
[09/22 14:44:25] lb.utils.events INFO:  eta: 11:08:04  iteration: 120099/375342  consumed_samples: 122982400  total_loss: 3.772  time: 0.3398 s/iter  data_time: 0.2215 s/iter total_throughput: 3013.55 samples/s lr: 7.70e-04  
[09/22 14:44:59] lb.utils.events INFO:  eta: 11:08:44  iteration: 120199/375342  consumed_samples: 123084800  total_loss: 3.762  time: 0.3398 s/iter  data_time: 0.2160 s/iter total_throughput: 3013.55 samples/s lr: 7.70e-04  
[09/22 14:45:33] lb.utils.events INFO:  eta: 11:08:32  iteration: 120299/375342  consumed_samples: 123187200  total_loss: 3.72  time: 0.3398 s/iter  data_time: 0.2241 s/iter total_throughput: 3013.53 samples/s lr: 7.70e-04  
[09/22 14:46:08] lb.utils.events INFO:  eta: 11:08:16  iteration: 120399/375342  consumed_samples: 123289600  total_loss: 3.738  time: 0.3398 s/iter  data_time: 0.2337 s/iter total_throughput: 3013.48 samples/s lr: 7.69e-04  
[09/22 14:46:42] lb.utils.events INFO:  eta: 11:06:42  iteration: 120499/375342  consumed_samples: 123392000  total_loss: 3.739  time: 0.3398 s/iter  data_time: 0.2063 s/iter total_throughput: 3013.48 samples/s lr: 7.69e-04  
[09/22 14:47:16] lb.utils.events INFO:  eta: 11:07:29  iteration: 120599/375342  consumed_samples: 123494400  total_loss: 3.733  time: 0.3398 s/iter  data_time: 0.2173 s/iter total_throughput: 3013.47 samples/s lr: 7.69e-04  
[09/22 14:47:49] lb.utils.events INFO:  eta: 11:08:20  iteration: 120699/375342  consumed_samples: 123596800  total_loss: 3.755  time: 0.3398 s/iter  data_time: 0.2096 s/iter total_throughput: 3013.50 samples/s lr: 7.68e-04  
[09/22 14:48:24] lb.utils.events INFO:  eta: 11:07:58  iteration: 120799/375342  consumed_samples: 123699200  total_loss: 3.74  time: 0.3398 s/iter  data_time: 0.2093 s/iter total_throughput: 3013.48 samples/s lr: 7.68e-04  
[09/22 14:48:58] lb.utils.events INFO:  eta: 11:07:12  iteration: 120899/375342  consumed_samples: 123801600  total_loss: 3.735  time: 0.3398 s/iter  data_time: 0.2118 s/iter total_throughput: 3013.47 samples/s lr: 7.67e-04  
[09/22 14:49:31] lb.utils.events INFO:  eta: 11:06:20  iteration: 120999/375342  consumed_samples: 123904000  total_loss: 3.757  time: 0.3398 s/iter  data_time: 0.2159 s/iter total_throughput: 3013.48 samples/s lr: 7.67e-04  
[09/22 14:50:05] lb.utils.events INFO:  eta: 11:02:56  iteration: 121099/375342  consumed_samples: 124006400  total_loss: 3.775  time: 0.3398 s/iter  data_time: 0.2209 s/iter total_throughput: 3013.49 samples/s lr: 7.67e-04  
[09/22 14:50:39] lb.utils.events INFO:  eta: 11:02:54  iteration: 121199/375342  consumed_samples: 124108800  total_loss: 3.745  time: 0.3398 s/iter  data_time: 0.2013 s/iter total_throughput: 3013.51 samples/s lr: 7.66e-04  
[09/22 14:51:13] lb.utils.events INFO:  eta: 11:04:32  iteration: 121299/375342  consumed_samples: 124211200  total_loss: 3.747  time: 0.3398 s/iter  data_time: 0.2102 s/iter total_throughput: 3013.53 samples/s lr: 7.66e-04  
[09/22 14:51:47] lb.utils.events INFO:  eta: 11:04:31  iteration: 121399/375342  consumed_samples: 124313600  total_loss: 3.755  time: 0.3398 s/iter  data_time: 0.2061 s/iter total_throughput: 3013.55 samples/s lr: 7.66e-04  
[09/22 14:52:20] lb.utils.events INFO:  eta: 11:05:01  iteration: 121499/375342  consumed_samples: 124416000  total_loss: 3.729  time: 0.3398 s/iter  data_time: 0.2087 s/iter total_throughput: 3013.59 samples/s lr: 7.65e-04  
[09/22 14:52:54] lb.utils.events INFO:  eta: 11:04:38  iteration: 121599/375342  consumed_samples: 124518400  total_loss: 3.734  time: 0.3398 s/iter  data_time: 0.2451 s/iter total_throughput: 3013.58 samples/s lr: 7.65e-04  
[09/22 14:53:28] lb.utils.events INFO:  eta: 11:04:17  iteration: 121699/375342  consumed_samples: 124620800  total_loss: 3.747  time: 0.3398 s/iter  data_time: 0.2092 s/iter total_throughput: 3013.59 samples/s lr: 7.65e-04  
[09/22 14:54:02] lb.utils.events INFO:  eta: 11:05:31  iteration: 121799/375342  consumed_samples: 124723200  total_loss: 3.746  time: 0.3398 s/iter  data_time: 0.2182 s/iter total_throughput: 3013.60 samples/s lr: 7.64e-04  
[09/22 14:54:36] lb.utils.events INFO:  eta: 11:05:35  iteration: 121899/375342  consumed_samples: 124825600  total_loss: 3.745  time: 0.3398 s/iter  data_time: 0.2308 s/iter total_throughput: 3013.59 samples/s lr: 7.64e-04  
[09/22 14:55:09] lb.utils.events INFO:  eta: 11:07:04  iteration: 121999/375342  consumed_samples: 124928000  total_loss: 3.74  time: 0.3398 s/iter  data_time: 0.2117 s/iter total_throughput: 3013.62 samples/s lr: 7.64e-04  
[09/22 14:55:43] lb.utils.events INFO:  eta: 11:07:17  iteration: 122099/375342  consumed_samples: 125030400  total_loss: 3.729  time: 0.3398 s/iter  data_time: 0.1902 s/iter total_throughput: 3013.63 samples/s lr: 7.63e-04  
[09/22 14:56:17] lb.utils.events INFO:  eta: 11:06:31  iteration: 122199/375342  consumed_samples: 125132800  total_loss: 3.724  time: 0.3398 s/iter  data_time: 0.2067 s/iter total_throughput: 3013.66 samples/s lr: 7.63e-04  
[09/22 14:56:51] lb.utils.events INFO:  eta: 11:06:04  iteration: 122299/375342  consumed_samples: 125235200  total_loss: 3.743  time: 0.3398 s/iter  data_time: 0.2279 s/iter total_throughput: 3013.67 samples/s lr: 7.63e-04  
[09/22 14:57:24] lb.utils.events INFO:  eta: 11:05:15  iteration: 122399/375342  consumed_samples: 125337600  total_loss: 3.743  time: 0.3398 s/iter  data_time: 0.2024 s/iter total_throughput: 3013.71 samples/s lr: 7.62e-04  
[09/22 14:57:58] lb.utils.events INFO:  eta: 11:04:00  iteration: 122499/375342  consumed_samples: 125440000  total_loss: 3.756  time: 0.3398 s/iter  data_time: 0.2198 s/iter total_throughput: 3013.72 samples/s lr: 7.62e-04  
[09/22 14:58:32] lb.utils.events INFO:  eta: 11:03:39  iteration: 122599/375342  consumed_samples: 125542400  total_loss: 3.752  time: 0.3398 s/iter  data_time: 0.1953 s/iter total_throughput: 3013.75 samples/s lr: 7.61e-04  
[09/22 14:59:06] lb.utils.events INFO:  eta: 11:02:30  iteration: 122699/375342  consumed_samples: 125644800  total_loss: 3.732  time: 0.3398 s/iter  data_time: 0.2074 s/iter total_throughput: 3013.75 samples/s lr: 7.61e-04  
[09/22 14:59:39] lb.utils.events INFO:  eta: 11:02:53  iteration: 122799/375342  consumed_samples: 125747200  total_loss: 3.733  time: 0.3398 s/iter  data_time: 0.2054 s/iter total_throughput: 3013.78 samples/s lr: 7.61e-04  
[09/22 15:00:13] lb.utils.events INFO:  eta: 11:03:26  iteration: 122899/375342  consumed_samples: 125849600  total_loss: 3.732  time: 0.3398 s/iter  data_time: 0.2066 s/iter total_throughput: 3013.79 samples/s lr: 7.60e-04  
[09/22 15:00:47] lb.utils.events INFO:  eta: 11:02:22  iteration: 122999/375342  consumed_samples: 125952000  total_loss: 3.735  time: 0.3398 s/iter  data_time: 0.2083 s/iter total_throughput: 3013.79 samples/s lr: 7.60e-04  
[09/22 15:01:21] lb.utils.events INFO:  eta: 10:59:08  iteration: 123099/375342  consumed_samples: 126054400  total_loss: 3.744  time: 0.3398 s/iter  data_time: 0.2093 s/iter total_throughput: 3013.77 samples/s lr: 7.60e-04  
[09/22 15:01:55] lb.utils.events INFO:  eta: 11:00:14  iteration: 123199/375342  consumed_samples: 126156800  total_loss: 3.736  time: 0.3398 s/iter  data_time: 0.2094 s/iter total_throughput: 3013.80 samples/s lr: 7.59e-04  
[09/22 15:02:28] lb.utils.events INFO:  eta: 11:00:45  iteration: 123299/375342  consumed_samples: 126259200  total_loss: 3.715  time: 0.3398 s/iter  data_time: 0.2098 s/iter total_throughput: 3013.84 samples/s lr: 7.59e-04  
[09/22 15:03:01] lb.utils.events INFO:  eta: 11:02:49  iteration: 123399/375342  consumed_samples: 126361600  total_loss: 3.722  time: 0.3398 s/iter  data_time: 0.2002 s/iter total_throughput: 3013.91 samples/s lr: 7.59e-04  
[09/22 15:03:34] lb.utils.events INFO:  eta: 11:04:10  iteration: 123499/375342  consumed_samples: 126464000  total_loss: 3.738  time: 0.3398 s/iter  data_time: 0.2012 s/iter total_throughput: 3013.98 samples/s lr: 7.58e-04  
[09/22 15:04:08] lb.utils.events INFO:  eta: 11:03:32  iteration: 123599/375342  consumed_samples: 126566400  total_loss: 3.738  time: 0.3397 s/iter  data_time: 0.2086 s/iter total_throughput: 3014.00 samples/s lr: 7.58e-04  
[09/22 15:04:41] lb.utils.events INFO:  eta: 11:04:20  iteration: 123699/375342  consumed_samples: 126668800  total_loss: 3.743  time: 0.3397 s/iter  data_time: 0.2048 s/iter total_throughput: 3014.05 samples/s lr: 7.58e-04  
[09/22 15:05:15] lb.utils.events INFO:  eta: 11:02:35  iteration: 123799/375342  consumed_samples: 126771200  total_loss: 3.736  time: 0.3397 s/iter  data_time: 0.2237 s/iter total_throughput: 3014.06 samples/s lr: 7.57e-04  
[09/22 15:05:49] lb.utils.events INFO:  eta: 11:01:32  iteration: 123899/375342  consumed_samples: 126873600  total_loss: 3.721  time: 0.3397 s/iter  data_time: 0.2046 s/iter total_throughput: 3014.10 samples/s lr: 7.57e-04  
[09/22 15:06:23] lb.utils.events INFO:  eta: 10:59:06  iteration: 123999/375342  consumed_samples: 126976000  total_loss: 3.721  time: 0.3397 s/iter  data_time: 0.2111 s/iter total_throughput: 3014.09 samples/s lr: 7.56e-04  
[09/22 15:06:56] lb.utils.events INFO:  eta: 10:59:09  iteration: 124099/375342  consumed_samples: 127078400  total_loss: 3.711  time: 0.3397 s/iter  data_time: 0.2143 s/iter total_throughput: 3014.13 samples/s lr: 7.56e-04  
[09/22 15:07:30] lb.utils.events INFO:  eta: 10:57:51  iteration: 124199/375342  consumed_samples: 127180800  total_loss: 3.717  time: 0.3397 s/iter  data_time: 0.2139 s/iter total_throughput: 3014.16 samples/s lr: 7.56e-04  
[09/22 15:08:03] lb.utils.events INFO:  eta: 10:57:18  iteration: 124299/375342  consumed_samples: 127283200  total_loss: 3.725  time: 0.3397 s/iter  data_time: 0.2142 s/iter total_throughput: 3014.20 samples/s lr: 7.55e-04  
[09/22 15:08:37] lb.utils.events INFO:  eta: 10:54:36  iteration: 124399/375342  consumed_samples: 127385600  total_loss: 3.72  time: 0.3397 s/iter  data_time: 0.2165 s/iter total_throughput: 3014.20 samples/s lr: 7.55e-04  
[09/22 15:09:11] lb.utils.events INFO:  eta: 10:53:11  iteration: 124499/375342  consumed_samples: 127488000  total_loss: 3.742  time: 0.3397 s/iter  data_time: 0.2106 s/iter total_throughput: 3014.23 samples/s lr: 7.55e-04  
[09/22 15:09:44] lb.utils.events INFO:  eta: 10:54:17  iteration: 124599/375342  consumed_samples: 127590400  total_loss: 3.756  time: 0.3397 s/iter  data_time: 0.2156 s/iter total_throughput: 3014.26 samples/s lr: 7.54e-04  
[09/22 15:10:18] lb.utils.events INFO:  eta: 10:53:19  iteration: 124699/375342  consumed_samples: 127692800  total_loss: 3.753  time: 0.3397 s/iter  data_time: 0.2044 s/iter total_throughput: 3014.29 samples/s lr: 7.54e-04  
[09/22 15:10:52] lb.utils.events INFO:  eta: 10:54:21  iteration: 124799/375342  consumed_samples: 127795200  total_loss: 3.734  time: 0.3397 s/iter  data_time: 0.2020 s/iter total_throughput: 3014.30 samples/s lr: 7.54e-04  
[09/22 15:11:25] lb.utils.events INFO:  eta: 10:55:03  iteration: 124899/375342  consumed_samples: 127897600  total_loss: 3.717  time: 0.3397 s/iter  data_time: 0.2070 s/iter total_throughput: 3014.34 samples/s lr: 7.53e-04  
[09/22 15:11:59] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0124999
[09/22 15:11:59] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/22 15:11:59] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/22 15:12:03] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0981 s/iter. Inference: 0.1652 s/iter. Eval: 0.0020 s/iter. Total: 0.2652 s/iter. ETA=0:00:09
[09/22 15:12:09] lb.evaluation.evaluator INFO: Inference done 29696/50000. Dataloading: 0.1176 s/iter. Inference: 0.1764 s/iter. Eval: 0.0020 s/iter. Total: 0.2961 s/iter. ETA=0:00:05
[09/22 15:12:14] lb.evaluation.evaluator INFO: Inference done 49152/50000. Dataloading: 0.1118 s/iter. Inference: 0.1687 s/iter. Eval: 0.0020 s/iter. Total: 0.2826 s/iter. ETA=0:00:00
[09/22 15:12:14] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/22 15:12:14] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.513201 (0.000250 s / iter per device, on 8 devices)
[09/22 15:12:14] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000149 s / iter per device, on 8 devices)
[09/22 15:12:14] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/22 15:12:14] lb.evaluation.utils INFO: copypaste: Acc@1=72.49600000000001
[09/22 15:12:14] lb.evaluation.utils INFO: copypaste: Acc@5=91.196
[09/22 15:12:14] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 72.49600, better than last best score 72.16600 @ iteration 119999.
[09/22 15:12:14] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/22 15:12:15] lb.utils.events INFO:  eta: 10:55:45  iteration: 124999/375342  consumed_samples: 128000000  total_loss: 3.748  time: 0.3397 s/iter  data_time: 0.2094 s/iter total_throughput: 3014.37 samples/s lr: 7.53e-04  
[09/22 15:12:46] lb.utils.events INFO:  eta: 10:58:49  iteration: 125099/375342  consumed_samples: 128102400  total_loss: 3.742  time: 0.3397 s/iter  data_time: 0.2419 s/iter total_throughput: 3014.58 samples/s lr: 7.53e-04  
[09/22 15:13:20] lb.utils.events INFO:  eta: 11:02:24  iteration: 125199/375342  consumed_samples: 128204800  total_loss: 3.712  time: 0.3397 s/iter  data_time: 0.2162 s/iter total_throughput: 3014.58 samples/s lr: 7.52e-04  
[09/22 15:13:54] lb.utils.events INFO:  eta: 11:00:41  iteration: 125299/375342  consumed_samples: 128307200  total_loss: 3.715  time: 0.3397 s/iter  data_time: 0.2260 s/iter total_throughput: 3014.58 samples/s lr: 7.52e-04  
[09/22 15:14:28] lb.utils.events INFO:  eta: 10:59:30  iteration: 125399/375342  consumed_samples: 128409600  total_loss: 3.736  time: 0.3397 s/iter  data_time: 0.2287 s/iter total_throughput: 3014.58 samples/s lr: 7.51e-04  
[09/22 15:15:01] lb.utils.events INFO:  eta: 10:59:59  iteration: 125499/375342  consumed_samples: 128512000  total_loss: 3.749  time: 0.3397 s/iter  data_time: 0.2135 s/iter total_throughput: 3014.61 samples/s lr: 7.51e-04  
[09/22 15:15:35] lb.utils.events INFO:  eta: 10:58:11  iteration: 125599/375342  consumed_samples: 128614400  total_loss: 3.732  time: 0.3397 s/iter  data_time: 0.2069 s/iter total_throughput: 3014.65 samples/s lr: 7.51e-04  
[09/22 15:16:08] lb.utils.events INFO:  eta: 10:58:30  iteration: 125699/375342  consumed_samples: 128716800  total_loss: 3.736  time: 0.3397 s/iter  data_time: 0.2122 s/iter total_throughput: 3014.69 samples/s lr: 7.50e-04  
[09/22 15:16:41] lb.utils.events INFO:  eta: 10:59:11  iteration: 125799/375342  consumed_samples: 128819200  total_loss: 3.722  time: 0.3397 s/iter  data_time: 0.2032 s/iter total_throughput: 3014.77 samples/s lr: 7.50e-04  
[09/22 15:17:14] lb.utils.events INFO:  eta: 10:57:43  iteration: 125899/375342  consumed_samples: 128921600  total_loss: 3.72  time: 0.3397 s/iter  data_time: 0.2084 s/iter total_throughput: 3014.83 samples/s lr: 7.50e-04  
[09/22 15:17:48] lb.utils.events INFO:  eta: 10:58:41  iteration: 125999/375342  consumed_samples: 129024000  total_loss: 3.751  time: 0.3397 s/iter  data_time: 0.2069 s/iter total_throughput: 3014.86 samples/s lr: 7.49e-04  
[09/22 15:18:21] lb.utils.events INFO:  eta: 10:56:07  iteration: 126099/375342  consumed_samples: 129126400  total_loss: 3.745  time: 0.3396 s/iter  data_time: 0.2068 s/iter total_throughput: 3014.91 samples/s lr: 7.49e-04  
[09/22 15:18:55] lb.utils.events INFO:  eta: 10:52:43  iteration: 126199/375342  consumed_samples: 129228800  total_loss: 3.728  time: 0.3396 s/iter  data_time: 0.2173 s/iter total_throughput: 3014.92 samples/s lr: 7.49e-04  
[09/22 15:19:29] lb.utils.events INFO:  eta: 10:51:38  iteration: 126299/375342  consumed_samples: 129331200  total_loss: 3.737  time: 0.3396 s/iter  data_time: 0.2213 s/iter total_throughput: 3014.89 samples/s lr: 7.48e-04  
[09/22 15:20:04] lb.utils.events INFO:  eta: 10:51:50  iteration: 126399/375342  consumed_samples: 129433600  total_loss: 3.724  time: 0.3397 s/iter  data_time: 0.2201 s/iter total_throughput: 3014.81 samples/s lr: 7.48e-04  
[09/22 15:20:40] lb.utils.events INFO:  eta: 10:48:52  iteration: 126499/375342  consumed_samples: 129536000  total_loss: 3.718  time: 0.3397 s/iter  data_time: 0.2182 s/iter total_throughput: 3014.72 samples/s lr: 7.48e-04  
[09/22 15:21:15] lb.utils.events INFO:  eta: 10:48:51  iteration: 126599/375342  consumed_samples: 129638400  total_loss: 3.713  time: 0.3397 s/iter  data_time: 0.2259 s/iter total_throughput: 3014.60 samples/s lr: 7.47e-04  
[09/22 15:21:51] lb.utils.events INFO:  eta: 10:47:13  iteration: 126699/375342  consumed_samples: 129740800  total_loss: 3.7  time: 0.3397 s/iter  data_time: 0.2385 s/iter total_throughput: 3014.49 samples/s lr: 7.47e-04  
[09/22 15:22:26] lb.utils.events INFO:  eta: 10:47:26  iteration: 126799/375342  consumed_samples: 129843200  total_loss: 3.727  time: 0.3397 s/iter  data_time: 0.2144 s/iter total_throughput: 3014.42 samples/s lr: 7.46e-04  
[09/22 15:23:01] lb.utils.events INFO:  eta: 10:45:24  iteration: 126899/375342  consumed_samples: 129945600  total_loss: 3.722  time: 0.3397 s/iter  data_time: 0.2343 s/iter total_throughput: 3014.31 samples/s lr: 7.46e-04  
[09/22 15:23:36] lb.utils.events INFO:  eta: 10:43:45  iteration: 126999/375342  consumed_samples: 130048000  total_loss: 3.723  time: 0.3397 s/iter  data_time: 0.2217 s/iter total_throughput: 3014.24 samples/s lr: 7.46e-04  
[09/22 15:24:12] lb.utils.events INFO:  eta: 10:43:00  iteration: 127099/375342  consumed_samples: 130150400  total_loss: 3.729  time: 0.3397 s/iter  data_time: 0.2254 s/iter total_throughput: 3014.15 samples/s lr: 7.45e-04  
[09/22 15:24:47] lb.utils.events INFO:  eta: 10:42:06  iteration: 127199/375342  consumed_samples: 130252800  total_loss: 3.715  time: 0.3397 s/iter  data_time: 0.2212 s/iter total_throughput: 3014.05 samples/s lr: 7.45e-04  
[09/22 15:25:22] lb.utils.events INFO:  eta: 10:40:07  iteration: 127299/375342  consumed_samples: 130355200  total_loss: 3.685  time: 0.3398 s/iter  data_time: 0.2268 s/iter total_throughput: 3013.96 samples/s lr: 7.45e-04  
[09/22 15:25:57] lb.utils.events INFO:  eta: 10:36:44  iteration: 127399/375342  consumed_samples: 130457600  total_loss: 3.687  time: 0.3398 s/iter  data_time: 0.2236 s/iter total_throughput: 3013.89 samples/s lr: 7.44e-04  
[09/22 15:26:32] lb.utils.events INFO:  eta: 10:37:48  iteration: 127499/375342  consumed_samples: 130560000  total_loss: 3.733  time: 0.3398 s/iter  data_time: 0.2279 s/iter total_throughput: 3013.82 samples/s lr: 7.44e-04  
[09/22 15:27:07] lb.utils.events INFO:  eta: 10:37:29  iteration: 127599/375342  consumed_samples: 130662400  total_loss: 3.744  time: 0.3398 s/iter  data_time: 0.2257 s/iter total_throughput: 3013.75 samples/s lr: 7.44e-04  
[09/22 15:27:42] lb.utils.events INFO:  eta: 10:38:33  iteration: 127699/375342  consumed_samples: 130764800  total_loss: 3.741  time: 0.3398 s/iter  data_time: 0.2226 s/iter total_throughput: 3013.68 samples/s lr: 7.43e-04  
[09/22 15:28:17] lb.utils.events INFO:  eta: 10:35:01  iteration: 127799/375342  consumed_samples: 130867200  total_loss: 3.731  time: 0.3398 s/iter  data_time: 0.2316 s/iter total_throughput: 3013.60 samples/s lr: 7.43e-04  
[09/22 15:28:52] lb.utils.events INFO:  eta: 10:39:49  iteration: 127899/375342  consumed_samples: 130969600  total_loss: 3.726  time: 0.3398 s/iter  data_time: 0.2082 s/iter total_throughput: 3013.55 samples/s lr: 7.42e-04  
[09/22 15:29:27] lb.utils.events INFO:  eta: 10:40:43  iteration: 127999/375342  consumed_samples: 131072000  total_loss: 3.731  time: 0.3398 s/iter  data_time: 0.2328 s/iter total_throughput: 3013.48 samples/s lr: 7.42e-04  
[09/22 15:30:03] lb.utils.events INFO:  eta: 10:39:18  iteration: 128099/375342  consumed_samples: 131174400  total_loss: 3.726  time: 0.3398 s/iter  data_time: 0.2262 s/iter total_throughput: 3013.36 samples/s lr: 7.42e-04  
[09/22 15:30:38] lb.utils.events INFO:  eta: 10:39:29  iteration: 128199/375342  consumed_samples: 131276800  total_loss: 3.723  time: 0.3398 s/iter  data_time: 0.2140 s/iter total_throughput: 3013.29 samples/s lr: 7.41e-04  
[09/22 15:31:13] lb.utils.events INFO:  eta: 10:39:32  iteration: 128299/375342  consumed_samples: 131379200  total_loss: 3.706  time: 0.3398 s/iter  data_time: 0.2200 s/iter total_throughput: 3013.23 samples/s lr: 7.41e-04  
[09/22 15:31:48] lb.utils.events INFO:  eta: 10:39:24  iteration: 128399/375342  consumed_samples: 131481600  total_loss: 3.709  time: 0.3398 s/iter  data_time: 0.2344 s/iter total_throughput: 3013.15 samples/s lr: 7.41e-04  
[09/22 15:32:23] lb.utils.events INFO:  eta: 10:38:32  iteration: 128499/375342  consumed_samples: 131584000  total_loss: 3.707  time: 0.3399 s/iter  data_time: 0.2299 s/iter total_throughput: 3013.05 samples/s lr: 7.40e-04  
[09/22 15:32:59] lb.utils.events INFO:  eta: 10:37:50  iteration: 128599/375342  consumed_samples: 131686400  total_loss: 3.722  time: 0.3399 s/iter  data_time: 0.2311 s/iter total_throughput: 3012.96 samples/s lr: 7.40e-04  
[09/22 15:33:34] lb.utils.events INFO:  eta: 10:35:12  iteration: 128699/375342  consumed_samples: 131788800  total_loss: 3.743  time: 0.3399 s/iter  data_time: 0.2187 s/iter total_throughput: 3012.89 samples/s lr: 7.40e-04  
[09/22 15:34:09] lb.utils.events INFO:  eta: 10:35:35  iteration: 128799/375342  consumed_samples: 131891200  total_loss: 3.74  time: 0.3399 s/iter  data_time: 0.2301 s/iter total_throughput: 3012.82 samples/s lr: 7.39e-04  
[09/22 15:34:43] lb.utils.events INFO:  eta: 10:35:20  iteration: 128899/375342  consumed_samples: 131993600  total_loss: 3.724  time: 0.3399 s/iter  data_time: 0.2253 s/iter total_throughput: 3012.78 samples/s lr: 7.39e-04  
[09/22 15:35:18] lb.utils.events INFO:  eta: 10:34:49  iteration: 128999/375342  consumed_samples: 132096000  total_loss: 3.697  time: 0.3399 s/iter  data_time: 0.2281 s/iter total_throughput: 3012.70 samples/s lr: 7.38e-04  
[09/22 15:35:54] lb.utils.events INFO:  eta: 10:34:55  iteration: 129099/375342  consumed_samples: 132198400  total_loss: 3.7  time: 0.3399 s/iter  data_time: 0.2180 s/iter total_throughput: 3012.63 samples/s lr: 7.38e-04  
[09/22 15:36:28] lb.utils.events INFO:  eta: 10:34:32  iteration: 129199/375342  consumed_samples: 132300800  total_loss: 3.708  time: 0.3399 s/iter  data_time: 0.2158 s/iter total_throughput: 3012.57 samples/s lr: 7.38e-04  
[09/22 15:37:03] lb.utils.events INFO:  eta: 10:34:16  iteration: 129299/375342  consumed_samples: 132403200  total_loss: 3.704  time: 0.3399 s/iter  data_time: 0.2241 s/iter total_throughput: 3012.51 samples/s lr: 7.37e-04  
[09/22 15:37:39] lb.utils.events INFO:  eta: 10:33:48  iteration: 129399/375342  consumed_samples: 132505600  total_loss: 3.722  time: 0.3399 s/iter  data_time: 0.2264 s/iter total_throughput: 3012.41 samples/s lr: 7.37e-04  
[09/22 15:38:14] lb.utils.events INFO:  eta: 10:34:01  iteration: 129499/375342  consumed_samples: 132608000  total_loss: 3.737  time: 0.3399 s/iter  data_time: 0.2188 s/iter total_throughput: 3012.35 samples/s lr: 7.37e-04  
[09/22 15:38:49] lb.utils.events INFO:  eta: 10:33:45  iteration: 129599/375342  consumed_samples: 132710400  total_loss: 3.726  time: 0.3399 s/iter  data_time: 0.2196 s/iter total_throughput: 3012.27 samples/s lr: 7.36e-04  
[09/22 15:39:24] lb.utils.events INFO:  eta: 10:34:19  iteration: 129699/375342  consumed_samples: 132812800  total_loss: 3.728  time: 0.3399 s/iter  data_time: 0.2166 s/iter total_throughput: 3012.21 samples/s lr: 7.36e-04  
[09/22 15:39:58] lb.utils.events INFO:  eta: 10:33:41  iteration: 129799/375342  consumed_samples: 132915200  total_loss: 3.717  time: 0.3400 s/iter  data_time: 0.2215 s/iter total_throughput: 3012.17 samples/s lr: 7.36e-04  
[09/22 15:40:33] lb.utils.events INFO:  eta: 10:32:33  iteration: 129899/375342  consumed_samples: 133017600  total_loss: 3.715  time: 0.3400 s/iter  data_time: 0.2261 s/iter total_throughput: 3012.10 samples/s lr: 7.35e-04  
[09/22 15:41:08] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0129999
[09/22 15:41:09] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/22 15:41:09] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/22 15:41:13] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0958 s/iter. Inference: 0.1614 s/iter. Eval: 0.0020 s/iter. Total: 0.2593 s/iter. ETA=0:00:09
[09/22 15:41:18] lb.evaluation.evaluator INFO: Inference done 29696/50000. Dataloading: 0.1319 s/iter. Inference: 0.1661 s/iter. Eval: 0.0020 s/iter. Total: 0.3001 s/iter. ETA=0:00:05
[09/22 15:41:24] lb.evaluation.evaluator INFO: Inference done 50000/50000. Dataloading: 0.1191 s/iter. Inference: 0.1651 s/iter. Eval: 0.0020 s/iter. Total: 0.2862 s/iter. ETA=0:00:00
[09/22 15:41:24] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/22 15:41:24] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.597294 (0.000252 s / iter per device, on 8 devices)
[09/22 15:41:24] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000145 s / iter per device, on 8 devices)
[09/22 15:41:24] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/22 15:41:24] lb.evaluation.utils INFO: copypaste: Acc@1=72.898
[09/22 15:41:24] lb.evaluation.utils INFO: copypaste: Acc@5=91.418
[09/22 15:41:24] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 72.89800, better than last best score 72.49600 @ iteration 124999.
[09/22 15:41:24] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/22 15:41:25] lb.utils.events INFO:  eta: 10:31:47  iteration: 129999/375342  consumed_samples: 133120000  total_loss: 3.734  time: 0.3400 s/iter  data_time: 0.2299 s/iter total_throughput: 3012.05 samples/s lr: 7.35e-04  
[09/22 15:41:57] lb.utils.events INFO:  eta: 10:33:17  iteration: 130099/375342  consumed_samples: 133222400  total_loss: 3.727  time: 0.3400 s/iter  data_time: 0.2243 s/iter total_throughput: 3012.14 samples/s lr: 7.34e-04  
[09/22 15:42:32] lb.utils.events INFO:  eta: 10:33:48  iteration: 130199/375342  consumed_samples: 133324800  total_loss: 3.722  time: 0.3400 s/iter  data_time: 0.2202 s/iter total_throughput: 3012.09 samples/s lr: 7.34e-04  
[09/22 15:43:07] lb.utils.events INFO:  eta: 10:34:07  iteration: 130299/375342  consumed_samples: 133427200  total_loss: 3.719  time: 0.3400 s/iter  data_time: 0.2273 s/iter total_throughput: 3012.02 samples/s lr: 7.34e-04  
[09/22 15:43:42] lb.utils.events INFO:  eta: 10:35:21  iteration: 130399/375342  consumed_samples: 133529600  total_loss: 3.704  time: 0.3400 s/iter  data_time: 0.2324 s/iter total_throughput: 3011.94 samples/s lr: 7.33e-04  
[09/22 15:44:18] lb.utils.events INFO:  eta: 10:34:37  iteration: 130499/375342  consumed_samples: 133632000  total_loss: 3.716  time: 0.3400 s/iter  data_time: 0.2387 s/iter total_throughput: 3011.85 samples/s lr: 7.33e-04  
[09/22 15:44:53] lb.utils.events INFO:  eta: 10:35:33  iteration: 130599/375342  consumed_samples: 133734400  total_loss: 3.719  time: 0.3400 s/iter  data_time: 0.2251 s/iter total_throughput: 3011.78 samples/s lr: 7.33e-04  
[09/22 15:45:28] lb.utils.events INFO:  eta: 10:35:18  iteration: 130699/375342  consumed_samples: 133836800  total_loss: 3.716  time: 0.3400 s/iter  data_time: 0.2328 s/iter total_throughput: 3011.71 samples/s lr: 7.32e-04  
[09/22 15:46:03] lb.utils.events INFO:  eta: 10:35:35  iteration: 130799/375342  consumed_samples: 133939200  total_loss: 3.716  time: 0.3400 s/iter  data_time: 0.2133 s/iter total_throughput: 3011.64 samples/s lr: 7.32e-04  
[09/22 15:46:38] lb.utils.events INFO:  eta: 10:35:16  iteration: 130899/375342  consumed_samples: 134041600  total_loss: 3.716  time: 0.3400 s/iter  data_time: 0.2275 s/iter total_throughput: 3011.58 samples/s lr: 7.31e-04  
[09/22 15:47:13] lb.utils.events INFO:  eta: 10:34:47  iteration: 130999/375342  consumed_samples: 134144000  total_loss: 3.723  time: 0.3400 s/iter  data_time: 0.2280 s/iter total_throughput: 3011.50 samples/s lr: 7.31e-04  
[09/22 15:47:48] lb.utils.events INFO:  eta: 10:30:39  iteration: 131099/375342  consumed_samples: 134246400  total_loss: 3.709  time: 0.3400 s/iter  data_time: 0.2323 s/iter total_throughput: 3011.40 samples/s lr: 7.31e-04  
[09/22 15:48:23] lb.utils.events INFO:  eta: 10:30:34  iteration: 131199/375342  consumed_samples: 134348800  total_loss: 3.702  time: 0.3400 s/iter  data_time: 0.2195 s/iter total_throughput: 3011.36 samples/s lr: 7.30e-04  
[09/22 15:48:58] lb.utils.events INFO:  eta: 10:29:37  iteration: 131299/375342  consumed_samples: 134451200  total_loss: 3.713  time: 0.3401 s/iter  data_time: 0.2110 s/iter total_throughput: 3011.30 samples/s lr: 7.30e-04  
[09/22 15:49:33] lb.utils.events INFO:  eta: 10:27:43  iteration: 131399/375342  consumed_samples: 134553600  total_loss: 3.704  time: 0.3401 s/iter  data_time: 0.2231 s/iter total_throughput: 3011.23 samples/s lr: 7.30e-04  
[09/22 15:50:08] lb.utils.events INFO:  eta: 10:27:18  iteration: 131499/375342  consumed_samples: 134656000  total_loss: 3.702  time: 0.3401 s/iter  data_time: 0.2185 s/iter total_throughput: 3011.17 samples/s lr: 7.29e-04  
[09/22 15:50:43] lb.utils.events INFO:  eta: 10:26:35  iteration: 131599/375342  consumed_samples: 134758400  total_loss: 3.713  time: 0.3401 s/iter  data_time: 0.2304 s/iter total_throughput: 3011.08 samples/s lr: 7.29e-04  
[09/22 15:51:18] lb.utils.events INFO:  eta: 10:26:41  iteration: 131699/375342  consumed_samples: 134860800  total_loss: 3.721  time: 0.3401 s/iter  data_time: 0.2300 s/iter total_throughput: 3011.02 samples/s lr: 7.29e-04  
[09/22 15:51:53] lb.utils.events INFO:  eta: 10:25:51  iteration: 131799/375342  consumed_samples: 134963200  total_loss: 3.726  time: 0.3401 s/iter  data_time: 0.2223 s/iter total_throughput: 3010.94 samples/s lr: 7.28e-04  
[09/22 15:52:28] lb.utils.events INFO:  eta: 10:25:33  iteration: 131899/375342  consumed_samples: 135065600  total_loss: 3.703  time: 0.3401 s/iter  data_time: 0.2295 s/iter total_throughput: 3010.87 samples/s lr: 7.28e-04  
[09/22 15:53:03] lb.utils.events INFO:  eta: 10:26:15  iteration: 131999/375342  consumed_samples: 135168000  total_loss: 3.703  time: 0.3401 s/iter  data_time: 0.2137 s/iter total_throughput: 3010.80 samples/s lr: 7.27e-04  
[09/22 15:53:39] lb.utils.events INFO:  eta: 10:27:07  iteration: 132099/375342  consumed_samples: 135270400  total_loss: 3.715  time: 0.3401 s/iter  data_time: 0.2242 s/iter total_throughput: 3010.72 samples/s lr: 7.27e-04  
[09/22 15:54:14] lb.utils.events INFO:  eta: 10:24:57  iteration: 132199/375342  consumed_samples: 135372800  total_loss: 3.712  time: 0.3401 s/iter  data_time: 0.2174 s/iter total_throughput: 3010.63 samples/s lr: 7.27e-04  
[09/22 15:54:49] lb.utils.events INFO:  eta: 10:25:38  iteration: 132299/375342  consumed_samples: 135475200  total_loss: 3.731  time: 0.3401 s/iter  data_time: 0.2282 s/iter total_throughput: 3010.58 samples/s lr: 7.26e-04  
[09/22 15:55:24] lb.utils.events INFO:  eta: 10:25:52  iteration: 132399/375342  consumed_samples: 135577600  total_loss: 3.729  time: 0.3401 s/iter  data_time: 0.2197 s/iter total_throughput: 3010.52 samples/s lr: 7.26e-04  
[09/22 15:55:58] lb.utils.events INFO:  eta: 10:26:55  iteration: 132499/375342  consumed_samples: 135680000  total_loss: 3.713  time: 0.3401 s/iter  data_time: 0.2219 s/iter total_throughput: 3010.48 samples/s lr: 7.26e-04  
[09/22 15:56:33] lb.utils.events INFO:  eta: 10:26:42  iteration: 132599/375342  consumed_samples: 135782400  total_loss: 3.715  time: 0.3401 s/iter  data_time: 0.2186 s/iter total_throughput: 3010.45 samples/s lr: 7.25e-04  
[09/22 15:57:08] lb.utils.events INFO:  eta: 10:26:37  iteration: 132699/375342  consumed_samples: 135884800  total_loss: 3.717  time: 0.3402 s/iter  data_time: 0.2240 s/iter total_throughput: 3010.38 samples/s lr: 7.25e-04  
[09/22 15:57:43] lb.utils.events INFO:  eta: 10:26:01  iteration: 132799/375342  consumed_samples: 135987200  total_loss: 3.7  time: 0.3402 s/iter  data_time: 0.2164 s/iter total_throughput: 3010.30 samples/s lr: 7.24e-04  
[09/22 15:58:18] lb.utils.events INFO:  eta: 10:25:29  iteration: 132899/375342  consumed_samples: 136089600  total_loss: 3.711  time: 0.3402 s/iter  data_time: 0.2319 s/iter total_throughput: 3010.22 samples/s lr: 7.24e-04  
[09/22 15:58:54] lb.utils.events INFO:  eta: 10:24:59  iteration: 132999/375342  consumed_samples: 136192000  total_loss: 3.711  time: 0.3402 s/iter  data_time: 0.2216 s/iter total_throughput: 3010.13 samples/s lr: 7.24e-04  
[09/22 15:59:29] lb.utils.events INFO:  eta: 10:25:36  iteration: 133099/375342  consumed_samples: 136294400  total_loss: 3.712  time: 0.3402 s/iter  data_time: 0.2260 s/iter total_throughput: 3010.07 samples/s lr: 7.23e-04  
[09/22 16:00:03] lb.utils.events INFO:  eta: 10:27:22  iteration: 133199/375342  consumed_samples: 136396800  total_loss: 3.73  time: 0.3402 s/iter  data_time: 0.2172 s/iter total_throughput: 3010.06 samples/s lr: 7.23e-04  
[09/22 16:00:37] lb.utils.events INFO:  eta: 10:26:54  iteration: 133299/375342  consumed_samples: 136499200  total_loss: 3.737  time: 0.3402 s/iter  data_time: 0.2188 s/iter total_throughput: 3010.02 samples/s lr: 7.23e-04  
[09/22 16:01:12] lb.utils.events INFO:  eta: 10:24:58  iteration: 133399/375342  consumed_samples: 136601600  total_loss: 3.734  time: 0.3402 s/iter  data_time: 0.2135 s/iter total_throughput: 3009.96 samples/s lr: 7.22e-04  
[09/22 16:01:47] lb.utils.events INFO:  eta: 10:23:25  iteration: 133499/375342  consumed_samples: 136704000  total_loss: 3.719  time: 0.3402 s/iter  data_time: 0.2209 s/iter total_throughput: 3009.88 samples/s lr: 7.22e-04  
[09/22 16:02:23] lb.utils.events INFO:  eta: 10:23:10  iteration: 133599/375342  consumed_samples: 136806400  total_loss: 3.702  time: 0.3402 s/iter  data_time: 0.2219 s/iter total_throughput: 3009.81 samples/s lr: 7.21e-04  
[09/22 16:02:58] lb.utils.events INFO:  eta: 10:22:54  iteration: 133699/375342  consumed_samples: 136908800  total_loss: 3.703  time: 0.3402 s/iter  data_time: 0.2228 s/iter total_throughput: 3009.74 samples/s lr: 7.21e-04  
[09/22 16:03:33] lb.utils.events INFO:  eta: 10:23:33  iteration: 133799/375342  consumed_samples: 137011200  total_loss: 3.706  time: 0.3402 s/iter  data_time: 0.2121 s/iter total_throughput: 3009.67 samples/s lr: 7.21e-04  
[09/22 16:04:07] lb.utils.events INFO:  eta: 10:23:47  iteration: 133899/375342  consumed_samples: 137113600  total_loss: 3.698  time: 0.3402 s/iter  data_time: 0.2228 s/iter total_throughput: 3009.62 samples/s lr: 7.20e-04  
[09/22 16:04:42] lb.utils.events INFO:  eta: 10:23:13  iteration: 133999/375342  consumed_samples: 137216000  total_loss: 3.681  time: 0.3402 s/iter  data_time: 0.2116 s/iter total_throughput: 3009.57 samples/s lr: 7.20e-04  
[09/22 16:05:17] lb.utils.events INFO:  eta: 10:25:02  iteration: 134099/375342  consumed_samples: 137318400  total_loss: 3.706  time: 0.3403 s/iter  data_time: 0.2137 s/iter total_throughput: 3009.55 samples/s lr: 7.20e-04  
[09/22 16:05:51] lb.utils.events INFO:  eta: 10:25:30  iteration: 134199/375342  consumed_samples: 137420800  total_loss: 3.732  time: 0.3403 s/iter  data_time: 0.2134 s/iter total_throughput: 3009.50 samples/s lr: 7.19e-04  
[09/22 16:06:26] lb.utils.events INFO:  eta: 10:26:57  iteration: 134299/375342  consumed_samples: 137523200  total_loss: 3.7  time: 0.3403 s/iter  data_time: 0.2302 s/iter total_throughput: 3009.44 samples/s lr: 7.19e-04  
[09/22 16:07:01] lb.utils.events INFO:  eta: 10:26:20  iteration: 134399/375342  consumed_samples: 137625600  total_loss: 3.675  time: 0.3403 s/iter  data_time: 0.2203 s/iter total_throughput: 3009.39 samples/s lr: 7.18e-04  
[09/22 16:07:36] lb.utils.events INFO:  eta: 10:25:26  iteration: 134499/375342  consumed_samples: 137728000  total_loss: 3.689  time: 0.3403 s/iter  data_time: 0.2173 s/iter total_throughput: 3009.34 samples/s lr: 7.18e-04  
[09/22 16:08:11] lb.utils.events INFO:  eta: 10:25:25  iteration: 134599/375342  consumed_samples: 137830400  total_loss: 3.704  time: 0.3403 s/iter  data_time: 0.2259 s/iter total_throughput: 3009.30 samples/s lr: 7.18e-04  
[09/22 16:08:46] lb.utils.events INFO:  eta: 10:24:19  iteration: 134699/375342  consumed_samples: 137932800  total_loss: 3.712  time: 0.3403 s/iter  data_time: 0.2091 s/iter total_throughput: 3009.25 samples/s lr: 7.17e-04  
[09/22 16:09:20] lb.utils.events INFO:  eta: 10:23:50  iteration: 134799/375342  consumed_samples: 138035200  total_loss: 3.723  time: 0.3403 s/iter  data_time: 0.2346 s/iter total_throughput: 3009.19 samples/s lr: 7.17e-04  
[09/22 16:09:55] lb.utils.events INFO:  eta: 10:22:43  iteration: 134899/375342  consumed_samples: 138137600  total_loss: 3.707  time: 0.3403 s/iter  data_time: 0.2115 s/iter total_throughput: 3009.15 samples/s lr: 7.17e-04  
[09/22 16:10:31] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0134999
[09/22 16:10:31] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/22 16:10:31] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/22 16:10:35] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0968 s/iter. Inference: 0.1593 s/iter. Eval: 0.0019 s/iter. Total: 0.2581 s/iter. ETA=0:00:09
[09/22 16:10:41] lb.evaluation.evaluator INFO: Inference done 29696/50000. Dataloading: 0.1185 s/iter. Inference: 0.1766 s/iter. Eval: 0.0020 s/iter. Total: 0.2971 s/iter. ETA=0:00:05
[09/22 16:10:46] lb.evaluation.evaluator INFO: Inference done 49152/50000. Dataloading: 0.1125 s/iter. Inference: 0.1689 s/iter. Eval: 0.0020 s/iter. Total: 0.2835 s/iter. ETA=0:00:00
[09/22 16:10:46] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/22 16:10:46] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.557946 (0.000251 s / iter per device, on 8 devices)
[09/22 16:10:46] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000149 s / iter per device, on 8 devices)
[09/22 16:10:46] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/22 16:10:46] lb.evaluation.utils INFO: copypaste: Acc@1=73.11800000000001
[09/22 16:10:46] lb.evaluation.utils INFO: copypaste: Acc@5=91.53
[09/22 16:10:46] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 73.11800, better than last best score 72.89800 @ iteration 129999.
[09/22 16:10:46] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/22 16:10:47] lb.utils.events INFO:  eta: 10:20:53  iteration: 134999/375342  consumed_samples: 138240000  total_loss: 3.705  time: 0.3403 s/iter  data_time: 0.2230 s/iter total_throughput: 3009.06 samples/s lr: 7.16e-04  
[09/22 16:11:20] lb.utils.events INFO:  eta: 10:22:29  iteration: 135099/375342  consumed_samples: 138342400  total_loss: 3.714  time: 0.3403 s/iter  data_time: 0.2277 s/iter total_throughput: 3009.14 samples/s lr: 7.16e-04  
[09/22 16:11:55] lb.utils.events INFO:  eta: 10:19:20  iteration: 135199/375342  consumed_samples: 138444800  total_loss: 3.699  time: 0.3403 s/iter  data_time: 0.2188 s/iter total_throughput: 3009.09 samples/s lr: 7.15e-04  
[09/22 16:12:29] lb.utils.events INFO:  eta: 10:19:40  iteration: 135299/375342  consumed_samples: 138547200  total_loss: 3.688  time: 0.3403 s/iter  data_time: 0.2131 s/iter total_throughput: 3009.05 samples/s lr: 7.15e-04  
[09/22 16:13:04] lb.utils.events INFO:  eta: 10:19:43  iteration: 135399/375342  consumed_samples: 138649600  total_loss: 3.701  time: 0.3403 s/iter  data_time: 0.2158 s/iter total_throughput: 3009.03 samples/s lr: 7.15e-04  
[09/22 16:13:38] lb.utils.events INFO:  eta: 10:19:21  iteration: 135499/375342  consumed_samples: 138752000  total_loss: 3.71  time: 0.3403 s/iter  data_time: 0.2347 s/iter total_throughput: 3008.98 samples/s lr: 7.14e-04  
[09/22 16:14:13] lb.utils.events INFO:  eta: 10:18:21  iteration: 135599/375342  consumed_samples: 138854400  total_loss: 3.704  time: 0.3403 s/iter  data_time: 0.2199 s/iter total_throughput: 3008.92 samples/s lr: 7.14e-04  
[09/22 16:14:48] lb.utils.events INFO:  eta: 10:17:44  iteration: 135699/375342  consumed_samples: 138956800  total_loss: 3.699  time: 0.3403 s/iter  data_time: 0.2159 s/iter total_throughput: 3008.87 samples/s lr: 7.14e-04  
[09/22 16:15:23] lb.utils.events INFO:  eta: 10:18:41  iteration: 135799/375342  consumed_samples: 139059200  total_loss: 3.695  time: 0.3403 s/iter  data_time: 0.2262 s/iter total_throughput: 3008.82 samples/s lr: 7.13e-04  
[09/22 16:15:58] lb.utils.events INFO:  eta: 10:18:24  iteration: 135899/375342  consumed_samples: 139161600  total_loss: 3.725  time: 0.3403 s/iter  data_time: 0.2269 s/iter total_throughput: 3008.78 samples/s lr: 7.13e-04  
[09/22 16:16:32] lb.utils.events INFO:  eta: 10:20:37  iteration: 135999/375342  consumed_samples: 139264000  total_loss: 3.724  time: 0.3403 s/iter  data_time: 0.2170 s/iter total_throughput: 3008.73 samples/s lr: 7.12e-04  
[09/22 16:17:07] lb.utils.events INFO:  eta: 10:17:12  iteration: 136099/375342  consumed_samples: 139366400  total_loss: 3.704  time: 0.3403 s/iter  data_time: 0.2186 s/iter total_throughput: 3008.68 samples/s lr: 7.12e-04  
[09/22 16:17:42] lb.utils.events INFO:  eta: 10:16:44  iteration: 136199/375342  consumed_samples: 139468800  total_loss: 3.717  time: 0.3404 s/iter  data_time: 0.2183 s/iter total_throughput: 3008.63 samples/s lr: 7.12e-04  
[09/22 16:18:17] lb.utils.events INFO:  eta: 10:16:01  iteration: 136299/375342  consumed_samples: 139571200  total_loss: 3.722  time: 0.3404 s/iter  data_time: 0.2162 s/iter total_throughput: 3008.60 samples/s lr: 7.11e-04  
[09/22 16:18:51] lb.utils.events INFO:  eta: 10:15:45  iteration: 136399/375342  consumed_samples: 139673600  total_loss: 3.7  time: 0.3404 s/iter  data_time: 0.2201 s/iter total_throughput: 3008.57 samples/s lr: 7.11e-04  
[09/22 16:19:26] lb.utils.events INFO:  eta: 10:16:50  iteration: 136499/375342  consumed_samples: 139776000  total_loss: 3.676  time: 0.3404 s/iter  data_time: 0.2194 s/iter total_throughput: 3008.52 samples/s lr: 7.11e-04  
[09/22 16:20:01] lb.utils.events INFO:  eta: 10:16:44  iteration: 136599/375342  consumed_samples: 139878400  total_loss: 3.691  time: 0.3404 s/iter  data_time: 0.2127 s/iter total_throughput: 3008.46 samples/s lr: 7.10e-04  
[09/22 16:20:36] lb.utils.events INFO:  eta: 10:16:25  iteration: 136699/375342  consumed_samples: 139980800  total_loss: 3.703  time: 0.3404 s/iter  data_time: 0.2296 s/iter total_throughput: 3008.40 samples/s lr: 7.10e-04  
[09/22 16:21:11] lb.utils.events INFO:  eta: 10:16:02  iteration: 136799/375342  consumed_samples: 140083200  total_loss: 3.705  time: 0.3404 s/iter  data_time: 0.2201 s/iter total_throughput: 3008.36 samples/s lr: 7.09e-04  
[09/22 16:21:45] lb.utils.events INFO:  eta: 10:15:46  iteration: 136899/375342  consumed_samples: 140185600  total_loss: 3.705  time: 0.3404 s/iter  data_time: 0.2352 s/iter total_throughput: 3008.31 samples/s lr: 7.09e-04  
[09/22 16:22:20] lb.utils.events INFO:  eta: 10:15:23  iteration: 136999/375342  consumed_samples: 140288000  total_loss: 3.679  time: 0.3404 s/iter  data_time: 0.2203 s/iter total_throughput: 3008.28 samples/s lr: 7.09e-04  
[09/22 16:22:54] lb.utils.events INFO:  eta: 10:15:11  iteration: 137099/375342  consumed_samples: 140390400  total_loss: 3.686  time: 0.3404 s/iter  data_time: 0.2178 s/iter total_throughput: 3008.25 samples/s lr: 7.08e-04  
[09/22 16:23:29] lb.utils.events INFO:  eta: 10:15:13  iteration: 137199/375342  consumed_samples: 140492800  total_loss: 3.699  time: 0.3404 s/iter  data_time: 0.2137 s/iter total_throughput: 3008.21 samples/s lr: 7.08e-04  
[09/22 16:24:03] lb.utils.events INFO:  eta: 10:15:01  iteration: 137299/375342  consumed_samples: 140595200  total_loss: 3.699  time: 0.3404 s/iter  data_time: 0.2260 s/iter total_throughput: 3008.19 samples/s lr: 7.08e-04  
[09/22 16:24:38] lb.utils.events INFO:  eta: 10:15:51  iteration: 137399/375342  consumed_samples: 140697600  total_loss: 3.71  time: 0.3404 s/iter  data_time: 0.2075 s/iter total_throughput: 3008.16 samples/s lr: 7.07e-04  
[09/22 16:25:13] lb.utils.events INFO:  eta: 10:15:20  iteration: 137499/375342  consumed_samples: 140800000  total_loss: 3.718  time: 0.3404 s/iter  data_time: 0.2342 s/iter total_throughput: 3008.12 samples/s lr: 7.07e-04  
[09/22 16:25:47] lb.utils.events INFO:  eta: 10:15:21  iteration: 137599/375342  consumed_samples: 140902400  total_loss: 3.687  time: 0.3404 s/iter  data_time: 0.2104 s/iter total_throughput: 3008.11 samples/s lr: 7.06e-04  
[09/22 16:26:22] lb.utils.events INFO:  eta: 10:16:08  iteration: 137699/375342  consumed_samples: 141004800  total_loss: 3.689  time: 0.3404 s/iter  data_time: 0.2098 s/iter total_throughput: 3008.05 samples/s lr: 7.06e-04  
[09/22 16:26:57] lb.utils.events INFO:  eta: 10:15:53  iteration: 137799/375342  consumed_samples: 141107200  total_loss: 3.695  time: 0.3404 s/iter  data_time: 0.2117 s/iter total_throughput: 3008.00 samples/s lr: 7.06e-04  
[09/22 16:27:31] lb.utils.events INFO:  eta: 10:16:49  iteration: 137899/375342  consumed_samples: 141209600  total_loss: 3.679  time: 0.3404 s/iter  data_time: 0.2122 s/iter total_throughput: 3007.98 samples/s lr: 7.05e-04  
[09/22 16:28:05] lb.utils.events INFO:  eta: 10:16:45  iteration: 137999/375342  consumed_samples: 141312000  total_loss: 3.675  time: 0.3404 s/iter  data_time: 0.2373 s/iter total_throughput: 3007.96 samples/s lr: 7.05e-04  
[09/22 16:28:40] lb.utils.events INFO:  eta: 10:17:34  iteration: 138099/375342  consumed_samples: 141414400  total_loss: 3.679  time: 0.3404 s/iter  data_time: 0.2193 s/iter total_throughput: 3007.94 samples/s lr: 7.05e-04  
[09/22 16:29:14] lb.utils.events INFO:  eta: 10:17:55  iteration: 138199/375342  consumed_samples: 141516800  total_loss: 3.679  time: 0.3404 s/iter  data_time: 0.2155 s/iter total_throughput: 3007.90 samples/s lr: 7.04e-04  
[09/22 16:29:49] lb.utils.events INFO:  eta: 10:16:40  iteration: 138299/375342  consumed_samples: 141619200  total_loss: 3.692  time: 0.3404 s/iter  data_time: 0.2089 s/iter total_throughput: 3007.88 samples/s lr: 7.04e-04  
[09/22 16:30:23] lb.utils.events INFO:  eta: 10:16:28  iteration: 138399/375342  consumed_samples: 141721600  total_loss: 3.698  time: 0.3404 s/iter  data_time: 0.2247 s/iter total_throughput: 3007.85 samples/s lr: 7.03e-04  
[09/22 16:30:58] lb.utils.events INFO:  eta: 10:14:53  iteration: 138499/375342  consumed_samples: 141824000  total_loss: 3.704  time: 0.3404 s/iter  data_time: 0.2153 s/iter total_throughput: 3007.83 samples/s lr: 7.03e-04  
[09/22 16:31:32] lb.utils.events INFO:  eta: 10:15:51  iteration: 138599/375342  consumed_samples: 141926400  total_loss: 3.723  time: 0.3404 s/iter  data_time: 0.2101 s/iter total_throughput: 3007.82 samples/s lr: 7.03e-04  
[09/22 16:32:06] lb.utils.events INFO:  eta: 10:14:44  iteration: 138699/375342  consumed_samples: 142028800  total_loss: 3.712  time: 0.3404 s/iter  data_time: 0.2172 s/iter total_throughput: 3007.81 samples/s lr: 7.02e-04  
[09/22 16:32:40] lb.utils.events INFO:  eta: 10:15:12  iteration: 138799/375342  consumed_samples: 142131200  total_loss: 3.706  time: 0.3404 s/iter  data_time: 0.2065 s/iter total_throughput: 3007.80 samples/s lr: 7.02e-04  
[09/22 16:33:14] lb.utils.events INFO:  eta: 10:15:20  iteration: 138899/375342  consumed_samples: 142233600  total_loss: 3.693  time: 0.3404 s/iter  data_time: 0.2042 s/iter total_throughput: 3007.81 samples/s lr: 7.02e-04  
[09/22 16:33:49] lb.utils.events INFO:  eta: 10:14:49  iteration: 138999/375342  consumed_samples: 142336000  total_loss: 3.684  time: 0.3404 s/iter  data_time: 0.2137 s/iter total_throughput: 3007.79 samples/s lr: 7.01e-04  
[09/22 16:34:23] lb.utils.events INFO:  eta: 10:12:37  iteration: 139099/375342  consumed_samples: 142438400  total_loss: 3.691  time: 0.3404 s/iter  data_time: 0.2148 s/iter total_throughput: 3007.79 samples/s lr: 7.01e-04  
[09/22 16:34:57] lb.utils.events INFO:  eta: 10:12:19  iteration: 139199/375342  consumed_samples: 142540800  total_loss: 3.702  time: 0.3405 s/iter  data_time: 0.2118 s/iter total_throughput: 3007.78 samples/s lr: 7.00e-04  
[09/22 16:35:31] lb.utils.events INFO:  eta: 10:13:07  iteration: 139299/375342  consumed_samples: 142643200  total_loss: 3.711  time: 0.3404 s/iter  data_time: 0.2094 s/iter total_throughput: 3007.80 samples/s lr: 7.00e-04  
[09/22 16:36:05] lb.utils.events INFO:  eta: 10:14:02  iteration: 139399/375342  consumed_samples: 142745600  total_loss: 3.703  time: 0.3405 s/iter  data_time: 0.2284 s/iter total_throughput: 3007.78 samples/s lr: 7.00e-04  
[09/22 16:36:40] lb.utils.events INFO:  eta: 10:14:17  iteration: 139499/375342  consumed_samples: 142848000  total_loss: 3.687  time: 0.3405 s/iter  data_time: 0.2347 s/iter total_throughput: 3007.73 samples/s lr: 6.99e-04  
[09/22 16:37:14] lb.utils.events INFO:  eta: 10:12:15  iteration: 139599/375342  consumed_samples: 142950400  total_loss: 3.688  time: 0.3405 s/iter  data_time: 0.2161 s/iter total_throughput: 3007.70 samples/s lr: 6.99e-04  
[09/22 16:37:48] lb.utils.events INFO:  eta: 10:12:51  iteration: 139699/375342  consumed_samples: 143052800  total_loss: 3.696  time: 0.3405 s/iter  data_time: 0.2062 s/iter total_throughput: 3007.70 samples/s lr: 6.98e-04  
[09/22 16:38:22] lb.utils.events INFO:  eta: 10:10:47  iteration: 139799/375342  consumed_samples: 143155200  total_loss: 3.691  time: 0.3405 s/iter  data_time: 0.2125 s/iter total_throughput: 3007.71 samples/s lr: 6.98e-04  
[09/22 16:38:56] lb.utils.events INFO:  eta: 10:09:56  iteration: 139899/375342  consumed_samples: 143257600  total_loss: 3.688  time: 0.3405 s/iter  data_time: 0.2097 s/iter total_throughput: 3007.73 samples/s lr: 6.98e-04  
[09/22 16:39:30] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0139999
[09/22 16:39:31] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/22 16:39:31] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/22 16:39:35] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0948 s/iter. Inference: 0.1641 s/iter. Eval: 0.0020 s/iter. Total: 0.2609 s/iter. ETA=0:00:09
[09/22 16:39:41] lb.evaluation.evaluator INFO: Inference done 29696/50000. Dataloading: 0.1177 s/iter. Inference: 0.1767 s/iter. Eval: 0.0019 s/iter. Total: 0.2964 s/iter. ETA=0:00:05
[09/22 16:39:46] lb.evaluation.evaluator INFO: Inference done 49152/50000. Dataloading: 0.1113 s/iter. Inference: 0.1691 s/iter. Eval: 0.0020 s/iter. Total: 0.2824 s/iter. ETA=0:00:00
[09/22 16:39:46] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/22 16:39:46] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.511276 (0.000250 s / iter per device, on 8 devices)
[09/22 16:39:46] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000149 s / iter per device, on 8 devices)
[09/22 16:39:46] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/22 16:39:46] lb.evaluation.utils INFO: copypaste: Acc@1=73.072
[09/22 16:39:46] lb.evaluation.utils INFO: copypaste: Acc@5=91.592
[09/22 16:39:46] lb.engine.hooks INFO: Not saving as latest eval score for Acc@1 is 73.07200, not better than best score 73.11800 @ iteration 134999.
[09/22 16:39:46] lb.utils.events INFO:  eta: 10:09:40  iteration: 139999/375342  consumed_samples: 143360000  total_loss: 3.7  time: 0.3405 s/iter  data_time: 0.2111 s/iter total_throughput: 3007.72 samples/s lr: 6.97e-04  
[09/22 16:40:19] lb.utils.events INFO:  eta: 10:12:34  iteration: 140099/375342  consumed_samples: 143462400  total_loss: 3.7  time: 0.3404 s/iter  data_time: 0.2334 s/iter total_throughput: 3007.81 samples/s lr: 6.97e-04  
[09/22 16:40:53] lb.utils.events INFO:  eta: 10:12:57  iteration: 140199/375342  consumed_samples: 143564800  total_loss: 3.703  time: 0.3404 s/iter  data_time: 0.2251 s/iter total_throughput: 3007.79 samples/s lr: 6.97e-04  
[09/22 16:41:27] lb.utils.events INFO:  eta: 10:11:35  iteration: 140299/375342  consumed_samples: 143667200  total_loss: 3.701  time: 0.3405 s/iter  data_time: 0.2141 s/iter total_throughput: 3007.76 samples/s lr: 6.96e-04  
[09/22 16:42:02] lb.utils.events INFO:  eta: 10:11:56  iteration: 140399/375342  consumed_samples: 143769600  total_loss: 3.691  time: 0.3405 s/iter  data_time: 0.2175 s/iter total_throughput: 3007.70 samples/s lr: 6.96e-04  
[09/22 16:42:37] lb.utils.events INFO:  eta: 10:11:04  iteration: 140499/375342  consumed_samples: 143872000  total_loss: 3.686  time: 0.3405 s/iter  data_time: 0.2222 s/iter total_throughput: 3007.65 samples/s lr: 6.95e-04  
[09/22 16:43:13] lb.utils.events INFO:  eta: 10:11:23  iteration: 140599/375342  consumed_samples: 143974400  total_loss: 3.672  time: 0.3405 s/iter  data_time: 0.2270 s/iter total_throughput: 3007.54 samples/s lr: 6.95e-04  
[09/22 16:43:49] lb.utils.events INFO:  eta: 10:09:49  iteration: 140699/375342  consumed_samples: 144076800  total_loss: 3.683  time: 0.3405 s/iter  data_time: 0.2226 s/iter total_throughput: 3007.46 samples/s lr: 6.95e-04  
[09/22 16:44:24] lb.utils.events INFO:  eta: 10:09:16  iteration: 140799/375342  consumed_samples: 144179200  total_loss: 3.693  time: 0.3405 s/iter  data_time: 0.2246 s/iter total_throughput: 3007.37 samples/s lr: 6.94e-04  
[09/22 16:44:59] lb.utils.events INFO:  eta: 10:09:24  iteration: 140899/375342  consumed_samples: 144281600  total_loss: 3.707  time: 0.3405 s/iter  data_time: 0.2233 s/iter total_throughput: 3007.31 samples/s lr: 6.94e-04  
[09/22 16:45:33] lb.utils.events INFO:  eta: 10:10:58  iteration: 140999/375342  consumed_samples: 144384000  total_loss: 3.709  time: 0.3405 s/iter  data_time: 0.2089 s/iter total_throughput: 3007.29 samples/s lr: 6.93e-04  
[09/22 16:46:08] lb.utils.events INFO:  eta: 10:07:34  iteration: 141099/375342  consumed_samples: 144486400  total_loss: 3.703  time: 0.3405 s/iter  data_time: 0.2189 s/iter total_throughput: 3007.26 samples/s lr: 6.93e-04  
[09/22 16:46:43] lb.utils.events INFO:  eta: 10:06:27  iteration: 141199/375342  consumed_samples: 144588800  total_loss: 3.701  time: 0.3405 s/iter  data_time: 0.2314 s/iter total_throughput: 3007.17 samples/s lr: 6.93e-04  
[09/22 16:47:19] lb.utils.events INFO:  eta: 10:05:12  iteration: 141299/375342  consumed_samples: 144691200  total_loss: 3.688  time: 0.3405 s/iter  data_time: 0.2194 s/iter total_throughput: 3007.10 samples/s lr: 6.92e-04  
[09/22 16:47:53] lb.utils.events INFO:  eta: 10:04:51  iteration: 141399/375342  consumed_samples: 144793600  total_loss: 3.691  time: 0.3405 s/iter  data_time: 0.2264 s/iter total_throughput: 3007.05 samples/s lr: 6.92e-04  
[09/22 16:48:29] lb.utils.events INFO:  eta: 10:04:16  iteration: 141499/375342  consumed_samples: 144896000  total_loss: 3.7  time: 0.3405 s/iter  data_time: 0.2296 s/iter total_throughput: 3006.95 samples/s lr: 6.92e-04  
[09/22 16:49:05] lb.utils.events INFO:  eta: 10:03:32  iteration: 141599/375342  consumed_samples: 144998400  total_loss: 3.682  time: 0.3406 s/iter  data_time: 0.2212 s/iter total_throughput: 3006.86 samples/s lr: 6.91e-04  
[09/22 16:49:39] lb.utils.events INFO:  eta: 10:04:27  iteration: 141699/375342  consumed_samples: 145100800  total_loss: 3.663  time: 0.3406 s/iter  data_time: 0.2179 s/iter total_throughput: 3006.83 samples/s lr: 6.91e-04  
[09/22 16:50:14] lb.utils.events INFO:  eta: 10:06:23  iteration: 141799/375342  consumed_samples: 145203200  total_loss: 3.668  time: 0.3406 s/iter  data_time: 0.2258 s/iter total_throughput: 3006.78 samples/s lr: 6.90e-04  
[09/22 16:50:48] lb.utils.events INFO:  eta: 10:04:21  iteration: 141899/375342  consumed_samples: 145305600  total_loss: 3.693  time: 0.3406 s/iter  data_time: 0.2323 s/iter total_throughput: 3006.77 samples/s lr: 6.90e-04  
[09/22 16:51:24] lb.utils.events INFO:  eta: 10:00:43  iteration: 141999/375342  consumed_samples: 145408000  total_loss: 3.7  time: 0.3406 s/iter  data_time: 0.2298 s/iter total_throughput: 3006.69 samples/s lr: 6.90e-04  
[09/22 16:51:58] lb.utils.events INFO:  eta: 10:00:53  iteration: 142099/375342  consumed_samples: 145510400  total_loss: 3.677  time: 0.3406 s/iter  data_time: 0.2229 s/iter total_throughput: 3006.64 samples/s lr: 6.89e-04  
[09/22 16:52:34] lb.utils.events INFO:  eta: 10:00:19  iteration: 142199/375342  consumed_samples: 145612800  total_loss: 3.685  time: 0.3406 s/iter  data_time: 0.2287 s/iter total_throughput: 3006.58 samples/s lr: 6.89e-04  
[09/22 16:53:08] lb.utils.events INFO:  eta: 10:01:18  iteration: 142299/375342  consumed_samples: 145715200  total_loss: 3.724  time: 0.3406 s/iter  data_time: 0.2176 s/iter total_throughput: 3006.55 samples/s lr: 6.88e-04  
[09/22 16:53:43] lb.utils.events INFO:  eta: 10:00:13  iteration: 142399/375342  consumed_samples: 145817600  total_loss: 3.717  time: 0.3406 s/iter  data_time: 0.2135 s/iter total_throughput: 3006.51 samples/s lr: 6.88e-04  
[09/22 16:54:17] lb.utils.events INFO:  eta: 10:01:54  iteration: 142499/375342  consumed_samples: 145920000  total_loss: 3.687  time: 0.3406 s/iter  data_time: 0.2183 s/iter total_throughput: 3006.49 samples/s lr: 6.88e-04  
[09/22 16:54:52] lb.utils.events INFO:  eta: 10:02:05  iteration: 142599/375342  consumed_samples: 146022400  total_loss: 3.682  time: 0.3406 s/iter  data_time: 0.2177 s/iter total_throughput: 3006.45 samples/s lr: 6.87e-04  
[09/22 16:55:27] lb.utils.events INFO:  eta: 10:02:09  iteration: 142699/375342  consumed_samples: 146124800  total_loss: 3.683  time: 0.3406 s/iter  data_time: 0.2176 s/iter total_throughput: 3006.40 samples/s lr: 6.87e-04  
[09/22 16:56:01] lb.utils.events INFO:  eta: 10:01:54  iteration: 142799/375342  consumed_samples: 146227200  total_loss: 3.673  time: 0.3406 s/iter  data_time: 0.2171 s/iter total_throughput: 3006.37 samples/s lr: 6.87e-04  
[09/22 16:56:36] lb.utils.events INFO:  eta: 10:02:08  iteration: 142899/375342  consumed_samples: 146329600  total_loss: 3.695  time: 0.3406 s/iter  data_time: 0.2202 s/iter total_throughput: 3006.33 samples/s lr: 6.86e-04  
[09/22 16:57:11] lb.utils.events INFO:  eta: 10:03:32  iteration: 142999/375342  consumed_samples: 146432000  total_loss: 3.689  time: 0.3406 s/iter  data_time: 0.2115 s/iter total_throughput: 3006.28 samples/s lr: 6.86e-04  
[09/22 16:57:46] lb.utils.events INFO:  eta: 10:03:08  iteration: 143099/375342  consumed_samples: 146534400  total_loss: 3.687  time: 0.3406 s/iter  data_time: 0.2376 s/iter total_throughput: 3006.19 samples/s lr: 6.85e-04  
[09/22 16:58:21] lb.utils.events INFO:  eta: 10:03:38  iteration: 143199/375342  consumed_samples: 146636800  total_loss: 3.691  time: 0.3406 s/iter  data_time: 0.2297 s/iter total_throughput: 3006.15 samples/s lr: 6.85e-04  
[09/22 16:58:56] lb.utils.events INFO:  eta: 10:03:25  iteration: 143299/375342  consumed_samples: 146739200  total_loss: 3.681  time: 0.3406 s/iter  data_time: 0.2118 s/iter total_throughput: 3006.09 samples/s lr: 6.85e-04  
[09/22 16:59:31] lb.utils.events INFO:  eta: 10:02:27  iteration: 143399/375342  consumed_samples: 146841600  total_loss: 3.682  time: 0.3406 s/iter  data_time: 0.2251 s/iter total_throughput: 3006.04 samples/s lr: 6.84e-04  
[09/22 17:00:05] lb.utils.events INFO:  eta: 10:01:33  iteration: 143499/375342  consumed_samples: 146944000  total_loss: 3.686  time: 0.3406 s/iter  data_time: 0.2085 s/iter total_throughput: 3006.02 samples/s lr: 6.84e-04  
[09/22 17:00:40] lb.utils.events INFO:  eta: 10:01:01  iteration: 143599/375342  consumed_samples: 147046400  total_loss: 3.68  time: 0.3407 s/iter  data_time: 0.2194 s/iter total_throughput: 3005.97 samples/s lr: 6.83e-04  
[09/22 17:01:16] lb.utils.events INFO:  eta: 9:59:14  iteration: 143699/375342  consumed_samples: 147148800  total_loss: 3.666  time: 0.3407 s/iter  data_time: 0.2360 s/iter total_throughput: 3005.89 samples/s lr: 6.83e-04  
[09/22 17:01:51] lb.utils.events INFO:  eta: 9:58:39  iteration: 143799/375342  consumed_samples: 147251200  total_loss: 3.672  time: 0.3407 s/iter  data_time: 0.2358 s/iter total_throughput: 3005.83 samples/s lr: 6.83e-04  
[09/22 17:02:26] lb.utils.events INFO:  eta: 9:57:50  iteration: 143899/375342  consumed_samples: 147353600  total_loss: 3.681  time: 0.3407 s/iter  data_time: 0.2385 s/iter total_throughput: 3005.74 samples/s lr: 6.82e-04  
[09/22 17:03:01] lb.utils.events INFO:  eta: 9:57:01  iteration: 143999/375342  consumed_samples: 147456000  total_loss: 3.659  time: 0.3407 s/iter  data_time: 0.2133 s/iter total_throughput: 3005.69 samples/s lr: 6.82e-04  
[09/22 17:03:36] lb.utils.events INFO:  eta: 9:57:34  iteration: 144099/375342  consumed_samples: 147558400  total_loss: 3.656  time: 0.3407 s/iter  data_time: 0.2232 s/iter total_throughput: 3005.68 samples/s lr: 6.82e-04  
[09/22 17:04:10] lb.utils.events INFO:  eta: 9:59:49  iteration: 144199/375342  consumed_samples: 147660800  total_loss: 3.66  time: 0.3407 s/iter  data_time: 0.2204 s/iter total_throughput: 3005.63 samples/s lr: 6.81e-04  
[09/22 17:04:45] lb.utils.events INFO:  eta: 9:59:36  iteration: 144299/375342  consumed_samples: 147763200  total_loss: 3.674  time: 0.3407 s/iter  data_time: 0.2174 s/iter total_throughput: 3005.58 samples/s lr: 6.81e-04  
[09/22 17:05:20] lb.utils.events INFO:  eta: 9:58:11  iteration: 144399/375342  consumed_samples: 147865600  total_loss: 3.665  time: 0.3407 s/iter  data_time: 0.2243 s/iter total_throughput: 3005.56 samples/s lr: 6.80e-04  
[09/22 17:05:54] lb.utils.events INFO:  eta: 9:58:35  iteration: 144499/375342  consumed_samples: 147968000  total_loss: 3.665  time: 0.3407 s/iter  data_time: 0.2206 s/iter total_throughput: 3005.52 samples/s lr: 6.80e-04  
[09/22 17:06:30] lb.utils.events INFO:  eta: 9:57:53  iteration: 144599/375342  consumed_samples: 148070400  total_loss: 3.689  time: 0.3407 s/iter  data_time: 0.2225 s/iter total_throughput: 3005.45 samples/s lr: 6.80e-04  
[09/22 17:07:04] lb.utils.events INFO:  eta: 9:58:21  iteration: 144699/375342  consumed_samples: 148172800  total_loss: 3.676  time: 0.3407 s/iter  data_time: 0.2206 s/iter total_throughput: 3005.41 samples/s lr: 6.79e-04  
[09/22 17:07:40] lb.utils.events INFO:  eta: 9:58:25  iteration: 144799/375342  consumed_samples: 148275200  total_loss: 3.655  time: 0.3407 s/iter  data_time: 0.2347 s/iter total_throughput: 3005.32 samples/s lr: 6.79e-04  
[09/22 17:08:15] lb.utils.events INFO:  eta: 9:58:25  iteration: 144899/375342  consumed_samples: 148377600  total_loss: 3.667  time: 0.3407 s/iter  data_time: 0.2148 s/iter total_throughput: 3005.29 samples/s lr: 6.78e-04  
[09/22 17:08:49] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0144999
[09/22 17:08:50] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/22 17:08:50] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/22 17:08:54] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0966 s/iter. Inference: 0.1604 s/iter. Eval: 0.0020 s/iter. Total: 0.2591 s/iter. ETA=0:00:09
[09/22 17:08:59] lb.evaluation.evaluator INFO: Inference done 29696/50000. Dataloading: 0.1061 s/iter. Inference: 0.1885 s/iter. Eval: 0.0020 s/iter. Total: 0.2968 s/iter. ETA=0:00:05
[09/22 17:09:04] lb.evaluation.evaluator INFO: Inference done 49152/50000. Dataloading: 0.1034 s/iter. Inference: 0.1787 s/iter. Eval: 0.0021 s/iter. Total: 0.2842 s/iter. ETA=0:00:00
[09/22 17:09:05] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/22 17:09:05] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.520151 (0.000250 s / iter per device, on 8 devices)
[09/22 17:09:05] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000158 s / iter per device, on 8 devices)
[09/22 17:09:05] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/22 17:09:05] lb.evaluation.utils INFO: copypaste: Acc@1=73.31400000000001
[09/22 17:09:05] lb.evaluation.utils INFO: copypaste: Acc@5=91.494
[09/22 17:09:05] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 73.31400, better than last best score 73.11800 @ iteration 134999.
[09/22 17:09:05] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/22 17:09:06] lb.utils.events INFO:  eta: 9:57:54  iteration: 144999/375342  consumed_samples: 148480000  total_loss: 3.678  time: 0.3407 s/iter  data_time: 0.2218 s/iter total_throughput: 3005.27 samples/s lr: 6.78e-04  
[09/22 17:09:38] lb.utils.events INFO:  eta: 9:59:44  iteration: 145099/375342  consumed_samples: 148582400  total_loss: 3.684  time: 0.3407 s/iter  data_time: 0.2155 s/iter total_throughput: 3005.34 samples/s lr: 6.78e-04  
[09/22 17:10:13] lb.utils.events INFO:  eta: 9:58:47  iteration: 145199/375342  consumed_samples: 148684800  total_loss: 3.687  time: 0.3407 s/iter  data_time: 0.2154 s/iter total_throughput: 3005.31 samples/s lr: 6.77e-04  
[09/22 17:10:48] lb.utils.events INFO:  eta: 9:58:31  iteration: 145299/375342  consumed_samples: 148787200  total_loss: 3.661  time: 0.3407 s/iter  data_time: 0.2143 s/iter total_throughput: 3005.26 samples/s lr: 6.77e-04  
[09/22 17:11:23] lb.utils.events INFO:  eta: 9:58:25  iteration: 145399/375342  consumed_samples: 148889600  total_loss: 3.653  time: 0.3407 s/iter  data_time: 0.2221 s/iter total_throughput: 3005.21 samples/s lr: 6.77e-04  
[09/22 17:11:58] lb.utils.events INFO:  eta: 9:57:56  iteration: 145499/375342  consumed_samples: 148992000  total_loss: 3.668  time: 0.3407 s/iter  data_time: 0.2281 s/iter total_throughput: 3005.15 samples/s lr: 6.76e-04  
[09/22 17:12:33] lb.utils.events INFO:  eta: 9:57:54  iteration: 145599/375342  consumed_samples: 149094400  total_loss: 3.66  time: 0.3408 s/iter  data_time: 0.2250 s/iter total_throughput: 3005.10 samples/s lr: 6.76e-04  
[09/22 17:13:07] lb.utils.events INFO:  eta: 9:57:12  iteration: 145699/375342  consumed_samples: 149196800  total_loss: 3.628  time: 0.3408 s/iter  data_time: 0.2222 s/iter total_throughput: 3005.07 samples/s lr: 6.75e-04  
[09/22 17:13:42] lb.utils.events INFO:  eta: 9:57:06  iteration: 145799/375342  consumed_samples: 149299200  total_loss: 3.646  time: 0.3408 s/iter  data_time: 0.2152 s/iter total_throughput: 3005.03 samples/s lr: 6.75e-04  
[09/22 17:14:17] lb.utils.events INFO:  eta: 9:56:41  iteration: 145899/375342  consumed_samples: 149401600  total_loss: 3.693  time: 0.3408 s/iter  data_time: 0.2202 s/iter total_throughput: 3004.98 samples/s lr: 6.75e-04  
[09/22 17:14:52] lb.utils.events INFO:  eta: 9:57:14  iteration: 145999/375342  consumed_samples: 149504000  total_loss: 3.689  time: 0.3408 s/iter  data_time: 0.2289 s/iter total_throughput: 3004.94 samples/s lr: 6.74e-04  
[09/22 17:15:26] lb.utils.events INFO:  eta: 9:53:55  iteration: 146099/375342  consumed_samples: 149606400  total_loss: 3.682  time: 0.3408 s/iter  data_time: 0.2211 s/iter total_throughput: 3004.91 samples/s lr: 6.74e-04  
[09/22 17:16:01] lb.utils.events INFO:  eta: 9:53:12  iteration: 146199/375342  consumed_samples: 149708800  total_loss: 3.69  time: 0.3408 s/iter  data_time: 0.2140 s/iter total_throughput: 3004.87 samples/s lr: 6.73e-04  
[09/22 17:16:36] lb.utils.events INFO:  eta: 9:53:32  iteration: 146299/375342  consumed_samples: 149811200  total_loss: 3.678  time: 0.3408 s/iter  data_time: 0.2275 s/iter total_throughput: 3004.83 samples/s lr: 6.73e-04  
[09/22 17:17:10] lb.utils.events INFO:  eta: 9:53:38  iteration: 146399/375342  consumed_samples: 149913600  total_loss: 3.65  time: 0.3408 s/iter  data_time: 0.2169 s/iter total_throughput: 3004.82 samples/s lr: 6.73e-04  
[09/22 17:17:45] lb.utils.events INFO:  eta: 9:53:22  iteration: 146499/375342  consumed_samples: 150016000  total_loss: 3.644  time: 0.3408 s/iter  data_time: 0.2278 s/iter total_throughput: 3004.79 samples/s lr: 6.72e-04  
[09/22 17:18:19] lb.utils.events INFO:  eta: 9:55:08  iteration: 146599/375342  consumed_samples: 150118400  total_loss: 3.648  time: 0.3408 s/iter  data_time: 0.2230 s/iter total_throughput: 3004.77 samples/s lr: 6.72e-04  
[09/22 17:18:54] lb.utils.events INFO:  eta: 9:55:45  iteration: 146699/375342  consumed_samples: 150220800  total_loss: 3.654  time: 0.3408 s/iter  data_time: 0.2152 s/iter total_throughput: 3004.75 samples/s lr: 6.71e-04  
[09/22 17:19:27] lb.utils.events INFO:  eta: 9:56:25  iteration: 146799/375342  consumed_samples: 150323200  total_loss: 3.666  time: 0.3408 s/iter  data_time: 0.2124 s/iter total_throughput: 3004.76 samples/s lr: 6.71e-04  
[09/22 17:20:02] lb.utils.events INFO:  eta: 9:56:36  iteration: 146899/375342  consumed_samples: 150425600  total_loss: 3.663  time: 0.3408 s/iter  data_time: 0.2086 s/iter total_throughput: 3004.72 samples/s lr: 6.71e-04  
[09/22 17:20:37] lb.utils.events INFO:  eta: 9:56:23  iteration: 146999/375342  consumed_samples: 150528000  total_loss: 3.661  time: 0.3408 s/iter  data_time: 0.2197 s/iter total_throughput: 3004.68 samples/s lr: 6.70e-04  
[09/22 17:21:12] lb.utils.events INFO:  eta: 9:56:08  iteration: 147099/375342  consumed_samples: 150630400  total_loss: 3.663  time: 0.3408 s/iter  data_time: 0.2195 s/iter total_throughput: 3004.65 samples/s lr: 6.70e-04  
[09/22 17:21:46] lb.utils.events INFO:  eta: 9:56:18  iteration: 147199/375342  consumed_samples: 150732800  total_loss: 3.646  time: 0.3408 s/iter  data_time: 0.2200 s/iter total_throughput: 3004.60 samples/s lr: 6.69e-04  
[09/22 17:22:21] lb.utils.events INFO:  eta: 9:56:11  iteration: 147299/375342  consumed_samples: 150835200  total_loss: 3.665  time: 0.3408 s/iter  data_time: 0.2154 s/iter total_throughput: 3004.57 samples/s lr: 6.69e-04  
[09/22 17:22:55] lb.utils.events INFO:  eta: 9:54:23  iteration: 147399/375342  consumed_samples: 150937600  total_loss: 3.684  time: 0.3408 s/iter  data_time: 0.2129 s/iter total_throughput: 3004.56 samples/s lr: 6.69e-04  
[09/22 17:23:30] lb.utils.events INFO:  eta: 9:54:09  iteration: 147499/375342  consumed_samples: 151040000  total_loss: 3.679  time: 0.3408 s/iter  data_time: 0.2131 s/iter total_throughput: 3004.54 samples/s lr: 6.68e-04  
[09/22 17:24:04] lb.utils.events INFO:  eta: 9:53:56  iteration: 147599/375342  consumed_samples: 151142400  total_loss: 3.679  time: 0.3408 s/iter  data_time: 0.2143 s/iter total_throughput: 3004.51 samples/s lr: 6.68e-04  
[09/22 17:24:39] lb.utils.events INFO:  eta: 9:52:51  iteration: 147699/375342  consumed_samples: 151244800  total_loss: 3.664  time: 0.3408 s/iter  data_time: 0.2197 s/iter total_throughput: 3004.47 samples/s lr: 6.68e-04  
[09/22 17:25:15] lb.utils.events INFO:  eta: 9:50:54  iteration: 147799/375342  consumed_samples: 151347200  total_loss: 3.628  time: 0.3408 s/iter  data_time: 0.2569 s/iter total_throughput: 3004.38 samples/s lr: 6.67e-04  
[09/22 17:25:49] lb.utils.events INFO:  eta: 9:49:14  iteration: 147899/375342  consumed_samples: 151449600  total_loss: 3.646  time: 0.3408 s/iter  data_time: 0.2226 s/iter total_throughput: 3004.35 samples/s lr: 6.67e-04  
[09/22 17:26:24] lb.utils.events INFO:  eta: 9:48:10  iteration: 147999/375342  consumed_samples: 151552000  total_loss: 3.671  time: 0.3408 s/iter  data_time: 0.2183 s/iter total_throughput: 3004.31 samples/s lr: 6.66e-04  
[09/22 17:26:59] lb.utils.events INFO:  eta: 9:48:37  iteration: 148099/375342  consumed_samples: 151654400  total_loss: 3.66  time: 0.3408 s/iter  data_time: 0.2137 s/iter total_throughput: 3004.27 samples/s lr: 6.66e-04  
[09/22 17:27:34] lb.utils.events INFO:  eta: 9:47:45  iteration: 148199/375342  consumed_samples: 151756800  total_loss: 3.654  time: 0.3409 s/iter  data_time: 0.2309 s/iter total_throughput: 3004.21 samples/s lr: 6.66e-04  
[09/22 17:28:09] lb.utils.events INFO:  eta: 9:47:24  iteration: 148299/375342  consumed_samples: 151859200  total_loss: 3.668  time: 0.3409 s/iter  data_time: 0.2263 s/iter total_throughput: 3004.17 samples/s lr: 6.65e-04  
[09/22 17:28:43] lb.utils.events INFO:  eta: 9:48:11  iteration: 148399/375342  consumed_samples: 151961600  total_loss: 3.676  time: 0.3409 s/iter  data_time: 0.2152 s/iter total_throughput: 3004.15 samples/s lr: 6.65e-04  
[09/22 17:29:18] lb.utils.events INFO:  eta: 9:49:29  iteration: 148499/375342  consumed_samples: 152064000  total_loss: 3.684  time: 0.3409 s/iter  data_time: 0.2172 s/iter total_throughput: 3004.12 samples/s lr: 6.64e-04  
[09/22 17:29:52] lb.utils.events INFO:  eta: 9:49:33  iteration: 148599/375342  consumed_samples: 152166400  total_loss: 3.684  time: 0.3409 s/iter  data_time: 0.2233 s/iter total_throughput: 3004.12 samples/s lr: 6.64e-04  
[09/22 17:30:27] lb.utils.events INFO:  eta: 9:49:51  iteration: 148699/375342  consumed_samples: 152268800  total_loss: 3.684  time: 0.3409 s/iter  data_time: 0.2156 s/iter total_throughput: 3004.07 samples/s lr: 6.64e-04  
[09/22 17:31:02] lb.utils.events INFO:  eta: 9:49:41  iteration: 148799/375342  consumed_samples: 152371200  total_loss: 3.668  time: 0.3409 s/iter  data_time: 0.2199 s/iter total_throughput: 3004.03 samples/s lr: 6.63e-04  
[09/22 17:31:37] lb.utils.events INFO:  eta: 9:49:31  iteration: 148899/375342  consumed_samples: 152473600  total_loss: 3.647  time: 0.3409 s/iter  data_time: 0.2383 s/iter total_throughput: 3003.95 samples/s lr: 6.63e-04  
[09/22 17:32:12] lb.utils.events INFO:  eta: 9:48:32  iteration: 148999/375342  consumed_samples: 152576000  total_loss: 3.66  time: 0.3409 s/iter  data_time: 0.2233 s/iter total_throughput: 3003.89 samples/s lr: 6.62e-04  
[09/22 17:32:47] lb.utils.events INFO:  eta: 9:47:23  iteration: 149099/375342  consumed_samples: 152678400  total_loss: 3.662  time: 0.3409 s/iter  data_time: 0.2226 s/iter total_throughput: 3003.84 samples/s lr: 6.62e-04  
[09/22 17:33:21] lb.utils.events INFO:  eta: 9:48:30  iteration: 149199/375342  consumed_samples: 152780800  total_loss: 3.668  time: 0.3409 s/iter  data_time: 0.2139 s/iter total_throughput: 3003.83 samples/s lr: 6.62e-04  
[09/22 17:33:56] lb.utils.events INFO:  eta: 9:48:11  iteration: 149299/375342  consumed_samples: 152883200  total_loss: 3.664  time: 0.3409 s/iter  data_time: 0.2245 s/iter total_throughput: 3003.80 samples/s lr: 6.61e-04  
[09/22 17:34:30] lb.utils.events INFO:  eta: 9:47:57  iteration: 149399/375342  consumed_samples: 152985600  total_loss: 3.668  time: 0.3409 s/iter  data_time: 0.2127 s/iter total_throughput: 3003.79 samples/s lr: 6.61e-04  
[09/22 17:35:05] lb.utils.events INFO:  eta: 9:47:32  iteration: 149499/375342  consumed_samples: 153088000  total_loss: 3.671  time: 0.3409 s/iter  data_time: 0.2327 s/iter total_throughput: 3003.73 samples/s lr: 6.60e-04  
[09/22 17:35:40] lb.utils.events INFO:  eta: 9:46:20  iteration: 149599/375342  consumed_samples: 153190400  total_loss: 3.66  time: 0.3409 s/iter  data_time: 0.2094 s/iter total_throughput: 3003.72 samples/s lr: 6.60e-04  
[09/22 17:36:14] lb.utils.events INFO:  eta: 9:45:06  iteration: 149699/375342  consumed_samples: 153292800  total_loss: 3.661  time: 0.3409 s/iter  data_time: 0.2204 s/iter total_throughput: 3003.68 samples/s lr: 6.60e-04  
[09/22 17:36:49] lb.utils.events INFO:  eta: 9:45:17  iteration: 149799/375342  consumed_samples: 153395200  total_loss: 3.667  time: 0.3409 s/iter  data_time: 0.2071 s/iter total_throughput: 3003.65 samples/s lr: 6.59e-04  
[09/22 17:37:23] lb.utils.events INFO:  eta: 9:45:15  iteration: 149899/375342  consumed_samples: 153497600  total_loss: 3.676  time: 0.3409 s/iter  data_time: 0.2135 s/iter total_throughput: 3003.65 samples/s lr: 6.59e-04  
[09/22 17:37:58] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0149999
[09/22 17:37:58] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/22 17:37:58] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/22 17:38:02] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0988 s/iter. Inference: 0.1584 s/iter. Eval: 0.0020 s/iter. Total: 0.2592 s/iter. ETA=0:00:09
[09/22 17:38:08] lb.evaluation.evaluator INFO: Inference done 29696/50000. Dataloading: 0.1424 s/iter. Inference: 0.1605 s/iter. Eval: 0.0020 s/iter. Total: 0.3049 s/iter. ETA=0:00:05
[09/22 17:38:13] lb.evaluation.evaluator INFO: Inference done 49152/50000. Dataloading: 0.1256 s/iter. Inference: 0.1612 s/iter. Eval: 0.0020 s/iter. Total: 0.2889 s/iter. ETA=0:00:00
[09/22 17:38:14] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/22 17:38:14] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.777679 (0.000256 s / iter per device, on 8 devices)
[09/22 17:38:14] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000143 s / iter per device, on 8 devices)
[09/22 17:38:14] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/22 17:38:14] lb.evaluation.utils INFO: copypaste: Acc@1=73.576
[09/22 17:38:14] lb.evaluation.utils INFO: copypaste: Acc@5=91.738
[09/22 17:38:14] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 73.57600, better than last best score 73.31400 @ iteration 144999.
[09/22 17:38:14] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/22 17:38:14] lb.utils.events INFO:  eta: 9:46:45  iteration: 149999/375342  consumed_samples: 153600000  total_loss: 3.667  time: 0.3409 s/iter  data_time: 0.2121 s/iter total_throughput: 3003.62 samples/s lr: 6.59e-04  
[09/22 17:38:47] lb.utils.events INFO:  eta: 9:49:47  iteration: 150099/375342  consumed_samples: 153702400  total_loss: 3.673  time: 0.3409 s/iter  data_time: 0.2506 s/iter total_throughput: 3003.74 samples/s lr: 6.58e-04  
[09/22 17:39:21] lb.utils.events INFO:  eta: 9:50:02  iteration: 150199/375342  consumed_samples: 153804800  total_loss: 3.68  time: 0.3409 s/iter  data_time: 0.2254 s/iter total_throughput: 3003.70 samples/s lr: 6.58e-04  
[09/22 17:39:56] lb.utils.events INFO:  eta: 9:48:10  iteration: 150299/375342  consumed_samples: 153907200  total_loss: 3.659  time: 0.3409 s/iter  data_time: 0.2228 s/iter total_throughput: 3003.64 samples/s lr: 6.57e-04  
[09/22 17:40:31] lb.utils.events INFO:  eta: 9:46:23  iteration: 150399/375342  consumed_samples: 154009600  total_loss: 3.653  time: 0.3409 s/iter  data_time: 0.2146 s/iter total_throughput: 3003.60 samples/s lr: 6.57e-04  
[09/22 17:41:06] lb.utils.events INFO:  eta: 9:45:06  iteration: 150499/375342  consumed_samples: 154112000  total_loss: 3.657  time: 0.3409 s/iter  data_time: 0.2101 s/iter total_throughput: 3003.58 samples/s lr: 6.57e-04  
[09/22 17:41:40] lb.utils.events INFO:  eta: 9:45:52  iteration: 150599/375342  consumed_samples: 154214400  total_loss: 3.655  time: 0.3409 s/iter  data_time: 0.2076 s/iter total_throughput: 3003.58 samples/s lr: 6.56e-04  
[09/22 17:42:15] lb.utils.events INFO:  eta: 9:45:52  iteration: 150699/375342  consumed_samples: 154316800  total_loss: 3.649  time: 0.3409 s/iter  data_time: 0.2231 s/iter total_throughput: 3003.51 samples/s lr: 6.56e-04  
[09/22 17:42:50] lb.utils.events INFO:  eta: 9:45:27  iteration: 150799/375342  consumed_samples: 154419200  total_loss: 3.648  time: 0.3409 s/iter  data_time: 0.2275 s/iter total_throughput: 3003.47 samples/s lr: 6.55e-04  
[09/22 17:43:24] lb.utils.events INFO:  eta: 9:43:54  iteration: 150899/375342  consumed_samples: 154521600  total_loss: 3.646  time: 0.3409 s/iter  data_time: 0.2191 s/iter total_throughput: 3003.44 samples/s lr: 6.55e-04  
[09/22 17:43:59] lb.utils.events INFO:  eta: 9:40:44  iteration: 150999/375342  consumed_samples: 154624000  total_loss: 3.652  time: 0.3409 s/iter  data_time: 0.2364 s/iter total_throughput: 3003.40 samples/s lr: 6.55e-04  
[09/22 17:44:33] lb.utils.events INFO:  eta: 9:37:18  iteration: 151099/375342  consumed_samples: 154726400  total_loss: 3.668  time: 0.3409 s/iter  data_time: 0.2130 s/iter total_throughput: 3003.39 samples/s lr: 6.54e-04  
[09/22 17:45:08] lb.utils.events INFO:  eta: 9:33:58  iteration: 151199/375342  consumed_samples: 154828800  total_loss: 3.66  time: 0.3410 s/iter  data_time: 0.2211 s/iter total_throughput: 3003.34 samples/s lr: 6.54e-04  
[09/22 17:45:43] lb.utils.events INFO:  eta: 9:35:07  iteration: 151299/375342  consumed_samples: 154931200  total_loss: 3.643  time: 0.3410 s/iter  data_time: 0.2184 s/iter total_throughput: 3003.30 samples/s lr: 6.53e-04  
[09/22 17:46:18] lb.utils.events INFO:  eta: 9:37:02  iteration: 151399/375342  consumed_samples: 155033600  total_loss: 3.659  time: 0.3410 s/iter  data_time: 0.2397 s/iter total_throughput: 3003.28 samples/s lr: 6.53e-04  
[09/22 17:46:52] lb.utils.events INFO:  eta: 9:37:00  iteration: 151499/375342  consumed_samples: 155136000  total_loss: 3.649  time: 0.3410 s/iter  data_time: 0.2288 s/iter total_throughput: 3003.25 samples/s lr: 6.53e-04  
[09/22 17:47:27] lb.utils.events INFO:  eta: 9:36:45  iteration: 151599/375342  consumed_samples: 155238400  total_loss: 3.639  time: 0.3410 s/iter  data_time: 0.2187 s/iter total_throughput: 3003.23 samples/s lr: 6.52e-04  
[09/22 17:48:01] lb.utils.events INFO:  eta: 9:38:10  iteration: 151699/375342  consumed_samples: 155340800  total_loss: 3.621  time: 0.3410 s/iter  data_time: 0.2205 s/iter total_throughput: 3003.21 samples/s lr: 6.52e-04  
[09/22 17:48:35] lb.utils.events INFO:  eta: 9:38:10  iteration: 151799/375342  consumed_samples: 155443200  total_loss: 3.618  time: 0.3410 s/iter  data_time: 0.2189 s/iter total_throughput: 3003.22 samples/s lr: 6.51e-04  
[09/22 17:49:09] lb.utils.events INFO:  eta: 9:39:44  iteration: 151899/375342  consumed_samples: 155545600  total_loss: 3.649  time: 0.3410 s/iter  data_time: 0.2114 s/iter total_throughput: 3003.23 samples/s lr: 6.51e-04  
[09/22 17:49:44] lb.utils.events INFO:  eta: 9:40:36  iteration: 151999/375342  consumed_samples: 155648000  total_loss: 3.664  time: 0.3410 s/iter  data_time: 0.2207 s/iter total_throughput: 3003.20 samples/s lr: 6.51e-04  
[09/22 17:50:18] lb.utils.events INFO:  eta: 9:41:29  iteration: 152099/375342  consumed_samples: 155750400  total_loss: 3.649  time: 0.3410 s/iter  data_time: 0.2198 s/iter total_throughput: 3003.19 samples/s lr: 6.50e-04  
[09/22 17:50:52] lb.utils.events INFO:  eta: 9:42:24  iteration: 152199/375342  consumed_samples: 155852800  total_loss: 3.649  time: 0.3410 s/iter  data_time: 0.2090 s/iter total_throughput: 3003.17 samples/s lr: 6.50e-04  
[09/22 17:51:27] lb.utils.events INFO:  eta: 9:41:57  iteration: 152299/375342  consumed_samples: 155955200  total_loss: 3.662  time: 0.3410 s/iter  data_time: 0.2147 s/iter total_throughput: 3003.14 samples/s lr: 6.49e-04  
[09/22 17:52:01] lb.utils.events INFO:  eta: 9:41:41  iteration: 152399/375342  consumed_samples: 156057600  total_loss: 3.655  time: 0.3410 s/iter  data_time: 0.2256 s/iter total_throughput: 3003.13 samples/s lr: 6.49e-04  
[09/22 17:52:36] lb.utils.events INFO:  eta: 9:42:34  iteration: 152499/375342  consumed_samples: 156160000  total_loss: 3.658  time: 0.3410 s/iter  data_time: 0.2256 s/iter total_throughput: 3003.12 samples/s lr: 6.49e-04  
[09/22 17:53:10] lb.utils.events INFO:  eta: 9:41:46  iteration: 152599/375342  consumed_samples: 156262400  total_loss: 3.68  time: 0.3410 s/iter  data_time: 0.2230 s/iter total_throughput: 3003.11 samples/s lr: 6.48e-04  
[09/22 17:53:44] lb.utils.events INFO:  eta: 9:41:22  iteration: 152699/375342  consumed_samples: 156364800  total_loss: 3.657  time: 0.3410 s/iter  data_time: 0.2154 s/iter total_throughput: 3003.10 samples/s lr: 6.48e-04  
[09/22 17:54:18] lb.utils.events INFO:  eta: 9:40:44  iteration: 152799/375342  consumed_samples: 156467200  total_loss: 3.641  time: 0.3410 s/iter  data_time: 0.2155 s/iter total_throughput: 3003.13 samples/s lr: 6.47e-04  
[09/22 17:54:52] lb.utils.events INFO:  eta: 9:41:06  iteration: 152899/375342  consumed_samples: 156569600  total_loss: 3.611  time: 0.3410 s/iter  data_time: 0.2118 s/iter total_throughput: 3003.13 samples/s lr: 6.47e-04  
[09/22 17:55:26] lb.utils.events INFO:  eta: 9:40:10  iteration: 152999/375342  consumed_samples: 156672000  total_loss: 3.638  time: 0.3410 s/iter  data_time: 0.2171 s/iter total_throughput: 3003.11 samples/s lr: 6.47e-04  
[09/22 17:56:01] lb.utils.events INFO:  eta: 9:39:19  iteration: 153099/375342  consumed_samples: 156774400  total_loss: 3.655  time: 0.3410 s/iter  data_time: 0.2233 s/iter total_throughput: 3003.09 samples/s lr: 6.46e-04  
[09/22 17:56:35] lb.utils.events INFO:  eta: 9:38:29  iteration: 153199/375342  consumed_samples: 156876800  total_loss: 3.655  time: 0.3410 s/iter  data_time: 0.2127 s/iter total_throughput: 3003.08 samples/s lr: 6.46e-04  
[09/22 17:57:09] lb.utils.events INFO:  eta: 9:38:08  iteration: 153299/375342  consumed_samples: 156979200  total_loss: 3.662  time: 0.3410 s/iter  data_time: 0.2139 s/iter total_throughput: 3003.08 samples/s lr: 6.45e-04  
[09/22 17:57:43] lb.utils.events INFO:  eta: 9:37:06  iteration: 153399/375342  consumed_samples: 157081600  total_loss: 3.661  time: 0.3410 s/iter  data_time: 0.2067 s/iter total_throughput: 3003.08 samples/s lr: 6.45e-04  
[09/22 17:58:17] lb.utils.events INFO:  eta: 9:36:31  iteration: 153499/375342  consumed_samples: 157184000  total_loss: 3.664  time: 0.3410 s/iter  data_time: 0.2086 s/iter total_throughput: 3003.09 samples/s lr: 6.45e-04  
[09/22 17:58:52] lb.utils.events INFO:  eta: 9:36:16  iteration: 153599/375342  consumed_samples: 157286400  total_loss: 3.676  time: 0.3410 s/iter  data_time: 0.2140 s/iter total_throughput: 3003.08 samples/s lr: 6.44e-04  
[09/22 17:59:26] lb.utils.events INFO:  eta: 9:34:30  iteration: 153699/375342  consumed_samples: 157388800  total_loss: 3.682  time: 0.3410 s/iter  data_time: 0.2081 s/iter total_throughput: 3003.05 samples/s lr: 6.44e-04  
[09/22 18:00:00] lb.utils.events INFO:  eta: 9:34:23  iteration: 153799/375342  consumed_samples: 157491200  total_loss: 3.665  time: 0.3410 s/iter  data_time: 0.2147 s/iter total_throughput: 3003.06 samples/s lr: 6.43e-04  
[09/22 18:00:34] lb.utils.events INFO:  eta: 9:34:01  iteration: 153899/375342  consumed_samples: 157593600  total_loss: 3.628  time: 0.3410 s/iter  data_time: 0.2029 s/iter total_throughput: 3003.07 samples/s lr: 6.43e-04  
[09/22 18:01:08] lb.utils.events INFO:  eta: 9:32:53  iteration: 153999/375342  consumed_samples: 157696000  total_loss: 3.634  time: 0.3410 s/iter  data_time: 0.2134 s/iter total_throughput: 3003.07 samples/s lr: 6.43e-04  
[09/22 18:01:43] lb.utils.events INFO:  eta: 9:32:47  iteration: 154099/375342  consumed_samples: 157798400  total_loss: 3.653  time: 0.3410 s/iter  data_time: 0.2380 s/iter total_throughput: 3003.03 samples/s lr: 6.42e-04  
[09/22 18:02:18] lb.utils.events INFO:  eta: 9:33:11  iteration: 154199/375342  consumed_samples: 157900800  total_loss: 3.652  time: 0.3410 s/iter  data_time: 0.2477 s/iter total_throughput: 3002.96 samples/s lr: 6.42e-04  
[09/22 18:02:53] lb.utils.events INFO:  eta: 9:31:25  iteration: 154299/375342  consumed_samples: 158003200  total_loss: 3.637  time: 0.3410 s/iter  data_time: 0.2350 s/iter total_throughput: 3002.90 samples/s lr: 6.41e-04  
[09/22 18:03:28] lb.utils.events INFO:  eta: 9:31:22  iteration: 154399/375342  consumed_samples: 158105600  total_loss: 3.637  time: 0.3410 s/iter  data_time: 0.2217 s/iter total_throughput: 3002.87 samples/s lr: 6.41e-04  
[09/22 18:04:03] lb.utils.events INFO:  eta: 9:29:25  iteration: 154499/375342  consumed_samples: 158208000  total_loss: 3.631  time: 0.3410 s/iter  data_time: 0.2345 s/iter total_throughput: 3002.81 samples/s lr: 6.41e-04  
[09/22 18:04:39] lb.utils.events INFO:  eta: 9:28:18  iteration: 154599/375342  consumed_samples: 158310400  total_loss: 3.625  time: 0.3410 s/iter  data_time: 0.2247 s/iter total_throughput: 3002.74 samples/s lr: 6.40e-04  
[09/22 18:05:14] lb.utils.events INFO:  eta: 9:28:54  iteration: 154699/375342  consumed_samples: 158412800  total_loss: 3.628  time: 0.3410 s/iter  data_time: 0.2304 s/iter total_throughput: 3002.67 samples/s lr: 6.40e-04  
[09/22 18:05:49] lb.utils.events INFO:  eta: 9:26:57  iteration: 154799/375342  consumed_samples: 158515200  total_loss: 3.652  time: 0.3410 s/iter  data_time: 0.2251 s/iter total_throughput: 3002.58 samples/s lr: 6.39e-04  
[09/22 18:06:25] lb.utils.events INFO:  eta: 9:26:41  iteration: 154899/375342  consumed_samples: 158617600  total_loss: 3.655  time: 0.3410 s/iter  data_time: 0.2241 s/iter total_throughput: 3002.52 samples/s lr: 6.39e-04  
[09/22 18:07:00] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0154999
[09/22 18:07:01] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/22 18:07:01] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/22 18:07:05] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.1028 s/iter. Inference: 0.1605 s/iter. Eval: 0.0020 s/iter. Total: 0.2653 s/iter. ETA=0:00:09
[09/22 18:07:10] lb.evaluation.evaluator INFO: Inference done 28672/50000. Dataloading: 0.0948 s/iter. Inference: 0.1927 s/iter. Eval: 0.0021 s/iter. Total: 0.2896 s/iter. ETA=0:00:05
[09/22 18:07:15] lb.evaluation.evaluator INFO: Inference done 46080/50000. Dataloading: 0.0932 s/iter. Inference: 0.1980 s/iter. Eval: 0.0021 s/iter. Total: 0.2933 s/iter. ETA=0:00:00
[09/22 18:07:16] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/22 18:07:16] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.684084 (0.000254 s / iter per device, on 8 devices)
[09/22 18:07:16] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:08 (0.000174 s / iter per device, on 8 devices)
[09/22 18:07:16] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/22 18:07:16] lb.evaluation.utils INFO: copypaste: Acc@1=73.75399999999999
[09/22 18:07:16] lb.evaluation.utils INFO: copypaste: Acc@5=91.874
[09/22 18:07:16] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 73.75400, better than last best score 73.57600 @ iteration 149999.
[09/22 18:07:16] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/22 18:07:17] lb.utils.events INFO:  eta: 9:26:53  iteration: 154999/375342  consumed_samples: 158720000  total_loss: 3.657  time: 0.3411 s/iter  data_time: 0.2299 s/iter total_throughput: 3002.46 samples/s lr: 6.39e-04  
[09/22 18:07:50] lb.utils.events INFO:  eta: 9:27:30  iteration: 155099/375342  consumed_samples: 158822400  total_loss: 3.645  time: 0.3410 s/iter  data_time: 0.2265 s/iter total_throughput: 3002.50 samples/s lr: 6.38e-04  
[09/22 18:08:25] lb.utils.events INFO:  eta: 9:27:28  iteration: 155199/375342  consumed_samples: 158924800  total_loss: 3.604  time: 0.3411 s/iter  data_time: 0.2217 s/iter total_throughput: 3002.46 samples/s lr: 6.38e-04  
[09/22 18:09:01] lb.utils.events INFO:  eta: 9:27:03  iteration: 155299/375342  consumed_samples: 159027200  total_loss: 3.621  time: 0.3411 s/iter  data_time: 0.2328 s/iter total_throughput: 3002.37 samples/s lr: 6.37e-04  
[09/22 18:09:36] lb.utils.events INFO:  eta: 9:26:53  iteration: 155399/375342  consumed_samples: 159129600  total_loss: 3.655  time: 0.3411 s/iter  data_time: 0.2340 s/iter total_throughput: 3002.28 samples/s lr: 6.37e-04  
[09/22 18:10:11] lb.utils.events INFO:  eta: 9:27:16  iteration: 155499/375342  consumed_samples: 159232000  total_loss: 3.651  time: 0.3411 s/iter  data_time: 0.2207 s/iter total_throughput: 3002.22 samples/s lr: 6.37e-04  
[09/22 18:10:47] lb.utils.events INFO:  eta: 9:27:02  iteration: 155599/375342  consumed_samples: 159334400  total_loss: 3.634  time: 0.3411 s/iter  data_time: 0.2343 s/iter total_throughput: 3002.15 samples/s lr: 6.36e-04  
[09/22 18:11:22] lb.utils.events INFO:  eta: 9:25:59  iteration: 155699/375342  consumed_samples: 159436800  total_loss: 3.638  time: 0.3411 s/iter  data_time: 0.2266 s/iter total_throughput: 3002.09 samples/s lr: 6.36e-04  
[09/22 18:11:57] lb.utils.events INFO:  eta: 9:26:20  iteration: 155799/375342  consumed_samples: 159539200  total_loss: 3.634  time: 0.3411 s/iter  data_time: 0.2346 s/iter total_throughput: 3002.03 samples/s lr: 6.35e-04  
[09/22 18:12:32] lb.utils.events INFO:  eta: 9:24:04  iteration: 155899/375342  consumed_samples: 159641600  total_loss: 3.633  time: 0.3411 s/iter  data_time: 0.2293 s/iter total_throughput: 3001.97 samples/s lr: 6.35e-04  
[09/22 18:13:07] lb.utils.events INFO:  eta: 9:23:49  iteration: 155999/375342  consumed_samples: 159744000  total_loss: 3.647  time: 0.3411 s/iter  data_time: 0.2180 s/iter total_throughput: 3001.92 samples/s lr: 6.35e-04  
[09/22 18:13:42] lb.utils.events INFO:  eta: 9:21:50  iteration: 156099/375342  consumed_samples: 159846400  total_loss: 3.65  time: 0.3411 s/iter  data_time: 0.2240 s/iter total_throughput: 3001.88 samples/s lr: 6.34e-04  
[09/22 18:14:17] lb.utils.events INFO:  eta: 9:21:49  iteration: 156199/375342  consumed_samples: 159948800  total_loss: 3.646  time: 0.3411 s/iter  data_time: 0.2254 s/iter total_throughput: 3001.83 samples/s lr: 6.34e-04  
[09/22 18:14:52] lb.utils.events INFO:  eta: 9:24:36  iteration: 156299/375342  consumed_samples: 160051200  total_loss: 3.654  time: 0.3411 s/iter  data_time: 0.2316 s/iter total_throughput: 3001.79 samples/s lr: 6.33e-04  
[09/22 18:15:27] lb.utils.events INFO:  eta: 9:24:54  iteration: 156399/375342  consumed_samples: 160153600  total_loss: 3.648  time: 0.3411 s/iter  data_time: 0.2145 s/iter total_throughput: 3001.75 samples/s lr: 6.33e-04  
[09/22 18:16:02] lb.utils.events INFO:  eta: 9:25:06  iteration: 156499/375342  consumed_samples: 160256000  total_loss: 3.639  time: 0.3411 s/iter  data_time: 0.2217 s/iter total_throughput: 3001.71 samples/s lr: 6.33e-04  
[09/22 18:16:36] lb.utils.events INFO:  eta: 9:24:48  iteration: 156599/375342  consumed_samples: 160358400  total_loss: 3.62  time: 0.3411 s/iter  data_time: 0.2216 s/iter total_throughput: 3001.67 samples/s lr: 6.32e-04  
[09/22 18:17:11] lb.utils.events INFO:  eta: 9:25:16  iteration: 156699/375342  consumed_samples: 160460800  total_loss: 3.613  time: 0.3411 s/iter  data_time: 0.2136 s/iter total_throughput: 3001.62 samples/s lr: 6.32e-04  
[09/22 18:17:46] lb.utils.events INFO:  eta: 9:25:15  iteration: 156799/375342  consumed_samples: 160563200  total_loss: 3.622  time: 0.3412 s/iter  data_time: 0.2247 s/iter total_throughput: 3001.57 samples/s lr: 6.31e-04  
[09/22 18:18:21] lb.utils.events INFO:  eta: 9:26:00  iteration: 156899/375342  consumed_samples: 160665600  total_loss: 3.637  time: 0.3412 s/iter  data_time: 0.2218 s/iter total_throughput: 3001.55 samples/s lr: 6.31e-04  
[09/22 18:18:56] lb.utils.events INFO:  eta: 9:25:11  iteration: 156999/375342  consumed_samples: 160768000  total_loss: 3.622  time: 0.3412 s/iter  data_time: 0.2165 s/iter total_throughput: 3001.51 samples/s lr: 6.31e-04  
[09/22 18:19:31] lb.utils.events INFO:  eta: 9:23:57  iteration: 157099/375342  consumed_samples: 160870400  total_loss: 3.633  time: 0.3412 s/iter  data_time: 0.2334 s/iter total_throughput: 3001.45 samples/s lr: 6.30e-04  
[09/22 18:20:06] lb.utils.events INFO:  eta: 9:21:58  iteration: 157199/375342  consumed_samples: 160972800  total_loss: 3.646  time: 0.3412 s/iter  data_time: 0.2202 s/iter total_throughput: 3001.39 samples/s lr: 6.30e-04  
[09/22 18:20:41] lb.utils.events INFO:  eta: 9:21:41  iteration: 157299/375342  consumed_samples: 161075200  total_loss: 3.625  time: 0.3412 s/iter  data_time: 0.2254 s/iter total_throughput: 3001.36 samples/s lr: 6.29e-04  
[09/22 18:21:16] lb.utils.events INFO:  eta: 9:20:46  iteration: 157399/375342  consumed_samples: 161177600  total_loss: 3.627  time: 0.3412 s/iter  data_time: 0.2121 s/iter total_throughput: 3001.31 samples/s lr: 6.29e-04  
[09/22 18:21:51] lb.utils.events INFO:  eta: 9:20:18  iteration: 157499/375342  consumed_samples: 161280000  total_loss: 3.66  time: 0.3412 s/iter  data_time: 0.2165 s/iter total_throughput: 3001.28 samples/s lr: 6.29e-04  
[09/22 18:22:26] lb.utils.events INFO:  eta: 9:20:08  iteration: 157599/375342  consumed_samples: 161382400  total_loss: 3.653  time: 0.3412 s/iter  data_time: 0.2134 s/iter total_throughput: 3001.22 samples/s lr: 6.28e-04  
[09/22 18:23:01] lb.utils.events INFO:  eta: 9:18:27  iteration: 157699/375342  consumed_samples: 161484800  total_loss: 3.632  time: 0.3412 s/iter  data_time: 0.2206 s/iter total_throughput: 3001.16 samples/s lr: 6.28e-04  
[09/22 18:23:36] lb.utils.events INFO:  eta: 9:17:30  iteration: 157799/375342  consumed_samples: 161587200  total_loss: 3.646  time: 0.3412 s/iter  data_time: 0.2160 s/iter total_throughput: 3001.10 samples/s lr: 6.27e-04  
[09/22 18:24:11] lb.utils.events INFO:  eta: 9:17:58  iteration: 157899/375342  consumed_samples: 161689600  total_loss: 3.646  time: 0.3412 s/iter  data_time: 0.2278 s/iter total_throughput: 3001.07 samples/s lr: 6.27e-04  
[09/22 18:24:46] lb.utils.events INFO:  eta: 9:18:27  iteration: 157999/375342  consumed_samples: 161792000  total_loss: 3.629  time: 0.3412 s/iter  data_time: 0.2319 s/iter total_throughput: 3001.01 samples/s lr: 6.27e-04  
[09/22 18:25:21] lb.utils.events INFO:  eta: 9:21:00  iteration: 158099/375342  consumed_samples: 161894400  total_loss: 3.626  time: 0.3412 s/iter  data_time: 0.2331 s/iter total_throughput: 3000.98 samples/s lr: 6.26e-04  
[09/22 18:25:55] lb.utils.events INFO:  eta: 9:21:32  iteration: 158199/375342  consumed_samples: 161996800  total_loss: 3.633  time: 0.3412 s/iter  data_time: 0.2195 s/iter total_throughput: 3000.95 samples/s lr: 6.26e-04  
[09/22 18:26:30] lb.utils.events INFO:  eta: 9:20:18  iteration: 158299/375342  consumed_samples: 162099200  total_loss: 3.627  time: 0.3412 s/iter  data_time: 0.2265 s/iter total_throughput: 3000.90 samples/s lr: 6.25e-04  
[09/22 18:27:05] lb.utils.events INFO:  eta: 9:20:51  iteration: 158399/375342  consumed_samples: 162201600  total_loss: 3.608  time: 0.3412 s/iter  data_time: 0.2150 s/iter total_throughput: 3000.87 samples/s lr: 6.25e-04  
[09/22 18:27:40] lb.utils.events INFO:  eta: 9:20:57  iteration: 158499/375342  consumed_samples: 162304000  total_loss: 3.623  time: 0.3412 s/iter  data_time: 0.2194 s/iter total_throughput: 3000.85 samples/s lr: 6.25e-04  
[09/22 18:28:15] lb.utils.events INFO:  eta: 9:20:43  iteration: 158599/375342  consumed_samples: 162406400  total_loss: 3.634  time: 0.3412 s/iter  data_time: 0.2249 s/iter total_throughput: 3000.80 samples/s lr: 6.24e-04  
[09/22 18:28:50] lb.utils.events INFO:  eta: 9:21:02  iteration: 158699/375342  consumed_samples: 162508800  total_loss: 3.619  time: 0.3412 s/iter  data_time: 0.2184 s/iter total_throughput: 3000.74 samples/s lr: 6.24e-04  
[09/22 18:29:25] lb.utils.events INFO:  eta: 9:20:38  iteration: 158799/375342  consumed_samples: 162611200  total_loss: 3.646  time: 0.3413 s/iter  data_time: 0.2334 s/iter total_throughput: 3000.68 samples/s lr: 6.23e-04  
[09/22 18:30:00] lb.utils.events INFO:  eta: 9:19:58  iteration: 158899/375342  consumed_samples: 162713600  total_loss: 3.639  time: 0.3413 s/iter  data_time: 0.2206 s/iter total_throughput: 3000.61 samples/s lr: 6.23e-04  
[09/22 18:30:35] lb.utils.events INFO:  eta: 9:19:47  iteration: 158999/375342  consumed_samples: 162816000  total_loss: 3.615  time: 0.3413 s/iter  data_time: 0.2202 s/iter total_throughput: 3000.58 samples/s lr: 6.23e-04  
[09/22 18:31:10] lb.utils.events INFO:  eta: 9:17:34  iteration: 159099/375342  consumed_samples: 162918400  total_loss: 3.606  time: 0.3413 s/iter  data_time: 0.2261 s/iter total_throughput: 3000.53 samples/s lr: 6.22e-04  
[09/22 18:31:46] lb.utils.events INFO:  eta: 9:17:09  iteration: 159199/375342  consumed_samples: 163020800  total_loss: 3.606  time: 0.3413 s/iter  data_time: 0.2261 s/iter total_throughput: 3000.46 samples/s lr: 6.22e-04  
[09/22 18:32:21] lb.utils.events INFO:  eta: 9:18:13  iteration: 159299/375342  consumed_samples: 163123200  total_loss: 3.636  time: 0.3413 s/iter  data_time: 0.2219 s/iter total_throughput: 3000.40 samples/s lr: 6.21e-04  
[09/22 18:32:56] lb.utils.events INFO:  eta: 9:17:23  iteration: 159399/375342  consumed_samples: 163225600  total_loss: 3.643  time: 0.3413 s/iter  data_time: 0.2246 s/iter total_throughput: 3000.33 samples/s lr: 6.21e-04  
[09/22 18:33:31] lb.utils.events INFO:  eta: 9:16:30  iteration: 159499/375342  consumed_samples: 163328000  total_loss: 3.641  time: 0.3413 s/iter  data_time: 0.2195 s/iter total_throughput: 3000.28 samples/s lr: 6.21e-04  
[09/22 18:34:06] lb.utils.events INFO:  eta: 9:17:31  iteration: 159599/375342  consumed_samples: 163430400  total_loss: 3.637  time: 0.3413 s/iter  data_time: 0.2173 s/iter total_throughput: 3000.25 samples/s lr: 6.20e-04  
[09/22 18:34:41] lb.utils.events INFO:  eta: 9:17:11  iteration: 159699/375342  consumed_samples: 163532800  total_loss: 3.629  time: 0.3413 s/iter  data_time: 0.2215 s/iter total_throughput: 3000.22 samples/s lr: 6.20e-04  
[09/22 18:35:15] lb.utils.events INFO:  eta: 9:17:50  iteration: 159799/375342  consumed_samples: 163635200  total_loss: 3.62  time: 0.3413 s/iter  data_time: 0.2147 s/iter total_throughput: 3000.21 samples/s lr: 6.19e-04  
[09/22 18:35:50] lb.utils.events INFO:  eta: 9:18:00  iteration: 159899/375342  consumed_samples: 163737600  total_loss: 3.608  time: 0.3413 s/iter  data_time: 0.2130 s/iter total_throughput: 3000.18 samples/s lr: 6.19e-04  
[09/22 18:36:25] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0159999
[09/22 18:36:25] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/22 18:36:25] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/22 18:36:30] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.1088 s/iter. Inference: 0.1598 s/iter. Eval: 0.0020 s/iter. Total: 0.2707 s/iter. ETA=0:00:10
[09/22 18:36:35] lb.evaluation.evaluator INFO: Inference done 28672/50000. Dataloading: 0.1091 s/iter. Inference: 0.1788 s/iter. Eval: 0.0020 s/iter. Total: 0.2899 s/iter. ETA=0:00:05
[09/22 18:36:40] lb.evaluation.evaluator INFO: Inference done 47104/50000. Dataloading: 0.1193 s/iter. Inference: 0.1717 s/iter. Eval: 0.0020 s/iter. Total: 0.2930 s/iter. ETA=0:00:00
[09/22 18:36:41] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/22 18:36:41] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.589060 (0.000252 s / iter per device, on 8 devices)
[09/22 18:36:41] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000151 s / iter per device, on 8 devices)
[09/22 18:36:41] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/22 18:36:41] lb.evaluation.utils INFO: copypaste: Acc@1=73.536
[09/22 18:36:41] lb.evaluation.utils INFO: copypaste: Acc@5=91.808
[09/22 18:36:41] lb.engine.hooks INFO: Not saving as latest eval score for Acc@1 is 73.53600, not better than best score 73.75400 @ iteration 154999.
[09/22 18:36:41] lb.utils.events INFO:  eta: 9:17:45  iteration: 159999/375342  consumed_samples: 163840000  total_loss: 3.622  time: 0.3413 s/iter  data_time: 0.2196 s/iter total_throughput: 3000.13 samples/s lr: 6.19e-04  
[09/22 18:37:13] lb.utils.events INFO:  eta: 9:19:28  iteration: 160099/375342  consumed_samples: 163942400  total_loss: 3.654  time: 0.3413 s/iter  data_time: 0.2239 s/iter total_throughput: 3000.19 samples/s lr: 6.18e-04  
[09/22 18:37:48] lb.utils.events INFO:  eta: 9:21:17  iteration: 160199/375342  consumed_samples: 164044800  total_loss: 3.646  time: 0.3413 s/iter  data_time: 0.2240 s/iter total_throughput: 3000.17 samples/s lr: 6.18e-04  
[09/22 18:38:23] lb.utils.events INFO:  eta: 9:20:56  iteration: 160299/375342  consumed_samples: 164147200  total_loss: 3.625  time: 0.3413 s/iter  data_time: 0.2368 s/iter total_throughput: 3000.13 samples/s lr: 6.17e-04  
[09/22 18:38:58] lb.utils.events INFO:  eta: 9:19:58  iteration: 160399/375342  consumed_samples: 164249600  total_loss: 3.624  time: 0.3413 s/iter  data_time: 0.2181 s/iter total_throughput: 3000.08 samples/s lr: 6.17e-04  
[09/22 18:39:33] lb.utils.events INFO:  eta: 9:19:33  iteration: 160499/375342  consumed_samples: 164352000  total_loss: 3.608  time: 0.3413 s/iter  data_time: 0.2352 s/iter total_throughput: 3000.03 samples/s lr: 6.17e-04  
[09/22 18:40:09] lb.utils.events INFO:  eta: 9:17:46  iteration: 160599/375342  consumed_samples: 164454400  total_loss: 3.636  time: 0.3413 s/iter  data_time: 0.2245 s/iter total_throughput: 2999.95 samples/s lr: 6.16e-04  
[09/22 18:40:44] lb.utils.events INFO:  eta: 9:17:39  iteration: 160699/375342  consumed_samples: 164556800  total_loss: 3.66  time: 0.3413 s/iter  data_time: 0.2192 s/iter total_throughput: 2999.91 samples/s lr: 6.16e-04  
[09/22 18:41:19] lb.utils.events INFO:  eta: 9:15:56  iteration: 160799/375342  consumed_samples: 164659200  total_loss: 3.621  time: 0.3414 s/iter  data_time: 0.2254 s/iter total_throughput: 2999.82 samples/s lr: 6.15e-04  
[09/22 18:41:55] lb.utils.events INFO:  eta: 9:15:04  iteration: 160899/375342  consumed_samples: 164761600  total_loss: 3.614  time: 0.3414 s/iter  data_time: 0.2353 s/iter total_throughput: 2999.76 samples/s lr: 6.15e-04  
[09/22 18:42:29] lb.utils.events INFO:  eta: 9:15:19  iteration: 160999/375342  consumed_samples: 164864000  total_loss: 3.619  time: 0.3414 s/iter  data_time: 0.2218 s/iter total_throughput: 2999.72 samples/s lr: 6.15e-04  
[09/22 18:43:05] lb.utils.events INFO:  eta: 9:13:48  iteration: 161099/375342  consumed_samples: 164966400  total_loss: 3.63  time: 0.3414 s/iter  data_time: 0.2157 s/iter total_throughput: 2999.66 samples/s lr: 6.14e-04  
[09/22 18:43:40] lb.utils.events INFO:  eta: 9:13:14  iteration: 161199/375342  consumed_samples: 165068800  total_loss: 3.634  time: 0.3414 s/iter  data_time: 0.2283 s/iter total_throughput: 2999.60 samples/s lr: 6.14e-04  
[09/22 18:44:15] lb.utils.events INFO:  eta: 9:13:17  iteration: 161299/375342  consumed_samples: 165171200  total_loss: 3.636  time: 0.3414 s/iter  data_time: 0.2096 s/iter total_throughput: 2999.56 samples/s lr: 6.13e-04  
[09/22 18:44:49] lb.utils.events INFO:  eta: 9:12:57  iteration: 161399/375342  consumed_samples: 165273600  total_loss: 3.624  time: 0.3414 s/iter  data_time: 0.2165 s/iter total_throughput: 2999.53 samples/s lr: 6.13e-04  
[09/22 18:45:24] lb.utils.events INFO:  eta: 9:13:38  iteration: 161499/375342  consumed_samples: 165376000  total_loss: 3.612  time: 0.3414 s/iter  data_time: 0.2233 s/iter total_throughput: 2999.48 samples/s lr: 6.13e-04  
[09/22 18:46:00] lb.utils.events INFO:  eta: 9:13:45  iteration: 161599/375342  consumed_samples: 165478400  total_loss: 3.625  time: 0.3414 s/iter  data_time: 0.2232 s/iter total_throughput: 2999.43 samples/s lr: 6.12e-04  
[09/22 18:46:35] lb.utils.events INFO:  eta: 9:14:02  iteration: 161699/375342  consumed_samples: 165580800  total_loss: 3.626  time: 0.3414 s/iter  data_time: 0.2193 s/iter total_throughput: 2999.39 samples/s lr: 6.12e-04  
[09/22 18:47:09] lb.utils.events INFO:  eta: 9:15:45  iteration: 161799/375342  consumed_samples: 165683200  total_loss: 3.626  time: 0.3414 s/iter  data_time: 0.2196 s/iter total_throughput: 2999.35 samples/s lr: 6.11e-04  
[09/22 18:47:44] lb.utils.events INFO:  eta: 9:16:05  iteration: 161899/375342  consumed_samples: 165785600  total_loss: 3.613  time: 0.3414 s/iter  data_time: 0.2178 s/iter total_throughput: 2999.31 samples/s lr: 6.11e-04  
[09/22 18:48:19] lb.utils.events INFO:  eta: 9:16:16  iteration: 161999/375342  consumed_samples: 165888000  total_loss: 3.606  time: 0.3414 s/iter  data_time: 0.2260 s/iter total_throughput: 2999.30 samples/s lr: 6.11e-04  
[09/22 18:48:53] lb.utils.events INFO:  eta: 9:16:13  iteration: 162099/375342  consumed_samples: 165990400  total_loss: 3.625  time: 0.3414 s/iter  data_time: 0.2170 s/iter total_throughput: 2999.28 samples/s lr: 6.10e-04  
[09/22 18:49:28] lb.utils.events INFO:  eta: 9:15:11  iteration: 162199/375342  consumed_samples: 166092800  total_loss: 3.65  time: 0.3414 s/iter  data_time: 0.2235 s/iter total_throughput: 2999.23 samples/s lr: 6.10e-04  
[09/22 18:50:03] lb.utils.events INFO:  eta: 9:12:23  iteration: 162299/375342  consumed_samples: 166195200  total_loss: 3.63  time: 0.3414 s/iter  data_time: 0.2312 s/iter total_throughput: 2999.20 samples/s lr: 6.09e-04  
[09/22 18:50:37] lb.utils.events INFO:  eta: 9:14:03  iteration: 162399/375342  consumed_samples: 166297600  total_loss: 3.627  time: 0.3414 s/iter  data_time: 0.2257 s/iter total_throughput: 2999.19 samples/s lr: 6.09e-04  
[09/22 18:51:12] lb.utils.events INFO:  eta: 9:13:47  iteration: 162499/375342  consumed_samples: 166400000  total_loss: 3.635  time: 0.3414 s/iter  data_time: 0.2219 s/iter total_throughput: 2999.16 samples/s lr: 6.09e-04  
[09/22 18:51:46] lb.utils.events INFO:  eta: 9:14:09  iteration: 162599/375342  consumed_samples: 166502400  total_loss: 3.617  time: 0.3414 s/iter  data_time: 0.2158 s/iter total_throughput: 2999.14 samples/s lr: 6.08e-04  
[09/22 18:52:21] lb.utils.events INFO:  eta: 9:13:19  iteration: 162699/375342  consumed_samples: 166604800  total_loss: 3.626  time: 0.3414 s/iter  data_time: 0.2215 s/iter total_throughput: 2999.09 samples/s lr: 6.08e-04  
[09/22 18:52:56] lb.utils.events INFO:  eta: 9:13:31  iteration: 162799/375342  consumed_samples: 166707200  total_loss: 3.614  time: 0.3414 s/iter  data_time: 0.2335 s/iter total_throughput: 2999.05 samples/s lr: 6.07e-04  
[09/22 18:53:31] lb.utils.events INFO:  eta: 9:13:46  iteration: 162899/375342  consumed_samples: 166809600  total_loss: 3.617  time: 0.3414 s/iter  data_time: 0.2215 s/iter total_throughput: 2999.03 samples/s lr: 6.07e-04  
[09/22 18:54:05] lb.utils.events INFO:  eta: 9:12:54  iteration: 162999/375342  consumed_samples: 166912000  total_loss: 3.626  time: 0.3414 s/iter  data_time: 0.2184 s/iter total_throughput: 2999.02 samples/s lr: 6.06e-04  
[09/22 18:54:40] lb.utils.events INFO:  eta: 9:12:03  iteration: 163099/375342  consumed_samples: 167014400  total_loss: 3.617  time: 0.3415 s/iter  data_time: 0.2454 s/iter total_throughput: 2998.96 samples/s lr: 6.06e-04  
[09/22 18:55:16] lb.utils.events INFO:  eta: 9:11:22  iteration: 163199/375342  consumed_samples: 167116800  total_loss: 3.609  time: 0.3415 s/iter  data_time: 0.2175 s/iter total_throughput: 2998.91 samples/s lr: 6.06e-04  
[09/22 18:55:50] lb.utils.events INFO:  eta: 9:11:14  iteration: 163299/375342  consumed_samples: 167219200  total_loss: 3.644  time: 0.3415 s/iter  data_time: 0.2230 s/iter total_throughput: 2998.87 samples/s lr: 6.05e-04  
[09/22 18:56:25] lb.utils.events INFO:  eta: 9:10:47  iteration: 163399/375342  consumed_samples: 167321600  total_loss: 3.663  time: 0.3415 s/iter  data_time: 0.2122 s/iter total_throughput: 2998.83 samples/s lr: 6.05e-04  
[09/22 18:57:00] lb.utils.events INFO:  eta: 9:10:46  iteration: 163499/375342  consumed_samples: 167424000  total_loss: 3.641  time: 0.3415 s/iter  data_time: 0.2116 s/iter total_throughput: 2998.82 samples/s lr: 6.04e-04  
[09/22 18:57:34] lb.utils.events INFO:  eta: 9:11:50  iteration: 163599/375342  consumed_samples: 167526400  total_loss: 3.622  time: 0.3415 s/iter  data_time: 0.2201 s/iter total_throughput: 2998.80 samples/s lr: 6.04e-04  
[09/22 18:58:09] lb.utils.events INFO:  eta: 9:10:58  iteration: 163699/375342  consumed_samples: 167628800  total_loss: 3.63  time: 0.3415 s/iter  data_time: 0.2166 s/iter total_throughput: 2998.77 samples/s lr: 6.04e-04  
[09/22 18:58:43] lb.utils.events INFO:  eta: 9:09:36  iteration: 163799/375342  consumed_samples: 167731200  total_loss: 3.622  time: 0.3415 s/iter  data_time: 0.2127 s/iter total_throughput: 2998.75 samples/s lr: 6.03e-04  
[09/22 18:59:18] lb.utils.events INFO:  eta: 9:09:36  iteration: 163899/375342  consumed_samples: 167833600  total_loss: 3.606  time: 0.3415 s/iter  data_time: 0.2123 s/iter total_throughput: 2998.76 samples/s lr: 6.03e-04  
[09/22 18:59:52] lb.utils.events INFO:  eta: 9:10:07  iteration: 163999/375342  consumed_samples: 167936000  total_loss: 3.59  time: 0.3415 s/iter  data_time: 0.2134 s/iter total_throughput: 2998.74 samples/s lr: 6.02e-04  
[09/22 19:00:27] lb.utils.events INFO:  eta: 9:10:44  iteration: 164099/375342  consumed_samples: 168038400  total_loss: 3.59  time: 0.3415 s/iter  data_time: 0.2263 s/iter total_throughput: 2998.72 samples/s lr: 6.02e-04  
[09/22 19:01:01] lb.utils.events INFO:  eta: 9:11:05  iteration: 164199/375342  consumed_samples: 168140800  total_loss: 3.598  time: 0.3415 s/iter  data_time: 0.2177 s/iter total_throughput: 2998.70 samples/s lr: 6.02e-04  
[09/22 19:01:36] lb.utils.events INFO:  eta: 9:10:30  iteration: 164299/375342  consumed_samples: 168243200  total_loss: 3.605  time: 0.3415 s/iter  data_time: 0.2184 s/iter total_throughput: 2998.67 samples/s lr: 6.01e-04  
[09/22 19:02:10] lb.utils.events INFO:  eta: 9:10:07  iteration: 164399/375342  consumed_samples: 168345600  total_loss: 3.615  time: 0.3415 s/iter  data_time: 0.2163 s/iter total_throughput: 2998.66 samples/s lr: 6.01e-04  
[09/22 19:02:45] lb.utils.events INFO:  eta: 9:08:39  iteration: 164499/375342  consumed_samples: 168448000  total_loss: 3.617  time: 0.3415 s/iter  data_time: 0.2204 s/iter total_throughput: 2998.64 samples/s lr: 6.00e-04  
[09/22 19:03:19] lb.utils.events INFO:  eta: 9:07:13  iteration: 164599/375342  consumed_samples: 168550400  total_loss: 3.604  time: 0.3415 s/iter  data_time: 0.2275 s/iter total_throughput: 2998.64 samples/s lr: 6.00e-04  
[09/22 19:03:54] lb.utils.events INFO:  eta: 9:08:01  iteration: 164699/375342  consumed_samples: 168652800  total_loss: 3.617  time: 0.3415 s/iter  data_time: 0.2123 s/iter total_throughput: 2998.60 samples/s lr: 6.00e-04  
[09/22 19:04:28] lb.utils.events INFO:  eta: 9:08:26  iteration: 164799/375342  consumed_samples: 168755200  total_loss: 3.617  time: 0.3415 s/iter  data_time: 0.2052 s/iter total_throughput: 2998.58 samples/s lr: 5.99e-04  
[09/22 19:05:03] lb.utils.events INFO:  eta: 9:06:37  iteration: 164899/375342  consumed_samples: 168857600  total_loss: 3.639  time: 0.3415 s/iter  data_time: 0.2053 s/iter total_throughput: 2998.57 samples/s lr: 5.99e-04  
[09/22 19:05:37] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0164999
[09/22 19:05:38] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/22 19:05:38] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/22 19:05:42] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0978 s/iter. Inference: 0.1608 s/iter. Eval: 0.0022 s/iter. Total: 0.2608 s/iter. ETA=0:00:09
[09/22 19:05:47] lb.evaluation.evaluator INFO: Inference done 29696/50000. Dataloading: 0.1180 s/iter. Inference: 0.1770 s/iter. Eval: 0.0020 s/iter. Total: 0.2971 s/iter. ETA=0:00:05
[09/22 19:05:52] lb.evaluation.evaluator INFO: Inference done 48128/50000. Dataloading: 0.1195 s/iter. Inference: 0.1698 s/iter. Eval: 0.0020 s/iter. Total: 0.2915 s/iter. ETA=0:00:00
[09/22 19:05:53] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/22 19:05:53] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.596519 (0.000252 s / iter per device, on 8 devices)
[09/22 19:05:53] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000149 s / iter per device, on 8 devices)
[09/22 19:05:53] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/22 19:05:53] lb.evaluation.utils INFO: copypaste: Acc@1=74.264
[09/22 19:05:53] lb.evaluation.utils INFO: copypaste: Acc@5=92.074
[09/22 19:05:53] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 74.26400, better than last best score 73.75400 @ iteration 154999.
[09/22 19:05:53] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/22 19:05:54] lb.utils.events INFO:  eta: 9:06:11  iteration: 164999/375342  consumed_samples: 168960000  total_loss: 3.648  time: 0.3415 s/iter  data_time: 0.2068 s/iter total_throughput: 2998.56 samples/s lr: 5.98e-04  
[09/22 19:06:26] lb.utils.events INFO:  eta: 9:08:27  iteration: 165099/375342  consumed_samples: 169062400  total_loss: 3.623  time: 0.3415 s/iter  data_time: 0.2117 s/iter total_throughput: 2998.66 samples/s lr: 5.98e-04  
[09/22 19:07:00] lb.utils.events INFO:  eta: 9:09:00  iteration: 165199/375342  consumed_samples: 169164800  total_loss: 3.593  time: 0.3415 s/iter  data_time: 0.2127 s/iter total_throughput: 2998.66 samples/s lr: 5.98e-04  
[09/22 19:07:35] lb.utils.events INFO:  eta: 9:08:42  iteration: 165299/375342  consumed_samples: 169267200  total_loss: 3.593  time: 0.3415 s/iter  data_time: 0.2224 s/iter total_throughput: 2998.64 samples/s lr: 5.97e-04  
[09/22 19:08:10] lb.utils.events INFO:  eta: 9:07:25  iteration: 165399/375342  consumed_samples: 169369600  total_loss: 3.604  time: 0.3415 s/iter  data_time: 0.2216 s/iter total_throughput: 2998.58 samples/s lr: 5.97e-04  
[09/22 19:08:44] lb.utils.events INFO:  eta: 9:07:01  iteration: 165499/375342  consumed_samples: 169472000  total_loss: 3.602  time: 0.3415 s/iter  data_time: 0.2169 s/iter total_throughput: 2998.56 samples/s lr: 5.96e-04  
[09/22 19:09:19] lb.utils.events INFO:  eta: 9:05:30  iteration: 165599/375342  consumed_samples: 169574400  total_loss: 3.605  time: 0.3415 s/iter  data_time: 0.2226 s/iter total_throughput: 2998.53 samples/s lr: 5.96e-04  
[09/22 19:09:54] lb.utils.events INFO:  eta: 9:04:01  iteration: 165699/375342  consumed_samples: 169676800  total_loss: 3.619  time: 0.3415 s/iter  data_time: 0.2373 s/iter total_throughput: 2998.47 samples/s lr: 5.96e-04  
[09/22 19:10:29] lb.utils.events INFO:  eta: 9:03:58  iteration: 165799/375342  consumed_samples: 169779200  total_loss: 3.605  time: 0.3415 s/iter  data_time: 0.2282 s/iter total_throughput: 2998.46 samples/s lr: 5.95e-04  
[09/22 19:11:03] lb.utils.events INFO:  eta: 9:04:37  iteration: 165899/375342  consumed_samples: 169881600  total_loss: 3.576  time: 0.3415 s/iter  data_time: 0.2005 s/iter total_throughput: 2998.47 samples/s lr: 5.95e-04  
[09/22 19:11:37] lb.utils.events INFO:  eta: 9:04:40  iteration: 165999/375342  consumed_samples: 169984000  total_loss: 3.594  time: 0.3415 s/iter  data_time: 0.2172 s/iter total_throughput: 2998.48 samples/s lr: 5.94e-04  
[09/22 19:12:11] lb.utils.events INFO:  eta: 9:00:36  iteration: 166099/375342  consumed_samples: 170086400  total_loss: 3.626  time: 0.3415 s/iter  data_time: 0.2110 s/iter total_throughput: 2998.45 samples/s lr: 5.94e-04  
[09/22 19:12:46] lb.utils.events INFO:  eta: 9:00:56  iteration: 166199/375342  consumed_samples: 170188800  total_loss: 3.625  time: 0.3415 s/iter  data_time: 0.2177 s/iter total_throughput: 2998.45 samples/s lr: 5.93e-04  
[09/22 19:13:20] lb.utils.events INFO:  eta: 9:01:52  iteration: 166299/375342  consumed_samples: 170291200  total_loss: 3.618  time: 0.3415 s/iter  data_time: 0.2139 s/iter total_throughput: 2998.43 samples/s lr: 5.93e-04  
[09/22 19:13:54] lb.utils.events INFO:  eta: 9:03:09  iteration: 166399/375342  consumed_samples: 170393600  total_loss: 3.594  time: 0.3415 s/iter  data_time: 0.2091 s/iter total_throughput: 2998.45 samples/s lr: 5.93e-04  
[09/22 19:14:29] lb.utils.events INFO:  eta: 9:04:21  iteration: 166499/375342  consumed_samples: 170496000  total_loss: 3.59  time: 0.3415 s/iter  data_time: 0.2181 s/iter total_throughput: 2998.43 samples/s lr: 5.92e-04  
[09/22 19:15:03] lb.utils.events INFO:  eta: 9:04:14  iteration: 166599/375342  consumed_samples: 170598400  total_loss: 3.599  time: 0.3415 s/iter  data_time: 0.2183 s/iter total_throughput: 2998.40 samples/s lr: 5.92e-04  
[09/22 19:15:37] lb.utils.events INFO:  eta: 9:04:41  iteration: 166699/375342  consumed_samples: 170700800  total_loss: 3.604  time: 0.3415 s/iter  data_time: 0.2161 s/iter total_throughput: 2998.40 samples/s lr: 5.91e-04  
[09/22 19:16:12] lb.utils.events INFO:  eta: 9:04:09  iteration: 166799/375342  consumed_samples: 170803200  total_loss: 3.621  time: 0.3415 s/iter  data_time: 0.2198 s/iter total_throughput: 2998.37 samples/s lr: 5.91e-04  
[09/22 19:16:46] lb.utils.events INFO:  eta: 9:02:59  iteration: 166899/375342  consumed_samples: 170905600  total_loss: 3.603  time: 0.3415 s/iter  data_time: 0.2174 s/iter total_throughput: 2998.38 samples/s lr: 5.91e-04  
[09/22 19:17:20] lb.utils.events INFO:  eta: 9:01:43  iteration: 166999/375342  consumed_samples: 171008000  total_loss: 3.578  time: 0.3415 s/iter  data_time: 0.2165 s/iter total_throughput: 2998.39 samples/s lr: 5.90e-04  
[09/22 19:17:54] lb.utils.events INFO:  eta: 9:02:13  iteration: 167099/375342  consumed_samples: 171110400  total_loss: 3.582  time: 0.3415 s/iter  data_time: 0.2147 s/iter total_throughput: 2998.40 samples/s lr: 5.90e-04  
[09/22 19:18:28] lb.utils.events INFO:  eta: 9:00:55  iteration: 167199/375342  consumed_samples: 171212800  total_loss: 3.596  time: 0.3415 s/iter  data_time: 0.2142 s/iter total_throughput: 2998.40 samples/s lr: 5.89e-04  
[09/22 19:19:02] lb.utils.events INFO:  eta: 9:01:21  iteration: 167299/375342  consumed_samples: 171315200  total_loss: 3.599  time: 0.3415 s/iter  data_time: 0.2118 s/iter total_throughput: 2998.42 samples/s lr: 5.89e-04  
[09/22 19:19:36] lb.utils.events INFO:  eta: 9:00:50  iteration: 167399/375342  consumed_samples: 171417600  total_loss: 3.609  time: 0.3415 s/iter  data_time: 0.2255 s/iter total_throughput: 2998.41 samples/s lr: 5.89e-04  
[09/22 19:20:10] lb.utils.events INFO:  eta: 9:00:32  iteration: 167499/375342  consumed_samples: 171520000  total_loss: 3.613  time: 0.3415 s/iter  data_time: 0.2174 s/iter total_throughput: 2998.42 samples/s lr: 5.88e-04  
[09/22 19:20:44] lb.utils.events INFO:  eta: 9:00:16  iteration: 167599/375342  consumed_samples: 171622400  total_loss: 3.621  time: 0.3415 s/iter  data_time: 0.2047 s/iter total_throughput: 2998.44 samples/s lr: 5.88e-04  
[09/22 19:21:18] lb.utils.events INFO:  eta: 9:00:01  iteration: 167699/375342  consumed_samples: 171724800  total_loss: 3.622  time: 0.3415 s/iter  data_time: 0.2112 s/iter total_throughput: 2998.46 samples/s lr: 5.87e-04  
[09/22 19:21:51] lb.utils.events INFO:  eta: 9:00:42  iteration: 167799/375342  consumed_samples: 171827200  total_loss: 3.617  time: 0.3415 s/iter  data_time: 0.2099 s/iter total_throughput: 2998.49 samples/s lr: 5.87e-04  
[09/22 19:22:26] lb.utils.events INFO:  eta: 9:00:37  iteration: 167899/375342  consumed_samples: 171929600  total_loss: 3.607  time: 0.3415 s/iter  data_time: 0.2124 s/iter total_throughput: 2998.46 samples/s lr: 5.87e-04  
[09/22 19:23:00] lb.utils.events INFO:  eta: 9:00:35  iteration: 167999/375342  consumed_samples: 172032000  total_loss: 3.608  time: 0.3415 s/iter  data_time: 0.2136 s/iter total_throughput: 2998.45 samples/s lr: 5.86e-04  
[09/22 19:23:35] lb.utils.events INFO:  eta: 9:01:47  iteration: 168099/375342  consumed_samples: 172134400  total_loss: 3.612  time: 0.3415 s/iter  data_time: 0.2275 s/iter total_throughput: 2998.45 samples/s lr: 5.86e-04  
[09/22 19:24:09] lb.utils.events INFO:  eta: 9:00:03  iteration: 168199/375342  consumed_samples: 172236800  total_loss: 3.625  time: 0.3415 s/iter  data_time: 0.2220 s/iter total_throughput: 2998.42 samples/s lr: 5.85e-04  
[09/22 19:24:45] lb.utils.events INFO:  eta: 8:58:32  iteration: 168299/375342  consumed_samples: 172339200  total_loss: 3.609  time: 0.3415 s/iter  data_time: 0.2215 s/iter total_throughput: 2998.36 samples/s lr: 5.85e-04  
[09/22 19:25:20] lb.utils.events INFO:  eta: 8:59:08  iteration: 168399/375342  consumed_samples: 172441600  total_loss: 3.591  time: 0.3415 s/iter  data_time: 0.2202 s/iter total_throughput: 2998.32 samples/s lr: 5.85e-04  
[09/22 19:25:55] lb.utils.events INFO:  eta: 8:57:53  iteration: 168499/375342  consumed_samples: 172544000  total_loss: 3.612  time: 0.3415 s/iter  data_time: 0.2351 s/iter total_throughput: 2998.27 samples/s lr: 5.84e-04  
[09/22 19:26:30] lb.utils.events INFO:  eta: 8:57:48  iteration: 168599/375342  consumed_samples: 172646400  total_loss: 3.606  time: 0.3415 s/iter  data_time: 0.2197 s/iter total_throughput: 2998.21 samples/s lr: 5.84e-04  
[09/22 19:27:06] lb.utils.events INFO:  eta: 8:56:24  iteration: 168699/375342  consumed_samples: 172748800  total_loss: 3.602  time: 0.3415 s/iter  data_time: 0.2213 s/iter total_throughput: 2998.13 samples/s lr: 5.83e-04  
[09/22 19:27:41] lb.utils.events INFO:  eta: 8:54:45  iteration: 168799/375342  consumed_samples: 172851200  total_loss: 3.598  time: 0.3416 s/iter  data_time: 0.2289 s/iter total_throughput: 2998.06 samples/s lr: 5.83e-04  
[09/22 19:28:17] lb.utils.events INFO:  eta: 8:53:24  iteration: 168899/375342  consumed_samples: 172953600  total_loss: 3.605  time: 0.3416 s/iter  data_time: 0.2362 s/iter total_throughput: 2997.99 samples/s lr: 5.82e-04  
[09/22 19:28:51] lb.utils.events INFO:  eta: 8:54:12  iteration: 168999/375342  consumed_samples: 173056000  total_loss: 3.601  time: 0.3416 s/iter  data_time: 0.2170 s/iter total_throughput: 2997.97 samples/s lr: 5.82e-04  
[09/22 19:29:26] lb.utils.events INFO:  eta: 8:52:55  iteration: 169099/375342  consumed_samples: 173158400  total_loss: 3.587  time: 0.3416 s/iter  data_time: 0.2179 s/iter total_throughput: 2997.94 samples/s lr: 5.82e-04  
[09/22 19:30:01] lb.utils.events INFO:  eta: 8:53:44  iteration: 169199/375342  consumed_samples: 173260800  total_loss: 3.599  time: 0.3416 s/iter  data_time: 0.2163 s/iter total_throughput: 2997.90 samples/s lr: 5.81e-04  
[09/22 19:30:36] lb.utils.events INFO:  eta: 8:52:19  iteration: 169299/375342  consumed_samples: 173363200  total_loss: 3.592  time: 0.3416 s/iter  data_time: 0.2303 s/iter total_throughput: 2997.85 samples/s lr: 5.81e-04  
[09/22 19:31:11] lb.utils.events INFO:  eta: 8:50:25  iteration: 169399/375342  consumed_samples: 173465600  total_loss: 3.584  time: 0.3416 s/iter  data_time: 0.2345 s/iter total_throughput: 2997.80 samples/s lr: 5.80e-04  
[09/22 19:31:47] lb.utils.events INFO:  eta: 8:50:41  iteration: 169499/375342  consumed_samples: 173568000  total_loss: 3.614  time: 0.3416 s/iter  data_time: 0.2216 s/iter total_throughput: 2997.71 samples/s lr: 5.80e-04  
[09/22 19:32:22] lb.utils.events INFO:  eta: 8:50:34  iteration: 169599/375342  consumed_samples: 173670400  total_loss: 3.6  time: 0.3416 s/iter  data_time: 0.2220 s/iter total_throughput: 2997.68 samples/s lr: 5.80e-04  
[09/22 19:32:57] lb.utils.events INFO:  eta: 8:50:29  iteration: 169699/375342  consumed_samples: 173772800  total_loss: 3.58  time: 0.3416 s/iter  data_time: 0.2245 s/iter total_throughput: 2997.63 samples/s lr: 5.79e-04  
[09/22 19:33:32] lb.utils.events INFO:  eta: 8:51:22  iteration: 169799/375342  consumed_samples: 173875200  total_loss: 3.586  time: 0.3416 s/iter  data_time: 0.2273 s/iter total_throughput: 2997.59 samples/s lr: 5.79e-04  
[09/22 19:34:07] lb.utils.events INFO:  eta: 8:51:56  iteration: 169899/375342  consumed_samples: 173977600  total_loss: 3.606  time: 0.3416 s/iter  data_time: 0.2380 s/iter total_throughput: 2997.55 samples/s lr: 5.78e-04  
[09/22 19:34:42] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0169999
[09/22 19:34:42] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/22 19:34:42] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/22 19:34:46] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0958 s/iter. Inference: 0.1614 s/iter. Eval: 0.0019 s/iter. Total: 0.2591 s/iter. ETA=0:00:09
[09/22 19:34:51] lb.evaluation.evaluator INFO: Inference done 28672/50000. Dataloading: 0.1055 s/iter. Inference: 0.1778 s/iter. Eval: 0.0020 s/iter. Total: 0.2853 s/iter. ETA=0:00:05
[09/22 19:34:56] lb.evaluation.evaluator INFO: Inference done 46080/50000. Dataloading: 0.1154 s/iter. Inference: 0.1719 s/iter. Eval: 0.0020 s/iter. Total: 0.2895 s/iter. ETA=0:00:00
[09/22 19:34:57] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/22 19:34:57] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.503556 (0.000250 s / iter per device, on 8 devices)
[09/22 19:34:57] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000151 s / iter per device, on 8 devices)
[09/22 19:34:57] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/22 19:34:57] lb.evaluation.utils INFO: copypaste: Acc@1=74.51
[09/22 19:34:57] lb.evaluation.utils INFO: copypaste: Acc@5=92.054
[09/22 19:34:57] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 74.51000, better than last best score 74.26400 @ iteration 164999.
[09/22 19:34:57] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/22 19:34:58] lb.utils.events INFO:  eta: 8:49:55  iteration: 169999/375342  consumed_samples: 174080000  total_loss: 3.615  time: 0.3416 s/iter  data_time: 0.2238 s/iter total_throughput: 2997.52 samples/s lr: 5.78e-04  
[09/22 19:35:31] lb.utils.events INFO:  eta: 8:52:41  iteration: 170099/375342  consumed_samples: 174182400  total_loss: 3.599  time: 0.3416 s/iter  data_time: 0.2354 s/iter total_throughput: 2997.60 samples/s lr: 5.78e-04  
[09/22 19:36:06] lb.utils.events INFO:  eta: 8:52:30  iteration: 170199/375342  consumed_samples: 174284800  total_loss: 3.596  time: 0.3416 s/iter  data_time: 0.2337 s/iter total_throughput: 2997.55 samples/s lr: 5.77e-04  
[09/22 19:36:41] lb.utils.events INFO:  eta: 8:54:15  iteration: 170299/375342  consumed_samples: 174387200  total_loss: 3.616  time: 0.3416 s/iter  data_time: 0.2222 s/iter total_throughput: 2997.50 samples/s lr: 5.77e-04  
[09/22 19:37:16] lb.utils.events INFO:  eta: 8:52:56  iteration: 170399/375342  consumed_samples: 174489600  total_loss: 3.624  time: 0.3416 s/iter  data_time: 0.2309 s/iter total_throughput: 2997.47 samples/s lr: 5.76e-04  
[09/22 19:37:51] lb.utils.events INFO:  eta: 8:52:49  iteration: 170499/375342  consumed_samples: 174592000  total_loss: 3.599  time: 0.3416 s/iter  data_time: 0.2155 s/iter total_throughput: 2997.43 samples/s lr: 5.76e-04  
[09/22 19:38:25] lb.utils.events INFO:  eta: 8:52:42  iteration: 170599/375342  consumed_samples: 174694400  total_loss: 3.598  time: 0.3416 s/iter  data_time: 0.2093 s/iter total_throughput: 2997.43 samples/s lr: 5.75e-04  
[09/22 19:39:00] lb.utils.events INFO:  eta: 8:55:04  iteration: 170699/375342  consumed_samples: 174796800  total_loss: 3.604  time: 0.3416 s/iter  data_time: 0.2224 s/iter total_throughput: 2997.39 samples/s lr: 5.75e-04  
[09/22 19:39:35] lb.utils.events INFO:  eta: 8:52:21  iteration: 170799/375342  consumed_samples: 174899200  total_loss: 3.623  time: 0.3416 s/iter  data_time: 0.2229 s/iter total_throughput: 2997.36 samples/s lr: 5.75e-04  
[09/22 19:40:10] lb.utils.events INFO:  eta: 8:53:22  iteration: 170899/375342  consumed_samples: 175001600  total_loss: 3.617  time: 0.3416 s/iter  data_time: 0.2366 s/iter total_throughput: 2997.31 samples/s lr: 5.74e-04  
[09/22 19:40:45] lb.utils.events INFO:  eta: 8:52:38  iteration: 170999/375342  consumed_samples: 175104000  total_loss: 3.591  time: 0.3416 s/iter  data_time: 0.2270 s/iter total_throughput: 2997.27 samples/s lr: 5.74e-04  
[09/22 19:41:21] lb.utils.events INFO:  eta: 8:48:32  iteration: 171099/375342  consumed_samples: 175206400  total_loss: 3.601  time: 0.3417 s/iter  data_time: 0.2499 s/iter total_throughput: 2997.18 samples/s lr: 5.73e-04  
[09/22 19:41:56] lb.utils.events INFO:  eta: 8:48:17  iteration: 171199/375342  consumed_samples: 175308800  total_loss: 3.598  time: 0.3417 s/iter  data_time: 0.2143 s/iter total_throughput: 2997.14 samples/s lr: 5.73e-04  
[09/22 19:42:30] lb.utils.events INFO:  eta: 8:48:03  iteration: 171299/375342  consumed_samples: 175411200  total_loss: 3.594  time: 0.3417 s/iter  data_time: 0.2125 s/iter total_throughput: 2997.11 samples/s lr: 5.73e-04  
[09/22 19:43:06] lb.utils.events INFO:  eta: 8:48:19  iteration: 171399/375342  consumed_samples: 175513600  total_loss: 3.603  time: 0.3417 s/iter  data_time: 0.2306 s/iter total_throughput: 2997.05 samples/s lr: 5.72e-04  
[09/22 19:43:41] lb.utils.events INFO:  eta: 8:48:27  iteration: 171499/375342  consumed_samples: 175616000  total_loss: 3.595  time: 0.3417 s/iter  data_time: 0.2208 s/iter total_throughput: 2997.02 samples/s lr: 5.72e-04  
[09/22 19:44:16] lb.utils.events INFO:  eta: 8:46:49  iteration: 171599/375342  consumed_samples: 175718400  total_loss: 3.583  time: 0.3417 s/iter  data_time: 0.2250 s/iter total_throughput: 2996.98 samples/s lr: 5.71e-04  
[09/22 19:44:50] lb.utils.events INFO:  eta: 8:47:15  iteration: 171699/375342  consumed_samples: 175820800  total_loss: 3.587  time: 0.3417 s/iter  data_time: 0.2270 s/iter total_throughput: 2996.94 samples/s lr: 5.71e-04  
[09/22 19:45:26] lb.utils.events INFO:  eta: 8:46:51  iteration: 171799/375342  consumed_samples: 175923200  total_loss: 3.6  time: 0.3417 s/iter  data_time: 0.2204 s/iter total_throughput: 2996.90 samples/s lr: 5.71e-04  
[09/22 19:46:00] lb.utils.events INFO:  eta: 8:45:48  iteration: 171899/375342  consumed_samples: 176025600  total_loss: 3.594  time: 0.3417 s/iter  data_time: 0.2295 s/iter total_throughput: 2996.88 samples/s lr: 5.70e-04  
[09/22 19:46:35] lb.utils.events INFO:  eta: 8:46:33  iteration: 171999/375342  consumed_samples: 176128000  total_loss: 3.597  time: 0.3417 s/iter  data_time: 0.2395 s/iter total_throughput: 2996.83 samples/s lr: 5.70e-04  
[09/22 19:47:10] lb.utils.events INFO:  eta: 8:47:03  iteration: 172099/375342  consumed_samples: 176230400  total_loss: 3.61  time: 0.3417 s/iter  data_time: 0.2169 s/iter total_throughput: 2996.79 samples/s lr: 5.69e-04  
[09/22 19:47:45] lb.utils.events INFO:  eta: 8:46:09  iteration: 172199/375342  consumed_samples: 176332800  total_loss: 3.604  time: 0.3417 s/iter  data_time: 0.2183 s/iter total_throughput: 2996.74 samples/s lr: 5.69e-04  
[09/22 19:48:21] lb.utils.events INFO:  eta: 8:44:53  iteration: 172299/375342  consumed_samples: 176435200  total_loss: 3.594  time: 0.3417 s/iter  data_time: 0.2132 s/iter total_throughput: 2996.69 samples/s lr: 5.69e-04  
[09/22 19:48:56] lb.utils.events INFO:  eta: 8:45:21  iteration: 172399/375342  consumed_samples: 176537600  total_loss: 3.587  time: 0.3417 s/iter  data_time: 0.2276 s/iter total_throughput: 2996.65 samples/s lr: 5.68e-04  
[09/22 19:49:30] lb.utils.events INFO:  eta: 8:45:24  iteration: 172499/375342  consumed_samples: 176640000  total_loss: 3.584  time: 0.3417 s/iter  data_time: 0.2249 s/iter total_throughput: 2996.64 samples/s lr: 5.68e-04  
[09/22 19:50:05] lb.utils.events INFO:  eta: 8:45:07  iteration: 172599/375342  consumed_samples: 176742400  total_loss: 3.581  time: 0.3417 s/iter  data_time: 0.2319 s/iter total_throughput: 2996.60 samples/s lr: 5.67e-04  
[09/22 19:50:39] lb.utils.events INFO:  eta: 8:44:26  iteration: 172699/375342  consumed_samples: 176844800  total_loss: 3.581  time: 0.3417 s/iter  data_time: 0.2175 s/iter total_throughput: 2996.60 samples/s lr: 5.67e-04  
[09/22 19:51:14] lb.utils.events INFO:  eta: 8:44:36  iteration: 172799/375342  consumed_samples: 176947200  total_loss: 3.571  time: 0.3417 s/iter  data_time: 0.2110 s/iter total_throughput: 2996.56 samples/s lr: 5.66e-04  
[09/22 19:51:49] lb.utils.events INFO:  eta: 8:44:39  iteration: 172899/375342  consumed_samples: 177049600  total_loss: 3.573  time: 0.3417 s/iter  data_time: 0.2279 s/iter total_throughput: 2996.53 samples/s lr: 5.66e-04  
[09/22 19:52:24] lb.utils.events INFO:  eta: 8:44:07  iteration: 172999/375342  consumed_samples: 177152000  total_loss: 3.592  time: 0.3417 s/iter  data_time: 0.2252 s/iter total_throughput: 2996.46 samples/s lr: 5.66e-04  
[09/22 19:52:59] lb.utils.events INFO:  eta: 8:44:03  iteration: 173099/375342  consumed_samples: 177254400  total_loss: 3.59  time: 0.3417 s/iter  data_time: 0.2293 s/iter total_throughput: 2996.42 samples/s lr: 5.65e-04  
[09/22 19:53:34] lb.utils.events INFO:  eta: 8:43:59  iteration: 173199/375342  consumed_samples: 177356800  total_loss: 3.582  time: 0.3417 s/iter  data_time: 0.2207 s/iter total_throughput: 2996.39 samples/s lr: 5.65e-04  
[09/22 19:54:09] lb.utils.events INFO:  eta: 8:43:55  iteration: 173299/375342  consumed_samples: 177459200  total_loss: 3.578  time: 0.3417 s/iter  data_time: 0.2294 s/iter total_throughput: 2996.35 samples/s lr: 5.64e-04  
[09/22 19:54:44] lb.utils.events INFO:  eta: 8:43:08  iteration: 173399/375342  consumed_samples: 177561600  total_loss: 3.578  time: 0.3418 s/iter  data_time: 0.2278 s/iter total_throughput: 2996.32 samples/s lr: 5.64e-04  
[09/22 19:55:19] lb.utils.events INFO:  eta: 8:43:17  iteration: 173499/375342  consumed_samples: 177664000  total_loss: 3.587  time: 0.3418 s/iter  data_time: 0.2147 s/iter total_throughput: 2996.29 samples/s lr: 5.64e-04  
[09/22 19:55:53] lb.utils.events INFO:  eta: 8:44:44  iteration: 173599/375342  consumed_samples: 177766400  total_loss: 3.605  time: 0.3418 s/iter  data_time: 0.2172 s/iter total_throughput: 2996.27 samples/s lr: 5.63e-04  
[09/22 19:56:28] lb.utils.events INFO:  eta: 8:44:16  iteration: 173699/375342  consumed_samples: 177868800  total_loss: 3.615  time: 0.3418 s/iter  data_time: 0.2275 s/iter total_throughput: 2996.24 samples/s lr: 5.63e-04  
[09/22 19:57:03] lb.utils.events INFO:  eta: 8:45:15  iteration: 173799/375342  consumed_samples: 177971200  total_loss: 3.577  time: 0.3418 s/iter  data_time: 0.2104 s/iter total_throughput: 2996.21 samples/s lr: 5.62e-04  
[09/22 19:57:37] lb.utils.events INFO:  eta: 8:44:50  iteration: 173899/375342  consumed_samples: 178073600  total_loss: 3.566  time: 0.3418 s/iter  data_time: 0.2204 s/iter total_throughput: 2996.19 samples/s lr: 5.62e-04  
[09/22 19:58:12] lb.utils.events INFO:  eta: 8:44:45  iteration: 173999/375342  consumed_samples: 178176000  total_loss: 3.573  time: 0.3418 s/iter  data_time: 0.2362 s/iter total_throughput: 2996.15 samples/s lr: 5.62e-04  
[09/22 19:58:48] lb.utils.events INFO:  eta: 8:43:04  iteration: 174099/375342  consumed_samples: 178278400  total_loss: 3.568  time: 0.3418 s/iter  data_time: 0.2211 s/iter total_throughput: 2996.09 samples/s lr: 5.61e-04  
[09/22 19:59:23] lb.utils.events INFO:  eta: 8:43:31  iteration: 174199/375342  consumed_samples: 178380800  total_loss: 3.583  time: 0.3418 s/iter  data_time: 0.2111 s/iter total_throughput: 2996.06 samples/s lr: 5.61e-04  
[09/22 19:59:57] lb.utils.events INFO:  eta: 8:45:24  iteration: 174299/375342  consumed_samples: 178483200  total_loss: 3.604  time: 0.3418 s/iter  data_time: 0.2088 s/iter total_throughput: 2996.05 samples/s lr: 5.60e-04  
[09/22 20:00:32] lb.utils.events INFO:  eta: 8:44:07  iteration: 174399/375342  consumed_samples: 178585600  total_loss: 3.591  time: 0.3418 s/iter  data_time: 0.2275 s/iter total_throughput: 2995.99 samples/s lr: 5.60e-04  
[09/22 20:01:07] lb.utils.events INFO:  eta: 8:42:56  iteration: 174499/375342  consumed_samples: 178688000  total_loss: 3.577  time: 0.3418 s/iter  data_time: 0.2112 s/iter total_throughput: 2995.95 samples/s lr: 5.59e-04  
[09/22 20:01:42] lb.utils.events INFO:  eta: 8:42:14  iteration: 174599/375342  consumed_samples: 178790400  total_loss: 3.592  time: 0.3418 s/iter  data_time: 0.2181 s/iter total_throughput: 2995.92 samples/s lr: 5.59e-04  
[09/22 20:02:17] lb.utils.events INFO:  eta: 8:41:30  iteration: 174699/375342  consumed_samples: 178892800  total_loss: 3.594  time: 0.3418 s/iter  data_time: 0.2254 s/iter total_throughput: 2995.88 samples/s lr: 5.59e-04  
[09/22 20:02:52] lb.utils.events INFO:  eta: 8:41:07  iteration: 174799/375342  consumed_samples: 178995200  total_loss: 3.587  time: 0.3418 s/iter  data_time: 0.2179 s/iter total_throughput: 2995.83 samples/s lr: 5.58e-04  
[09/22 20:03:27] lb.utils.events INFO:  eta: 8:40:00  iteration: 174899/375342  consumed_samples: 179097600  total_loss: 3.585  time: 0.3418 s/iter  data_time: 0.2118 s/iter total_throughput: 2995.81 samples/s lr: 5.58e-04  
[09/22 20:04:01] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0174999
[09/22 20:04:02] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/22 20:04:02] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/22 20:04:06] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0982 s/iter. Inference: 0.1609 s/iter. Eval: 0.0022 s/iter. Total: 0.2614 s/iter. ETA=0:00:09
[09/22 20:04:12] lb.evaluation.evaluator INFO: Inference done 29696/50000. Dataloading: 0.1261 s/iter. Inference: 0.1702 s/iter. Eval: 0.0021 s/iter. Total: 0.2985 s/iter. ETA=0:00:05
[09/22 20:04:17] lb.evaluation.evaluator INFO: Inference done 49152/50000. Dataloading: 0.1167 s/iter. Inference: 0.1645 s/iter. Eval: 0.0021 s/iter. Total: 0.2834 s/iter. ETA=0:00:00
[09/22 20:04:17] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/22 20:04:17] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.632253 (0.000253 s / iter per device, on 8 devices)
[09/22 20:04:17] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000146 s / iter per device, on 8 devices)
[09/22 20:04:17] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/22 20:04:17] lb.evaluation.utils INFO: copypaste: Acc@1=74.49
[09/22 20:04:17] lb.evaluation.utils INFO: copypaste: Acc@5=92.412
[09/22 20:04:17] lb.engine.hooks INFO: Not saving as latest eval score for Acc@1 is 74.49000, not better than best score 74.51000 @ iteration 169999.
[09/22 20:04:17] lb.utils.events INFO:  eta: 8:40:13  iteration: 174999/375342  consumed_samples: 179200000  total_loss: 3.592  time: 0.3418 s/iter  data_time: 0.2265 s/iter total_throughput: 2995.80 samples/s lr: 5.57e-04  
[09/22 20:04:50] lb.utils.events INFO:  eta: 8:41:21  iteration: 175099/375342  consumed_samples: 179302400  total_loss: 3.582  time: 0.3418 s/iter  data_time: 0.2076 s/iter total_throughput: 2995.85 samples/s lr: 5.57e-04  
[09/22 20:05:25] lb.utils.events INFO:  eta: 8:40:14  iteration: 175199/375342  consumed_samples: 179404800  total_loss: 3.573  time: 0.3418 s/iter  data_time: 0.2186 s/iter total_throughput: 2995.83 samples/s lr: 5.57e-04  
[09/22 20:05:59] lb.utils.events INFO:  eta: 8:39:23  iteration: 175299/375342  consumed_samples: 179507200  total_loss: 3.593  time: 0.3418 s/iter  data_time: 0.2191 s/iter total_throughput: 2995.81 samples/s lr: 5.56e-04  
[09/22 20:06:34] lb.utils.events INFO:  eta: 8:39:32  iteration: 175399/375342  consumed_samples: 179609600  total_loss: 3.59  time: 0.3418 s/iter  data_time: 0.2269 s/iter total_throughput: 2995.79 samples/s lr: 5.56e-04  
[09/22 20:07:09] lb.utils.events INFO:  eta: 8:38:49  iteration: 175499/375342  consumed_samples: 179712000  total_loss: 3.567  time: 0.3418 s/iter  data_time: 0.2109 s/iter total_throughput: 2995.76 samples/s lr: 5.55e-04  
[09/22 20:07:44] lb.utils.events INFO:  eta: 8:37:37  iteration: 175599/375342  consumed_samples: 179814400  total_loss: 3.557  time: 0.3418 s/iter  data_time: 0.2346 s/iter total_throughput: 2995.72 samples/s lr: 5.55e-04  
[09/22 20:08:19] lb.utils.events INFO:  eta: 8:37:11  iteration: 175699/375342  consumed_samples: 179916800  total_loss: 3.578  time: 0.3418 s/iter  data_time: 0.2210 s/iter total_throughput: 2995.68 samples/s lr: 5.55e-04  
[09/22 20:08:53] lb.utils.events INFO:  eta: 8:36:39  iteration: 175799/375342  consumed_samples: 180019200  total_loss: 3.601  time: 0.3418 s/iter  data_time: 0.2207 s/iter total_throughput: 2995.66 samples/s lr: 5.54e-04  
[09/22 20:09:28] lb.utils.events INFO:  eta: 8:36:22  iteration: 175899/375342  consumed_samples: 180121600  total_loss: 3.594  time: 0.3418 s/iter  data_time: 0.2273 s/iter total_throughput: 2995.62 samples/s lr: 5.54e-04  
[09/22 20:10:03] lb.utils.events INFO:  eta: 8:35:59  iteration: 175999/375342  consumed_samples: 180224000  total_loss: 3.571  time: 0.3418 s/iter  data_time: 0.2356 s/iter total_throughput: 2995.59 samples/s lr: 5.53e-04  
[09/22 20:10:38] lb.utils.events INFO:  eta: 8:34:32  iteration: 176099/375342  consumed_samples: 180326400  total_loss: 3.57  time: 0.3418 s/iter  data_time: 0.2280 s/iter total_throughput: 2995.57 samples/s lr: 5.53e-04  
[09/22 20:11:12] lb.utils.events INFO:  eta: 8:34:29  iteration: 176199/375342  consumed_samples: 180428800  total_loss: 3.583  time: 0.3418 s/iter  data_time: 0.2095 s/iter total_throughput: 2995.55 samples/s lr: 5.52e-04  
[09/22 20:11:47] lb.utils.events INFO:  eta: 8:34:22  iteration: 176299/375342  consumed_samples: 180531200  total_loss: 3.585  time: 0.3418 s/iter  data_time: 0.2154 s/iter total_throughput: 2995.53 samples/s lr: 5.52e-04  
[09/22 20:12:21] lb.utils.events INFO:  eta: 8:34:04  iteration: 176399/375342  consumed_samples: 180633600  total_loss: 3.593  time: 0.3418 s/iter  data_time: 0.2111 s/iter total_throughput: 2995.52 samples/s lr: 5.52e-04  
[09/22 20:12:56] lb.utils.events INFO:  eta: 8:33:53  iteration: 176499/375342  consumed_samples: 180736000  total_loss: 3.584  time: 0.3418 s/iter  data_time: 0.2123 s/iter total_throughput: 2995.51 samples/s lr: 5.51e-04  
[09/22 20:13:30] lb.utils.events INFO:  eta: 8:34:33  iteration: 176599/375342  consumed_samples: 180838400  total_loss: 3.606  time: 0.3418 s/iter  data_time: 0.2210 s/iter total_throughput: 2995.51 samples/s lr: 5.51e-04  
[09/22 20:14:05] lb.utils.events INFO:  eta: 8:34:17  iteration: 176699/375342  consumed_samples: 180940800  total_loss: 3.612  time: 0.3418 s/iter  data_time: 0.2175 s/iter total_throughput: 2995.47 samples/s lr: 5.50e-04  
[09/22 20:14:40] lb.utils.events INFO:  eta: 8:34:02  iteration: 176799/375342  consumed_samples: 181043200  total_loss: 3.604  time: 0.3419 s/iter  data_time: 0.2099 s/iter total_throughput: 2995.45 samples/s lr: 5.50e-04  
[09/22 20:15:14] lb.utils.events INFO:  eta: 8:34:39  iteration: 176899/375342  consumed_samples: 181145600  total_loss: 3.594  time: 0.3419 s/iter  data_time: 0.2172 s/iter total_throughput: 2995.44 samples/s lr: 5.50e-04  
[09/22 20:15:48] lb.utils.events INFO:  eta: 8:34:23  iteration: 176999/375342  consumed_samples: 181248000  total_loss: 3.571  time: 0.3419 s/iter  data_time: 0.2182 s/iter total_throughput: 2995.42 samples/s lr: 5.49e-04  
[09/22 20:16:23] lb.utils.events INFO:  eta: 8:35:33  iteration: 177099/375342  consumed_samples: 181350400  total_loss: 3.585  time: 0.3419 s/iter  data_time: 0.2259 s/iter total_throughput: 2995.39 samples/s lr: 5.49e-04  
[09/22 20:16:58] lb.utils.events INFO:  eta: 8:34:01  iteration: 177199/375342  consumed_samples: 181452800  total_loss: 3.603  time: 0.3419 s/iter  data_time: 0.2106 s/iter total_throughput: 2995.37 samples/s lr: 5.48e-04  
[09/22 20:17:33] lb.utils.events INFO:  eta: 8:33:54  iteration: 177299/375342  consumed_samples: 181555200  total_loss: 3.594  time: 0.3419 s/iter  data_time: 0.2195 s/iter total_throughput: 2995.35 samples/s lr: 5.48e-04  
[09/22 20:18:07] lb.utils.events INFO:  eta: 8:34:53  iteration: 177399/375342  consumed_samples: 181657600  total_loss: 3.564  time: 0.3419 s/iter  data_time: 0.2144 s/iter total_throughput: 2995.35 samples/s lr: 5.48e-04  
[09/22 20:18:41] lb.utils.events INFO:  eta: 8:35:28  iteration: 177499/375342  consumed_samples: 181760000  total_loss: 3.57  time: 0.3419 s/iter  data_time: 0.2212 s/iter total_throughput: 2995.34 samples/s lr: 5.47e-04  
[09/22 20:19:16] lb.utils.events INFO:  eta: 8:35:12  iteration: 177599/375342  consumed_samples: 181862400  total_loss: 3.579  time: 0.3419 s/iter  data_time: 0.2076 s/iter total_throughput: 2995.33 samples/s lr: 5.47e-04  
[09/22 20:19:51] lb.utils.events INFO:  eta: 8:35:32  iteration: 177699/375342  consumed_samples: 181964800  total_loss: 3.565  time: 0.3419 s/iter  data_time: 0.2368 s/iter total_throughput: 2995.28 samples/s lr: 5.46e-04  
[09/22 20:20:26] lb.utils.events INFO:  eta: 8:34:54  iteration: 177799/375342  consumed_samples: 182067200  total_loss: 3.554  time: 0.3419 s/iter  data_time: 0.2284 s/iter total_throughput: 2995.24 samples/s lr: 5.46e-04  
[09/22 20:21:00] lb.utils.events INFO:  eta: 8:34:04  iteration: 177899/375342  consumed_samples: 182169600  total_loss: 3.562  time: 0.3419 s/iter  data_time: 0.2147 s/iter total_throughput: 2995.22 samples/s lr: 5.45e-04  
[09/22 20:21:35] lb.utils.events INFO:  eta: 8:33:28  iteration: 177999/375342  consumed_samples: 182272000  total_loss: 3.571  time: 0.3419 s/iter  data_time: 0.2181 s/iter total_throughput: 2995.19 samples/s lr: 5.45e-04  
[09/22 20:22:09] lb.utils.events INFO:  eta: 8:33:16  iteration: 178099/375342  consumed_samples: 182374400  total_loss: 3.589  time: 0.3419 s/iter  data_time: 0.2198 s/iter total_throughput: 2995.18 samples/s lr: 5.45e-04  
[09/22 20:22:44] lb.utils.events INFO:  eta: 8:32:57  iteration: 178199/375342  consumed_samples: 182476800  total_loss: 3.596  time: 0.3419 s/iter  data_time: 0.2329 s/iter total_throughput: 2995.15 samples/s lr: 5.44e-04  
[09/22 20:23:19] lb.utils.events INFO:  eta: 8:32:17  iteration: 178299/375342  consumed_samples: 182579200  total_loss: 3.571  time: 0.3419 s/iter  data_time: 0.2244 s/iter total_throughput: 2995.12 samples/s lr: 5.44e-04  
[09/22 20:23:54] lb.utils.events INFO:  eta: 8:31:25  iteration: 178399/375342  consumed_samples: 182681600  total_loss: 3.57  time: 0.3419 s/iter  data_time: 0.2168 s/iter total_throughput: 2995.10 samples/s lr: 5.43e-04  
[09/22 20:24:29] lb.utils.events INFO:  eta: 8:29:56  iteration: 178499/375342  consumed_samples: 182784000  total_loss: 3.562  time: 0.3419 s/iter  data_time: 0.2383 s/iter total_throughput: 2995.05 samples/s lr: 5.43e-04  
[09/22 20:25:03] lb.utils.events INFO:  eta: 8:29:52  iteration: 178599/375342  consumed_samples: 182886400  total_loss: 3.57  time: 0.3419 s/iter  data_time: 0.2207 s/iter total_throughput: 2995.04 samples/s lr: 5.43e-04  
[09/22 20:25:38] lb.utils.events INFO:  eta: 8:29:41  iteration: 178699/375342  consumed_samples: 182988800  total_loss: 3.573  time: 0.3419 s/iter  data_time: 0.2137 s/iter total_throughput: 2995.02 samples/s lr: 5.42e-04  
[09/22 20:26:13] lb.utils.events INFO:  eta: 8:29:57  iteration: 178799/375342  consumed_samples: 183091200  total_loss: 3.572  time: 0.3419 s/iter  data_time: 0.2052 s/iter total_throughput: 2995.00 samples/s lr: 5.42e-04  
[09/22 20:26:47] lb.utils.events INFO:  eta: 8:30:01  iteration: 178899/375342  consumed_samples: 183193600  total_loss: 3.573  time: 0.3419 s/iter  data_time: 0.2178 s/iter total_throughput: 2995.00 samples/s lr: 5.41e-04  
[09/22 20:27:21] lb.utils.events INFO:  eta: 8:30:34  iteration: 178999/375342  consumed_samples: 183296000  total_loss: 3.579  time: 0.3419 s/iter  data_time: 0.2164 s/iter total_throughput: 2995.00 samples/s lr: 5.41e-04  
[09/22 20:27:55] lb.utils.events INFO:  eta: 8:29:35  iteration: 179099/375342  consumed_samples: 183398400  total_loss: 3.567  time: 0.3419 s/iter  data_time: 0.2137 s/iter total_throughput: 2995.01 samples/s lr: 5.40e-04  
[09/22 20:28:29] lb.utils.events INFO:  eta: 8:29:33  iteration: 179199/375342  consumed_samples: 183500800  total_loss: 3.571  time: 0.3419 s/iter  data_time: 0.2171 s/iter total_throughput: 2995.00 samples/s lr: 5.40e-04  
[09/22 20:29:04] lb.utils.events INFO:  eta: 8:30:22  iteration: 179299/375342  consumed_samples: 183603200  total_loss: 3.571  time: 0.3419 s/iter  data_time: 0.2236 s/iter total_throughput: 2994.99 samples/s lr: 5.40e-04  
[09/22 20:29:38] lb.utils.events INFO:  eta: 8:29:46  iteration: 179399/375342  consumed_samples: 183705600  total_loss: 3.559  time: 0.3419 s/iter  data_time: 0.2238 s/iter total_throughput: 2994.97 samples/s lr: 5.39e-04  
[09/22 20:30:13] lb.utils.events INFO:  eta: 8:30:29  iteration: 179499/375342  consumed_samples: 183808000  total_loss: 3.578  time: 0.3419 s/iter  data_time: 0.2157 s/iter total_throughput: 2994.93 samples/s lr: 5.39e-04  
[09/22 20:30:48] lb.utils.events INFO:  eta: 8:29:25  iteration: 179599/375342  consumed_samples: 183910400  total_loss: 3.561  time: 0.3419 s/iter  data_time: 0.2168 s/iter total_throughput: 2994.93 samples/s lr: 5.38e-04  
[09/22 20:31:22] lb.utils.events INFO:  eta: 8:28:31  iteration: 179699/375342  consumed_samples: 184012800  total_loss: 3.559  time: 0.3419 s/iter  data_time: 0.2206 s/iter total_throughput: 2994.90 samples/s lr: 5.38e-04  
[09/22 20:31:57] lb.utils.events INFO:  eta: 8:28:04  iteration: 179799/375342  consumed_samples: 184115200  total_loss: 3.584  time: 0.3419 s/iter  data_time: 0.2132 s/iter total_throughput: 2994.90 samples/s lr: 5.38e-04  
[09/22 20:32:31] lb.utils.events INFO:  eta: 8:27:38  iteration: 179899/375342  consumed_samples: 184217600  total_loss: 3.565  time: 0.3419 s/iter  data_time: 0.2141 s/iter total_throughput: 2994.88 samples/s lr: 5.37e-04  
[09/22 20:33:06] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0179999
[09/22 20:33:07] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/22 20:33:07] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/22 20:33:11] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0915 s/iter. Inference: 0.1606 s/iter. Eval: 0.0021 s/iter. Total: 0.2542 s/iter. ETA=0:00:09
[09/22 20:33:17] lb.evaluation.evaluator INFO: Inference done 29696/50000. Dataloading: 0.1418 s/iter. Inference: 0.1611 s/iter. Eval: 0.0021 s/iter. Total: 0.3050 s/iter. ETA=0:00:05
[09/22 20:33:22] lb.evaluation.evaluator INFO: Inference done 50000/50000. Dataloading: 0.1249 s/iter. Inference: 0.1627 s/iter. Eval: 0.0020 s/iter. Total: 0.2897 s/iter. ETA=0:00:00
[09/22 20:33:22] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/22 20:33:22] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.751464 (0.000255 s / iter per device, on 8 devices)
[09/22 20:33:22] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000143 s / iter per device, on 8 devices)
[09/22 20:33:22] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/22 20:33:22] lb.evaluation.utils INFO: copypaste: Acc@1=74.57000000000001
[09/22 20:33:22] lb.evaluation.utils INFO: copypaste: Acc@5=92.202
[09/22 20:33:22] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 74.57000, better than last best score 74.51000 @ iteration 169999.
[09/22 20:33:22] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/22 20:33:23] lb.utils.events INFO:  eta: 8:27:23  iteration: 179999/375342  consumed_samples: 184320000  total_loss: 3.537  time: 0.3419 s/iter  data_time: 0.2265 s/iter total_throughput: 2994.86 samples/s lr: 5.37e-04  
[09/22 20:33:55] lb.utils.events INFO:  eta: 8:28:13  iteration: 180099/375342  consumed_samples: 184422400  total_loss: 3.536  time: 0.3419 s/iter  data_time: 0.2107 s/iter total_throughput: 2994.96 samples/s lr: 5.36e-04  
[09/22 20:34:30] lb.utils.events INFO:  eta: 8:27:20  iteration: 180199/375342  consumed_samples: 184524800  total_loss: 3.545  time: 0.3419 s/iter  data_time: 0.2247 s/iter total_throughput: 2994.93 samples/s lr: 5.36e-04  
[09/22 20:35:04] lb.utils.events INFO:  eta: 8:26:58  iteration: 180299/375342  consumed_samples: 184627200  total_loss: 3.542  time: 0.3419 s/iter  data_time: 0.2132 s/iter total_throughput: 2994.93 samples/s lr: 5.36e-04  
[09/22 20:35:38] lb.utils.events INFO:  eta: 8:26:55  iteration: 180399/375342  consumed_samples: 184729600  total_loss: 3.545  time: 0.3419 s/iter  data_time: 0.2101 s/iter total_throughput: 2994.93 samples/s lr: 5.35e-04  
[09/22 20:36:13] lb.utils.events INFO:  eta: 8:26:06  iteration: 180499/375342  consumed_samples: 184832000  total_loss: 3.554  time: 0.3419 s/iter  data_time: 0.2189 s/iter total_throughput: 2994.92 samples/s lr: 5.35e-04  
[09/22 20:36:47] lb.utils.events INFO:  eta: 8:26:55  iteration: 180599/375342  consumed_samples: 184934400  total_loss: 3.556  time: 0.3419 s/iter  data_time: 0.2221 s/iter total_throughput: 2994.92 samples/s lr: 5.34e-04  
[09/22 20:37:21] lb.utils.events INFO:  eta: 8:27:25  iteration: 180699/375342  consumed_samples: 185036800  total_loss: 3.551  time: 0.3419 s/iter  data_time: 0.2066 s/iter total_throughput: 2994.92 samples/s lr: 5.34e-04  
[09/22 20:37:55] lb.utils.events INFO:  eta: 8:25:57  iteration: 180799/375342  consumed_samples: 185139200  total_loss: 3.541  time: 0.3419 s/iter  data_time: 0.2263 s/iter total_throughput: 2994.92 samples/s lr: 5.33e-04  
[09/22 20:38:30] lb.utils.events INFO:  eta: 8:24:57  iteration: 180899/375342  consumed_samples: 185241600  total_loss: 3.565  time: 0.3419 s/iter  data_time: 0.2178 s/iter total_throughput: 2994.89 samples/s lr: 5.33e-04  
[09/22 20:39:04] lb.utils.events INFO:  eta: 8:22:45  iteration: 180999/375342  consumed_samples: 185344000  total_loss: 3.586  time: 0.3419 s/iter  data_time: 0.2148 s/iter total_throughput: 2994.89 samples/s lr: 5.33e-04  
[09/22 20:39:39] lb.utils.events INFO:  eta: 8:21:30  iteration: 181099/375342  consumed_samples: 185446400  total_loss: 3.568  time: 0.3419 s/iter  data_time: 0.2223 s/iter total_throughput: 2994.88 samples/s lr: 5.32e-04  
[09/22 20:40:13] lb.utils.events INFO:  eta: 8:21:20  iteration: 181199/375342  consumed_samples: 185548800  total_loss: 3.568  time: 0.3419 s/iter  data_time: 0.2186 s/iter total_throughput: 2994.87 samples/s lr: 5.32e-04  
[09/22 20:40:48] lb.utils.events INFO:  eta: 8:20:41  iteration: 181299/375342  consumed_samples: 185651200  total_loss: 3.587  time: 0.3419 s/iter  data_time: 0.2117 s/iter total_throughput: 2994.85 samples/s lr: 5.31e-04  
[09/22 20:41:22] lb.utils.events INFO:  eta: 8:20:11  iteration: 181399/375342  consumed_samples: 185753600  total_loss: 3.572  time: 0.3419 s/iter  data_time: 0.2158 s/iter total_throughput: 2994.82 samples/s lr: 5.31e-04  
[09/22 20:41:56] lb.utils.events INFO:  eta: 8:20:38  iteration: 181499/375342  consumed_samples: 185856000  total_loss: 3.54  time: 0.3419 s/iter  data_time: 0.2096 s/iter total_throughput: 2994.83 samples/s lr: 5.31e-04  
[09/22 20:42:30] lb.utils.events INFO:  eta: 8:20:09  iteration: 181599/375342  consumed_samples: 185958400  total_loss: 3.526  time: 0.3419 s/iter  data_time: 0.2121 s/iter total_throughput: 2994.84 samples/s lr: 5.30e-04  
[09/22 20:43:05] lb.utils.events INFO:  eta: 8:20:02  iteration: 181699/375342  consumed_samples: 186060800  total_loss: 3.54  time: 0.3419 s/iter  data_time: 0.2054 s/iter total_throughput: 2994.82 samples/s lr: 5.30e-04  
[09/22 20:43:39] lb.utils.events INFO:  eta: 8:19:58  iteration: 181799/375342  consumed_samples: 186163200  total_loss: 3.552  time: 0.3419 s/iter  data_time: 0.2119 s/iter total_throughput: 2994.83 samples/s lr: 5.29e-04  
[09/22 20:44:13] lb.utils.events INFO:  eta: 8:20:36  iteration: 181899/375342  consumed_samples: 186265600  total_loss: 3.573  time: 0.3419 s/iter  data_time: 0.2126 s/iter total_throughput: 2994.83 samples/s lr: 5.29e-04  
[09/22 20:44:47] lb.utils.events INFO:  eta: 8:20:50  iteration: 181999/375342  consumed_samples: 186368000  total_loss: 3.549  time: 0.3419 s/iter  data_time: 0.2209 s/iter total_throughput: 2994.84 samples/s lr: 5.28e-04  
[09/22 20:45:21] lb.utils.events INFO:  eta: 8:21:13  iteration: 182099/375342  consumed_samples: 186470400  total_loss: 3.548  time: 0.3419 s/iter  data_time: 0.2178 s/iter total_throughput: 2994.86 samples/s lr: 5.28e-04  
[09/22 20:45:56] lb.utils.events INFO:  eta: 8:21:33  iteration: 182199/375342  consumed_samples: 186572800  total_loss: 3.566  time: 0.3419 s/iter  data_time: 0.2140 s/iter total_throughput: 2994.80 samples/s lr: 5.28e-04  
[09/22 20:46:32] lb.utils.events INFO:  eta: 8:20:17  iteration: 182299/375342  consumed_samples: 186675200  total_loss: 3.562  time: 0.3419 s/iter  data_time: 0.2266 s/iter total_throughput: 2994.74 samples/s lr: 5.27e-04  
[09/22 20:47:07] lb.utils.events INFO:  eta: 8:19:35  iteration: 182399/375342  consumed_samples: 186777600  total_loss: 3.57  time: 0.3419 s/iter  data_time: 0.2289 s/iter total_throughput: 2994.70 samples/s lr: 5.27e-04  
[09/22 20:47:42] lb.utils.events INFO:  eta: 8:17:49  iteration: 182499/375342  consumed_samples: 186880000  total_loss: 3.581  time: 0.3419 s/iter  data_time: 0.2268 s/iter total_throughput: 2994.65 samples/s lr: 5.26e-04  
[09/22 20:48:17] lb.utils.events INFO:  eta: 8:17:17  iteration: 182599/375342  consumed_samples: 186982400  total_loss: 3.572  time: 0.3419 s/iter  data_time: 0.2248 s/iter total_throughput: 2994.60 samples/s lr: 5.26e-04  
[09/22 20:48:53] lb.utils.events INFO:  eta: 8:17:05  iteration: 182699/375342  consumed_samples: 187084800  total_loss: 3.574  time: 0.3420 s/iter  data_time: 0.2394 s/iter total_throughput: 2994.54 samples/s lr: 5.26e-04  
[09/22 20:49:28] lb.utils.events INFO:  eta: 8:15:54  iteration: 182799/375342  consumed_samples: 187187200  total_loss: 3.572  time: 0.3420 s/iter  data_time: 0.2256 s/iter total_throughput: 2994.48 samples/s lr: 5.25e-04  
[09/22 20:50:03] lb.utils.events INFO:  eta: 8:15:29  iteration: 182899/375342  consumed_samples: 187289600  total_loss: 3.572  time: 0.3420 s/iter  data_time: 0.2215 s/iter total_throughput: 2994.44 samples/s lr: 5.25e-04  
[09/22 20:50:38] lb.utils.events INFO:  eta: 8:15:24  iteration: 182999/375342  consumed_samples: 187392000  total_loss: 3.569  time: 0.3420 s/iter  data_time: 0.2065 s/iter total_throughput: 2994.40 samples/s lr: 5.24e-04  
[09/22 20:51:13] lb.utils.events INFO:  eta: 8:15:13  iteration: 183099/375342  consumed_samples: 187494400  total_loss: 3.537  time: 0.3420 s/iter  data_time: 0.2444 s/iter total_throughput: 2994.36 samples/s lr: 5.24e-04  
[09/22 20:51:49] lb.utils.events INFO:  eta: 8:15:02  iteration: 183199/375342  consumed_samples: 187596800  total_loss: 3.522  time: 0.3420 s/iter  data_time: 0.2233 s/iter total_throughput: 2994.30 samples/s lr: 5.24e-04  
[09/22 20:52:24] lb.utils.events INFO:  eta: 8:15:10  iteration: 183299/375342  consumed_samples: 187699200  total_loss: 3.539  time: 0.3420 s/iter  data_time: 0.2237 s/iter total_throughput: 2994.27 samples/s lr: 5.23e-04  
[09/22 20:52:59] lb.utils.events INFO:  eta: 8:15:39  iteration: 183399/375342  consumed_samples: 187801600  total_loss: 3.551  time: 0.3420 s/iter  data_time: 0.2166 s/iter total_throughput: 2994.22 samples/s lr: 5.23e-04  
[09/22 20:53:35] lb.utils.events INFO:  eta: 8:15:33  iteration: 183499/375342  consumed_samples: 187904000  total_loss: 3.568  time: 0.3420 s/iter  data_time: 0.2295 s/iter total_throughput: 2994.15 samples/s lr: 5.22e-04  
[09/22 20:54:09] lb.utils.events INFO:  eta: 8:15:35  iteration: 183599/375342  consumed_samples: 188006400  total_loss: 3.562  time: 0.3420 s/iter  data_time: 0.2225 s/iter total_throughput: 2994.12 samples/s lr: 5.22e-04  
[09/22 20:54:45] lb.utils.events INFO:  eta: 8:14:24  iteration: 183699/375342  consumed_samples: 188108800  total_loss: 3.546  time: 0.3420 s/iter  data_time: 0.2307 s/iter total_throughput: 2994.08 samples/s lr: 5.21e-04  
[09/22 20:55:19] lb.utils.events INFO:  eta: 8:14:02  iteration: 183799/375342  consumed_samples: 188211200  total_loss: 3.544  time: 0.3420 s/iter  data_time: 0.2299 s/iter total_throughput: 2994.05 samples/s lr: 5.21e-04  
[09/22 20:55:55] lb.utils.events INFO:  eta: 8:13:01  iteration: 183899/375342  consumed_samples: 188313600  total_loss: 3.537  time: 0.3420 s/iter  data_time: 0.2342 s/iter total_throughput: 2994.00 samples/s lr: 5.21e-04  
[09/22 20:56:29] lb.utils.events INFO:  eta: 8:13:08  iteration: 183999/375342  consumed_samples: 188416000  total_loss: 3.535  time: 0.3420 s/iter  data_time: 0.2111 s/iter total_throughput: 2993.98 samples/s lr: 5.20e-04  
[09/22 20:57:04] lb.utils.events INFO:  eta: 8:12:51  iteration: 184099/375342  consumed_samples: 188518400  total_loss: 3.544  time: 0.3420 s/iter  data_time: 0.2238 s/iter total_throughput: 2993.93 samples/s lr: 5.20e-04  
[09/22 20:57:40] lb.utils.events INFO:  eta: 8:12:03  iteration: 184199/375342  consumed_samples: 188620800  total_loss: 3.543  time: 0.3420 s/iter  data_time: 0.2289 s/iter total_throughput: 2993.87 samples/s lr: 5.19e-04  
[09/22 20:58:14] lb.utils.events INFO:  eta: 8:13:44  iteration: 184299/375342  consumed_samples: 188723200  total_loss: 3.547  time: 0.3420 s/iter  data_time: 0.2118 s/iter total_throughput: 2993.86 samples/s lr: 5.19e-04  
[09/22 20:58:49] lb.utils.events INFO:  eta: 8:13:26  iteration: 184399/375342  consumed_samples: 188825600  total_loss: 3.561  time: 0.3420 s/iter  data_time: 0.2192 s/iter total_throughput: 2993.83 samples/s lr: 5.19e-04  
[09/22 20:59:24] lb.utils.events INFO:  eta: 8:13:27  iteration: 184499/375342  consumed_samples: 188928000  total_loss: 3.553  time: 0.3420 s/iter  data_time: 0.2197 s/iter total_throughput: 2993.78 samples/s lr: 5.18e-04  
[09/22 21:00:00] lb.utils.events INFO:  eta: 8:12:55  iteration: 184599/375342  consumed_samples: 189030400  total_loss: 3.538  time: 0.3420 s/iter  data_time: 0.2339 s/iter total_throughput: 2993.72 samples/s lr: 5.18e-04  
[09/22 21:00:35] lb.utils.events INFO:  eta: 8:13:14  iteration: 184699/375342  consumed_samples: 189132800  total_loss: 3.529  time: 0.3421 s/iter  data_time: 0.2249 s/iter total_throughput: 2993.68 samples/s lr: 5.17e-04  
[09/22 21:01:10] lb.utils.events INFO:  eta: 8:13:33  iteration: 184799/375342  consumed_samples: 189235200  total_loss: 3.542  time: 0.3421 s/iter  data_time: 0.2124 s/iter total_throughput: 2993.66 samples/s lr: 5.17e-04  
[09/22 21:01:45] lb.utils.events INFO:  eta: 8:13:24  iteration: 184899/375342  consumed_samples: 189337600  total_loss: 3.555  time: 0.3421 s/iter  data_time: 0.2279 s/iter total_throughput: 2993.60 samples/s lr: 5.16e-04  
[09/22 21:02:21] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0184999
[09/22 21:02:21] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/22 21:02:21] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/22 21:02:25] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0913 s/iter. Inference: 0.1656 s/iter. Eval: 0.0022 s/iter. Total: 0.2590 s/iter. ETA=0:00:09
[09/22 21:02:31] lb.evaluation.evaluator INFO: Inference done 29696/50000. Dataloading: 0.1323 s/iter. Inference: 0.1685 s/iter. Eval: 0.0021 s/iter. Total: 0.3029 s/iter. ETA=0:00:05
[09/22 21:02:36] lb.evaluation.evaluator INFO: Inference done 49152/50000. Dataloading: 0.1208 s/iter. Inference: 0.1647 s/iter. Eval: 0.0020 s/iter. Total: 0.2876 s/iter. ETA=0:00:00
[09/22 21:02:36] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/22 21:02:36] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.664004 (0.000253 s / iter per device, on 8 devices)
[09/22 21:02:36] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000146 s / iter per device, on 8 devices)
[09/22 21:02:36] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/22 21:02:36] lb.evaluation.utils INFO: copypaste: Acc@1=75.21
[09/22 21:02:36] lb.evaluation.utils INFO: copypaste: Acc@5=92.55799999999999
[09/22 21:02:36] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 75.21000, better than last best score 74.57000 @ iteration 179999.
[09/22 21:02:36] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/22 21:02:37] lb.utils.events INFO:  eta: 8:12:30  iteration: 184999/375342  consumed_samples: 189440000  total_loss: 3.554  time: 0.3421 s/iter  data_time: 0.2268 s/iter total_throughput: 2993.55 samples/s lr: 5.16e-04  
[09/22 21:03:10] lb.utils.events INFO:  eta: 8:12:55  iteration: 185099/375342  consumed_samples: 189542400  total_loss: 3.548  time: 0.3421 s/iter  data_time: 0.2398 s/iter total_throughput: 2993.60 samples/s lr: 5.16e-04  
[09/22 21:03:46] lb.utils.events INFO:  eta: 8:13:45  iteration: 185199/375342  consumed_samples: 189644800  total_loss: 3.562  time: 0.3421 s/iter  data_time: 0.2294 s/iter total_throughput: 2993.55 samples/s lr: 5.15e-04  
[09/22 21:04:21] lb.utils.events INFO:  eta: 8:12:15  iteration: 185299/375342  consumed_samples: 189747200  total_loss: 3.54  time: 0.3421 s/iter  data_time: 0.2361 s/iter total_throughput: 2993.51 samples/s lr: 5.15e-04  
[09/22 21:04:56] lb.utils.events INFO:  eta: 8:12:45  iteration: 185399/375342  consumed_samples: 189849600  total_loss: 3.521  time: 0.3421 s/iter  data_time: 0.2099 s/iter total_throughput: 2993.47 samples/s lr: 5.14e-04  
[09/22 21:05:31] lb.utils.events INFO:  eta: 8:11:28  iteration: 185499/375342  consumed_samples: 189952000  total_loss: 3.525  time: 0.3421 s/iter  data_time: 0.2285 s/iter total_throughput: 2993.42 samples/s lr: 5.14e-04  
[09/22 21:06:06] lb.utils.events INFO:  eta: 8:10:36  iteration: 185599/375342  consumed_samples: 190054400  total_loss: 3.542  time: 0.3421 s/iter  data_time: 0.2287 s/iter total_throughput: 2993.37 samples/s lr: 5.14e-04  
[09/22 21:06:41] lb.utils.events INFO:  eta: 8:09:28  iteration: 185699/375342  consumed_samples: 190156800  total_loss: 3.558  time: 0.3421 s/iter  data_time: 0.2303 s/iter total_throughput: 2993.33 samples/s lr: 5.13e-04  
[09/22 21:07:17] lb.utils.events INFO:  eta: 8:09:36  iteration: 185799/375342  consumed_samples: 190259200  total_loss: 3.558  time: 0.3421 s/iter  data_time: 0.2212 s/iter total_throughput: 2993.29 samples/s lr: 5.13e-04  
[09/22 21:07:51] lb.utils.events INFO:  eta: 8:10:13  iteration: 185899/375342  consumed_samples: 190361600  total_loss: 3.542  time: 0.3421 s/iter  data_time: 0.2115 s/iter total_throughput: 2993.25 samples/s lr: 5.12e-04  
[09/22 21:08:26] lb.utils.events INFO:  eta: 8:10:31  iteration: 185999/375342  consumed_samples: 190464000  total_loss: 3.536  time: 0.3421 s/iter  data_time: 0.2166 s/iter total_throughput: 2993.22 samples/s lr: 5.12e-04  
[09/22 21:09:01] lb.utils.events INFO:  eta: 8:08:27  iteration: 186099/375342  consumed_samples: 190566400  total_loss: 3.543  time: 0.3421 s/iter  data_time: 0.2336 s/iter total_throughput: 2993.19 samples/s lr: 5.12e-04  
[09/22 21:09:36] lb.utils.events INFO:  eta: 8:08:07  iteration: 186199/375342  consumed_samples: 190668800  total_loss: 3.54  time: 0.3421 s/iter  data_time: 0.2089 s/iter total_throughput: 2993.17 samples/s lr: 5.11e-04  
[09/22 21:10:11] lb.utils.events INFO:  eta: 8:07:45  iteration: 186299/375342  consumed_samples: 190771200  total_loss: 3.536  time: 0.3421 s/iter  data_time: 0.2233 s/iter total_throughput: 2993.12 samples/s lr: 5.11e-04  
[09/22 21:10:46] lb.utils.events INFO:  eta: 8:07:12  iteration: 186399/375342  consumed_samples: 190873600  total_loss: 3.55  time: 0.3421 s/iter  data_time: 0.2375 s/iter total_throughput: 2993.09 samples/s lr: 5.10e-04  
[09/22 21:11:21] lb.utils.events INFO:  eta: 8:08:32  iteration: 186499/375342  consumed_samples: 190976000  total_loss: 3.544  time: 0.3421 s/iter  data_time: 0.2301 s/iter total_throughput: 2993.05 samples/s lr: 5.10e-04  
[09/22 21:11:56] lb.utils.events INFO:  eta: 8:08:54  iteration: 186599/375342  consumed_samples: 191078400  total_loss: 3.543  time: 0.3421 s/iter  data_time: 0.2330 s/iter total_throughput: 2993.00 samples/s lr: 5.09e-04  
[09/22 21:12:31] lb.utils.events INFO:  eta: 8:08:44  iteration: 186699/375342  consumed_samples: 191180800  total_loss: 3.546  time: 0.3421 s/iter  data_time: 0.2473 s/iter total_throughput: 2992.96 samples/s lr: 5.09e-04  
[09/22 21:13:07] lb.utils.events INFO:  eta: 8:07:41  iteration: 186799/375342  consumed_samples: 191283200  total_loss: 3.543  time: 0.3421 s/iter  data_time: 0.2175 s/iter total_throughput: 2992.91 samples/s lr: 5.09e-04  
[09/22 21:13:42] lb.utils.events INFO:  eta: 8:06:24  iteration: 186899/375342  consumed_samples: 191385600  total_loss: 3.536  time: 0.3421 s/iter  data_time: 0.2307 s/iter total_throughput: 2992.85 samples/s lr: 5.08e-04  
[09/22 21:14:17] lb.utils.events INFO:  eta: 8:05:38  iteration: 186999/375342  consumed_samples: 191488000  total_loss: 3.525  time: 0.3422 s/iter  data_time: 0.2271 s/iter total_throughput: 2992.81 samples/s lr: 5.08e-04  
[09/22 21:14:53] lb.utils.events INFO:  eta: 8:05:26  iteration: 187099/375342  consumed_samples: 191590400  total_loss: 3.529  time: 0.3422 s/iter  data_time: 0.2468 s/iter total_throughput: 2992.76 samples/s lr: 5.07e-04  
[09/22 21:15:27] lb.utils.events INFO:  eta: 8:04:44  iteration: 187199/375342  consumed_samples: 191692800  total_loss: 3.547  time: 0.3422 s/iter  data_time: 0.2181 s/iter total_throughput: 2992.73 samples/s lr: 5.07e-04  
[09/22 21:16:03] lb.utils.events INFO:  eta: 8:06:07  iteration: 187299/375342  consumed_samples: 191795200  total_loss: 3.554  time: 0.3422 s/iter  data_time: 0.2478 s/iter total_throughput: 2992.69 samples/s lr: 5.07e-04  
[09/22 21:16:38] lb.utils.events INFO:  eta: 8:04:08  iteration: 187399/375342  consumed_samples: 191897600  total_loss: 3.551  time: 0.3422 s/iter  data_time: 0.2267 s/iter total_throughput: 2992.63 samples/s lr: 5.06e-04  
[09/22 21:17:13] lb.utils.events INFO:  eta: 8:03:14  iteration: 187499/375342  consumed_samples: 192000000  total_loss: 3.544  time: 0.3422 s/iter  data_time: 0.2255 s/iter total_throughput: 2992.59 samples/s lr: 5.06e-04  
[09/22 21:17:49] lb.utils.events INFO:  eta: 8:01:32  iteration: 187599/375342  consumed_samples: 192102400  total_loss: 3.54  time: 0.3422 s/iter  data_time: 0.2204 s/iter total_throughput: 2992.53 samples/s lr: 5.05e-04  
[09/22 21:18:23] lb.utils.events INFO:  eta: 8:01:34  iteration: 187699/375342  consumed_samples: 192204800  total_loss: 3.552  time: 0.3422 s/iter  data_time: 0.2141 s/iter total_throughput: 2992.51 samples/s lr: 5.05e-04  
[09/22 21:18:58] lb.utils.events INFO:  eta: 8:02:49  iteration: 187799/375342  consumed_samples: 192307200  total_loss: 3.546  time: 0.3422 s/iter  data_time: 0.2174 s/iter total_throughput: 2992.48 samples/s lr: 5.04e-04  
[09/22 21:19:33] lb.utils.events INFO:  eta: 8:03:41  iteration: 187899/375342  consumed_samples: 192409600  total_loss: 3.515  time: 0.3422 s/iter  data_time: 0.2255 s/iter total_throughput: 2992.46 samples/s lr: 5.04e-04  
[09/22 21:20:08] lb.utils.events INFO:  eta: 8:02:34  iteration: 187999/375342  consumed_samples: 192512000  total_loss: 3.519  time: 0.3422 s/iter  data_time: 0.2402 s/iter total_throughput: 2992.40 samples/s lr: 5.04e-04  
[09/22 21:20:43] lb.utils.events INFO:  eta: 8:01:52  iteration: 188099/375342  consumed_samples: 192614400  total_loss: 3.527  time: 0.3422 s/iter  data_time: 0.2204 s/iter total_throughput: 2992.36 samples/s lr: 5.03e-04  
[09/22 21:21:18] lb.utils.events INFO:  eta: 8:04:16  iteration: 188199/375342  consumed_samples: 192716800  total_loss: 3.538  time: 0.3422 s/iter  data_time: 0.2136 s/iter total_throughput: 2992.35 samples/s lr: 5.03e-04  
[09/22 21:21:53] lb.utils.events INFO:  eta: 8:02:14  iteration: 188299/375342  consumed_samples: 192819200  total_loss: 3.551  time: 0.3422 s/iter  data_time: 0.2221 s/iter total_throughput: 2992.32 samples/s lr: 5.02e-04  
[09/22 21:22:27] lb.utils.events INFO:  eta: 8:04:25  iteration: 188399/375342  consumed_samples: 192921600  total_loss: 3.541  time: 0.3422 s/iter  data_time: 0.2207 s/iter total_throughput: 2992.30 samples/s lr: 5.02e-04  
[09/22 21:23:03] lb.utils.events INFO:  eta: 8:03:49  iteration: 188499/375342  consumed_samples: 193024000  total_loss: 3.541  time: 0.3422 s/iter  data_time: 0.2213 s/iter total_throughput: 2992.25 samples/s lr: 5.02e-04  
[09/22 21:23:38] lb.utils.events INFO:  eta: 8:03:55  iteration: 188599/375342  consumed_samples: 193126400  total_loss: 3.544  time: 0.3422 s/iter  data_time: 0.2238 s/iter total_throughput: 2992.22 samples/s lr: 5.01e-04  
[09/22 21:24:12] lb.utils.events INFO:  eta: 8:03:41  iteration: 188699/375342  consumed_samples: 193228800  total_loss: 3.541  time: 0.3422 s/iter  data_time: 0.2308 s/iter total_throughput: 2992.19 samples/s lr: 5.01e-04  
[09/22 21:24:47] lb.utils.events INFO:  eta: 8:02:35  iteration: 188799/375342  consumed_samples: 193331200  total_loss: 3.548  time: 0.3422 s/iter  data_time: 0.2241 s/iter total_throughput: 2992.17 samples/s lr: 5.00e-04  
[09/22 21:25:22] lb.utils.events INFO:  eta: 8:01:08  iteration: 188899/375342  consumed_samples: 193433600  total_loss: 3.556  time: 0.3422 s/iter  data_time: 0.2186 s/iter total_throughput: 2992.15 samples/s lr: 5.00e-04  
[09/22 21:25:57] lb.utils.events INFO:  eta: 8:02:22  iteration: 188999/375342  consumed_samples: 193536000  total_loss: 3.529  time: 0.3422 s/iter  data_time: 0.2228 s/iter total_throughput: 2992.11 samples/s lr: 4.99e-04  
[09/22 21:26:32] lb.utils.events INFO:  eta: 8:02:24  iteration: 189099/375342  consumed_samples: 193638400  total_loss: 3.51  time: 0.3422 s/iter  data_time: 0.2176 s/iter total_throughput: 2992.09 samples/s lr: 4.99e-04  
[09/22 21:27:07] lb.utils.events INFO:  eta: 8:02:04  iteration: 189199/375342  consumed_samples: 193740800  total_loss: 3.541  time: 0.3422 s/iter  data_time: 0.2232 s/iter total_throughput: 2992.04 samples/s lr: 4.99e-04  
[09/22 21:27:42] lb.utils.events INFO:  eta: 8:01:53  iteration: 189299/375342  consumed_samples: 193843200  total_loss: 3.535  time: 0.3422 s/iter  data_time: 0.2292 s/iter total_throughput: 2992.01 samples/s lr: 4.98e-04  
[09/22 21:28:17] lb.utils.events INFO:  eta: 8:01:08  iteration: 189399/375342  consumed_samples: 193945600  total_loss: 3.546  time: 0.3422 s/iter  data_time: 0.2214 s/iter total_throughput: 2991.97 samples/s lr: 4.98e-04  
[09/22 21:28:52] lb.utils.events INFO:  eta: 8:01:48  iteration: 189499/375342  consumed_samples: 194048000  total_loss: 3.517  time: 0.3423 s/iter  data_time: 0.2254 s/iter total_throughput: 2991.92 samples/s lr: 4.97e-04  
[09/22 21:29:27] lb.utils.events INFO:  eta: 8:03:13  iteration: 189599/375342  consumed_samples: 194150400  total_loss: 3.501  time: 0.3423 s/iter  data_time: 0.2254 s/iter total_throughput: 2991.90 samples/s lr: 4.97e-04  
[09/22 21:30:01] lb.utils.events INFO:  eta: 8:01:46  iteration: 189699/375342  consumed_samples: 194252800  total_loss: 3.524  time: 0.3423 s/iter  data_time: 0.2065 s/iter total_throughput: 2991.89 samples/s lr: 4.97e-04  
[09/22 21:30:36] lb.utils.events INFO:  eta: 8:02:15  iteration: 189799/375342  consumed_samples: 194355200  total_loss: 3.519  time: 0.3423 s/iter  data_time: 0.2219 s/iter total_throughput: 2991.87 samples/s lr: 4.96e-04  
[09/22 21:31:11] lb.utils.events INFO:  eta: 8:02:13  iteration: 189899/375342  consumed_samples: 194457600  total_loss: 3.531  time: 0.3423 s/iter  data_time: 0.2232 s/iter total_throughput: 2991.85 samples/s lr: 4.96e-04  
[09/22 21:31:46] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0189999
[09/22 21:31:46] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/22 21:31:46] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/22 21:31:50] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0983 s/iter. Inference: 0.1623 s/iter. Eval: 0.0020 s/iter. Total: 0.2626 s/iter. ETA=0:00:09
[09/22 21:31:55] lb.evaluation.evaluator INFO: Inference done 28672/50000. Dataloading: 0.0943 s/iter. Inference: 0.1927 s/iter. Eval: 0.0020 s/iter. Total: 0.2891 s/iter. ETA=0:00:05
[09/22 21:32:01] lb.evaluation.evaluator INFO: Inference done 46080/50000. Dataloading: 0.0909 s/iter. Inference: 0.2002 s/iter. Eval: 0.0020 s/iter. Total: 0.2932 s/iter. ETA=0:00:00
[09/22 21:32:01] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/22 21:32:01] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.663567 (0.000253 s / iter per device, on 8 devices)
[09/22 21:32:01] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:08 (0.000177 s / iter per device, on 8 devices)
[09/22 21:32:01] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/22 21:32:01] lb.evaluation.utils INFO: copypaste: Acc@1=75.166
[09/22 21:32:01] lb.evaluation.utils INFO: copypaste: Acc@5=92.586
[09/22 21:32:01] lb.engine.hooks INFO: Not saving as latest eval score for Acc@1 is 75.16600, not better than best score 75.21000 @ iteration 184999.
[09/22 21:32:01] lb.utils.events INFO:  eta: 8:00:59  iteration: 189999/375342  consumed_samples: 194560000  total_loss: 3.531  time: 0.3423 s/iter  data_time: 0.2148 s/iter total_throughput: 2991.82 samples/s lr: 4.95e-04  
[09/22 21:32:34] lb.utils.events INFO:  eta: 8:03:12  iteration: 190099/375342  consumed_samples: 194662400  total_loss: 3.537  time: 0.3423 s/iter  data_time: 0.2180 s/iter total_throughput: 2991.89 samples/s lr: 4.95e-04  
[09/22 21:33:09] lb.utils.events INFO:  eta: 8:02:10  iteration: 190199/375342  consumed_samples: 194764800  total_loss: 3.526  time: 0.3423 s/iter  data_time: 0.2287 s/iter total_throughput: 2991.85 samples/s lr: 4.95e-04  
[09/22 21:33:44] lb.utils.events INFO:  eta: 8:00:53  iteration: 190299/375342  consumed_samples: 194867200  total_loss: 3.522  time: 0.3423 s/iter  data_time: 0.2197 s/iter total_throughput: 2991.84 samples/s lr: 4.94e-04  
[09/22 21:34:18] lb.utils.events INFO:  eta: 8:00:54  iteration: 190399/375342  consumed_samples: 194969600  total_loss: 3.527  time: 0.3423 s/iter  data_time: 0.2224 s/iter total_throughput: 2991.84 samples/s lr: 4.94e-04  
[09/22 21:34:53] lb.utils.events INFO:  eta: 8:00:55  iteration: 190499/375342  consumed_samples: 195072000  total_loss: 3.52  time: 0.3423 s/iter  data_time: 0.2249 s/iter total_throughput: 2991.83 samples/s lr: 4.93e-04  
[09/22 21:35:27] lb.utils.events INFO:  eta: 8:00:40  iteration: 190599/375342  consumed_samples: 195174400  total_loss: 3.518  time: 0.3423 s/iter  data_time: 0.2171 s/iter total_throughput: 2991.80 samples/s lr: 4.93e-04  
[09/22 21:36:02] lb.utils.events INFO:  eta: 8:00:57  iteration: 190699/375342  consumed_samples: 195276800  total_loss: 3.525  time: 0.3423 s/iter  data_time: 0.2101 s/iter total_throughput: 2991.79 samples/s lr: 4.92e-04  
[09/22 21:36:36] lb.utils.events INFO:  eta: 7:59:55  iteration: 190799/375342  consumed_samples: 195379200  total_loss: 3.549  time: 0.3423 s/iter  data_time: 0.2260 s/iter total_throughput: 2991.77 samples/s lr: 4.92e-04  
[09/22 21:37:11] lb.utils.events INFO:  eta: 7:59:27  iteration: 190899/375342  consumed_samples: 195481600  total_loss: 3.519  time: 0.3423 s/iter  data_time: 0.2343 s/iter total_throughput: 2991.74 samples/s lr: 4.92e-04  
[09/22 21:37:46] lb.utils.events INFO:  eta: 7:59:15  iteration: 190999/375342  consumed_samples: 195584000  total_loss: 3.526  time: 0.3423 s/iter  data_time: 0.2129 s/iter total_throughput: 2991.73 samples/s lr: 4.91e-04  
[09/22 21:38:20] lb.utils.events INFO:  eta: 7:58:20  iteration: 191099/375342  consumed_samples: 195686400  total_loss: 3.547  time: 0.3423 s/iter  data_time: 0.2159 s/iter total_throughput: 2991.74 samples/s lr: 4.91e-04  
[09/22 21:38:55] lb.utils.events INFO:  eta: 7:58:09  iteration: 191199/375342  consumed_samples: 195788800  total_loss: 3.534  time: 0.3423 s/iter  data_time: 0.2369 s/iter total_throughput: 2991.70 samples/s lr: 4.90e-04  
[09/22 21:39:29] lb.utils.events INFO:  eta: 7:57:49  iteration: 191299/375342  consumed_samples: 195891200  total_loss: 3.542  time: 0.3423 s/iter  data_time: 0.2063 s/iter total_throughput: 2991.70 samples/s lr: 4.90e-04  
[09/22 21:40:04] lb.utils.events INFO:  eta: 7:55:50  iteration: 191399/375342  consumed_samples: 195993600  total_loss: 3.55  time: 0.3423 s/iter  data_time: 0.2146 s/iter total_throughput: 2991.66 samples/s lr: 4.90e-04  
[09/22 21:40:39] lb.utils.events INFO:  eta: 7:55:27  iteration: 191499/375342  consumed_samples: 196096000  total_loss: 3.523  time: 0.3423 s/iter  data_time: 0.2070 s/iter total_throughput: 2991.63 samples/s lr: 4.89e-04  
[09/22 21:41:14] lb.utils.events INFO:  eta: 7:53:58  iteration: 191599/375342  consumed_samples: 196198400  total_loss: 3.522  time: 0.3423 s/iter  data_time: 0.2239 s/iter total_throughput: 2991.59 samples/s lr: 4.89e-04  
[09/22 21:41:49] lb.utils.events INFO:  eta: 7:53:39  iteration: 191699/375342  consumed_samples: 196300800  total_loss: 3.519  time: 0.3423 s/iter  data_time: 0.2273 s/iter total_throughput: 2991.58 samples/s lr: 4.88e-04  
[09/22 21:42:23] lb.utils.events INFO:  eta: 7:55:27  iteration: 191799/375342  consumed_samples: 196403200  total_loss: 3.51  time: 0.3423 s/iter  data_time: 0.2106 s/iter total_throughput: 2991.58 samples/s lr: 4.88e-04  
[09/22 21:42:58] lb.utils.events INFO:  eta: 7:56:24  iteration: 191899/375342  consumed_samples: 196505600  total_loss: 3.52  time: 0.3423 s/iter  data_time: 0.2226 s/iter total_throughput: 2991.57 samples/s lr: 4.87e-04  
[09/22 21:43:33] lb.utils.events INFO:  eta: 7:55:48  iteration: 191999/375342  consumed_samples: 196608000  total_loss: 3.524  time: 0.3423 s/iter  data_time: 0.2264 s/iter total_throughput: 2991.53 samples/s lr: 4.87e-04  
[09/22 21:44:07] lb.utils.events INFO:  eta: 7:54:34  iteration: 192099/375342  consumed_samples: 196710400  total_loss: 3.529  time: 0.3423 s/iter  data_time: 0.2149 s/iter total_throughput: 2991.51 samples/s lr: 4.87e-04  
[09/22 21:44:42] lb.utils.events INFO:  eta: 7:54:08  iteration: 192199/375342  consumed_samples: 196812800  total_loss: 3.536  time: 0.3423 s/iter  data_time: 0.2181 s/iter total_throughput: 2991.51 samples/s lr: 4.86e-04  
[09/22 21:45:17] lb.utils.events INFO:  eta: 7:53:59  iteration: 192299/375342  consumed_samples: 196915200  total_loss: 3.513  time: 0.3423 s/iter  data_time: 0.2342 s/iter total_throughput: 2991.47 samples/s lr: 4.86e-04  
[09/22 21:45:51] lb.utils.events INFO:  eta: 7:54:50  iteration: 192399/375342  consumed_samples: 197017600  total_loss: 3.511  time: 0.3423 s/iter  data_time: 0.2069 s/iter total_throughput: 2991.46 samples/s lr: 4.85e-04  
[09/22 21:46:26] lb.utils.events INFO:  eta: 7:54:22  iteration: 192499/375342  consumed_samples: 197120000  total_loss: 3.53  time: 0.3423 s/iter  data_time: 0.2272 s/iter total_throughput: 2991.42 samples/s lr: 4.85e-04  
[09/22 21:47:00] lb.utils.events INFO:  eta: 7:55:25  iteration: 192599/375342  consumed_samples: 197222400  total_loss: 3.531  time: 0.3423 s/iter  data_time: 0.2180 s/iter total_throughput: 2991.43 samples/s lr: 4.85e-04  
[09/22 21:47:35] lb.utils.events INFO:  eta: 7:54:15  iteration: 192699/375342  consumed_samples: 197324800  total_loss: 3.516  time: 0.3423 s/iter  data_time: 0.2216 s/iter total_throughput: 2991.42 samples/s lr: 4.84e-04  
[09/22 21:48:09] lb.utils.events INFO:  eta: 7:53:38  iteration: 192799/375342  consumed_samples: 197427200  total_loss: 3.52  time: 0.3423 s/iter  data_time: 0.2113 s/iter total_throughput: 2991.41 samples/s lr: 4.84e-04  
[09/22 21:48:43] lb.utils.events INFO:  eta: 7:53:26  iteration: 192899/375342  consumed_samples: 197529600  total_loss: 3.52  time: 0.3423 s/iter  data_time: 0.2139 s/iter total_throughput: 2991.41 samples/s lr: 4.83e-04  
[09/22 21:49:18] lb.utils.events INFO:  eta: 7:53:34  iteration: 192999/375342  consumed_samples: 197632000  total_loss: 3.51  time: 0.3423 s/iter  data_time: 0.2129 s/iter total_throughput: 2991.40 samples/s lr: 4.83e-04  
[09/22 21:49:52] lb.utils.events INFO:  eta: 7:53:34  iteration: 193099/375342  consumed_samples: 197734400  total_loss: 3.508  time: 0.3423 s/iter  data_time: 0.2230 s/iter total_throughput: 2991.40 samples/s lr: 4.83e-04  
[09/22 21:50:27] lb.utils.events INFO:  eta: 7:53:32  iteration: 193199/375342  consumed_samples: 197836800  total_loss: 3.522  time: 0.3423 s/iter  data_time: 0.2153 s/iter total_throughput: 2991.38 samples/s lr: 4.82e-04  
[09/22 21:51:01] lb.utils.events INFO:  eta: 7:52:37  iteration: 193299/375342  consumed_samples: 197939200  total_loss: 3.499  time: 0.3423 s/iter  data_time: 0.2173 s/iter total_throughput: 2991.37 samples/s lr: 4.82e-04  
[09/22 21:51:36] lb.utils.events INFO:  eta: 7:52:08  iteration: 193399/375342  consumed_samples: 198041600  total_loss: 3.499  time: 0.3423 s/iter  data_time: 0.2213 s/iter total_throughput: 2991.35 samples/s lr: 4.81e-04  
[09/22 21:52:10] lb.utils.events INFO:  eta: 7:52:12  iteration: 193499/375342  consumed_samples: 198144000  total_loss: 3.527  time: 0.3423 s/iter  data_time: 0.2043 s/iter total_throughput: 2991.34 samples/s lr: 4.81e-04  
[09/22 21:52:45] lb.utils.events INFO:  eta: 7:51:30  iteration: 193599/375342  consumed_samples: 198246400  total_loss: 3.52  time: 0.3423 s/iter  data_time: 0.2257 s/iter total_throughput: 2991.31 samples/s lr: 4.80e-04  
[09/22 21:53:20] lb.utils.events INFO:  eta: 7:51:33  iteration: 193699/375342  consumed_samples: 198348800  total_loss: 3.51  time: 0.3423 s/iter  data_time: 0.2197 s/iter total_throughput: 2991.30 samples/s lr: 4.80e-04  
[09/22 21:53:54] lb.utils.events INFO:  eta: 7:50:35  iteration: 193799/375342  consumed_samples: 198451200  total_loss: 3.519  time: 0.3423 s/iter  data_time: 0.2177 s/iter total_throughput: 2991.28 samples/s lr: 4.80e-04  
[09/22 21:54:29] lb.utils.events INFO:  eta: 7:48:57  iteration: 193899/375342  consumed_samples: 198553600  total_loss: 3.515  time: 0.3423 s/iter  data_time: 0.2240 s/iter total_throughput: 2991.26 samples/s lr: 4.79e-04  
[09/22 21:55:04] lb.utils.events INFO:  eta: 7:48:33  iteration: 193999/375342  consumed_samples: 198656000  total_loss: 3.519  time: 0.3423 s/iter  data_time: 0.2185 s/iter total_throughput: 2991.24 samples/s lr: 4.79e-04  
[09/22 21:55:39] lb.utils.events INFO:  eta: 7:47:14  iteration: 194099/375342  consumed_samples: 198758400  total_loss: 3.527  time: 0.3423 s/iter  data_time: 0.2321 s/iter total_throughput: 2991.20 samples/s lr: 4.78e-04  
[09/22 21:56:14] lb.utils.events INFO:  eta: 7:46:28  iteration: 194199/375342  consumed_samples: 198860800  total_loss: 3.516  time: 0.3423 s/iter  data_time: 0.2212 s/iter total_throughput: 2991.17 samples/s lr: 4.78e-04  
[09/22 21:56:48] lb.utils.events INFO:  eta: 7:47:17  iteration: 194299/375342  consumed_samples: 198963200  total_loss: 3.503  time: 0.3423 s/iter  data_time: 0.2245 s/iter total_throughput: 2991.16 samples/s lr: 4.78e-04  
[09/22 21:57:23] lb.utils.events INFO:  eta: 7:45:24  iteration: 194399/375342  consumed_samples: 199065600  total_loss: 3.514  time: 0.3423 s/iter  data_time: 0.2186 s/iter total_throughput: 2991.14 samples/s lr: 4.77e-04  
[09/22 21:57:57] lb.utils.events INFO:  eta: 7:46:53  iteration: 194499/375342  consumed_samples: 199168000  total_loss: 3.512  time: 0.3423 s/iter  data_time: 0.2055 s/iter total_throughput: 2991.13 samples/s lr: 4.77e-04  
[09/22 21:58:32] lb.utils.events INFO:  eta: 7:47:28  iteration: 194599/375342  consumed_samples: 199270400  total_loss: 3.512  time: 0.3423 s/iter  data_time: 0.2026 s/iter total_throughput: 2991.13 samples/s lr: 4.76e-04  
[09/22 21:59:06] lb.utils.events INFO:  eta: 7:47:16  iteration: 194699/375342  consumed_samples: 199372800  total_loss: 3.515  time: 0.3423 s/iter  data_time: 0.2263 s/iter total_throughput: 2991.12 samples/s lr: 4.76e-04  
[09/22 21:59:41] lb.utils.events INFO:  eta: 7:47:35  iteration: 194799/375342  consumed_samples: 199475200  total_loss: 3.521  time: 0.3423 s/iter  data_time: 0.2189 s/iter total_throughput: 2991.10 samples/s lr: 4.75e-04  
[09/22 22:00:15] lb.utils.events INFO:  eta: 7:49:12  iteration: 194899/375342  consumed_samples: 199577600  total_loss: 3.539  time: 0.3423 s/iter  data_time: 0.2204 s/iter total_throughput: 2991.11 samples/s lr: 4.75e-04  
[09/22 22:00:49] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0194999
[09/22 22:00:50] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/22 22:00:50] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/22 22:00:54] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0920 s/iter. Inference: 0.1639 s/iter. Eval: 0.0022 s/iter. Total: 0.2581 s/iter. ETA=0:00:09
[09/22 22:01:00] lb.evaluation.evaluator INFO: Inference done 29696/50000. Dataloading: 0.1352 s/iter. Inference: 0.1648 s/iter. Eval: 0.0021 s/iter. Total: 0.3021 s/iter. ETA=0:00:05
[09/22 22:01:05] lb.evaluation.evaluator INFO: Inference done 49152/50000. Dataloading: 0.1201 s/iter. Inference: 0.1630 s/iter. Eval: 0.0021 s/iter. Total: 0.2853 s/iter. ETA=0:00:00
[09/22 22:01:05] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/22 22:01:05] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.727652 (0.000255 s / iter per device, on 8 devices)
[09/22 22:01:05] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000144 s / iter per device, on 8 devices)
[09/22 22:01:05] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/22 22:01:05] lb.evaluation.utils INFO: copypaste: Acc@1=75.36
[09/22 22:01:05] lb.evaluation.utils INFO: copypaste: Acc@5=92.80199999999999
[09/22 22:01:05] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 75.36000, better than last best score 75.21000 @ iteration 184999.
[09/22 22:01:05] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/22 22:01:06] lb.utils.events INFO:  eta: 7:48:51  iteration: 194999/375342  consumed_samples: 199680000  total_loss: 3.523  time: 0.3423 s/iter  data_time: 0.2130 s/iter total_throughput: 2991.11 samples/s lr: 4.75e-04  
[09/22 22:01:38] lb.utils.events INFO:  eta: 7:49:51  iteration: 195099/375342  consumed_samples: 199782400  total_loss: 3.515  time: 0.3423 s/iter  data_time: 0.2105 s/iter total_throughput: 2991.19 samples/s lr: 4.74e-04  
[09/22 22:02:13] lb.utils.events INFO:  eta: 7:49:46  iteration: 195199/375342  consumed_samples: 199884800  total_loss: 3.514  time: 0.3423 s/iter  data_time: 0.2091 s/iter total_throughput: 2991.19 samples/s lr: 4.74e-04  
[09/22 22:02:47] lb.utils.events INFO:  eta: 7:49:43  iteration: 195299/375342  consumed_samples: 199987200  total_loss: 3.508  time: 0.3423 s/iter  data_time: 0.2109 s/iter total_throughput: 2991.19 samples/s lr: 4.73e-04  
[09/22 22:03:21] lb.utils.events INFO:  eta: 7:50:05  iteration: 195399/375342  consumed_samples: 200089600  total_loss: 3.497  time: 0.3423 s/iter  data_time: 0.2145 s/iter total_throughput: 2991.18 samples/s lr: 4.73e-04  
[09/22 22:03:55] lb.utils.events INFO:  eta: 7:49:04  iteration: 195499/375342  consumed_samples: 200192000  total_loss: 3.499  time: 0.3423 s/iter  data_time: 0.2219 s/iter total_throughput: 2991.20 samples/s lr: 4.73e-04  
[09/22 22:04:30] lb.utils.events INFO:  eta: 7:48:26  iteration: 195599/375342  consumed_samples: 200294400  total_loss: 3.514  time: 0.3423 s/iter  data_time: 0.2133 s/iter total_throughput: 2991.19 samples/s lr: 4.72e-04  
[09/22 22:05:03] lb.utils.events INFO:  eta: 7:48:13  iteration: 195699/375342  consumed_samples: 200396800  total_loss: 3.527  time: 0.3423 s/iter  data_time: 0.2101 s/iter total_throughput: 2991.22 samples/s lr: 4.72e-04  
[09/22 22:05:37] lb.utils.events INFO:  eta: 7:48:20  iteration: 195799/375342  consumed_samples: 200499200  total_loss: 3.523  time: 0.3423 s/iter  data_time: 0.2164 s/iter total_throughput: 2991.22 samples/s lr: 4.71e-04  
[09/22 22:06:11] lb.utils.events INFO:  eta: 7:47:13  iteration: 195899/375342  consumed_samples: 200601600  total_loss: 3.499  time: 0.3423 s/iter  data_time: 0.2122 s/iter total_throughput: 2991.23 samples/s lr: 4.71e-04  
[09/22 22:06:46] lb.utils.events INFO:  eta: 7:47:48  iteration: 195999/375342  consumed_samples: 200704000  total_loss: 3.514  time: 0.3423 s/iter  data_time: 0.2117 s/iter total_throughput: 2991.23 samples/s lr: 4.71e-04  
[09/22 22:07:20] lb.utils.events INFO:  eta: 7:46:16  iteration: 196099/375342  consumed_samples: 200806400  total_loss: 3.521  time: 0.3423 s/iter  data_time: 0.2099 s/iter total_throughput: 2991.24 samples/s lr: 4.70e-04  
[09/22 22:07:54] lb.utils.events INFO:  eta: 7:44:46  iteration: 196199/375342  consumed_samples: 200908800  total_loss: 3.506  time: 0.3423 s/iter  data_time: 0.2124 s/iter total_throughput: 2991.24 samples/s lr: 4.70e-04  
[09/22 22:08:29] lb.utils.events INFO:  eta: 7:44:16  iteration: 196299/375342  consumed_samples: 201011200  total_loss: 3.503  time: 0.3423 s/iter  data_time: 0.2152 s/iter total_throughput: 2991.21 samples/s lr: 4.69e-04  
[09/22 22:09:04] lb.utils.events INFO:  eta: 7:43:52  iteration: 196399/375342  consumed_samples: 201113600  total_loss: 3.515  time: 0.3423 s/iter  data_time: 0.2263 s/iter total_throughput: 2991.18 samples/s lr: 4.69e-04  
[09/22 22:09:38] lb.utils.events INFO:  eta: 7:44:02  iteration: 196499/375342  consumed_samples: 201216000  total_loss: 3.502  time: 0.3423 s/iter  data_time: 0.2241 s/iter total_throughput: 2991.16 samples/s lr: 4.68e-04  
[09/22 22:10:14] lb.utils.events INFO:  eta: 7:44:40  iteration: 196599/375342  consumed_samples: 201318400  total_loss: 3.485  time: 0.3423 s/iter  data_time: 0.2200 s/iter total_throughput: 2991.12 samples/s lr: 4.68e-04  
[09/22 22:10:49] lb.utils.events INFO:  eta: 7:43:25  iteration: 196699/375342  consumed_samples: 201420800  total_loss: 3.495  time: 0.3424 s/iter  data_time: 0.2286 s/iter total_throughput: 2991.08 samples/s lr: 4.68e-04  
[09/22 22:11:24] lb.utils.events INFO:  eta: 7:42:35  iteration: 196799/375342  consumed_samples: 201523200  total_loss: 3.497  time: 0.3424 s/iter  data_time: 0.2235 s/iter total_throughput: 2991.04 samples/s lr: 4.67e-04  
[09/22 22:11:59] lb.utils.events INFO:  eta: 7:42:20  iteration: 196899/375342  consumed_samples: 201625600  total_loss: 3.512  time: 0.3424 s/iter  data_time: 0.2266 s/iter total_throughput: 2991.00 samples/s lr: 4.67e-04  
[09/22 22:12:34] lb.utils.events INFO:  eta: 7:41:45  iteration: 196999/375342  consumed_samples: 201728000  total_loss: 3.523  time: 0.3424 s/iter  data_time: 0.2188 s/iter total_throughput: 2990.96 samples/s lr: 4.66e-04  
[09/22 22:13:09] lb.utils.events INFO:  eta: 7:41:01  iteration: 197099/375342  consumed_samples: 201830400  total_loss: 3.516  time: 0.3424 s/iter  data_time: 0.2333 s/iter total_throughput: 2990.91 samples/s lr: 4.66e-04  
[09/22 22:13:44] lb.utils.events INFO:  eta: 7:40:30  iteration: 197199/375342  consumed_samples: 201932800  total_loss: 3.503  time: 0.3424 s/iter  data_time: 0.2183 s/iter total_throughput: 2990.88 samples/s lr: 4.66e-04  
[09/22 22:14:19] lb.utils.events INFO:  eta: 7:40:32  iteration: 197299/375342  consumed_samples: 202035200  total_loss: 3.514  time: 0.3424 s/iter  data_time: 0.2186 s/iter total_throughput: 2990.85 samples/s lr: 4.65e-04  
[09/22 22:14:55] lb.utils.events INFO:  eta: 7:40:49  iteration: 197399/375342  consumed_samples: 202137600  total_loss: 3.526  time: 0.3424 s/iter  data_time: 0.2336 s/iter total_throughput: 2990.81 samples/s lr: 4.65e-04  
[09/22 22:15:30] lb.utils.events INFO:  eta: 7:38:13  iteration: 197499/375342  consumed_samples: 202240000  total_loss: 3.529  time: 0.3424 s/iter  data_time: 0.2342 s/iter total_throughput: 2990.76 samples/s lr: 4.64e-04  
[09/22 22:16:05] lb.utils.events INFO:  eta: 7:37:26  iteration: 197599/375342  consumed_samples: 202342400  total_loss: 3.518  time: 0.3424 s/iter  data_time: 0.2348 s/iter total_throughput: 2990.71 samples/s lr: 4.64e-04  
[09/22 22:16:40] lb.utils.events INFO:  eta: 7:36:55  iteration: 197699/375342  consumed_samples: 202444800  total_loss: 3.503  time: 0.3424 s/iter  data_time: 0.2247 s/iter total_throughput: 2990.68 samples/s lr: 4.64e-04  
[09/22 22:17:15] lb.utils.events INFO:  eta: 7:36:00  iteration: 197799/375342  consumed_samples: 202547200  total_loss: 3.515  time: 0.3424 s/iter  data_time: 0.2230 s/iter total_throughput: 2990.65 samples/s lr: 4.63e-04  
[09/22 22:17:50] lb.utils.events INFO:  eta: 7:35:02  iteration: 197899/375342  consumed_samples: 202649600  total_loss: 3.495  time: 0.3424 s/iter  data_time: 0.2217 s/iter total_throughput: 2990.60 samples/s lr: 4.63e-04  
[09/22 22:18:26] lb.utils.events INFO:  eta: 7:34:27  iteration: 197999/375342  consumed_samples: 202752000  total_loss: 3.477  time: 0.3424 s/iter  data_time: 0.2297 s/iter total_throughput: 2990.56 samples/s lr: 4.62e-04  
[09/22 22:19:01] lb.utils.events INFO:  eta: 7:33:16  iteration: 198099/375342  consumed_samples: 202854400  total_loss: 3.498  time: 0.3424 s/iter  data_time: 0.2248 s/iter total_throughput: 2990.53 samples/s lr: 4.62e-04  
[09/22 22:19:36] lb.utils.events INFO:  eta: 7:33:25  iteration: 198199/375342  consumed_samples: 202956800  total_loss: 3.503  time: 0.3424 s/iter  data_time: 0.2283 s/iter total_throughput: 2990.49 samples/s lr: 4.61e-04  
[09/22 22:20:10] lb.utils.events INFO:  eta: 7:32:54  iteration: 198299/375342  consumed_samples: 203059200  total_loss: 3.506  time: 0.3424 s/iter  data_time: 0.2201 s/iter total_throughput: 2990.47 samples/s lr: 4.61e-04  
[09/22 22:20:45] lb.utils.events INFO:  eta: 7:32:43  iteration: 198399/375342  consumed_samples: 203161600  total_loss: 3.494  time: 0.3424 s/iter  data_time: 0.2294 s/iter total_throughput: 2990.44 samples/s lr: 4.61e-04  
[09/22 22:21:20] lb.utils.events INFO:  eta: 7:32:59  iteration: 198499/375342  consumed_samples: 203264000  total_loss: 3.494  time: 0.3424 s/iter  data_time: 0.2178 s/iter total_throughput: 2990.42 samples/s lr: 4.60e-04  
[09/22 22:21:55] lb.utils.events INFO:  eta: 7:33:30  iteration: 198599/375342  consumed_samples: 203366400  total_loss: 3.51  time: 0.3424 s/iter  data_time: 0.2151 s/iter total_throughput: 2990.41 samples/s lr: 4.60e-04  
[09/22 22:22:29] lb.utils.events INFO:  eta: 7:34:18  iteration: 198699/375342  consumed_samples: 203468800  total_loss: 3.498  time: 0.3424 s/iter  data_time: 0.2237 s/iter total_throughput: 2990.38 samples/s lr: 4.59e-04  
[09/22 22:23:04] lb.utils.events INFO:  eta: 7:34:36  iteration: 198799/375342  consumed_samples: 203571200  total_loss: 3.504  time: 0.3424 s/iter  data_time: 0.2084 s/iter total_throughput: 2990.37 samples/s lr: 4.59e-04  
[09/22 22:23:39] lb.utils.events INFO:  eta: 7:35:20  iteration: 198899/375342  consumed_samples: 203673600  total_loss: 3.526  time: 0.3424 s/iter  data_time: 0.2191 s/iter total_throughput: 2990.34 samples/s lr: 4.59e-04  
[09/22 22:24:13] lb.utils.events INFO:  eta: 7:36:12  iteration: 198999/375342  consumed_samples: 203776000  total_loss: 3.51  time: 0.3424 s/iter  data_time: 0.2152 s/iter total_throughput: 2990.32 samples/s lr: 4.58e-04  
[09/22 22:24:49] lb.utils.events INFO:  eta: 7:36:38  iteration: 199099/375342  consumed_samples: 203878400  total_loss: 3.469  time: 0.3424 s/iter  data_time: 0.2387 s/iter total_throughput: 2990.28 samples/s lr: 4.58e-04  
[09/22 22:25:24] lb.utils.events INFO:  eta: 7:36:26  iteration: 199199/375342  consumed_samples: 203980800  total_loss: 3.461  time: 0.3424 s/iter  data_time: 0.2169 s/iter total_throughput: 2990.25 samples/s lr: 4.57e-04  
[09/22 22:25:59] lb.utils.events INFO:  eta: 7:34:41  iteration: 199299/375342  consumed_samples: 204083200  total_loss: 3.501  time: 0.3425 s/iter  data_time: 0.2283 s/iter total_throughput: 2990.20 samples/s lr: 4.57e-04  
[09/22 22:26:34] lb.utils.events INFO:  eta: 7:33:54  iteration: 199399/375342  consumed_samples: 204185600  total_loss: 3.506  time: 0.3425 s/iter  data_time: 0.2352 s/iter total_throughput: 2990.16 samples/s lr: 4.56e-04  
[09/22 22:27:10] lb.utils.events INFO:  eta: 7:33:21  iteration: 199499/375342  consumed_samples: 204288000  total_loss: 3.501  time: 0.3425 s/iter  data_time: 0.2215 s/iter total_throughput: 2990.10 samples/s lr: 4.56e-04  
[09/22 22:27:45] lb.utils.events INFO:  eta: 7:32:54  iteration: 199599/375342  consumed_samples: 204390400  total_loss: 3.498  time: 0.3425 s/iter  data_time: 0.2186 s/iter total_throughput: 2990.06 samples/s lr: 4.56e-04  
[09/22 22:28:20] lb.utils.events INFO:  eta: 7:32:41  iteration: 199699/375342  consumed_samples: 204492800  total_loss: 3.496  time: 0.3425 s/iter  data_time: 0.2400 s/iter total_throughput: 2990.03 samples/s lr: 4.55e-04  
[09/22 22:28:55] lb.utils.events INFO:  eta: 7:32:20  iteration: 199799/375342  consumed_samples: 204595200  total_loss: 3.51  time: 0.3425 s/iter  data_time: 0.2380 s/iter total_throughput: 2990.00 samples/s lr: 4.55e-04  
[09/22 22:29:29] lb.utils.events INFO:  eta: 7:32:12  iteration: 199899/375342  consumed_samples: 204697600  total_loss: 3.508  time: 0.3425 s/iter  data_time: 0.2163 s/iter total_throughput: 2989.99 samples/s lr: 4.54e-04  
[09/22 22:30:05] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0199999
[09/22 22:30:05] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/22 22:30:05] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/22 22:30:09] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0966 s/iter. Inference: 0.1658 s/iter. Eval: 0.0020 s/iter. Total: 0.2644 s/iter. ETA=0:00:09
[09/22 22:30:14] lb.evaluation.evaluator INFO: Inference done 28672/50000. Dataloading: 0.1115 s/iter. Inference: 0.1730 s/iter. Eval: 0.0020 s/iter. Total: 0.2865 s/iter. ETA=0:00:05
[09/22 22:30:19] lb.evaluation.evaluator INFO: Inference done 46080/50000. Dataloading: 0.1228 s/iter. Inference: 0.1677 s/iter. Eval: 0.0020 s/iter. Total: 0.2925 s/iter. ETA=0:00:00
[09/22 22:30:20] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/22 22:30:20] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.771609 (0.000255 s / iter per device, on 8 devices)
[09/22 22:30:20] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000148 s / iter per device, on 8 devices)
[09/22 22:30:20] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/22 22:30:20] lb.evaluation.utils INFO: copypaste: Acc@1=75.332
[09/22 22:30:20] lb.evaluation.utils INFO: copypaste: Acc@5=92.812
[09/22 22:30:20] lb.engine.hooks INFO: Not saving as latest eval score for Acc@1 is 75.33200, not better than best score 75.36000 @ iteration 194999.
[09/22 22:30:20] lb.utils.events INFO:  eta: 7:31:22  iteration: 199999/375342  consumed_samples: 204800000  total_loss: 3.496  time: 0.3425 s/iter  data_time: 0.2304 s/iter total_throughput: 2989.95 samples/s lr: 4.54e-04  
[09/22 22:30:54] lb.utils.events INFO:  eta: 7:31:12  iteration: 200099/375342  consumed_samples: 204902400  total_loss: 3.504  time: 0.3425 s/iter  data_time: 0.2341 s/iter total_throughput: 2990.00 samples/s lr: 4.54e-04  
[09/22 22:31:28] lb.utils.events INFO:  eta: 7:30:33  iteration: 200199/375342  consumed_samples: 205004800  total_loss: 3.502  time: 0.3425 s/iter  data_time: 0.2175 s/iter total_throughput: 2989.98 samples/s lr: 4.53e-04  
[09/22 22:32:03] lb.utils.events INFO:  eta: 7:30:56  iteration: 200299/375342  consumed_samples: 205107200  total_loss: 3.5  time: 0.3425 s/iter  data_time: 0.2241 s/iter total_throughput: 2989.95 samples/s lr: 4.53e-04  
[09/22 22:32:39] lb.utils.events INFO:  eta: 7:30:40  iteration: 200399/375342  consumed_samples: 205209600  total_loss: 3.491  time: 0.3425 s/iter  data_time: 0.2286 s/iter total_throughput: 2989.91 samples/s lr: 4.52e-04  
[09/22 22:33:13] lb.utils.events INFO:  eta: 7:30:49  iteration: 200499/375342  consumed_samples: 205312000  total_loss: 3.501  time: 0.3425 s/iter  data_time: 0.2262 s/iter total_throughput: 2989.89 samples/s lr: 4.52e-04  
[09/22 22:33:48] lb.utils.events INFO:  eta: 7:31:02  iteration: 200599/375342  consumed_samples: 205414400  total_loss: 3.519  time: 0.3425 s/iter  data_time: 0.2173 s/iter total_throughput: 2989.88 samples/s lr: 4.52e-04  
[09/22 22:34:22] lb.utils.events INFO:  eta: 7:30:30  iteration: 200699/375342  consumed_samples: 205516800  total_loss: 3.517  time: 0.3425 s/iter  data_time: 0.2163 s/iter total_throughput: 2989.87 samples/s lr: 4.51e-04  
[09/22 22:34:57] lb.utils.events INFO:  eta: 7:30:23  iteration: 200799/375342  consumed_samples: 205619200  total_loss: 3.495  time: 0.3425 s/iter  data_time: 0.2133 s/iter total_throughput: 2989.85 samples/s lr: 4.51e-04  
[09/22 22:35:32] lb.utils.events INFO:  eta: 7:29:43  iteration: 200899/375342  consumed_samples: 205721600  total_loss: 3.488  time: 0.3425 s/iter  data_time: 0.2207 s/iter total_throughput: 2989.82 samples/s lr: 4.50e-04  
[09/22 22:36:07] lb.utils.events INFO:  eta: 7:29:35  iteration: 200999/375342  consumed_samples: 205824000  total_loss: 3.488  time: 0.3425 s/iter  data_time: 0.2221 s/iter total_throughput: 2989.80 samples/s lr: 4.50e-04  
[09/22 22:36:42] lb.utils.events INFO:  eta: 7:29:09  iteration: 201099/375342  consumed_samples: 205926400  total_loss: 3.5  time: 0.3425 s/iter  data_time: 0.2283 s/iter total_throughput: 2989.76 samples/s lr: 4.49e-04  
[09/22 22:37:16] lb.utils.events INFO:  eta: 7:29:04  iteration: 201199/375342  consumed_samples: 206028800  total_loss: 3.508  time: 0.3425 s/iter  data_time: 0.2143 s/iter total_throughput: 2989.75 samples/s lr: 4.49e-04  
[09/22 22:37:51] lb.utils.events INFO:  eta: 7:28:22  iteration: 201299/375342  consumed_samples: 206131200  total_loss: 3.506  time: 0.3425 s/iter  data_time: 0.2284 s/iter total_throughput: 2989.72 samples/s lr: 4.49e-04  
[09/22 22:38:26] lb.utils.events INFO:  eta: 7:29:11  iteration: 201399/375342  consumed_samples: 206233600  total_loss: 3.516  time: 0.3425 s/iter  data_time: 0.2234 s/iter total_throughput: 2989.68 samples/s lr: 4.48e-04  
[09/22 22:39:01] lb.utils.events INFO:  eta: 7:28:56  iteration: 201499/375342  consumed_samples: 206336000  total_loss: 3.498  time: 0.3425 s/iter  data_time: 0.2272 s/iter total_throughput: 2989.65 samples/s lr: 4.48e-04  
[09/22 22:39:36] lb.utils.events INFO:  eta: 7:28:40  iteration: 201599/375342  consumed_samples: 206438400  total_loss: 3.489  time: 0.3425 s/iter  data_time: 0.2203 s/iter total_throughput: 2989.63 samples/s lr: 4.47e-04  
[09/22 22:40:11] lb.utils.events INFO:  eta: 7:28:23  iteration: 201699/375342  consumed_samples: 206540800  total_loss: 3.492  time: 0.3425 s/iter  data_time: 0.2238 s/iter total_throughput: 2989.61 samples/s lr: 4.47e-04  
[09/22 22:40:46] lb.utils.events INFO:  eta: 7:28:58  iteration: 201799/375342  consumed_samples: 206643200  total_loss: 3.482  time: 0.3425 s/iter  data_time: 0.2219 s/iter total_throughput: 2989.59 samples/s lr: 4.47e-04  
[09/22 22:41:20] lb.utils.events INFO:  eta: 7:29:24  iteration: 201899/375342  consumed_samples: 206745600  total_loss: 3.48  time: 0.3425 s/iter  data_time: 0.2092 s/iter total_throughput: 2989.58 samples/s lr: 4.46e-04  
[09/22 22:41:55] lb.utils.events INFO:  eta: 7:29:11  iteration: 201999/375342  consumed_samples: 206848000  total_loss: 3.485  time: 0.3425 s/iter  data_time: 0.2193 s/iter total_throughput: 2989.55 samples/s lr: 4.46e-04  
[09/22 22:42:30] lb.utils.events INFO:  eta: 7:28:56  iteration: 202099/375342  consumed_samples: 206950400  total_loss: 3.492  time: 0.3425 s/iter  data_time: 0.2202 s/iter total_throughput: 2989.53 samples/s lr: 4.45e-04  
[09/22 22:43:04] lb.utils.events INFO:  eta: 7:29:03  iteration: 202199/375342  consumed_samples: 207052800  total_loss: 3.49  time: 0.3425 s/iter  data_time: 0.2179 s/iter total_throughput: 2989.52 samples/s lr: 4.45e-04  
[09/22 22:43:39] lb.utils.events INFO:  eta: 7:30:11  iteration: 202299/375342  consumed_samples: 207155200  total_loss: 3.493  time: 0.3425 s/iter  data_time: 0.2197 s/iter total_throughput: 2989.51 samples/s lr: 4.45e-04  
[09/22 22:44:14] lb.utils.events INFO:  eta: 7:29:05  iteration: 202399/375342  consumed_samples: 207257600  total_loss: 3.512  time: 0.3425 s/iter  data_time: 0.2185 s/iter total_throughput: 2989.48 samples/s lr: 4.44e-04  
[09/22 22:44:49] lb.utils.events INFO:  eta: 7:28:49  iteration: 202499/375342  consumed_samples: 207360000  total_loss: 3.502  time: 0.3425 s/iter  data_time: 0.2307 s/iter total_throughput: 2989.45 samples/s lr: 4.44e-04  
[09/22 22:45:24] lb.utils.events INFO:  eta: 7:27:52  iteration: 202599/375342  consumed_samples: 207462400  total_loss: 3.482  time: 0.3425 s/iter  data_time: 0.2277 s/iter total_throughput: 2989.40 samples/s lr: 4.43e-04  
[09/22 22:45:58] lb.utils.events INFO:  eta: 7:28:08  iteration: 202699/375342  consumed_samples: 207564800  total_loss: 3.483  time: 0.3425 s/iter  data_time: 0.2146 s/iter total_throughput: 2989.39 samples/s lr: 4.43e-04  
[09/22 22:46:33] lb.utils.events INFO:  eta: 7:28:06  iteration: 202799/375342  consumed_samples: 207667200  total_loss: 3.483  time: 0.3425 s/iter  data_time: 0.2200 s/iter total_throughput: 2989.38 samples/s lr: 4.42e-04  
[09/22 22:47:08] lb.utils.events INFO:  eta: 7:25:15  iteration: 202899/375342  consumed_samples: 207769600  total_loss: 3.491  time: 0.3426 s/iter  data_time: 0.2217 s/iter total_throughput: 2989.34 samples/s lr: 4.42e-04  
[09/22 22:47:43] lb.utils.events INFO:  eta: 7:24:40  iteration: 202999/375342  consumed_samples: 207872000  total_loss: 3.491  time: 0.3426 s/iter  data_time: 0.2254 s/iter total_throughput: 2989.30 samples/s lr: 4.42e-04  
[09/22 22:48:18] lb.utils.events INFO:  eta: 7:25:10  iteration: 203099/375342  consumed_samples: 207974400  total_loss: 3.473  time: 0.3426 s/iter  data_time: 0.2195 s/iter total_throughput: 2989.27 samples/s lr: 4.41e-04  
[09/22 22:48:53] lb.utils.events INFO:  eta: 7:26:45  iteration: 203199/375342  consumed_samples: 208076800  total_loss: 3.465  time: 0.3426 s/iter  data_time: 0.2126 s/iter total_throughput: 2989.27 samples/s lr: 4.41e-04  
[09/22 22:49:28] lb.utils.events INFO:  eta: 7:24:31  iteration: 203299/375342  consumed_samples: 208179200  total_loss: 3.465  time: 0.3426 s/iter  data_time: 0.2296 s/iter total_throughput: 2989.22 samples/s lr: 4.40e-04  
[09/22 22:50:03] lb.utils.events INFO:  eta: 7:25:52  iteration: 203399/375342  consumed_samples: 208281600  total_loss: 3.485  time: 0.3426 s/iter  data_time: 0.2122 s/iter total_throughput: 2989.20 samples/s lr: 4.40e-04  
[09/22 22:50:38] lb.utils.events INFO:  eta: 7:25:53  iteration: 203499/375342  consumed_samples: 208384000  total_loss: 3.483  time: 0.3426 s/iter  data_time: 0.2226 s/iter total_throughput: 2989.17 samples/s lr: 4.40e-04  
[09/22 22:51:12] lb.utils.events INFO:  eta: 7:26:47  iteration: 203599/375342  consumed_samples: 208486400  total_loss: 3.472  time: 0.3426 s/iter  data_time: 0.2132 s/iter total_throughput: 2989.16 samples/s lr: 4.39e-04  
[09/22 22:51:47] lb.utils.events INFO:  eta: 7:26:01  iteration: 203699/375342  consumed_samples: 208588800  total_loss: 3.486  time: 0.3426 s/iter  data_time: 0.2253 s/iter total_throughput: 2989.13 samples/s lr: 4.39e-04  
[09/22 22:52:22] lb.utils.events INFO:  eta: 7:25:21  iteration: 203799/375342  consumed_samples: 208691200  total_loss: 3.491  time: 0.3426 s/iter  data_time: 0.2261 s/iter total_throughput: 2989.12 samples/s lr: 4.38e-04  
[09/22 22:52:57] lb.utils.events INFO:  eta: 7:25:53  iteration: 203899/375342  consumed_samples: 208793600  total_loss: 3.476  time: 0.3426 s/iter  data_time: 0.2313 s/iter total_throughput: 2989.10 samples/s lr: 4.38e-04  
[09/22 22:53:31] lb.utils.events INFO:  eta: 7:25:14  iteration: 203999/375342  consumed_samples: 208896000  total_loss: 3.482  time: 0.3426 s/iter  data_time: 0.2099 s/iter total_throughput: 2989.08 samples/s lr: 4.38e-04  
[09/22 22:54:06] lb.utils.events INFO:  eta: 7:24:39  iteration: 204099/375342  consumed_samples: 208998400  total_loss: 3.482  time: 0.3426 s/iter  data_time: 0.2210 s/iter total_throughput: 2989.06 samples/s lr: 4.37e-04  
[09/22 22:54:41] lb.utils.events INFO:  eta: 7:22:23  iteration: 204199/375342  consumed_samples: 209100800  total_loss: 3.474  time: 0.3426 s/iter  data_time: 0.2374 s/iter total_throughput: 2989.02 samples/s lr: 4.37e-04  
[09/22 22:55:16] lb.utils.events INFO:  eta: 7:21:46  iteration: 204299/375342  consumed_samples: 209203200  total_loss: 3.47  time: 0.3426 s/iter  data_time: 0.2222 s/iter total_throughput: 2988.99 samples/s lr: 4.36e-04  
[09/22 22:55:51] lb.utils.events INFO:  eta: 7:21:07  iteration: 204399/375342  consumed_samples: 209305600  total_loss: 3.474  time: 0.3426 s/iter  data_time: 0.2299 s/iter total_throughput: 2988.95 samples/s lr: 4.36e-04  
[09/22 22:56:26] lb.utils.events INFO:  eta: 7:20:28  iteration: 204499/375342  consumed_samples: 209408000  total_loss: 3.468  time: 0.3426 s/iter  data_time: 0.2116 s/iter total_throughput: 2988.94 samples/s lr: 4.36e-04  
[09/22 22:57:01] lb.utils.events INFO:  eta: 7:20:07  iteration: 204599/375342  consumed_samples: 209510400  total_loss: 3.47  time: 0.3426 s/iter  data_time: 0.2114 s/iter total_throughput: 2988.92 samples/s lr: 4.35e-04  
[09/22 22:57:36] lb.utils.events INFO:  eta: 7:19:52  iteration: 204699/375342  consumed_samples: 209612800  total_loss: 3.499  time: 0.3426 s/iter  data_time: 0.2321 s/iter total_throughput: 2988.89 samples/s lr: 4.35e-04  
[09/22 22:58:10] lb.utils.events INFO:  eta: 7:19:48  iteration: 204799/375342  consumed_samples: 209715200  total_loss: 3.497  time: 0.3426 s/iter  data_time: 0.2093 s/iter total_throughput: 2988.89 samples/s lr: 4.34e-04  
[09/22 22:58:45] lb.utils.events INFO:  eta: 7:19:25  iteration: 204899/375342  consumed_samples: 209817600  total_loss: 3.494  time: 0.3426 s/iter  data_time: 0.2143 s/iter total_throughput: 2988.86 samples/s lr: 4.34e-04  
[09/22 22:59:20] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0204999
[09/22 22:59:20] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/22 22:59:20] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/22 22:59:25] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0960 s/iter. Inference: 0.1676 s/iter. Eval: 0.0019 s/iter. Total: 0.2655 s/iter. ETA=0:00:09
[09/22 22:59:30] lb.evaluation.evaluator INFO: Inference done 29696/50000. Dataloading: 0.1248 s/iter. Inference: 0.1705 s/iter. Eval: 0.0020 s/iter. Total: 0.2974 s/iter. ETA=0:00:05
[09/22 22:59:35] lb.evaluation.evaluator INFO: Inference done 48128/50000. Dataloading: 0.1232 s/iter. Inference: 0.1669 s/iter. Eval: 0.0020 s/iter. Total: 0.2922 s/iter. ETA=0:00:00
[09/22 22:59:36] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/22 22:59:36] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.948284 (0.000259 s / iter per device, on 8 devices)
[09/22 22:59:36] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000147 s / iter per device, on 8 devices)
[09/22 22:59:36] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/22 22:59:36] lb.evaluation.utils INFO: copypaste: Acc@1=75.752
[09/22 22:59:36] lb.evaluation.utils INFO: copypaste: Acc@5=92.83
[09/22 22:59:36] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 75.75200, better than last best score 75.36000 @ iteration 194999.
[09/22 22:59:36] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/22 22:59:37] lb.utils.events INFO:  eta: 7:20:10  iteration: 204999/375342  consumed_samples: 209920000  total_loss: 3.51  time: 0.3426 s/iter  data_time: 0.2216 s/iter total_throughput: 2988.83 samples/s lr: 4.33e-04  
[09/22 23:00:10] lb.utils.events INFO:  eta: 7:21:26  iteration: 205099/375342  consumed_samples: 210022400  total_loss: 3.524  time: 0.3426 s/iter  data_time: 0.2238 s/iter total_throughput: 2988.88 samples/s lr: 4.33e-04  
[09/22 23:00:44] lb.utils.events INFO:  eta: 7:21:41  iteration: 205199/375342  consumed_samples: 210124800  total_loss: 3.515  time: 0.3426 s/iter  data_time: 0.2241 s/iter total_throughput: 2988.86 samples/s lr: 4.33e-04  
[09/22 23:01:19] lb.utils.events INFO:  eta: 7:21:49  iteration: 205299/375342  consumed_samples: 210227200  total_loss: 3.499  time: 0.3426 s/iter  data_time: 0.2095 s/iter total_throughput: 2988.85 samples/s lr: 4.32e-04  
[09/22 23:01:54] lb.utils.events INFO:  eta: 7:21:53  iteration: 205399/375342  consumed_samples: 210329600  total_loss: 3.478  time: 0.3426 s/iter  data_time: 0.2150 s/iter total_throughput: 2988.83 samples/s lr: 4.32e-04  
[09/22 23:02:29] lb.utils.events INFO:  eta: 7:21:12  iteration: 205499/375342  consumed_samples: 210432000  total_loss: 3.473  time: 0.3426 s/iter  data_time: 0.2235 s/iter total_throughput: 2988.80 samples/s lr: 4.31e-04  
[09/22 23:03:04] lb.utils.events INFO:  eta: 7:20:55  iteration: 205599/375342  consumed_samples: 210534400  total_loss: 3.485  time: 0.3426 s/iter  data_time: 0.2237 s/iter total_throughput: 2988.77 samples/s lr: 4.31e-04  
[09/22 23:03:39] lb.utils.events INFO:  eta: 7:20:03  iteration: 205699/375342  consumed_samples: 210636800  total_loss: 3.488  time: 0.3426 s/iter  data_time: 0.2096 s/iter total_throughput: 2988.73 samples/s lr: 4.31e-04  
[09/22 23:04:13] lb.utils.events INFO:  eta: 7:19:58  iteration: 205799/375342  consumed_samples: 210739200  total_loss: 3.497  time: 0.3426 s/iter  data_time: 0.2312 s/iter total_throughput: 2988.72 samples/s lr: 4.30e-04  
[09/22 23:04:48] lb.utils.events INFO:  eta: 7:19:49  iteration: 205899/375342  consumed_samples: 210841600  total_loss: 3.489  time: 0.3426 s/iter  data_time: 0.2175 s/iter total_throughput: 2988.71 samples/s lr: 4.30e-04  
[09/22 23:05:22] lb.utils.events INFO:  eta: 7:20:05  iteration: 205999/375342  consumed_samples: 210944000  total_loss: 3.484  time: 0.3426 s/iter  data_time: 0.2162 s/iter total_throughput: 2988.72 samples/s lr: 4.29e-04  
[09/22 23:05:57] lb.utils.events INFO:  eta: 7:18:37  iteration: 206099/375342  consumed_samples: 211046400  total_loss: 3.501  time: 0.3426 s/iter  data_time: 0.2270 s/iter total_throughput: 2988.71 samples/s lr: 4.29e-04  
[09/22 23:06:31] lb.utils.events INFO:  eta: 7:18:30  iteration: 206199/375342  consumed_samples: 211148800  total_loss: 3.5  time: 0.3426 s/iter  data_time: 0.2107 s/iter total_throughput: 2988.71 samples/s lr: 4.29e-04  
[09/22 23:07:05] lb.utils.events INFO:  eta: 7:18:21  iteration: 206299/375342  consumed_samples: 211251200  total_loss: 3.478  time: 0.3426 s/iter  data_time: 0.2201 s/iter total_throughput: 2988.71 samples/s lr: 4.28e-04  
[09/22 23:07:40] lb.utils.events INFO:  eta: 7:17:53  iteration: 206399/375342  consumed_samples: 211353600  total_loss: 3.45  time: 0.3426 s/iter  data_time: 0.2239 s/iter total_throughput: 2988.68 samples/s lr: 4.28e-04  
[09/22 23:08:14] lb.utils.events INFO:  eta: 7:18:54  iteration: 206499/375342  consumed_samples: 211456000  total_loss: 3.445  time: 0.3426 s/iter  data_time: 0.2183 s/iter total_throughput: 2988.68 samples/s lr: 4.27e-04  
[09/22 23:08:49] lb.utils.events INFO:  eta: 7:18:39  iteration: 206599/375342  consumed_samples: 211558400  total_loss: 3.465  time: 0.3426 s/iter  data_time: 0.2264 s/iter total_throughput: 2988.67 samples/s lr: 4.27e-04  
[09/22 23:09:24] lb.utils.events INFO:  eta: 7:18:38  iteration: 206699/375342  consumed_samples: 211660800  total_loss: 3.478  time: 0.3426 s/iter  data_time: 0.2176 s/iter total_throughput: 2988.65 samples/s lr: 4.26e-04  
[09/22 23:09:58] lb.utils.events INFO:  eta: 7:18:07  iteration: 206799/375342  consumed_samples: 211763200  total_loss: 3.491  time: 0.3426 s/iter  data_time: 0.2160 s/iter total_throughput: 2988.63 samples/s lr: 4.26e-04  
[09/22 23:10:33] lb.utils.events INFO:  eta: 7:16:46  iteration: 206899/375342  consumed_samples: 211865600  total_loss: 3.487  time: 0.3426 s/iter  data_time: 0.2293 s/iter total_throughput: 2988.61 samples/s lr: 4.26e-04  
[09/22 23:11:07] lb.utils.events INFO:  eta: 7:16:46  iteration: 206999/375342  consumed_samples: 211968000  total_loss: 3.496  time: 0.3426 s/iter  data_time: 0.2109 s/iter total_throughput: 2988.61 samples/s lr: 4.25e-04  
[09/22 23:11:42] lb.utils.events INFO:  eta: 7:16:30  iteration: 207099/375342  consumed_samples: 212070400  total_loss: 3.488  time: 0.3426 s/iter  data_time: 0.2080 s/iter total_throughput: 2988.60 samples/s lr: 4.25e-04  
[09/22 23:12:17] lb.utils.events INFO:  eta: 7:16:36  iteration: 207199/375342  consumed_samples: 212172800  total_loss: 3.485  time: 0.3426 s/iter  data_time: 0.2216 s/iter total_throughput: 2988.57 samples/s lr: 4.24e-04  
[09/22 23:12:52] lb.utils.events INFO:  eta: 7:15:35  iteration: 207299/375342  consumed_samples: 212275200  total_loss: 3.488  time: 0.3426 s/iter  data_time: 0.2200 s/iter total_throughput: 2988.54 samples/s lr: 4.24e-04  
[09/22 23:13:26] lb.utils.events INFO:  eta: 7:15:16  iteration: 207399/375342  consumed_samples: 212377600  total_loss: 3.485  time: 0.3426 s/iter  data_time: 0.2125 s/iter total_throughput: 2988.53 samples/s lr: 4.24e-04  
[09/22 23:14:01] lb.utils.events INFO:  eta: 7:15:18  iteration: 207499/375342  consumed_samples: 212480000  total_loss: 3.479  time: 0.3426 s/iter  data_time: 0.2069 s/iter total_throughput: 2988.51 samples/s lr: 4.23e-04  
[09/22 23:14:36] lb.utils.events INFO:  eta: 7:14:48  iteration: 207599/375342  consumed_samples: 212582400  total_loss: 3.481  time: 0.3426 s/iter  data_time: 0.2081 s/iter total_throughput: 2988.50 samples/s lr: 4.23e-04  
[09/22 23:15:10] lb.utils.events INFO:  eta: 7:15:02  iteration: 207699/375342  consumed_samples: 212684800  total_loss: 3.477  time: 0.3426 s/iter  data_time: 0.2193 s/iter total_throughput: 2988.48 samples/s lr: 4.22e-04  
[09/22 23:15:45] lb.utils.events INFO:  eta: 7:13:43  iteration: 207799/375342  consumed_samples: 212787200  total_loss: 3.468  time: 0.3427 s/iter  data_time: 0.2138 s/iter total_throughput: 2988.47 samples/s lr: 4.22e-04  
[09/22 23:16:19] lb.utils.events INFO:  eta: 7:14:21  iteration: 207899/375342  consumed_samples: 212889600  total_loss: 3.48  time: 0.3427 s/iter  data_time: 0.2246 s/iter total_throughput: 2988.46 samples/s lr: 4.22e-04  
[09/22 23:16:54] lb.utils.events INFO:  eta: 7:13:57  iteration: 207999/375342  consumed_samples: 212992000  total_loss: 3.475  time: 0.3427 s/iter  data_time: 0.2285 s/iter total_throughput: 2988.45 samples/s lr: 4.21e-04  
[09/22 23:17:29] lb.utils.events INFO:  eta: 7:13:01  iteration: 208099/375342  consumed_samples: 213094400  total_loss: 3.472  time: 0.3427 s/iter  data_time: 0.2129 s/iter total_throughput: 2988.42 samples/s lr: 4.21e-04  
[09/22 23:18:03] lb.utils.events INFO:  eta: 7:12:00  iteration: 208199/375342  consumed_samples: 213196800  total_loss: 3.477  time: 0.3427 s/iter  data_time: 0.2163 s/iter total_throughput: 2988.42 samples/s lr: 4.20e-04  
[09/22 23:18:38] lb.utils.events INFO:  eta: 7:12:37  iteration: 208299/375342  consumed_samples: 213299200  total_loss: 3.439  time: 0.3427 s/iter  data_time: 0.2168 s/iter total_throughput: 2988.41 samples/s lr: 4.20e-04  
[09/22 23:19:12] lb.utils.events INFO:  eta: 7:11:43  iteration: 208399/375342  consumed_samples: 213401600  total_loss: 3.436  time: 0.3427 s/iter  data_time: 0.2229 s/iter total_throughput: 2988.40 samples/s lr: 4.20e-04  
[09/22 23:19:48] lb.utils.events INFO:  eta: 7:09:51  iteration: 208499/375342  consumed_samples: 213504000  total_loss: 3.461  time: 0.3427 s/iter  data_time: 0.2340 s/iter total_throughput: 2988.36 samples/s lr: 4.19e-04  
[09/22 23:20:22] lb.utils.events INFO:  eta: 7:09:22  iteration: 208599/375342  consumed_samples: 213606400  total_loss: 3.493  time: 0.3427 s/iter  data_time: 0.2218 s/iter total_throughput: 2988.33 samples/s lr: 4.19e-04  
[09/22 23:20:57] lb.utils.events INFO:  eta: 7:09:13  iteration: 208699/375342  consumed_samples: 213708800  total_loss: 3.507  time: 0.3427 s/iter  data_time: 0.2250 s/iter total_throughput: 2988.33 samples/s lr: 4.18e-04  
[09/22 23:21:31] lb.utils.events INFO:  eta: 7:08:58  iteration: 208799/375342  consumed_samples: 213811200  total_loss: 3.479  time: 0.3427 s/iter  data_time: 0.2156 s/iter total_throughput: 2988.32 samples/s lr: 4.18e-04  
[09/22 23:22:06] lb.utils.events INFO:  eta: 7:08:30  iteration: 208899/375342  consumed_samples: 213913600  total_loss: 3.447  time: 0.3427 s/iter  data_time: 0.2183 s/iter total_throughput: 2988.31 samples/s lr: 4.18e-04  
[09/22 23:22:40] lb.utils.events INFO:  eta: 7:08:07  iteration: 208999/375342  consumed_samples: 214016000  total_loss: 3.442  time: 0.3427 s/iter  data_time: 0.2061 s/iter total_throughput: 2988.30 samples/s lr: 4.17e-04  
[09/22 23:23:15] lb.utils.events INFO:  eta: 7:07:51  iteration: 209099/375342  consumed_samples: 214118400  total_loss: 3.448  time: 0.3427 s/iter  data_time: 0.2134 s/iter total_throughput: 2988.30 samples/s lr: 4.17e-04  
[09/22 23:23:49] lb.utils.events INFO:  eta: 7:07:36  iteration: 209199/375342  consumed_samples: 214220800  total_loss: 3.455  time: 0.3427 s/iter  data_time: 0.2184 s/iter total_throughput: 2988.29 samples/s lr: 4.16e-04  
[09/22 23:24:23] lb.utils.events INFO:  eta: 7:07:35  iteration: 209299/375342  consumed_samples: 214323200  total_loss: 3.475  time: 0.3427 s/iter  data_time: 0.2122 s/iter total_throughput: 2988.30 samples/s lr: 4.16e-04  
[09/22 23:24:58] lb.utils.events INFO:  eta: 7:08:10  iteration: 209399/375342  consumed_samples: 214425600  total_loss: 3.458  time: 0.3427 s/iter  data_time: 0.2277 s/iter total_throughput: 2988.28 samples/s lr: 4.15e-04  
[09/22 23:25:32] lb.utils.events INFO:  eta: 7:08:57  iteration: 209499/375342  consumed_samples: 214528000  total_loss: 3.451  time: 0.3427 s/iter  data_time: 0.2193 s/iter total_throughput: 2988.27 samples/s lr: 4.15e-04  
[09/22 23:26:07] lb.utils.events INFO:  eta: 7:09:18  iteration: 209599/375342  consumed_samples: 214630400  total_loss: 3.478  time: 0.3427 s/iter  data_time: 0.2144 s/iter total_throughput: 2988.25 samples/s lr: 4.15e-04  
[09/22 23:26:41] lb.utils.events INFO:  eta: 7:08:26  iteration: 209699/375342  consumed_samples: 214732800  total_loss: 3.481  time: 0.3427 s/iter  data_time: 0.2178 s/iter total_throughput: 2988.25 samples/s lr: 4.14e-04  
[09/22 23:27:16] lb.utils.events INFO:  eta: 7:07:50  iteration: 209799/375342  consumed_samples: 214835200  total_loss: 3.47  time: 0.3427 s/iter  data_time: 0.2364 s/iter total_throughput: 2988.24 samples/s lr: 4.14e-04  
[09/22 23:27:50] lb.utils.events INFO:  eta: 7:08:10  iteration: 209899/375342  consumed_samples: 214937600  total_loss: 3.477  time: 0.3427 s/iter  data_time: 0.2040 s/iter total_throughput: 2988.26 samples/s lr: 4.13e-04  
[09/22 23:28:24] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0209999
[09/22 23:28:25] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/22 23:28:25] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/22 23:28:29] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0979 s/iter. Inference: 0.1608 s/iter. Eval: 0.0021 s/iter. Total: 0.2608 s/iter. ETA=0:00:09
[09/22 23:28:34] lb.evaluation.evaluator INFO: Inference done 29696/50000. Dataloading: 0.1144 s/iter. Inference: 0.1796 s/iter. Eval: 0.0022 s/iter. Total: 0.2963 s/iter. ETA=0:00:05
[09/22 23:28:39] lb.evaluation.evaluator INFO: Inference done 48128/50000. Dataloading: 0.1152 s/iter. Inference: 0.1719 s/iter. Eval: 0.0021 s/iter. Total: 0.2894 s/iter. ETA=0:00:00
[09/22 23:28:40] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/22 23:28:40] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.538280 (0.000251 s / iter per device, on 8 devices)
[09/22 23:28:40] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000152 s / iter per device, on 8 devices)
[09/22 23:28:40] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/22 23:28:40] lb.evaluation.utils INFO: copypaste: Acc@1=76.024
[09/22 23:28:40] lb.evaluation.utils INFO: copypaste: Acc@5=92.988
[09/22 23:28:40] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 76.02400, better than last best score 75.75200 @ iteration 204999.
[09/22 23:28:40] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/22 23:28:41] lb.utils.events INFO:  eta: 7:07:43  iteration: 209999/375342  consumed_samples: 215040000  total_loss: 3.483  time: 0.3427 s/iter  data_time: 0.2171 s/iter total_throughput: 2988.25 samples/s lr: 4.13e-04  
[09/22 23:29:13] lb.utils.events INFO:  eta: 7:09:28  iteration: 210099/375342  consumed_samples: 215142400  total_loss: 3.504  time: 0.3427 s/iter  data_time: 0.2492 s/iter total_throughput: 2988.33 samples/s lr: 4.13e-04  
[09/22 23:29:48] lb.utils.events INFO:  eta: 7:09:00  iteration: 210199/375342  consumed_samples: 215244800  total_loss: 3.484  time: 0.3427 s/iter  data_time: 0.2242 s/iter total_throughput: 2988.31 samples/s lr: 4.12e-04  
[09/22 23:30:23] lb.utils.events INFO:  eta: 7:06:35  iteration: 210299/375342  consumed_samples: 215347200  total_loss: 3.469  time: 0.3427 s/iter  data_time: 0.2289 s/iter total_throughput: 2988.29 samples/s lr: 4.12e-04  
[09/22 23:30:58] lb.utils.events INFO:  eta: 7:05:07  iteration: 210399/375342  consumed_samples: 215449600  total_loss: 3.456  time: 0.3427 s/iter  data_time: 0.2239 s/iter total_throughput: 2988.25 samples/s lr: 4.11e-04  
[09/22 23:31:33] lb.utils.events INFO:  eta: 7:06:17  iteration: 210499/375342  consumed_samples: 215552000  total_loss: 3.434  time: 0.3427 s/iter  data_time: 0.2390 s/iter total_throughput: 2988.20 samples/s lr: 4.11e-04  
[09/22 23:32:08] lb.utils.events INFO:  eta: 7:05:45  iteration: 210599/375342  consumed_samples: 215654400  total_loss: 3.446  time: 0.3427 s/iter  data_time: 0.2273 s/iter total_throughput: 2988.16 samples/s lr: 4.11e-04  
[09/22 23:32:44] lb.utils.events INFO:  eta: 7:05:29  iteration: 210699/375342  consumed_samples: 215756800  total_loss: 3.464  time: 0.3427 s/iter  data_time: 0.2226 s/iter total_throughput: 2988.12 samples/s lr: 4.10e-04  
[09/22 23:33:19] lb.utils.events INFO:  eta: 7:06:16  iteration: 210799/375342  consumed_samples: 215859200  total_loss: 3.454  time: 0.3427 s/iter  data_time: 0.2165 s/iter total_throughput: 2988.09 samples/s lr: 4.10e-04  
[09/22 23:33:54] lb.utils.events INFO:  eta: 7:05:38  iteration: 210899/375342  consumed_samples: 215961600  total_loss: 3.463  time: 0.3427 s/iter  data_time: 0.2185 s/iter total_throughput: 2988.06 samples/s lr: 4.09e-04  
[09/22 23:34:29] lb.utils.events INFO:  eta: 7:06:09  iteration: 210999/375342  consumed_samples: 216064000  total_loss: 3.473  time: 0.3427 s/iter  data_time: 0.2228 s/iter total_throughput: 2988.02 samples/s lr: 4.09e-04  
[09/22 23:35:04] lb.utils.events INFO:  eta: 7:04:47  iteration: 211099/375342  consumed_samples: 216166400  total_loss: 3.474  time: 0.3427 s/iter  data_time: 0.2127 s/iter total_throughput: 2988.00 samples/s lr: 4.09e-04  
[09/22 23:35:39] lb.utils.events INFO:  eta: 7:05:26  iteration: 211199/375342  consumed_samples: 216268800  total_loss: 3.473  time: 0.3427 s/iter  data_time: 0.2182 s/iter total_throughput: 2987.97 samples/s lr: 4.08e-04  
[09/22 23:36:14] lb.utils.events INFO:  eta: 7:05:54  iteration: 211299/375342  consumed_samples: 216371200  total_loss: 3.465  time: 0.3427 s/iter  data_time: 0.2180 s/iter total_throughput: 2987.92 samples/s lr: 4.08e-04  
[09/22 23:36:50] lb.utils.events INFO:  eta: 7:06:25  iteration: 211399/375342  consumed_samples: 216473600  total_loss: 3.459  time: 0.3427 s/iter  data_time: 0.2203 s/iter total_throughput: 2987.86 samples/s lr: 4.07e-04  
[09/22 23:37:25] lb.utils.events INFO:  eta: 7:04:59  iteration: 211499/375342  consumed_samples: 216576000  total_loss: 3.448  time: 0.3427 s/iter  data_time: 0.2195 s/iter total_throughput: 2987.82 samples/s lr: 4.07e-04  
[09/22 23:38:00] lb.utils.events INFO:  eta: 7:06:00  iteration: 211599/375342  consumed_samples: 216678400  total_loss: 3.449  time: 0.3427 s/iter  data_time: 0.2160 s/iter total_throughput: 2987.79 samples/s lr: 4.07e-04  
[09/22 23:38:36] lb.utils.events INFO:  eta: 7:06:04  iteration: 211699/375342  consumed_samples: 216780800  total_loss: 3.453  time: 0.3427 s/iter  data_time: 0.2321 s/iter total_throughput: 2987.74 samples/s lr: 4.06e-04  
[09/22 23:39:11] lb.utils.events INFO:  eta: 7:04:26  iteration: 211799/375342  consumed_samples: 216883200  total_loss: 3.464  time: 0.3427 s/iter  data_time: 0.2215 s/iter total_throughput: 2987.72 samples/s lr: 4.06e-04  
[09/22 23:39:46] lb.utils.events INFO:  eta: 7:04:11  iteration: 211899/375342  consumed_samples: 216985600  total_loss: 3.468  time: 0.3427 s/iter  data_time: 0.2335 s/iter total_throughput: 2987.67 samples/s lr: 4.05e-04  
[09/22 23:40:21] lb.utils.events INFO:  eta: 7:03:15  iteration: 211999/375342  consumed_samples: 217088000  total_loss: 3.442  time: 0.3427 s/iter  data_time: 0.2264 s/iter total_throughput: 2987.64 samples/s lr: 4.05e-04  
[09/22 23:40:57] lb.utils.events INFO:  eta: 7:01:02  iteration: 212099/375342  consumed_samples: 217190400  total_loss: 3.446  time: 0.3428 s/iter  data_time: 0.2294 s/iter total_throughput: 2987.59 samples/s lr: 4.04e-04  
[09/22 23:41:32] lb.utils.events INFO:  eta: 7:00:10  iteration: 212199/375342  consumed_samples: 217292800  total_loss: 3.444  time: 0.3428 s/iter  data_time: 0.2210 s/iter total_throughput: 2987.55 samples/s lr: 4.04e-04  
[09/22 23:42:07] lb.utils.events INFO:  eta: 6:59:34  iteration: 212299/375342  consumed_samples: 217395200  total_loss: 3.459  time: 0.3428 s/iter  data_time: 0.2154 s/iter total_throughput: 2987.50 samples/s lr: 4.04e-04  
[09/22 23:42:42] lb.utils.events INFO:  eta: 6:58:34  iteration: 212399/375342  consumed_samples: 217497600  total_loss: 3.475  time: 0.3428 s/iter  data_time: 0.2329 s/iter total_throughput: 2987.47 samples/s lr: 4.03e-04  
[09/22 23:43:18] lb.utils.events INFO:  eta: 6:57:43  iteration: 212499/375342  consumed_samples: 217600000  total_loss: 3.469  time: 0.3428 s/iter  data_time: 0.2219 s/iter total_throughput: 2987.43 samples/s lr: 4.03e-04  
[09/22 23:43:53] lb.utils.events INFO:  eta: 6:57:48  iteration: 212599/375342  consumed_samples: 217702400  total_loss: 3.452  time: 0.3428 s/iter  data_time: 0.2290 s/iter total_throughput: 2987.40 samples/s lr: 4.02e-04  
[09/22 23:44:28] lb.utils.events INFO:  eta: 6:57:18  iteration: 212699/375342  consumed_samples: 217804800  total_loss: 3.457  time: 0.3428 s/iter  data_time: 0.2159 s/iter total_throughput: 2987.38 samples/s lr: 4.02e-04  
[09/22 23:45:02] lb.utils.events INFO:  eta: 6:57:03  iteration: 212799/375342  consumed_samples: 217907200  total_loss: 3.448  time: 0.3428 s/iter  data_time: 0.2336 s/iter total_throughput: 2987.36 samples/s lr: 4.02e-04  
[09/22 23:45:37] lb.utils.events INFO:  eta: 6:56:57  iteration: 212899/375342  consumed_samples: 218009600  total_loss: 3.437  time: 0.3428 s/iter  data_time: 0.2285 s/iter total_throughput: 2987.32 samples/s lr: 4.01e-04  
[09/22 23:46:12] lb.utils.events INFO:  eta: 6:56:21  iteration: 212999/375342  consumed_samples: 218112000  total_loss: 3.434  time: 0.3428 s/iter  data_time: 0.2159 s/iter total_throughput: 2987.29 samples/s lr: 4.01e-04  
[09/22 23:46:47] lb.utils.events INFO:  eta: 6:57:50  iteration: 213099/375342  consumed_samples: 218214400  total_loss: 3.437  time: 0.3428 s/iter  data_time: 0.2260 s/iter total_throughput: 2987.27 samples/s lr: 4.00e-04  
[09/22 23:47:23] lb.utils.events INFO:  eta: 6:57:13  iteration: 213199/375342  consumed_samples: 218316800  total_loss: 3.45  time: 0.3428 s/iter  data_time: 0.2285 s/iter total_throughput: 2987.22 samples/s lr: 4.00e-04  
[09/22 23:47:58] lb.utils.events INFO:  eta: 6:56:12  iteration: 213299/375342  consumed_samples: 218419200  total_loss: 3.458  time: 0.3428 s/iter  data_time: 0.2160 s/iter total_throughput: 2987.20 samples/s lr: 4.00e-04  
[09/22 23:48:33] lb.utils.events INFO:  eta: 6:57:14  iteration: 213399/375342  consumed_samples: 218521600  total_loss: 3.459  time: 0.3428 s/iter  data_time: 0.2320 s/iter total_throughput: 2987.16 samples/s lr: 3.99e-04  
[09/22 23:49:08] lb.utils.events INFO:  eta: 6:57:48  iteration: 213499/375342  consumed_samples: 218624000  total_loss: 3.456  time: 0.3428 s/iter  data_time: 0.2231 s/iter total_throughput: 2987.13 samples/s lr: 3.99e-04  
[09/22 23:49:43] lb.utils.events INFO:  eta: 6:57:13  iteration: 213599/375342  consumed_samples: 218726400  total_loss: 3.443  time: 0.3428 s/iter  data_time: 0.2344 s/iter total_throughput: 2987.11 samples/s lr: 3.98e-04  
[09/22 23:50:17] lb.utils.events INFO:  eta: 6:57:29  iteration: 213699/375342  consumed_samples: 218828800  total_loss: 3.456  time: 0.3428 s/iter  data_time: 0.2264 s/iter total_throughput: 2987.09 samples/s lr: 3.98e-04  
[09/22 23:50:52] lb.utils.events INFO:  eta: 6:56:58  iteration: 213799/375342  consumed_samples: 218931200  total_loss: 3.464  time: 0.3428 s/iter  data_time: 0.2263 s/iter total_throughput: 2987.06 samples/s lr: 3.98e-04  
[09/22 23:51:28] lb.utils.events INFO:  eta: 6:56:19  iteration: 213899/375342  consumed_samples: 219033600  total_loss: 3.452  time: 0.3428 s/iter  data_time: 0.2250 s/iter total_throughput: 2987.02 samples/s lr: 3.97e-04  
[09/22 23:52:03] lb.utils.events INFO:  eta: 6:56:48  iteration: 213999/375342  consumed_samples: 219136000  total_loss: 3.447  time: 0.3428 s/iter  data_time: 0.2338 s/iter total_throughput: 2986.99 samples/s lr: 3.97e-04  
[09/22 23:52:37] lb.utils.events INFO:  eta: 6:56:39  iteration: 214099/375342  consumed_samples: 219238400  total_loss: 3.452  time: 0.3428 s/iter  data_time: 0.2145 s/iter total_throughput: 2986.98 samples/s lr: 3.96e-04  
[09/22 23:53:12] lb.utils.events INFO:  eta: 6:55:27  iteration: 214199/375342  consumed_samples: 219340800  total_loss: 3.46  time: 0.3428 s/iter  data_time: 0.2206 s/iter total_throughput: 2986.95 samples/s lr: 3.96e-04  
[09/22 23:53:47] lb.utils.events INFO:  eta: 6:55:35  iteration: 214299/375342  consumed_samples: 219443200  total_loss: 3.461  time: 0.3428 s/iter  data_time: 0.2253 s/iter total_throughput: 2986.92 samples/s lr: 3.96e-04  
[09/22 23:54:22] lb.utils.events INFO:  eta: 6:56:22  iteration: 214399/375342  consumed_samples: 219545600  total_loss: 3.457  time: 0.3428 s/iter  data_time: 0.2140 s/iter total_throughput: 2986.90 samples/s lr: 3.95e-04  
[09/22 23:54:57] lb.utils.events INFO:  eta: 6:56:40  iteration: 214499/375342  consumed_samples: 219648000  total_loss: 3.461  time: 0.3428 s/iter  data_time: 0.2222 s/iter total_throughput: 2986.89 samples/s lr: 3.95e-04  
[09/22 23:55:31] lb.utils.events INFO:  eta: 6:57:07  iteration: 214599/375342  consumed_samples: 219750400  total_loss: 3.456  time: 0.3428 s/iter  data_time: 0.2257 s/iter total_throughput: 2986.87 samples/s lr: 3.94e-04  
[09/22 23:56:06] lb.utils.events INFO:  eta: 6:55:58  iteration: 214699/375342  consumed_samples: 219852800  total_loss: 3.45  time: 0.3428 s/iter  data_time: 0.2160 s/iter total_throughput: 2986.85 samples/s lr: 3.94e-04  
[09/22 23:56:41] lb.utils.events INFO:  eta: 6:55:20  iteration: 214799/375342  consumed_samples: 219955200  total_loss: 3.473  time: 0.3428 s/iter  data_time: 0.2301 s/iter total_throughput: 2986.82 samples/s lr: 3.94e-04  
[09/22 23:57:16] lb.utils.events INFO:  eta: 6:55:12  iteration: 214899/375342  consumed_samples: 220057600  total_loss: 3.473  time: 0.3428 s/iter  data_time: 0.2181 s/iter total_throughput: 2986.81 samples/s lr: 3.93e-04  
[09/22 23:57:51] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0214999
[09/22 23:57:52] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/22 23:57:52] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/22 23:57:56] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.1279 s/iter. Inference: 0.1602 s/iter. Eval: 0.0020 s/iter. Total: 0.2901 s/iter. ETA=0:00:10
[09/22 23:58:01] lb.evaluation.evaluator INFO: Inference done 29696/50000. Dataloading: 0.1165 s/iter. Inference: 0.1778 s/iter. Eval: 0.0020 s/iter. Total: 0.2963 s/iter. ETA=0:00:05
[09/22 23:58:06] lb.evaluation.evaluator INFO: Inference done 48128/50000. Dataloading: 0.1226 s/iter. Inference: 0.1691 s/iter. Eval: 0.0020 s/iter. Total: 0.2938 s/iter. ETA=0:00:00
[09/22 23:58:07] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/22 23:58:07] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.686537 (0.000254 s / iter per device, on 8 devices)
[09/22 23:58:07] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000149 s / iter per device, on 8 devices)
[09/22 23:58:07] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/22 23:58:07] lb.evaluation.utils INFO: copypaste: Acc@1=76.13799999999999
[09/22 23:58:07] lb.evaluation.utils INFO: copypaste: Acc@5=93.2
[09/22 23:58:07] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 76.13800, better than last best score 76.02400 @ iteration 209999.
[09/22 23:58:07] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/22 23:58:07] lb.utils.events INFO:  eta: 6:54:38  iteration: 214999/375342  consumed_samples: 220160000  total_loss: 3.455  time: 0.3428 s/iter  data_time: 0.2245 s/iter total_throughput: 2986.78 samples/s lr: 3.93e-04  
[09/22 23:58:41] lb.utils.events INFO:  eta: 6:55:22  iteration: 215099/375342  consumed_samples: 220262400  total_loss: 3.453  time: 0.3428 s/iter  data_time: 0.2322 s/iter total_throughput: 2986.82 samples/s lr: 3.92e-04  
[09/22 23:59:16] lb.utils.events INFO:  eta: 6:56:36  iteration: 215199/375342  consumed_samples: 220364800  total_loss: 3.453  time: 0.3428 s/iter  data_time: 0.2131 s/iter total_throughput: 2986.79 samples/s lr: 3.92e-04  
[09/22 23:59:51] lb.utils.events INFO:  eta: 6:55:52  iteration: 215299/375342  consumed_samples: 220467200  total_loss: 3.438  time: 0.3428 s/iter  data_time: 0.2234 s/iter total_throughput: 2986.76 samples/s lr: 3.92e-04  
[09/23 00:00:25] lb.utils.events INFO:  eta: 6:54:45  iteration: 215399/375342  consumed_samples: 220569600  total_loss: 3.433  time: 0.3428 s/iter  data_time: 0.2146 s/iter total_throughput: 2986.75 samples/s lr: 3.91e-04  
[09/23 00:01:00] lb.utils.events INFO:  eta: 6:53:48  iteration: 215499/375342  consumed_samples: 220672000  total_loss: 3.453  time: 0.3429 s/iter  data_time: 0.2236 s/iter total_throughput: 2986.72 samples/s lr: 3.91e-04  
[09/23 00:01:36] lb.utils.events INFO:  eta: 6:52:06  iteration: 215599/375342  consumed_samples: 220774400  total_loss: 3.45  time: 0.3429 s/iter  data_time: 0.2329 s/iter total_throughput: 2986.68 samples/s lr: 3.90e-04  
[09/23 00:02:10] lb.utils.events INFO:  eta: 6:51:16  iteration: 215699/375342  consumed_samples: 220876800  total_loss: 3.448  time: 0.3429 s/iter  data_time: 0.2311 s/iter total_throughput: 2986.67 samples/s lr: 3.90e-04  
[09/23 00:02:45] lb.utils.events INFO:  eta: 6:52:15  iteration: 215799/375342  consumed_samples: 220979200  total_loss: 3.458  time: 0.3429 s/iter  data_time: 0.2157 s/iter total_throughput: 2986.66 samples/s lr: 3.90e-04  
[09/23 00:03:19] lb.utils.events INFO:  eta: 6:52:37  iteration: 215899/375342  consumed_samples: 221081600  total_loss: 3.464  time: 0.3429 s/iter  data_time: 0.2155 s/iter total_throughput: 2986.64 samples/s lr: 3.89e-04  
[09/23 00:03:55] lb.utils.events INFO:  eta: 6:52:27  iteration: 215999/375342  consumed_samples: 221184000  total_loss: 3.457  time: 0.3429 s/iter  data_time: 0.2232 s/iter total_throughput: 2986.61 samples/s lr: 3.89e-04  
[09/23 00:04:30] lb.utils.events INFO:  eta: 6:51:00  iteration: 216099/375342  consumed_samples: 221286400  total_loss: 3.445  time: 0.3429 s/iter  data_time: 0.2247 s/iter total_throughput: 2986.58 samples/s lr: 3.88e-04  
[09/23 00:05:04] lb.utils.events INFO:  eta: 6:50:09  iteration: 216199/375342  consumed_samples: 221388800  total_loss: 3.451  time: 0.3429 s/iter  data_time: 0.2127 s/iter total_throughput: 2986.56 samples/s lr: 3.88e-04  
[09/23 00:05:40] lb.utils.events INFO:  eta: 6:50:48  iteration: 216299/375342  consumed_samples: 221491200  total_loss: 3.443  time: 0.3429 s/iter  data_time: 0.2214 s/iter total_throughput: 2986.52 samples/s lr: 3.88e-04  
[09/23 00:06:14] lb.utils.events INFO:  eta: 6:50:42  iteration: 216399/375342  consumed_samples: 221593600  total_loss: 3.441  time: 0.3429 s/iter  data_time: 0.2171 s/iter total_throughput: 2986.50 samples/s lr: 3.87e-04  
[09/23 00:06:49] lb.utils.events INFO:  eta: 6:50:54  iteration: 216499/375342  consumed_samples: 221696000  total_loss: 3.442  time: 0.3429 s/iter  data_time: 0.2169 s/iter total_throughput: 2986.50 samples/s lr: 3.87e-04  
[09/23 00:07:24] lb.utils.events INFO:  eta: 6:51:46  iteration: 216599/375342  consumed_samples: 221798400  total_loss: 3.43  time: 0.3429 s/iter  data_time: 0.2242 s/iter total_throughput: 2986.48 samples/s lr: 3.86e-04  
[09/23 00:07:59] lb.utils.events INFO:  eta: 6:52:07  iteration: 216699/375342  consumed_samples: 221900800  total_loss: 3.439  time: 0.3429 s/iter  data_time: 0.2175 s/iter total_throughput: 2986.44 samples/s lr: 3.86e-04  
[09/23 00:08:34] lb.utils.events INFO:  eta: 6:51:41  iteration: 216799/375342  consumed_samples: 222003200  total_loss: 3.458  time: 0.3429 s/iter  data_time: 0.2217 s/iter total_throughput: 2986.41 samples/s lr: 3.86e-04  
[09/23 00:09:09] lb.utils.events INFO:  eta: 6:51:11  iteration: 216899/375342  consumed_samples: 222105600  total_loss: 3.456  time: 0.3429 s/iter  data_time: 0.2295 s/iter total_throughput: 2986.37 samples/s lr: 3.85e-04  
[09/23 00:09:44] lb.utils.events INFO:  eta: 6:50:17  iteration: 216999/375342  consumed_samples: 222208000  total_loss: 3.443  time: 0.3429 s/iter  data_time: 0.2195 s/iter total_throughput: 2986.34 samples/s lr: 3.85e-04  
[09/23 00:10:19] lb.utils.events INFO:  eta: 6:50:34  iteration: 217099/375342  consumed_samples: 222310400  total_loss: 3.465  time: 0.3429 s/iter  data_time: 0.2150 s/iter total_throughput: 2986.34 samples/s lr: 3.84e-04  
[09/23 00:10:53] lb.utils.events INFO:  eta: 6:50:15  iteration: 217199/375342  consumed_samples: 222412800  total_loss: 3.462  time: 0.3429 s/iter  data_time: 0.2204 s/iter total_throughput: 2986.34 samples/s lr: 3.84e-04  
[09/23 00:11:28] lb.utils.events INFO:  eta: 6:49:34  iteration: 217299/375342  consumed_samples: 222515200  total_loss: 3.446  time: 0.3429 s/iter  data_time: 0.2273 s/iter total_throughput: 2986.31 samples/s lr: 3.84e-04  
[09/23 00:12:03] lb.utils.events INFO:  eta: 6:49:03  iteration: 217399/375342  consumed_samples: 222617600  total_loss: 3.436  time: 0.3429 s/iter  data_time: 0.2187 s/iter total_throughput: 2986.26 samples/s lr: 3.83e-04  
[09/23 00:12:38] lb.utils.events INFO:  eta: 6:48:55  iteration: 217499/375342  consumed_samples: 222720000  total_loss: 3.449  time: 0.3429 s/iter  data_time: 0.2210 s/iter total_throughput: 2986.23 samples/s lr: 3.83e-04  
[09/23 00:13:14] lb.utils.events INFO:  eta: 6:48:00  iteration: 217599/375342  consumed_samples: 222822400  total_loss: 3.464  time: 0.3429 s/iter  data_time: 0.2375 s/iter total_throughput: 2986.20 samples/s lr: 3.82e-04  
[09/23 00:13:49] lb.utils.events INFO:  eta: 6:47:21  iteration: 217699/375342  consumed_samples: 222924800  total_loss: 3.466  time: 0.3429 s/iter  data_time: 0.2235 s/iter total_throughput: 2986.16 samples/s lr: 3.82e-04  
[09/23 00:14:23] lb.utils.events INFO:  eta: 6:47:15  iteration: 217799/375342  consumed_samples: 223027200  total_loss: 3.449  time: 0.3429 s/iter  data_time: 0.2205 s/iter total_throughput: 2986.15 samples/s lr: 3.81e-04  
[09/23 00:14:58] lb.utils.events INFO:  eta: 6:47:16  iteration: 217899/375342  consumed_samples: 223129600  total_loss: 3.431  time: 0.3429 s/iter  data_time: 0.2103 s/iter total_throughput: 2986.15 samples/s lr: 3.81e-04  
[09/23 00:15:33] lb.utils.events INFO:  eta: 6:46:56  iteration: 217999/375342  consumed_samples: 223232000  total_loss: 3.444  time: 0.3429 s/iter  data_time: 0.2181 s/iter total_throughput: 2986.12 samples/s lr: 3.81e-04  
[09/23 00:16:08] lb.utils.events INFO:  eta: 6:46:20  iteration: 218099/375342  consumed_samples: 223334400  total_loss: 3.444  time: 0.3429 s/iter  data_time: 0.2293 s/iter total_throughput: 2986.10 samples/s lr: 3.80e-04  
[09/23 00:16:42] lb.utils.events INFO:  eta: 6:45:45  iteration: 218199/375342  consumed_samples: 223436800  total_loss: 3.418  time: 0.3429 s/iter  data_time: 0.2181 s/iter total_throughput: 2986.08 samples/s lr: 3.80e-04  
[09/23 00:17:17] lb.utils.events INFO:  eta: 6:46:14  iteration: 218299/375342  consumed_samples: 223539200  total_loss: 3.437  time: 0.3429 s/iter  data_time: 0.2166 s/iter total_throughput: 2986.07 samples/s lr: 3.79e-04  
[09/23 00:17:51] lb.utils.events INFO:  eta: 6:46:19  iteration: 218399/375342  consumed_samples: 223641600  total_loss: 3.445  time: 0.3429 s/iter  data_time: 0.2180 s/iter total_throughput: 2986.07 samples/s lr: 3.79e-04  
[09/23 00:18:26] lb.utils.events INFO:  eta: 6:45:54  iteration: 218499/375342  consumed_samples: 223744000  total_loss: 3.438  time: 0.3429 s/iter  data_time: 0.2212 s/iter total_throughput: 2986.05 samples/s lr: 3.79e-04  
[09/23 00:19:01] lb.utils.events INFO:  eta: 6:45:51  iteration: 218599/375342  consumed_samples: 223846400  total_loss: 3.427  time: 0.3429 s/iter  data_time: 0.2118 s/iter total_throughput: 2986.03 samples/s lr: 3.78e-04  
[09/23 00:19:36] lb.utils.events INFO:  eta: 6:46:46  iteration: 218699/375342  consumed_samples: 223948800  total_loss: 3.431  time: 0.3429 s/iter  data_time: 0.2244 s/iter total_throughput: 2986.00 samples/s lr: 3.78e-04  
[09/23 00:20:10] lb.utils.events INFO:  eta: 6:45:38  iteration: 218799/375342  consumed_samples: 224051200  total_loss: 3.436  time: 0.3429 s/iter  data_time: 0.2264 s/iter total_throughput: 2985.99 samples/s lr: 3.77e-04  
[09/23 00:20:45] lb.utils.events INFO:  eta: 6:44:51  iteration: 218899/375342  consumed_samples: 224153600  total_loss: 3.434  time: 0.3429 s/iter  data_time: 0.2177 s/iter total_throughput: 2985.97 samples/s lr: 3.77e-04  
[09/23 00:21:19] lb.utils.events INFO:  eta: 6:46:40  iteration: 218999/375342  consumed_samples: 224256000  total_loss: 3.433  time: 0.3429 s/iter  data_time: 0.2162 s/iter total_throughput: 2985.98 samples/s lr: 3.77e-04  
[09/23 00:21:54] lb.utils.events INFO:  eta: 6:46:24  iteration: 219099/375342  consumed_samples: 224358400  total_loss: 3.419  time: 0.3429 s/iter  data_time: 0.2169 s/iter total_throughput: 2985.97 samples/s lr: 3.76e-04  
[09/23 00:22:28] lb.utils.events INFO:  eta: 6:46:20  iteration: 219199/375342  consumed_samples: 224460800  total_loss: 3.419  time: 0.3429 s/iter  data_time: 0.2168 s/iter total_throughput: 2985.97 samples/s lr: 3.76e-04  
[09/23 00:23:03] lb.utils.events INFO:  eta: 6:44:46  iteration: 219299/375342  consumed_samples: 224563200  total_loss: 3.422  time: 0.3429 s/iter  data_time: 0.2171 s/iter total_throughput: 2985.95 samples/s lr: 3.75e-04  
[09/23 00:23:38] lb.utils.events INFO:  eta: 6:44:41  iteration: 219399/375342  consumed_samples: 224665600  total_loss: 3.42  time: 0.3429 s/iter  data_time: 0.2180 s/iter total_throughput: 2985.94 samples/s lr: 3.75e-04  
[09/23 00:24:12] lb.utils.events INFO:  eta: 6:44:25  iteration: 219499/375342  consumed_samples: 224768000  total_loss: 3.43  time: 0.3429 s/iter  data_time: 0.2212 s/iter total_throughput: 2985.93 samples/s lr: 3.75e-04  
[09/23 00:24:47] lb.utils.events INFO:  eta: 6:44:56  iteration: 219599/375342  consumed_samples: 224870400  total_loss: 3.43  time: 0.3429 s/iter  data_time: 0.2113 s/iter total_throughput: 2985.90 samples/s lr: 3.74e-04  
[09/23 00:25:22] lb.utils.events INFO:  eta: 6:44:47  iteration: 219699/375342  consumed_samples: 224972800  total_loss: 3.422  time: 0.3429 s/iter  data_time: 0.2347 s/iter total_throughput: 2985.88 samples/s lr: 3.74e-04  
[09/23 00:25:57] lb.utils.events INFO:  eta: 6:43:20  iteration: 219799/375342  consumed_samples: 225075200  total_loss: 3.424  time: 0.3430 s/iter  data_time: 0.2417 s/iter total_throughput: 2985.85 samples/s lr: 3.73e-04  
[09/23 00:26:32] lb.utils.events INFO:  eta: 6:43:24  iteration: 219899/375342  consumed_samples: 225177600  total_loss: 3.419  time: 0.3430 s/iter  data_time: 0.2216 s/iter total_throughput: 2985.83 samples/s lr: 3.73e-04  
[09/23 00:27:07] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0219999
[09/23 00:27:07] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/23 00:27:07] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/23 00:27:11] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.1029 s/iter. Inference: 0.1615 s/iter. Eval: 0.0020 s/iter. Total: 0.2664 s/iter. ETA=0:00:09
[09/23 00:27:17] lb.evaluation.evaluator INFO: Inference done 28672/50000. Dataloading: 0.1195 s/iter. Inference: 0.1689 s/iter. Eval: 0.0020 s/iter. Total: 0.2904 s/iter. ETA=0:00:05
[09/23 00:27:22] lb.evaluation.evaluator INFO: Inference done 47104/50000. Dataloading: 0.1250 s/iter. Inference: 0.1657 s/iter. Eval: 0.0020 s/iter. Total: 0.2927 s/iter. ETA=0:00:00
[09/23 00:27:22] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/23 00:27:22] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.579033 (0.000252 s / iter per device, on 8 devices)
[09/23 00:27:22] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000146 s / iter per device, on 8 devices)
[09/23 00:27:22] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/23 00:27:22] lb.evaluation.utils INFO: copypaste: Acc@1=75.994
[09/23 00:27:22] lb.evaluation.utils INFO: copypaste: Acc@5=93.108
[09/23 00:27:22] lb.engine.hooks INFO: Not saving as latest eval score for Acc@1 is 75.99400, not better than best score 76.13800 @ iteration 214999.
[09/23 00:27:22] lb.utils.events INFO:  eta: 6:42:40  iteration: 219999/375342  consumed_samples: 225280000  total_loss: 3.438  time: 0.3430 s/iter  data_time: 0.2268 s/iter total_throughput: 2985.81 samples/s lr: 3.73e-04  
[09/23 00:27:55] lb.utils.events INFO:  eta: 6:44:28  iteration: 220099/375342  consumed_samples: 225382400  total_loss: 3.445  time: 0.3429 s/iter  data_time: 0.2271 s/iter total_throughput: 2985.89 samples/s lr: 3.72e-04  
[09/23 00:28:29] lb.utils.events INFO:  eta: 6:44:56  iteration: 220199/375342  consumed_samples: 225484800  total_loss: 3.438  time: 0.3429 s/iter  data_time: 0.2184 s/iter total_throughput: 2985.88 samples/s lr: 3.72e-04  
[09/23 00:29:04] lb.utils.events INFO:  eta: 6:45:00  iteration: 220299/375342  consumed_samples: 225587200  total_loss: 3.439  time: 0.3430 s/iter  data_time: 0.2346 s/iter total_throughput: 2985.86 samples/s lr: 3.71e-04  
[09/23 00:29:39] lb.utils.events INFO:  eta: 6:44:27  iteration: 220399/375342  consumed_samples: 225689600  total_loss: 3.438  time: 0.3430 s/iter  data_time: 0.2170 s/iter total_throughput: 2985.85 samples/s lr: 3.71e-04  
[09/23 00:30:13] lb.utils.events INFO:  eta: 6:44:29  iteration: 220499/375342  consumed_samples: 225792000  total_loss: 3.416  time: 0.3430 s/iter  data_time: 0.2140 s/iter total_throughput: 2985.85 samples/s lr: 3.71e-04  
[09/23 00:30:47] lb.utils.events INFO:  eta: 6:44:22  iteration: 220599/375342  consumed_samples: 225894400  total_loss: 3.414  time: 0.3430 s/iter  data_time: 0.2244 s/iter total_throughput: 2985.85 samples/s lr: 3.70e-04  
[09/23 00:31:22] lb.utils.events INFO:  eta: 6:44:06  iteration: 220699/375342  consumed_samples: 225996800  total_loss: 3.426  time: 0.3430 s/iter  data_time: 0.2168 s/iter total_throughput: 2985.85 samples/s lr: 3.70e-04  
[09/23 00:31:56] lb.utils.events INFO:  eta: 6:44:32  iteration: 220799/375342  consumed_samples: 226099200  total_loss: 3.438  time: 0.3430 s/iter  data_time: 0.2235 s/iter total_throughput: 2985.84 samples/s lr: 3.69e-04  
[09/23 00:32:31] lb.utils.events INFO:  eta: 6:44:07  iteration: 220899/375342  consumed_samples: 226201600  total_loss: 3.443  time: 0.3430 s/iter  data_time: 0.2200 s/iter total_throughput: 2985.83 samples/s lr: 3.69e-04  
[09/23 00:33:06] lb.utils.events INFO:  eta: 6:43:42  iteration: 220999/375342  consumed_samples: 226304000  total_loss: 3.443  time: 0.3430 s/iter  data_time: 0.2157 s/iter total_throughput: 2985.81 samples/s lr: 3.69e-04  
[09/23 00:33:40] lb.utils.events INFO:  eta: 6:41:32  iteration: 221099/375342  consumed_samples: 226406400  total_loss: 3.418  time: 0.3430 s/iter  data_time: 0.2175 s/iter total_throughput: 2985.80 samples/s lr: 3.68e-04  
[09/23 00:34:15] lb.utils.events INFO:  eta: 6:41:01  iteration: 221199/375342  consumed_samples: 226508800  total_loss: 3.431  time: 0.3430 s/iter  data_time: 0.2205 s/iter total_throughput: 2985.79 samples/s lr: 3.68e-04  
[09/23 00:34:50] lb.utils.events INFO:  eta: 6:40:42  iteration: 221299/375342  consumed_samples: 226611200  total_loss: 3.443  time: 0.3430 s/iter  data_time: 0.2312 s/iter total_throughput: 2985.76 samples/s lr: 3.68e-04  
[09/23 00:35:25] lb.utils.events INFO:  eta: 6:40:21  iteration: 221399/375342  consumed_samples: 226713600  total_loss: 3.44  time: 0.3430 s/iter  data_time: 0.2200 s/iter total_throughput: 2985.74 samples/s lr: 3.67e-04  
[09/23 00:35:59] lb.utils.events INFO:  eta: 6:39:17  iteration: 221499/375342  consumed_samples: 226816000  total_loss: 3.428  time: 0.3430 s/iter  data_time: 0.2246 s/iter total_throughput: 2985.73 samples/s lr: 3.67e-04  
[09/23 00:36:34] lb.utils.events INFO:  eta: 6:38:53  iteration: 221599/375342  consumed_samples: 226918400  total_loss: 3.413  time: 0.3430 s/iter  data_time: 0.2264 s/iter total_throughput: 2985.71 samples/s lr: 3.66e-04  
[09/23 00:37:09] lb.utils.events INFO:  eta: 6:38:10  iteration: 221699/375342  consumed_samples: 227020800  total_loss: 3.42  time: 0.3430 s/iter  data_time: 0.2188 s/iter total_throughput: 2985.69 samples/s lr: 3.66e-04  
[09/23 00:37:43] lb.utils.events INFO:  eta: 6:38:10  iteration: 221799/375342  consumed_samples: 227123200  total_loss: 3.43  time: 0.3430 s/iter  data_time: 0.2104 s/iter total_throughput: 2985.68 samples/s lr: 3.66e-04  
[09/23 00:38:18] lb.utils.events INFO:  eta: 6:37:55  iteration: 221899/375342  consumed_samples: 227225600  total_loss: 3.432  time: 0.3430 s/iter  data_time: 0.2218 s/iter total_throughput: 2985.65 samples/s lr: 3.65e-04  
[09/23 00:38:53] lb.utils.events INFO:  eta: 6:36:35  iteration: 221999/375342  consumed_samples: 227328000  total_loss: 3.421  time: 0.3430 s/iter  data_time: 0.2308 s/iter total_throughput: 2985.64 samples/s lr: 3.65e-04  
[09/23 00:39:28] lb.utils.events INFO:  eta: 6:36:20  iteration: 222099/375342  consumed_samples: 227430400  total_loss: 3.429  time: 0.3430 s/iter  data_time: 0.2185 s/iter total_throughput: 2985.62 samples/s lr: 3.64e-04  
[09/23 00:40:02] lb.utils.events INFO:  eta: 6:36:32  iteration: 222199/375342  consumed_samples: 227532800  total_loss: 3.442  time: 0.3430 s/iter  data_time: 0.2161 s/iter total_throughput: 2985.61 samples/s lr: 3.64e-04  
[09/23 00:40:37] lb.utils.events INFO:  eta: 6:36:10  iteration: 222299/375342  consumed_samples: 227635200  total_loss: 3.439  time: 0.3430 s/iter  data_time: 0.2130 s/iter total_throughput: 2985.60 samples/s lr: 3.64e-04  
[09/23 00:41:12] lb.utils.events INFO:  eta: 6:36:02  iteration: 222399/375342  consumed_samples: 227737600  total_loss: 3.41  time: 0.3430 s/iter  data_time: 0.2150 s/iter total_throughput: 2985.57 samples/s lr: 3.63e-04  
[09/23 00:41:46] lb.utils.events INFO:  eta: 6:36:26  iteration: 222499/375342  consumed_samples: 227840000  total_loss: 3.432  time: 0.3430 s/iter  data_time: 0.2187 s/iter total_throughput: 2985.57 samples/s lr: 3.63e-04  
[09/23 00:42:21] lb.utils.events INFO:  eta: 6:35:53  iteration: 222599/375342  consumed_samples: 227942400  total_loss: 3.447  time: 0.3430 s/iter  data_time: 0.2187 s/iter total_throughput: 2985.55 samples/s lr: 3.62e-04  
[09/23 00:42:56] lb.utils.events INFO:  eta: 6:35:38  iteration: 222699/375342  consumed_samples: 228044800  total_loss: 3.423  time: 0.3430 s/iter  data_time: 0.2149 s/iter total_throughput: 2985.54 samples/s lr: 3.62e-04  
[09/23 00:43:30] lb.utils.events INFO:  eta: 6:34:58  iteration: 222799/375342  consumed_samples: 228147200  total_loss: 3.434  time: 0.3430 s/iter  data_time: 0.2225 s/iter total_throughput: 2985.55 samples/s lr: 3.62e-04  
[09/23 00:44:04] lb.utils.events INFO:  eta: 6:33:41  iteration: 222899/375342  consumed_samples: 228249600  total_loss: 3.431  time: 0.3430 s/iter  data_time: 0.2080 s/iter total_throughput: 2985.54 samples/s lr: 3.61e-04  
[09/23 00:44:39] lb.utils.events INFO:  eta: 6:34:31  iteration: 222999/375342  consumed_samples: 228352000  total_loss: 3.417  time: 0.3430 s/iter  data_time: 0.2246 s/iter total_throughput: 2985.54 samples/s lr: 3.61e-04  
[09/23 00:45:13] lb.utils.events INFO:  eta: 6:34:23  iteration: 223099/375342  consumed_samples: 228454400  total_loss: 3.422  time: 0.3430 s/iter  data_time: 0.2125 s/iter total_throughput: 2985.54 samples/s lr: 3.60e-04  
[09/23 00:45:47] lb.utils.events INFO:  eta: 6:34:07  iteration: 223199/375342  consumed_samples: 228556800  total_loss: 3.419  time: 0.3430 s/iter  data_time: 0.2118 s/iter total_throughput: 2985.55 samples/s lr: 3.60e-04  
[09/23 00:46:21] lb.utils.events INFO:  eta: 6:33:48  iteration: 223299/375342  consumed_samples: 228659200  total_loss: 3.397  time: 0.3430 s/iter  data_time: 0.2099 s/iter total_throughput: 2985.55 samples/s lr: 3.60e-04  
[09/23 00:46:56] lb.utils.events INFO:  eta: 6:33:58  iteration: 223399/375342  consumed_samples: 228761600  total_loss: 3.391  time: 0.3430 s/iter  data_time: 0.2064 s/iter total_throughput: 2985.55 samples/s lr: 3.59e-04  
[09/23 00:47:30] lb.utils.events INFO:  eta: 6:35:18  iteration: 223499/375342  consumed_samples: 228864000  total_loss: 3.415  time: 0.3430 s/iter  data_time: 0.2298 s/iter total_throughput: 2985.55 samples/s lr: 3.59e-04  
[09/23 00:48:04] lb.utils.events INFO:  eta: 6:36:01  iteration: 223599/375342  consumed_samples: 228966400  total_loss: 3.421  time: 0.3430 s/iter  data_time: 0.2106 s/iter total_throughput: 2985.56 samples/s lr: 3.58e-04  
[09/23 00:48:39] lb.utils.events INFO:  eta: 6:35:09  iteration: 223699/375342  consumed_samples: 229068800  total_loss: 3.423  time: 0.3430 s/iter  data_time: 0.2291 s/iter total_throughput: 2985.54 samples/s lr: 3.58e-04  
[09/23 00:49:13] lb.utils.events INFO:  eta: 6:34:47  iteration: 223799/375342  consumed_samples: 229171200  total_loss: 3.423  time: 0.3430 s/iter  data_time: 0.2095 s/iter total_throughput: 2985.55 samples/s lr: 3.58e-04  
[09/23 00:49:47] lb.utils.events INFO:  eta: 6:35:06  iteration: 223899/375342  consumed_samples: 229273600  total_loss: 3.412  time: 0.3430 s/iter  data_time: 0.2150 s/iter total_throughput: 2985.55 samples/s lr: 3.57e-04  
[09/23 00:50:22] lb.utils.events INFO:  eta: 6:35:30  iteration: 223999/375342  consumed_samples: 229376000  total_loss: 3.414  time: 0.3430 s/iter  data_time: 0.2187 s/iter total_throughput: 2985.55 samples/s lr: 3.57e-04  
[09/23 00:50:56] lb.utils.events INFO:  eta: 6:35:08  iteration: 224099/375342  consumed_samples: 229478400  total_loss: 3.411  time: 0.3430 s/iter  data_time: 0.2195 s/iter total_throughput: 2985.53 samples/s lr: 3.56e-04  
[09/23 00:51:31] lb.utils.events INFO:  eta: 6:33:08  iteration: 224199/375342  consumed_samples: 229580800  total_loss: 3.406  time: 0.3430 s/iter  data_time: 0.2092 s/iter total_throughput: 2985.52 samples/s lr: 3.56e-04  
[09/23 00:52:06] lb.utils.events INFO:  eta: 6:33:11  iteration: 224299/375342  consumed_samples: 229683200  total_loss: 3.44  time: 0.3430 s/iter  data_time: 0.2234 s/iter total_throughput: 2985.50 samples/s lr: 3.56e-04  
[09/23 00:52:41] lb.utils.events INFO:  eta: 6:32:26  iteration: 224399/375342  consumed_samples: 229785600  total_loss: 3.424  time: 0.3430 s/iter  data_time: 0.2403 s/iter total_throughput: 2985.46 samples/s lr: 3.55e-04  
[09/23 00:53:16] lb.utils.events INFO:  eta: 6:30:42  iteration: 224499/375342  consumed_samples: 229888000  total_loss: 3.396  time: 0.3430 s/iter  data_time: 0.2236 s/iter total_throughput: 2985.42 samples/s lr: 3.55e-04  
[09/23 00:53:52] lb.utils.events INFO:  eta: 6:29:47  iteration: 224599/375342  consumed_samples: 229990400  total_loss: 3.409  time: 0.3430 s/iter  data_time: 0.2197 s/iter total_throughput: 2985.37 samples/s lr: 3.54e-04  
[09/23 00:54:27] lb.utils.events INFO:  eta: 6:30:08  iteration: 224699/375342  consumed_samples: 230092800  total_loss: 3.411  time: 0.3430 s/iter  data_time: 0.2341 s/iter total_throughput: 2985.33 samples/s lr: 3.54e-04  
[09/23 00:55:02] lb.utils.events INFO:  eta: 6:30:00  iteration: 224799/375342  consumed_samples: 230195200  total_loss: 3.422  time: 0.3430 s/iter  data_time: 0.2113 s/iter total_throughput: 2985.31 samples/s lr: 3.54e-04  
[09/23 00:55:37] lb.utils.events INFO:  eta: 6:29:56  iteration: 224899/375342  consumed_samples: 230297600  total_loss: 3.414  time: 0.3430 s/iter  data_time: 0.2338 s/iter total_throughput: 2985.29 samples/s lr: 3.53e-04  
[09/23 00:56:12] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0224999
[09/23 00:56:13] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/23 00:56:13] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/23 00:56:17] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0914 s/iter. Inference: 0.1610 s/iter. Eval: 0.0017 s/iter. Total: 0.2542 s/iter. ETA=0:00:09
[09/23 00:56:22] lb.evaluation.evaluator INFO: Inference done 29696/50000. Dataloading: 0.1374 s/iter. Inference: 0.1625 s/iter. Eval: 0.0020 s/iter. Total: 0.3019 s/iter. ETA=0:00:05
[09/23 00:56:27] lb.evaluation.evaluator INFO: Inference done 49152/50000. Dataloading: 0.1206 s/iter. Inference: 0.1624 s/iter. Eval: 0.0020 s/iter. Total: 0.2852 s/iter. ETA=0:00:00
[09/23 00:56:28] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/23 00:56:28] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.645186 (0.000253 s / iter per device, on 8 devices)
[09/23 00:56:28] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000144 s / iter per device, on 8 devices)
[09/23 00:56:28] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/23 00:56:28] lb.evaluation.utils INFO: copypaste: Acc@1=76.41
[09/23 00:56:28] lb.evaluation.utils INFO: copypaste: Acc@5=93.176
[09/23 00:56:28] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 76.41000, better than last best score 76.13800 @ iteration 214999.
[09/23 00:56:28] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/23 00:56:29] lb.utils.events INFO:  eta: 6:29:41  iteration: 224999/375342  consumed_samples: 230400000  total_loss: 3.409  time: 0.3430 s/iter  data_time: 0.2178 s/iter total_throughput: 2985.26 samples/s lr: 3.53e-04  
[09/23 00:57:01] lb.utils.events INFO:  eta: 6:30:00  iteration: 225099/375342  consumed_samples: 230502400  total_loss: 3.419  time: 0.3430 s/iter  data_time: 0.2161 s/iter total_throughput: 2985.32 samples/s lr: 3.52e-04  
[09/23 00:57:36] lb.utils.events INFO:  eta: 6:30:20  iteration: 225199/375342  consumed_samples: 230604800  total_loss: 3.4  time: 0.3430 s/iter  data_time: 0.2129 s/iter total_throughput: 2985.30 samples/s lr: 3.52e-04  
[09/23 00:58:11] lb.utils.events INFO:  eta: 6:29:03  iteration: 225299/375342  consumed_samples: 230707200  total_loss: 3.376  time: 0.3430 s/iter  data_time: 0.2229 s/iter total_throughput: 2985.27 samples/s lr: 3.52e-04  
[09/23 00:58:47] lb.utils.events INFO:  eta: 6:28:58  iteration: 225399/375342  consumed_samples: 230809600  total_loss: 3.381  time: 0.3430 s/iter  data_time: 0.2335 s/iter total_throughput: 2985.23 samples/s lr: 3.51e-04  
[09/23 00:59:22] lb.utils.events INFO:  eta: 6:28:29  iteration: 225499/375342  consumed_samples: 230912000  total_loss: 3.416  time: 0.3430 s/iter  data_time: 0.2226 s/iter total_throughput: 2985.20 samples/s lr: 3.51e-04  
[09/23 00:59:57] lb.utils.events INFO:  eta: 6:28:10  iteration: 225599/375342  consumed_samples: 231014400  total_loss: 3.413  time: 0.3430 s/iter  data_time: 0.2273 s/iter total_throughput: 2985.16 samples/s lr: 3.50e-04  
[09/23 01:00:32] lb.utils.events INFO:  eta: 6:28:11  iteration: 225699/375342  consumed_samples: 231116800  total_loss: 3.396  time: 0.3430 s/iter  data_time: 0.2213 s/iter total_throughput: 2985.14 samples/s lr: 3.50e-04  
[09/23 01:01:07] lb.utils.events INFO:  eta: 6:29:04  iteration: 225799/375342  consumed_samples: 231219200  total_loss: 3.396  time: 0.3430 s/iter  data_time: 0.2272 s/iter total_throughput: 2985.12 samples/s lr: 3.50e-04  
[09/23 01:01:41] lb.utils.events INFO:  eta: 6:28:28  iteration: 225899/375342  consumed_samples: 231321600  total_loss: 3.416  time: 0.3430 s/iter  data_time: 0.2268 s/iter total_throughput: 2985.11 samples/s lr: 3.49e-04  
[09/23 01:02:17] lb.utils.events INFO:  eta: 6:27:30  iteration: 225999/375342  consumed_samples: 231424000  total_loss: 3.43  time: 0.3430 s/iter  data_time: 0.2257 s/iter total_throughput: 2985.08 samples/s lr: 3.49e-04  
[09/23 01:02:51] lb.utils.events INFO:  eta: 6:26:18  iteration: 226099/375342  consumed_samples: 231526400  total_loss: 3.427  time: 0.3430 s/iter  data_time: 0.2201 s/iter total_throughput: 2985.07 samples/s lr: 3.49e-04  
[09/23 01:03:26] lb.utils.events INFO:  eta: 6:26:25  iteration: 226199/375342  consumed_samples: 231628800  total_loss: 3.41  time: 0.3430 s/iter  data_time: 0.2211 s/iter total_throughput: 2985.05 samples/s lr: 3.48e-04  
[09/23 01:04:01] lb.utils.events INFO:  eta: 6:26:49  iteration: 226299/375342  consumed_samples: 231731200  total_loss: 3.408  time: 0.3430 s/iter  data_time: 0.2190 s/iter total_throughput: 2985.03 samples/s lr: 3.48e-04  
[09/23 01:04:35] lb.utils.events INFO:  eta: 6:26:51  iteration: 226399/375342  consumed_samples: 231833600  total_loss: 3.399  time: 0.3430 s/iter  data_time: 0.2287 s/iter total_throughput: 2985.01 samples/s lr: 3.47e-04  
[09/23 01:05:10] lb.utils.events INFO:  eta: 6:26:05  iteration: 226499/375342  consumed_samples: 231936000  total_loss: 3.384  time: 0.3431 s/iter  data_time: 0.2238 s/iter total_throughput: 2984.99 samples/s lr: 3.47e-04  
[09/23 01:05:45] lb.utils.events INFO:  eta: 6:25:49  iteration: 226599/375342  consumed_samples: 232038400  total_loss: 3.378  time: 0.3431 s/iter  data_time: 0.2158 s/iter total_throughput: 2984.96 samples/s lr: 3.47e-04  
[09/23 01:06:21] lb.utils.events INFO:  eta: 6:24:22  iteration: 226699/375342  consumed_samples: 232140800  total_loss: 3.397  time: 0.3431 s/iter  data_time: 0.2205 s/iter total_throughput: 2984.92 samples/s lr: 3.46e-04  
[09/23 01:06:55] lb.utils.events INFO:  eta: 6:23:33  iteration: 226799/375342  consumed_samples: 232243200  total_loss: 3.398  time: 0.3431 s/iter  data_time: 0.2255 s/iter total_throughput: 2984.91 samples/s lr: 3.46e-04  
[09/23 01:07:30] lb.utils.events INFO:  eta: 6:24:05  iteration: 226899/375342  consumed_samples: 232345600  total_loss: 3.393  time: 0.3431 s/iter  data_time: 0.2166 s/iter total_throughput: 2984.91 samples/s lr: 3.45e-04  
[09/23 01:08:05] lb.utils.events INFO:  eta: 6:23:35  iteration: 226999/375342  consumed_samples: 232448000  total_loss: 3.397  time: 0.3431 s/iter  data_time: 0.2317 s/iter total_throughput: 2984.89 samples/s lr: 3.45e-04  
[09/23 01:08:40] lb.utils.events INFO:  eta: 6:23:12  iteration: 227099/375342  consumed_samples: 232550400  total_loss: 3.398  time: 0.3431 s/iter  data_time: 0.2221 s/iter total_throughput: 2984.86 samples/s lr: 3.45e-04  
[09/23 01:09:15] lb.utils.events INFO:  eta: 6:22:42  iteration: 227199/375342  consumed_samples: 232652800  total_loss: 3.408  time: 0.3431 s/iter  data_time: 0.2165 s/iter total_throughput: 2984.84 samples/s lr: 3.44e-04  
[09/23 01:09:50] lb.utils.events INFO:  eta: 6:22:45  iteration: 227299/375342  consumed_samples: 232755200  total_loss: 3.407  time: 0.3431 s/iter  data_time: 0.2191 s/iter total_throughput: 2984.80 samples/s lr: 3.44e-04  
[09/23 01:10:24] lb.utils.events INFO:  eta: 6:22:01  iteration: 227399/375342  consumed_samples: 232857600  total_loss: 3.396  time: 0.3431 s/iter  data_time: 0.2173 s/iter total_throughput: 2984.79 samples/s lr: 3.43e-04  
[09/23 01:11:00] lb.utils.events INFO:  eta: 6:22:13  iteration: 227499/375342  consumed_samples: 232960000  total_loss: 3.404  time: 0.3431 s/iter  data_time: 0.2058 s/iter total_throughput: 2984.74 samples/s lr: 3.43e-04  
[09/23 01:11:36] lb.utils.events INFO:  eta: 6:21:36  iteration: 227599/375342  consumed_samples: 233062400  total_loss: 3.424  time: 0.3431 s/iter  data_time: 0.2292 s/iter total_throughput: 2984.70 samples/s lr: 3.43e-04  
[09/23 01:12:10] lb.utils.events INFO:  eta: 6:22:06  iteration: 227699/375342  consumed_samples: 233164800  total_loss: 3.423  time: 0.3431 s/iter  data_time: 0.2130 s/iter total_throughput: 2984.67 samples/s lr: 3.42e-04  
[09/23 01:12:46] lb.utils.events INFO:  eta: 6:21:05  iteration: 227799/375342  consumed_samples: 233267200  total_loss: 3.403  time: 0.3431 s/iter  data_time: 0.2267 s/iter total_throughput: 2984.64 samples/s lr: 3.42e-04  
[09/23 01:13:20] lb.utils.events INFO:  eta: 6:20:32  iteration: 227899/375342  consumed_samples: 233369600  total_loss: 3.394  time: 0.3431 s/iter  data_time: 0.2203 s/iter total_throughput: 2984.63 samples/s lr: 3.41e-04  
[09/23 01:13:55] lb.utils.events INFO:  eta: 6:20:16  iteration: 227999/375342  consumed_samples: 233472000  total_loss: 3.401  time: 0.3431 s/iter  data_time: 0.2258 s/iter total_throughput: 2984.60 samples/s lr: 3.41e-04  
[09/23 01:14:30] lb.utils.events INFO:  eta: 6:19:53  iteration: 228099/375342  consumed_samples: 233574400  total_loss: 3.408  time: 0.3431 s/iter  data_time: 0.2175 s/iter total_throughput: 2984.58 samples/s lr: 3.41e-04  
[09/23 01:15:05] lb.utils.events INFO:  eta: 6:19:41  iteration: 228199/375342  consumed_samples: 233676800  total_loss: 3.402  time: 0.3431 s/iter  data_time: 0.2232 s/iter total_throughput: 2984.56 samples/s lr: 3.40e-04  
[09/23 01:15:40] lb.utils.events INFO:  eta: 6:19:15  iteration: 228299/375342  consumed_samples: 233779200  total_loss: 3.394  time: 0.3431 s/iter  data_time: 0.2273 s/iter total_throughput: 2984.54 samples/s lr: 3.40e-04  
[09/23 01:16:15] lb.utils.events INFO:  eta: 6:18:58  iteration: 228399/375342  consumed_samples: 233881600  total_loss: 3.402  time: 0.3431 s/iter  data_time: 0.2279 s/iter total_throughput: 2984.51 samples/s lr: 3.40e-04  
[09/23 01:16:50] lb.utils.events INFO:  eta: 6:19:14  iteration: 228499/375342  consumed_samples: 233984000  total_loss: 3.422  time: 0.3431 s/iter  data_time: 0.2241 s/iter total_throughput: 2984.50 samples/s lr: 3.39e-04  
[09/23 01:17:25] lb.utils.events INFO:  eta: 6:19:10  iteration: 228599/375342  consumed_samples: 234086400  total_loss: 3.411  time: 0.3431 s/iter  data_time: 0.2225 s/iter total_throughput: 2984.46 samples/s lr: 3.39e-04  
[09/23 01:18:00] lb.utils.events INFO:  eta: 6:20:11  iteration: 228699/375342  consumed_samples: 234188800  total_loss: 3.405  time: 0.3431 s/iter  data_time: 0.2138 s/iter total_throughput: 2984.44 samples/s lr: 3.38e-04  
[09/23 01:18:35] lb.utils.events INFO:  eta: 6:19:55  iteration: 228799/375342  consumed_samples: 234291200  total_loss: 3.417  time: 0.3431 s/iter  data_time: 0.2342 s/iter total_throughput: 2984.41 samples/s lr: 3.38e-04  
[09/23 01:19:10] lb.utils.events INFO:  eta: 6:19:04  iteration: 228899/375342  consumed_samples: 234393600  total_loss: 3.412  time: 0.3431 s/iter  data_time: 0.2254 s/iter total_throughput: 2984.38 samples/s lr: 3.38e-04  
[09/23 01:19:45] lb.utils.events INFO:  eta: 6:19:33  iteration: 228999/375342  consumed_samples: 234496000  total_loss: 3.394  time: 0.3431 s/iter  data_time: 0.2176 s/iter total_throughput: 2984.37 samples/s lr: 3.37e-04  
[09/23 01:20:20] lb.utils.events INFO:  eta: 6:19:25  iteration: 229099/375342  consumed_samples: 234598400  total_loss: 3.387  time: 0.3431 s/iter  data_time: 0.2314 s/iter total_throughput: 2984.33 samples/s lr: 3.37e-04  
[09/23 01:20:55] lb.utils.events INFO:  eta: 6:17:18  iteration: 229199/375342  consumed_samples: 234700800  total_loss: 3.398  time: 0.3431 s/iter  data_time: 0.2278 s/iter total_throughput: 2984.29 samples/s lr: 3.36e-04  
[09/23 01:21:30] lb.utils.events INFO:  eta: 6:18:11  iteration: 229299/375342  consumed_samples: 234803200  total_loss: 3.401  time: 0.3431 s/iter  data_time: 0.2192 s/iter total_throughput: 2984.28 samples/s lr: 3.36e-04  
[09/23 01:22:05] lb.utils.events INFO:  eta: 6:18:16  iteration: 229399/375342  consumed_samples: 234905600  total_loss: 3.399  time: 0.3431 s/iter  data_time: 0.2157 s/iter total_throughput: 2984.25 samples/s lr: 3.36e-04  
[09/23 01:22:40] lb.utils.events INFO:  eta: 6:16:56  iteration: 229499/375342  consumed_samples: 235008000  total_loss: 3.403  time: 0.3431 s/iter  data_time: 0.2318 s/iter total_throughput: 2984.23 samples/s lr: 3.35e-04  
[09/23 01:23:15] lb.utils.events INFO:  eta: 6:16:15  iteration: 229599/375342  consumed_samples: 235110400  total_loss: 3.401  time: 0.3431 s/iter  data_time: 0.2400 s/iter total_throughput: 2984.19 samples/s lr: 3.35e-04  
[09/23 01:23:51] lb.utils.events INFO:  eta: 6:15:22  iteration: 229699/375342  consumed_samples: 235212800  total_loss: 3.397  time: 0.3431 s/iter  data_time: 0.2175 s/iter total_throughput: 2984.15 samples/s lr: 3.34e-04  
[09/23 01:24:26] lb.utils.events INFO:  eta: 6:16:24  iteration: 229799/375342  consumed_samples: 235315200  total_loss: 3.393  time: 0.3431 s/iter  data_time: 0.2146 s/iter total_throughput: 2984.13 samples/s lr: 3.34e-04  
[09/23 01:25:01] lb.utils.events INFO:  eta: 6:15:34  iteration: 229899/375342  consumed_samples: 235417600  total_loss: 3.398  time: 0.3432 s/iter  data_time: 0.2340 s/iter total_throughput: 2984.09 samples/s lr: 3.34e-04  
[09/23 01:25:36] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0229999
[09/23 01:25:36] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/23 01:25:36] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/23 01:25:40] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0924 s/iter. Inference: 0.1702 s/iter. Eval: 0.0021 s/iter. Total: 0.2647 s/iter. ETA=0:00:09
[09/23 01:25:46] lb.evaluation.evaluator INFO: Inference done 28672/50000. Dataloading: 0.1037 s/iter. Inference: 0.1848 s/iter. Eval: 0.0020 s/iter. Total: 0.2906 s/iter. ETA=0:00:05
[09/23 01:25:51] lb.evaluation.evaluator INFO: Inference done 47104/50000. Dataloading: 0.1167 s/iter. Inference: 0.1749 s/iter. Eval: 0.0020 s/iter. Total: 0.2938 s/iter. ETA=0:00:00
[09/23 01:25:51] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/23 01:25:51] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.555834 (0.000251 s / iter per device, on 8 devices)
[09/23 01:25:51] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000153 s / iter per device, on 8 devices)
[09/23 01:25:51] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/23 01:25:51] lb.evaluation.utils INFO: copypaste: Acc@1=76.57000000000001
[09/23 01:25:51] lb.evaluation.utils INFO: copypaste: Acc@5=93.286
[09/23 01:25:51] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 76.57000, better than last best score 76.41000 @ iteration 224999.
[09/23 01:25:51] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/23 01:25:52] lb.utils.events INFO:  eta: 6:15:10  iteration: 229999/375342  consumed_samples: 235520000  total_loss: 3.401  time: 0.3432 s/iter  data_time: 0.2218 s/iter total_throughput: 2984.07 samples/s lr: 3.33e-04  
[09/23 01:26:25] lb.utils.events INFO:  eta: 6:18:20  iteration: 230099/375342  consumed_samples: 235622400  total_loss: 3.404  time: 0.3431 s/iter  data_time: 0.2159 s/iter total_throughput: 2984.14 samples/s lr: 3.33e-04  
[09/23 01:26:59] lb.utils.events INFO:  eta: 6:20:35  iteration: 230199/375342  consumed_samples: 235724800  total_loss: 3.402  time: 0.3431 s/iter  data_time: 0.2109 s/iter total_throughput: 2984.13 samples/s lr: 3.32e-04  
[09/23 01:27:34] lb.utils.events INFO:  eta: 6:18:57  iteration: 230299/375342  consumed_samples: 235827200  total_loss: 3.391  time: 0.3432 s/iter  data_time: 0.2199 s/iter total_throughput: 2984.11 samples/s lr: 3.32e-04  
[09/23 01:28:09] lb.utils.events INFO:  eta: 6:19:00  iteration: 230399/375342  consumed_samples: 235929600  total_loss: 3.388  time: 0.3432 s/iter  data_time: 0.2174 s/iter total_throughput: 2984.09 samples/s lr: 3.32e-04  
[09/23 01:28:44] lb.utils.events INFO:  eta: 6:19:35  iteration: 230499/375342  consumed_samples: 236032000  total_loss: 3.38  time: 0.3432 s/iter  data_time: 0.2341 s/iter total_throughput: 2984.07 samples/s lr: 3.31e-04  
[09/23 01:29:19] lb.utils.events INFO:  eta: 6:19:30  iteration: 230599/375342  consumed_samples: 236134400  total_loss: 3.388  time: 0.3432 s/iter  data_time: 0.2261 s/iter total_throughput: 2984.05 samples/s lr: 3.31e-04  
[09/23 01:29:54] lb.utils.events INFO:  eta: 6:19:04  iteration: 230699/375342  consumed_samples: 236236800  total_loss: 3.391  time: 0.3432 s/iter  data_time: 0.2297 s/iter total_throughput: 2984.01 samples/s lr: 3.31e-04  
[09/23 01:30:29] lb.utils.events INFO:  eta: 6:16:59  iteration: 230799/375342  consumed_samples: 236339200  total_loss: 3.399  time: 0.3432 s/iter  data_time: 0.2157 s/iter total_throughput: 2983.99 samples/s lr: 3.30e-04  
[09/23 01:31:04] lb.utils.events INFO:  eta: 6:16:35  iteration: 230899/375342  consumed_samples: 236441600  total_loss: 3.387  time: 0.3432 s/iter  data_time: 0.2382 s/iter total_throughput: 2983.96 samples/s lr: 3.30e-04  
[09/23 01:31:39] lb.utils.events INFO:  eta: 6:15:41  iteration: 230999/375342  consumed_samples: 236544000  total_loss: 3.381  time: 0.3432 s/iter  data_time: 0.2188 s/iter total_throughput: 2983.92 samples/s lr: 3.29e-04  
[09/23 01:32:14] lb.utils.events INFO:  eta: 6:12:46  iteration: 231099/375342  consumed_samples: 236646400  total_loss: 3.397  time: 0.3432 s/iter  data_time: 0.2158 s/iter total_throughput: 2983.91 samples/s lr: 3.29e-04  
[09/23 01:32:49] lb.utils.events INFO:  eta: 6:12:45  iteration: 231199/375342  consumed_samples: 236748800  total_loss: 3.389  time: 0.3432 s/iter  data_time: 0.2094 s/iter total_throughput: 2983.90 samples/s lr: 3.29e-04  
[09/23 01:33:24] lb.utils.events INFO:  eta: 6:12:24  iteration: 231299/375342  consumed_samples: 236851200  total_loss: 3.398  time: 0.3432 s/iter  data_time: 0.2272 s/iter total_throughput: 2983.87 samples/s lr: 3.28e-04  
[09/23 01:33:59] lb.utils.events INFO:  eta: 6:11:51  iteration: 231399/375342  consumed_samples: 236953600  total_loss: 3.412  time: 0.3432 s/iter  data_time: 0.2128 s/iter total_throughput: 2983.85 samples/s lr: 3.28e-04  
[09/23 01:34:33] lb.utils.events INFO:  eta: 6:11:47  iteration: 231499/375342  consumed_samples: 237056000  total_loss: 3.383  time: 0.3432 s/iter  data_time: 0.2225 s/iter total_throughput: 2983.83 samples/s lr: 3.27e-04  
[09/23 01:35:09] lb.utils.events INFO:  eta: 6:10:30  iteration: 231599/375342  consumed_samples: 237158400  total_loss: 3.389  time: 0.3432 s/iter  data_time: 0.2150 s/iter total_throughput: 2983.80 samples/s lr: 3.27e-04  
[09/23 01:35:43] lb.utils.events INFO:  eta: 6:11:50  iteration: 231699/375342  consumed_samples: 237260800  total_loss: 3.404  time: 0.3432 s/iter  data_time: 0.2256 s/iter total_throughput: 2983.79 samples/s lr: 3.27e-04  
[09/23 01:36:18] lb.utils.events INFO:  eta: 6:12:37  iteration: 231799/375342  consumed_samples: 237363200  total_loss: 3.394  time: 0.3432 s/iter  data_time: 0.2249 s/iter total_throughput: 2983.78 samples/s lr: 3.26e-04  
[09/23 01:36:53] lb.utils.events INFO:  eta: 6:12:59  iteration: 231899/375342  consumed_samples: 237465600  total_loss: 3.384  time: 0.3432 s/iter  data_time: 0.2084 s/iter total_throughput: 2983.77 samples/s lr: 3.26e-04  
[09/23 01:37:27] lb.utils.events INFO:  eta: 6:12:46  iteration: 231999/375342  consumed_samples: 237568000  total_loss: 3.371  time: 0.3432 s/iter  data_time: 0.2159 s/iter total_throughput: 2983.75 samples/s lr: 3.26e-04  
[09/23 01:38:02] lb.utils.events INFO:  eta: 6:12:46  iteration: 232099/375342  consumed_samples: 237670400  total_loss: 3.371  time: 0.3432 s/iter  data_time: 0.2272 s/iter total_throughput: 2983.72 samples/s lr: 3.25e-04  
[09/23 01:38:37] lb.utils.events INFO:  eta: 6:12:00  iteration: 232199/375342  consumed_samples: 237772800  total_loss: 3.371  time: 0.3432 s/iter  data_time: 0.2131 s/iter total_throughput: 2983.72 samples/s lr: 3.25e-04  
[09/23 01:39:11] lb.utils.events INFO:  eta: 6:11:43  iteration: 232299/375342  consumed_samples: 237875200  total_loss: 3.381  time: 0.3432 s/iter  data_time: 0.2285 s/iter total_throughput: 2983.70 samples/s lr: 3.24e-04  
[09/23 01:39:47] lb.utils.events INFO:  eta: 6:10:27  iteration: 232399/375342  consumed_samples: 237977600  total_loss: 3.381  time: 0.3432 s/iter  data_time: 0.2298 s/iter total_throughput: 2983.66 samples/s lr: 3.24e-04  
[09/23 01:40:22] lb.utils.events INFO:  eta: 6:09:20  iteration: 232499/375342  consumed_samples: 238080000  total_loss: 3.38  time: 0.3432 s/iter  data_time: 0.2171 s/iter total_throughput: 2983.64 samples/s lr: 3.24e-04  
[09/23 01:40:57] lb.utils.events INFO:  eta: 6:09:27  iteration: 232599/375342  consumed_samples: 238182400  total_loss: 3.404  time: 0.3432 s/iter  data_time: 0.2180 s/iter total_throughput: 2983.61 samples/s lr: 3.23e-04  
[09/23 01:41:32] lb.utils.events INFO:  eta: 6:07:48  iteration: 232699/375342  consumed_samples: 238284800  total_loss: 3.406  time: 0.3432 s/iter  data_time: 0.2221 s/iter total_throughput: 2983.58 samples/s lr: 3.23e-04  
[09/23 01:42:07] lb.utils.events INFO:  eta: 6:07:21  iteration: 232799/375342  consumed_samples: 238387200  total_loss: 3.378  time: 0.3432 s/iter  data_time: 0.2125 s/iter total_throughput: 2983.58 samples/s lr: 3.22e-04  
[09/23 01:42:42] lb.utils.events INFO:  eta: 6:06:23  iteration: 232899/375342  consumed_samples: 238489600  total_loss: 3.376  time: 0.3432 s/iter  data_time: 0.2285 s/iter total_throughput: 2983.55 samples/s lr: 3.22e-04  
[09/23 01:43:17] lb.utils.events INFO:  eta: 6:05:49  iteration: 232999/375342  consumed_samples: 238592000  total_loss: 3.386  time: 0.3432 s/iter  data_time: 0.2231 s/iter total_throughput: 2983.53 samples/s lr: 3.22e-04  
[09/23 01:43:52] lb.utils.events INFO:  eta: 6:05:27  iteration: 233099/375342  consumed_samples: 238694400  total_loss: 3.367  time: 0.3432 s/iter  data_time: 0.2282 s/iter total_throughput: 2983.49 samples/s lr: 3.21e-04  
[09/23 01:44:27] lb.utils.events INFO:  eta: 6:04:31  iteration: 233199/375342  consumed_samples: 238796800  total_loss: 3.367  time: 0.3432 s/iter  data_time: 0.2339 s/iter total_throughput: 2983.47 samples/s lr: 3.21e-04  
[09/23 01:45:02] lb.utils.events INFO:  eta: 6:04:13  iteration: 233299/375342  consumed_samples: 238899200  total_loss: 3.373  time: 0.3432 s/iter  data_time: 0.2153 s/iter total_throughput: 2983.43 samples/s lr: 3.21e-04  
[09/23 01:45:37] lb.utils.events INFO:  eta: 6:05:04  iteration: 233399/375342  consumed_samples: 239001600  total_loss: 3.392  time: 0.3432 s/iter  data_time: 0.2250 s/iter total_throughput: 2983.41 samples/s lr: 3.20e-04  
[09/23 01:46:12] lb.utils.events INFO:  eta: 6:05:40  iteration: 233499/375342  consumed_samples: 239104000  total_loss: 3.396  time: 0.3432 s/iter  data_time: 0.2205 s/iter total_throughput: 2983.40 samples/s lr: 3.20e-04  
[09/23 01:46:47] lb.utils.events INFO:  eta: 6:04:42  iteration: 233599/375342  consumed_samples: 239206400  total_loss: 3.383  time: 0.3432 s/iter  data_time: 0.2331 s/iter total_throughput: 2983.37 samples/s lr: 3.19e-04  
[09/23 01:47:22] lb.utils.events INFO:  eta: 6:05:36  iteration: 233699/375342  consumed_samples: 239308800  total_loss: 3.388  time: 0.3432 s/iter  data_time: 0.2178 s/iter total_throughput: 2983.35 samples/s lr: 3.19e-04  
[09/23 01:47:56] lb.utils.events INFO:  eta: 6:04:08  iteration: 233799/375342  consumed_samples: 239411200  total_loss: 3.387  time: 0.3432 s/iter  data_time: 0.2211 s/iter total_throughput: 2983.35 samples/s lr: 3.19e-04  
[09/23 01:48:30] lb.utils.events INFO:  eta: 6:04:28  iteration: 233899/375342  consumed_samples: 239513600  total_loss: 3.393  time: 0.3432 s/iter  data_time: 0.2202 s/iter total_throughput: 2983.34 samples/s lr: 3.18e-04  
[09/23 01:49:05] lb.utils.events INFO:  eta: 6:05:26  iteration: 233999/375342  consumed_samples: 239616000  total_loss: 3.393  time: 0.3432 s/iter  data_time: 0.2378 s/iter total_throughput: 2983.33 samples/s lr: 3.18e-04  
[09/23 01:49:40] lb.utils.events INFO:  eta: 6:04:37  iteration: 234099/375342  consumed_samples: 239718400  total_loss: 3.355  time: 0.3432 s/iter  data_time: 0.2132 s/iter total_throughput: 2983.32 samples/s lr: 3.17e-04  
[09/23 01:50:14] lb.utils.events INFO:  eta: 6:04:46  iteration: 234199/375342  consumed_samples: 239820800  total_loss: 3.345  time: 0.3432 s/iter  data_time: 0.2206 s/iter total_throughput: 2983.31 samples/s lr: 3.17e-04  
[09/23 01:50:49] lb.utils.events INFO:  eta: 6:05:28  iteration: 234299/375342  consumed_samples: 239923200  total_loss: 3.364  time: 0.3432 s/iter  data_time: 0.2225 s/iter total_throughput: 2983.31 samples/s lr: 3.17e-04  
[09/23 01:51:23] lb.utils.events INFO:  eta: 6:05:06  iteration: 234399/375342  consumed_samples: 240025600  total_loss: 3.373  time: 0.3432 s/iter  data_time: 0.2226 s/iter total_throughput: 2983.29 samples/s lr: 3.16e-04  
[09/23 01:51:58] lb.utils.events INFO:  eta: 6:04:50  iteration: 234499/375342  consumed_samples: 240128000  total_loss: 3.393  time: 0.3432 s/iter  data_time: 0.2048 s/iter total_throughput: 2983.30 samples/s lr: 3.16e-04  
[09/23 01:52:33] lb.utils.events INFO:  eta: 6:04:48  iteration: 234599/375342  consumed_samples: 240230400  total_loss: 3.409  time: 0.3432 s/iter  data_time: 0.2253 s/iter total_throughput: 2983.28 samples/s lr: 3.16e-04  
[09/23 01:53:07] lb.utils.events INFO:  eta: 6:04:17  iteration: 234699/375342  consumed_samples: 240332800  total_loss: 3.376  time: 0.3432 s/iter  data_time: 0.2273 s/iter total_throughput: 2983.26 samples/s lr: 3.15e-04  
[09/23 01:53:42] lb.utils.events INFO:  eta: 6:05:09  iteration: 234799/375342  consumed_samples: 240435200  total_loss: 3.376  time: 0.3433 s/iter  data_time: 0.2128 s/iter total_throughput: 2983.25 samples/s lr: 3.15e-04  
[09/23 01:54:16] lb.utils.events INFO:  eta: 6:04:12  iteration: 234899/375342  consumed_samples: 240537600  total_loss: 3.397  time: 0.3432 s/iter  data_time: 0.2181 s/iter total_throughput: 2983.25 samples/s lr: 3.14e-04  
[09/23 01:54:51] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0234999
[09/23 01:54:52] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/23 01:54:52] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/23 01:54:56] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.1063 s/iter. Inference: 0.1608 s/iter. Eval: 0.0021 s/iter. Total: 0.2692 s/iter. ETA=0:00:09
[09/23 01:55:02] lb.evaluation.evaluator INFO: Inference done 29696/50000. Dataloading: 0.1359 s/iter. Inference: 0.1635 s/iter. Eval: 0.0019 s/iter. Total: 0.3013 s/iter. ETA=0:00:05
[09/23 01:55:07] lb.evaluation.evaluator INFO: Inference done 49152/50000. Dataloading: 0.1243 s/iter. Inference: 0.1617 s/iter. Eval: 0.0020 s/iter. Total: 0.2880 s/iter. ETA=0:00:00
[09/23 01:55:07] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/23 01:55:07] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.672490 (0.000253 s / iter per device, on 8 devices)
[09/23 01:55:07] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000143 s / iter per device, on 8 devices)
[09/23 01:55:07] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/23 01:55:07] lb.evaluation.utils INFO: copypaste: Acc@1=76.82
[09/23 01:55:07] lb.evaluation.utils INFO: copypaste: Acc@5=93.374
[09/23 01:55:07] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 76.82000, better than last best score 76.57000 @ iteration 229999.
[09/23 01:55:07] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/23 01:55:08] lb.utils.events INFO:  eta: 6:03:44  iteration: 234999/375342  consumed_samples: 240640000  total_loss: 3.401  time: 0.3433 s/iter  data_time: 0.2272 s/iter total_throughput: 2983.23 samples/s lr: 3.14e-04  
[09/23 01:55:40] lb.utils.events INFO:  eta: 6:06:21  iteration: 235099/375342  consumed_samples: 240742400  total_loss: 3.403  time: 0.3432 s/iter  data_time: 0.2244 s/iter total_throughput: 2983.30 samples/s lr: 3.14e-04  
[09/23 01:56:15] lb.utils.events INFO:  eta: 6:06:11  iteration: 235199/375342  consumed_samples: 240844800  total_loss: 3.387  time: 0.3432 s/iter  data_time: 0.2175 s/iter total_throughput: 2983.28 samples/s lr: 3.13e-04  
[09/23 01:56:50] lb.utils.events INFO:  eta: 6:05:40  iteration: 235299/375342  consumed_samples: 240947200  total_loss: 3.376  time: 0.3432 s/iter  data_time: 0.2169 s/iter total_throughput: 2983.28 samples/s lr: 3.13e-04  
[09/23 01:57:24] lb.utils.events INFO:  eta: 6:05:52  iteration: 235399/375342  consumed_samples: 241049600  total_loss: 3.372  time: 0.3432 s/iter  data_time: 0.2203 s/iter total_throughput: 2983.28 samples/s lr: 3.12e-04  
[09/23 01:57:59] lb.utils.events INFO:  eta: 6:05:28  iteration: 235499/375342  consumed_samples: 241152000  total_loss: 3.36  time: 0.3432 s/iter  data_time: 0.2253 s/iter total_throughput: 2983.27 samples/s lr: 3.12e-04  
[09/23 01:58:33] lb.utils.events INFO:  eta: 6:04:13  iteration: 235599/375342  consumed_samples: 241254400  total_loss: 3.351  time: 0.3432 s/iter  data_time: 0.2241 s/iter total_throughput: 2983.26 samples/s lr: 3.12e-04  
[09/23 01:59:08] lb.utils.events INFO:  eta: 6:04:16  iteration: 235699/375342  consumed_samples: 241356800  total_loss: 3.355  time: 0.3432 s/iter  data_time: 0.2228 s/iter total_throughput: 2983.25 samples/s lr: 3.11e-04  
[09/23 01:59:43] lb.utils.events INFO:  eta: 6:02:51  iteration: 235799/375342  consumed_samples: 241459200  total_loss: 3.373  time: 0.3433 s/iter  data_time: 0.2314 s/iter total_throughput: 2983.23 samples/s lr: 3.11e-04  
[09/23 02:00:17] lb.utils.events INFO:  eta: 6:03:02  iteration: 235899/375342  consumed_samples: 241561600  total_loss: 3.385  time: 0.3433 s/iter  data_time: 0.2222 s/iter total_throughput: 2983.22 samples/s lr: 3.11e-04  
[09/23 02:00:52] lb.utils.events INFO:  eta: 6:02:29  iteration: 235999/375342  consumed_samples: 241664000  total_loss: 3.371  time: 0.3433 s/iter  data_time: 0.2289 s/iter total_throughput: 2983.20 samples/s lr: 3.10e-04  
[09/23 02:01:27] lb.utils.events INFO:  eta: 6:00:13  iteration: 236099/375342  consumed_samples: 241766400  total_loss: 3.391  time: 0.3433 s/iter  data_time: 0.2170 s/iter total_throughput: 2983.19 samples/s lr: 3.10e-04  
[09/23 02:02:01] lb.utils.events INFO:  eta: 6:00:10  iteration: 236199/375342  consumed_samples: 241868800  total_loss: 3.391  time: 0.3433 s/iter  data_time: 0.2112 s/iter total_throughput: 2983.18 samples/s lr: 3.09e-04  
[09/23 02:02:35] lb.utils.events INFO:  eta: 5:59:53  iteration: 236299/375342  consumed_samples: 241971200  total_loss: 3.356  time: 0.3433 s/iter  data_time: 0.2077 s/iter total_throughput: 2983.19 samples/s lr: 3.09e-04  
[09/23 02:03:10] lb.utils.events INFO:  eta: 5:59:44  iteration: 236399/375342  consumed_samples: 242073600  total_loss: 3.369  time: 0.3433 s/iter  data_time: 0.2207 s/iter total_throughput: 2983.19 samples/s lr: 3.09e-04  
[09/23 02:03:44] lb.utils.events INFO:  eta: 5:59:45  iteration: 236499/375342  consumed_samples: 242176000  total_loss: 3.383  time: 0.3433 s/iter  data_time: 0.2185 s/iter total_throughput: 2983.19 samples/s lr: 3.08e-04  
[09/23 02:04:19] lb.utils.events INFO:  eta: 5:59:38  iteration: 236599/375342  consumed_samples: 242278400  total_loss: 3.383  time: 0.3433 s/iter  data_time: 0.2163 s/iter total_throughput: 2983.18 samples/s lr: 3.08e-04  
[09/23 02:04:53] lb.utils.events INFO:  eta: 6:00:02  iteration: 236699/375342  consumed_samples: 242380800  total_loss: 3.378  time: 0.3433 s/iter  data_time: 0.2243 s/iter total_throughput: 2983.17 samples/s lr: 3.08e-04  
[09/23 02:05:28] lb.utils.events INFO:  eta: 6:00:31  iteration: 236799/375342  consumed_samples: 242483200  total_loss: 3.374  time: 0.3433 s/iter  data_time: 0.2155 s/iter total_throughput: 2983.16 samples/s lr: 3.07e-04  
[09/23 02:06:03] lb.utils.events INFO:  eta: 5:59:22  iteration: 236899/375342  consumed_samples: 242585600  total_loss: 3.364  time: 0.3433 s/iter  data_time: 0.2218 s/iter total_throughput: 2983.15 samples/s lr: 3.07e-04  
[09/23 02:06:37] lb.utils.events INFO:  eta: 5:58:27  iteration: 236999/375342  consumed_samples: 242688000  total_loss: 3.347  time: 0.3433 s/iter  data_time: 0.2268 s/iter total_throughput: 2983.14 samples/s lr: 3.06e-04  
[09/23 02:07:12] lb.utils.events INFO:  eta: 5:58:12  iteration: 237099/375342  consumed_samples: 242790400  total_loss: 3.379  time: 0.3433 s/iter  data_time: 0.2271 s/iter total_throughput: 2983.14 samples/s lr: 3.06e-04  
[09/23 02:07:46] lb.utils.events INFO:  eta: 5:57:41  iteration: 237199/375342  consumed_samples: 242892800  total_loss: 3.385  time: 0.3433 s/iter  data_time: 0.2137 s/iter total_throughput: 2983.13 samples/s lr: 3.06e-04  
[09/23 02:08:21] lb.utils.events INFO:  eta: 5:56:58  iteration: 237299/375342  consumed_samples: 242995200  total_loss: 3.355  time: 0.3433 s/iter  data_time: 0.2309 s/iter total_throughput: 2983.12 samples/s lr: 3.05e-04  
[09/23 02:08:55] lb.utils.events INFO:  eta: 5:56:32  iteration: 237399/375342  consumed_samples: 243097600  total_loss: 3.348  time: 0.3433 s/iter  data_time: 0.2075 s/iter total_throughput: 2983.12 samples/s lr: 3.05e-04  
[09/23 02:09:29] lb.utils.events INFO:  eta: 5:56:31  iteration: 237499/375342  consumed_samples: 243200000  total_loss: 3.346  time: 0.3433 s/iter  data_time: 0.2264 s/iter total_throughput: 2983.13 samples/s lr: 3.04e-04  
[09/23 02:10:04] lb.utils.events INFO:  eta: 5:56:02  iteration: 237599/375342  consumed_samples: 243302400  total_loss: 3.363  time: 0.3433 s/iter  data_time: 0.2102 s/iter total_throughput: 2983.12 samples/s lr: 3.04e-04  
[09/23 02:10:38] lb.utils.events INFO:  eta: 5:56:00  iteration: 237699/375342  consumed_samples: 243404800  total_loss: 3.385  time: 0.3433 s/iter  data_time: 0.2155 s/iter total_throughput: 2983.12 samples/s lr: 3.04e-04  
[09/23 02:11:12] lb.utils.events INFO:  eta: 5:55:28  iteration: 237799/375342  consumed_samples: 243507200  total_loss: 3.377  time: 0.3433 s/iter  data_time: 0.2034 s/iter total_throughput: 2983.13 samples/s lr: 3.03e-04  
[09/23 02:11:47] lb.utils.events INFO:  eta: 5:55:15  iteration: 237899/375342  consumed_samples: 243609600  total_loss: 3.354  time: 0.3433 s/iter  data_time: 0.2297 s/iter total_throughput: 2983.12 samples/s lr: 3.03e-04  
[09/23 02:12:21] lb.utils.events INFO:  eta: 5:55:13  iteration: 237999/375342  consumed_samples: 243712000  total_loss: 3.358  time: 0.3433 s/iter  data_time: 0.2096 s/iter total_throughput: 2983.13 samples/s lr: 3.03e-04  
[09/23 02:12:56] lb.utils.events INFO:  eta: 5:54:56  iteration: 238099/375342  consumed_samples: 243814400  total_loss: 3.374  time: 0.3433 s/iter  data_time: 0.2245 s/iter total_throughput: 2983.11 samples/s lr: 3.02e-04  
[09/23 02:13:30] lb.utils.events INFO:  eta: 5:54:34  iteration: 238199/375342  consumed_samples: 243916800  total_loss: 3.384  time: 0.3433 s/iter  data_time: 0.2413 s/iter total_throughput: 2983.09 samples/s lr: 3.02e-04  
[09/23 02:14:06] lb.utils.events INFO:  eta: 5:53:40  iteration: 238299/375342  consumed_samples: 244019200  total_loss: 3.374  time: 0.3433 s/iter  data_time: 0.2280 s/iter total_throughput: 2983.06 samples/s lr: 3.01e-04  
[09/23 02:14:41] lb.utils.events INFO:  eta: 5:52:14  iteration: 238399/375342  consumed_samples: 244121600  total_loss: 3.355  time: 0.3433 s/iter  data_time: 0.2230 s/iter total_throughput: 2983.02 samples/s lr: 3.01e-04  
[09/23 02:15:17] lb.utils.events INFO:  eta: 5:51:34  iteration: 238499/375342  consumed_samples: 244224000  total_loss: 3.343  time: 0.3433 s/iter  data_time: 0.2261 s/iter total_throughput: 2982.98 samples/s lr: 3.01e-04  
[09/23 02:15:52] lb.utils.events INFO:  eta: 5:51:16  iteration: 238599/375342  consumed_samples: 244326400  total_loss: 3.364  time: 0.3433 s/iter  data_time: 0.2320 s/iter total_throughput: 2982.93 samples/s lr: 3.00e-04  
[09/23 02:16:27] lb.utils.events INFO:  eta: 5:50:40  iteration: 238699/375342  consumed_samples: 244428800  total_loss: 3.385  time: 0.3433 s/iter  data_time: 0.2266 s/iter total_throughput: 2982.90 samples/s lr: 3.00e-04  
[09/23 02:17:02] lb.utils.events INFO:  eta: 5:50:06  iteration: 238799/375342  consumed_samples: 244531200  total_loss: 3.386  time: 0.3433 s/iter  data_time: 0.2246 s/iter total_throughput: 2982.87 samples/s lr: 3.00e-04  
[09/23 02:17:37] lb.utils.events INFO:  eta: 5:50:27  iteration: 238899/375342  consumed_samples: 244633600  total_loss: 3.393  time: 0.3433 s/iter  data_time: 0.2308 s/iter total_throughput: 2982.85 samples/s lr: 2.99e-04  
[09/23 02:18:13] lb.utils.events INFO:  eta: 5:49:41  iteration: 238999/375342  consumed_samples: 244736000  total_loss: 3.359  time: 0.3433 s/iter  data_time: 0.2193 s/iter total_throughput: 2982.82 samples/s lr: 2.99e-04  
[09/23 02:18:48] lb.utils.events INFO:  eta: 5:49:20  iteration: 239099/375342  consumed_samples: 244838400  total_loss: 3.363  time: 0.3433 s/iter  data_time: 0.2264 s/iter total_throughput: 2982.77 samples/s lr: 2.98e-04  
[09/23 02:19:23] lb.utils.events INFO:  eta: 5:50:18  iteration: 239199/375342  consumed_samples: 244940800  total_loss: 3.363  time: 0.3433 s/iter  data_time: 0.2204 s/iter total_throughput: 2982.75 samples/s lr: 2.98e-04  
[09/23 02:19:59] lb.utils.events INFO:  eta: 5:51:12  iteration: 239299/375342  consumed_samples: 245043200  total_loss: 3.346  time: 0.3433 s/iter  data_time: 0.2482 s/iter total_throughput: 2982.71 samples/s lr: 2.98e-04  
[09/23 02:20:34] lb.utils.events INFO:  eta: 5:51:07  iteration: 239399/375342  consumed_samples: 245145600  total_loss: 3.341  time: 0.3433 s/iter  data_time: 0.2264 s/iter total_throughput: 2982.66 samples/s lr: 2.97e-04  
[09/23 02:21:09] lb.utils.events INFO:  eta: 5:50:43  iteration: 239499/375342  consumed_samples: 245248000  total_loss: 3.356  time: 0.3433 s/iter  data_time: 0.2306 s/iter total_throughput: 2982.63 samples/s lr: 2.97e-04  
[09/23 02:21:45] lb.utils.events INFO:  eta: 5:51:02  iteration: 239599/375342  consumed_samples: 245350400  total_loss: 3.367  time: 0.3433 s/iter  data_time: 0.2339 s/iter total_throughput: 2982.60 samples/s lr: 2.97e-04  
[09/23 02:22:20] lb.utils.events INFO:  eta: 5:50:12  iteration: 239699/375342  consumed_samples: 245452800  total_loss: 3.37  time: 0.3433 s/iter  data_time: 0.2302 s/iter total_throughput: 2982.56 samples/s lr: 2.96e-04  
[09/23 02:22:56] lb.utils.events INFO:  eta: 5:50:05  iteration: 239799/375342  consumed_samples: 245555200  total_loss: 3.369  time: 0.3433 s/iter  data_time: 0.2359 s/iter total_throughput: 2982.52 samples/s lr: 2.96e-04  
[09/23 02:23:30] lb.utils.events INFO:  eta: 5:50:03  iteration: 239899/375342  consumed_samples: 245657600  total_loss: 3.352  time: 0.3433 s/iter  data_time: 0.2164 s/iter total_throughput: 2982.50 samples/s lr: 2.95e-04  
[09/23 02:24:05] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0239999
[09/23 02:24:06] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/23 02:24:06] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/23 02:24:10] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.1048 s/iter. Inference: 0.1613 s/iter. Eval: 0.0020 s/iter. Total: 0.2682 s/iter. ETA=0:00:09
[09/23 02:24:15] lb.evaluation.evaluator INFO: Inference done 28672/50000. Dataloading: 0.1142 s/iter. Inference: 0.1738 s/iter. Eval: 0.0020 s/iter. Total: 0.2902 s/iter. ETA=0:00:05
[09/23 02:24:21] lb.evaluation.evaluator INFO: Inference done 47104/50000. Dataloading: 0.1214 s/iter. Inference: 0.1680 s/iter. Eval: 0.0021 s/iter. Total: 0.2915 s/iter. ETA=0:00:00
[09/23 02:24:21] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/23 02:24:21] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.603027 (0.000252 s / iter per device, on 8 devices)
[09/23 02:24:21] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000148 s / iter per device, on 8 devices)
[09/23 02:24:21] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/23 02:24:21] lb.evaluation.utils INFO: copypaste: Acc@1=77.13
[09/23 02:24:21] lb.evaluation.utils INFO: copypaste: Acc@5=93.53
[09/23 02:24:21] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 77.13000, better than last best score 76.82000 @ iteration 234999.
[09/23 02:24:21] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/23 02:24:22] lb.utils.events INFO:  eta: 5:49:43  iteration: 239999/375342  consumed_samples: 245760000  total_loss: 3.354  time: 0.3433 s/iter  data_time: 0.2331 s/iter total_throughput: 2982.48 samples/s lr: 2.95e-04  
[09/23 02:24:55] lb.utils.events INFO:  eta: 5:51:29  iteration: 240099/375342  consumed_samples: 245862400  total_loss: 3.378  time: 0.3433 s/iter  data_time: 0.2223 s/iter total_throughput: 2982.53 samples/s lr: 2.95e-04  
[09/23 02:25:30] lb.utils.events INFO:  eta: 5:51:25  iteration: 240199/375342  consumed_samples: 245964800  total_loss: 3.36  time: 0.3433 s/iter  data_time: 0.2177 s/iter total_throughput: 2982.52 samples/s lr: 2.94e-04  
[09/23 02:26:05] lb.utils.events INFO:  eta: 5:50:46  iteration: 240299/375342  consumed_samples: 246067200  total_loss: 3.34  time: 0.3433 s/iter  data_time: 0.2251 s/iter total_throughput: 2982.49 samples/s lr: 2.94e-04  
[09/23 02:26:40] lb.utils.events INFO:  eta: 5:51:49  iteration: 240399/375342  consumed_samples: 246169600  total_loss: 3.342  time: 0.3433 s/iter  data_time: 0.2221 s/iter total_throughput: 2982.48 samples/s lr: 2.94e-04  
[09/23 02:27:15] lb.utils.events INFO:  eta: 5:52:13  iteration: 240499/375342  consumed_samples: 246272000  total_loss: 3.347  time: 0.3433 s/iter  data_time: 0.2305 s/iter total_throughput: 2982.44 samples/s lr: 2.93e-04  
[09/23 02:27:50] lb.utils.events INFO:  eta: 5:52:21  iteration: 240599/375342  consumed_samples: 246374400  total_loss: 3.354  time: 0.3433 s/iter  data_time: 0.2237 s/iter total_throughput: 2982.43 samples/s lr: 2.93e-04  
[09/23 02:28:25] lb.utils.events INFO:  eta: 5:52:24  iteration: 240699/375342  consumed_samples: 246476800  total_loss: 3.363  time: 0.3433 s/iter  data_time: 0.2438 s/iter total_throughput: 2982.40 samples/s lr: 2.92e-04  
[09/23 02:29:00] lb.utils.events INFO:  eta: 5:52:24  iteration: 240799/375342  consumed_samples: 246579200  total_loss: 3.349  time: 0.3434 s/iter  data_time: 0.2394 s/iter total_throughput: 2982.36 samples/s lr: 2.92e-04  
[09/23 02:29:35] lb.utils.events INFO:  eta: 5:51:56  iteration: 240899/375342  consumed_samples: 246681600  total_loss: 3.345  time: 0.3434 s/iter  data_time: 0.2183 s/iter total_throughput: 2982.33 samples/s lr: 2.92e-04  
[09/23 02:30:10] lb.utils.events INFO:  eta: 5:50:56  iteration: 240999/375342  consumed_samples: 246784000  total_loss: 3.356  time: 0.3434 s/iter  data_time: 0.2198 s/iter total_throughput: 2982.30 samples/s lr: 2.91e-04  
[09/23 02:30:45] lb.utils.events INFO:  eta: 5:49:53  iteration: 241099/375342  consumed_samples: 246886400  total_loss: 3.367  time: 0.3434 s/iter  data_time: 0.2229 s/iter total_throughput: 2982.28 samples/s lr: 2.91e-04  
[09/23 02:31:21] lb.utils.events INFO:  eta: 5:48:56  iteration: 241199/375342  consumed_samples: 246988800  total_loss: 3.359  time: 0.3434 s/iter  data_time: 0.2355 s/iter total_throughput: 2982.23 samples/s lr: 2.91e-04  
[09/23 02:31:56] lb.utils.events INFO:  eta: 5:48:57  iteration: 241299/375342  consumed_samples: 247091200  total_loss: 3.354  time: 0.3434 s/iter  data_time: 0.2278 s/iter total_throughput: 2982.21 samples/s lr: 2.90e-04  
[09/23 02:32:31] lb.utils.events INFO:  eta: 5:48:44  iteration: 241399/375342  consumed_samples: 247193600  total_loss: 3.356  time: 0.3434 s/iter  data_time: 0.2195 s/iter total_throughput: 2982.19 samples/s lr: 2.90e-04  
[09/23 02:33:06] lb.utils.events INFO:  eta: 5:48:26  iteration: 241499/375342  consumed_samples: 247296000  total_loss: 3.368  time: 0.3434 s/iter  data_time: 0.2210 s/iter total_throughput: 2982.17 samples/s lr: 2.89e-04  
[09/23 02:33:41] lb.utils.events INFO:  eta: 5:47:22  iteration: 241599/375342  consumed_samples: 247398400  total_loss: 3.354  time: 0.3434 s/iter  data_time: 0.2285 s/iter total_throughput: 2982.15 samples/s lr: 2.89e-04  
[09/23 02:34:16] lb.utils.events INFO:  eta: 5:47:23  iteration: 241699/375342  consumed_samples: 247500800  total_loss: 3.341  time: 0.3434 s/iter  data_time: 0.2188 s/iter total_throughput: 2982.12 samples/s lr: 2.89e-04  
[09/23 02:34:51] lb.utils.events INFO:  eta: 5:46:35  iteration: 241799/375342  consumed_samples: 247603200  total_loss: 3.347  time: 0.3434 s/iter  data_time: 0.2352 s/iter total_throughput: 2982.08 samples/s lr: 2.88e-04  
[09/23 02:35:26] lb.utils.events INFO:  eta: 5:45:56  iteration: 241899/375342  consumed_samples: 247705600  total_loss: 3.348  time: 0.3434 s/iter  data_time: 0.2131 s/iter total_throughput: 2982.05 samples/s lr: 2.88e-04  
[09/23 02:36:02] lb.utils.events INFO:  eta: 5:45:49  iteration: 241999/375342  consumed_samples: 247808000  total_loss: 3.346  time: 0.3434 s/iter  data_time: 0.2390 s/iter total_throughput: 2982.02 samples/s lr: 2.88e-04  
[09/23 02:36:37] lb.utils.events INFO:  eta: 5:45:17  iteration: 242099/375342  consumed_samples: 247910400  total_loss: 3.346  time: 0.3434 s/iter  data_time: 0.2204 s/iter total_throughput: 2981.99 samples/s lr: 2.87e-04  
[09/23 02:37:11] lb.utils.events INFO:  eta: 5:45:37  iteration: 242199/375342  consumed_samples: 248012800  total_loss: 3.346  time: 0.3434 s/iter  data_time: 0.2151 s/iter total_throughput: 2981.99 samples/s lr: 2.87e-04  
[09/23 02:37:46] lb.utils.events INFO:  eta: 5:45:02  iteration: 242299/375342  consumed_samples: 248115200  total_loss: 3.362  time: 0.3434 s/iter  data_time: 0.2202 s/iter total_throughput: 2981.98 samples/s lr: 2.86e-04  
[09/23 02:38:21] lb.utils.events INFO:  eta: 5:44:03  iteration: 242399/375342  consumed_samples: 248217600  total_loss: 3.348  time: 0.3434 s/iter  data_time: 0.2150 s/iter total_throughput: 2981.96 samples/s lr: 2.86e-04  
[09/23 02:38:56] lb.utils.events INFO:  eta: 5:43:28  iteration: 242499/375342  consumed_samples: 248320000  total_loss: 3.339  time: 0.3434 s/iter  data_time: 0.2303 s/iter total_throughput: 2981.93 samples/s lr: 2.86e-04  
[09/23 02:39:31] lb.utils.events INFO:  eta: 5:43:27  iteration: 242599/375342  consumed_samples: 248422400  total_loss: 3.337  time: 0.3434 s/iter  data_time: 0.2190 s/iter total_throughput: 2981.91 samples/s lr: 2.85e-04  
[09/23 02:40:06] lb.utils.events INFO:  eta: 5:43:23  iteration: 242699/375342  consumed_samples: 248524800  total_loss: 3.342  time: 0.3434 s/iter  data_time: 0.2141 s/iter total_throughput: 2981.90 samples/s lr: 2.85e-04  
[09/23 02:40:41] lb.utils.events INFO:  eta: 5:43:23  iteration: 242799/375342  consumed_samples: 248627200  total_loss: 3.342  time: 0.3434 s/iter  data_time: 0.2188 s/iter total_throughput: 2981.87 samples/s lr: 2.85e-04  
[09/23 02:41:15] lb.utils.events INFO:  eta: 5:43:32  iteration: 242899/375342  consumed_samples: 248729600  total_loss: 3.358  time: 0.3434 s/iter  data_time: 0.2136 s/iter total_throughput: 2981.86 samples/s lr: 2.84e-04  
[09/23 02:41:51] lb.utils.events INFO:  eta: 5:43:18  iteration: 242999/375342  consumed_samples: 248832000  total_loss: 3.361  time: 0.3434 s/iter  data_time: 0.2390 s/iter total_throughput: 2981.83 samples/s lr: 2.84e-04  
[09/23 02:42:25] lb.utils.events INFO:  eta: 5:42:42  iteration: 243099/375342  consumed_samples: 248934400  total_loss: 3.32  time: 0.3434 s/iter  data_time: 0.2145 s/iter total_throughput: 2981.81 samples/s lr: 2.84e-04  
[09/23 02:43:01] lb.utils.events INFO:  eta: 5:42:12  iteration: 243199/375342  consumed_samples: 249036800  total_loss: 3.32  time: 0.3434 s/iter  data_time: 0.2267 s/iter total_throughput: 2981.77 samples/s lr: 2.83e-04  
[09/23 02:43:36] lb.utils.events INFO:  eta: 5:41:57  iteration: 243299/375342  consumed_samples: 249139200  total_loss: 3.332  time: 0.3434 s/iter  data_time: 0.2183 s/iter total_throughput: 2981.76 samples/s lr: 2.83e-04  
[09/23 02:44:11] lb.utils.events INFO:  eta: 5:41:21  iteration: 243399/375342  consumed_samples: 249241600  total_loss: 3.333  time: 0.3434 s/iter  data_time: 0.2166 s/iter total_throughput: 2981.74 samples/s lr: 2.82e-04  
[09/23 02:44:46] lb.utils.events INFO:  eta: 5:40:51  iteration: 243499/375342  consumed_samples: 249344000  total_loss: 3.351  time: 0.3434 s/iter  data_time: 0.2382 s/iter total_throughput: 2981.70 samples/s lr: 2.82e-04  
[09/23 02:45:21] lb.utils.events INFO:  eta: 5:40:50  iteration: 243599/375342  consumed_samples: 249446400  total_loss: 3.358  time: 0.3434 s/iter  data_time: 0.2275 s/iter total_throughput: 2981.67 samples/s lr: 2.82e-04  
[09/23 02:45:56] lb.utils.events INFO:  eta: 5:40:14  iteration: 243699/375342  consumed_samples: 249548800  total_loss: 3.363  time: 0.3434 s/iter  data_time: 0.2316 s/iter total_throughput: 2981.66 samples/s lr: 2.81e-04  
[09/23 02:46:31] lb.utils.events INFO:  eta: 5:39:45  iteration: 243799/375342  consumed_samples: 249651200  total_loss: 3.361  time: 0.3434 s/iter  data_time: 0.2223 s/iter total_throughput: 2981.63 samples/s lr: 2.81e-04  
[09/23 02:47:06] lb.utils.events INFO:  eta: 5:39:32  iteration: 243899/375342  consumed_samples: 249753600  total_loss: 3.349  time: 0.3434 s/iter  data_time: 0.2126 s/iter total_throughput: 2981.60 samples/s lr: 2.81e-04  
[09/23 02:47:42] lb.utils.events INFO:  eta: 5:39:28  iteration: 243999/375342  consumed_samples: 249856000  total_loss: 3.349  time: 0.3434 s/iter  data_time: 0.2212 s/iter total_throughput: 2981.56 samples/s lr: 2.80e-04  
[09/23 02:48:17] lb.utils.events INFO:  eta: 5:39:34  iteration: 244099/375342  consumed_samples: 249958400  total_loss: 3.336  time: 0.3434 s/iter  data_time: 0.2329 s/iter total_throughput: 2981.52 samples/s lr: 2.80e-04  
[09/23 02:48:52] lb.utils.events INFO:  eta: 5:39:25  iteration: 244199/375342  consumed_samples: 250060800  total_loss: 3.318  time: 0.3435 s/iter  data_time: 0.2162 s/iter total_throughput: 2981.51 samples/s lr: 2.79e-04  
[09/23 02:49:27] lb.utils.events INFO:  eta: 5:38:42  iteration: 244299/375342  consumed_samples: 250163200  total_loss: 3.318  time: 0.3435 s/iter  data_time: 0.2276 s/iter total_throughput: 2981.47 samples/s lr: 2.79e-04  
[09/23 02:50:02] lb.utils.events INFO:  eta: 5:39:08  iteration: 244399/375342  consumed_samples: 250265600  total_loss: 3.318  time: 0.3435 s/iter  data_time: 0.2296 s/iter total_throughput: 2981.45 samples/s lr: 2.79e-04  
[09/23 02:50:38] lb.utils.events INFO:  eta: 5:38:52  iteration: 244499/375342  consumed_samples: 250368000  total_loss: 3.312  time: 0.3435 s/iter  data_time: 0.2396 s/iter total_throughput: 2981.41 samples/s lr: 2.78e-04  
[09/23 02:51:12] lb.utils.events INFO:  eta: 5:38:39  iteration: 244599/375342  consumed_samples: 250470400  total_loss: 3.333  time: 0.3435 s/iter  data_time: 0.2246 s/iter total_throughput: 2981.40 samples/s lr: 2.78e-04  
[09/23 02:51:47] lb.utils.events INFO:  eta: 5:38:16  iteration: 244699/375342  consumed_samples: 250572800  total_loss: 3.355  time: 0.3435 s/iter  data_time: 0.2179 s/iter total_throughput: 2981.38 samples/s lr: 2.78e-04  
[09/23 02:52:23] lb.utils.events INFO:  eta: 5:37:58  iteration: 244799/375342  consumed_samples: 250675200  total_loss: 3.347  time: 0.3435 s/iter  data_time: 0.2172 s/iter total_throughput: 2981.33 samples/s lr: 2.77e-04  
[09/23 02:52:58] lb.utils.events INFO:  eta: 5:37:38  iteration: 244899/375342  consumed_samples: 250777600  total_loss: 3.348  time: 0.3435 s/iter  data_time: 0.2176 s/iter total_throughput: 2981.31 samples/s lr: 2.77e-04  
[09/23 02:53:33] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0244999
[09/23 02:53:34] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/23 02:53:34] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/23 02:53:38] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0826 s/iter. Inference: 0.1671 s/iter. Eval: 0.0020 s/iter. Total: 0.2518 s/iter. ETA=0:00:09
[09/23 02:53:43] lb.evaluation.evaluator INFO: Inference done 28672/50000. Dataloading: 0.1183 s/iter. Inference: 0.1633 s/iter. Eval: 0.0020 s/iter. Total: 0.2836 s/iter. ETA=0:00:05
[09/23 02:53:48] lb.evaluation.evaluator INFO: Inference done 46080/50000. Dataloading: 0.1274 s/iter. Inference: 0.1628 s/iter. Eval: 0.0021 s/iter. Total: 0.2924 s/iter. ETA=0:00:00
[09/23 02:53:49] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/23 02:53:49] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.638263 (0.000253 s / iter per device, on 8 devices)
[09/23 02:53:49] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000143 s / iter per device, on 8 devices)
[09/23 02:53:49] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/23 02:53:49] lb.evaluation.utils INFO: copypaste: Acc@1=77.21000000000001
[09/23 02:53:49] lb.evaluation.utils INFO: copypaste: Acc@5=93.446
[09/23 02:53:49] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 77.21000, better than last best score 77.13000 @ iteration 239999.
[09/23 02:53:49] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/23 02:53:50] lb.utils.events INFO:  eta: 5:36:57  iteration: 244999/375342  consumed_samples: 250880000  total_loss: 3.334  time: 0.3435 s/iter  data_time: 0.2204 s/iter total_throughput: 2981.28 samples/s lr: 2.76e-04  
[09/23 02:54:23] lb.utils.events INFO:  eta: 5:37:39  iteration: 245099/375342  consumed_samples: 250982400  total_loss: 3.348  time: 0.3435 s/iter  data_time: 0.2248 s/iter total_throughput: 2981.32 samples/s lr: 2.76e-04  
[09/23 02:54:58] lb.utils.events INFO:  eta: 5:36:56  iteration: 245199/375342  consumed_samples: 251084800  total_loss: 3.355  time: 0.3435 s/iter  data_time: 0.2533 s/iter total_throughput: 2981.30 samples/s lr: 2.76e-04  
[09/23 02:55:33] lb.utils.events INFO:  eta: 5:36:40  iteration: 245299/375342  consumed_samples: 251187200  total_loss: 3.351  time: 0.3435 s/iter  data_time: 0.2271 s/iter total_throughput: 2981.27 samples/s lr: 2.75e-04  
[09/23 02:56:09] lb.utils.events INFO:  eta: 5:35:13  iteration: 245399/375342  consumed_samples: 251289600  total_loss: 3.323  time: 0.3435 s/iter  data_time: 0.2351 s/iter total_throughput: 2981.24 samples/s lr: 2.75e-04  
[09/23 02:56:44] lb.utils.events INFO:  eta: 5:35:01  iteration: 245499/375342  consumed_samples: 251392000  total_loss: 3.323  time: 0.3435 s/iter  data_time: 0.2230 s/iter total_throughput: 2981.21 samples/s lr: 2.75e-04  
[09/23 02:57:19] lb.utils.events INFO:  eta: 5:34:42  iteration: 245599/375342  consumed_samples: 251494400  total_loss: 3.317  time: 0.3435 s/iter  data_time: 0.2196 s/iter total_throughput: 2981.19 samples/s lr: 2.74e-04  
[09/23 02:57:54] lb.utils.events INFO:  eta: 5:34:20  iteration: 245699/375342  consumed_samples: 251596800  total_loss: 3.318  time: 0.3435 s/iter  data_time: 0.2232 s/iter total_throughput: 2981.17 samples/s lr: 2.74e-04  
[09/23 02:58:28] lb.utils.events INFO:  eta: 5:34:40  iteration: 245799/375342  consumed_samples: 251699200  total_loss: 3.323  time: 0.3435 s/iter  data_time: 0.2237 s/iter total_throughput: 2981.16 samples/s lr: 2.74e-04  
[09/23 02:59:03] lb.utils.events INFO:  eta: 5:34:43  iteration: 245899/375342  consumed_samples: 251801600  total_loss: 3.311  time: 0.3435 s/iter  data_time: 0.2259 s/iter total_throughput: 2981.14 samples/s lr: 2.73e-04  
[09/23 02:59:38] lb.utils.events INFO:  eta: 5:34:23  iteration: 245999/375342  consumed_samples: 251904000  total_loss: 3.343  time: 0.3435 s/iter  data_time: 0.2229 s/iter total_throughput: 2981.11 samples/s lr: 2.73e-04  
[09/23 03:00:14] lb.utils.events INFO:  eta: 5:33:18  iteration: 246099/375342  consumed_samples: 252006400  total_loss: 3.356  time: 0.3435 s/iter  data_time: 0.2180 s/iter total_throughput: 2981.08 samples/s lr: 2.72e-04  
[09/23 03:00:48] lb.utils.events INFO:  eta: 5:33:44  iteration: 246199/375342  consumed_samples: 252108800  total_loss: 3.322  time: 0.3435 s/iter  data_time: 0.2090 s/iter total_throughput: 2981.08 samples/s lr: 2.72e-04  
[09/23 03:01:23] lb.utils.events INFO:  eta: 5:33:40  iteration: 246299/375342  consumed_samples: 252211200  total_loss: 3.321  time: 0.3435 s/iter  data_time: 0.2173 s/iter total_throughput: 2981.07 samples/s lr: 2.72e-04  
[09/23 03:01:57] lb.utils.events INFO:  eta: 5:34:54  iteration: 246399/375342  consumed_samples: 252313600  total_loss: 3.336  time: 0.3435 s/iter  data_time: 0.2277 s/iter total_throughput: 2981.06 samples/s lr: 2.71e-04  
[09/23 03:02:32] lb.utils.events INFO:  eta: 5:34:38  iteration: 246499/375342  consumed_samples: 252416000  total_loss: 3.332  time: 0.3435 s/iter  data_time: 0.2163 s/iter total_throughput: 2981.05 samples/s lr: 2.71e-04  
[09/23 03:03:07] lb.utils.events INFO:  eta: 5:34:23  iteration: 246599/375342  consumed_samples: 252518400  total_loss: 3.318  time: 0.3435 s/iter  data_time: 0.2300 s/iter total_throughput: 2981.04 samples/s lr: 2.71e-04  
[09/23 03:03:41] lb.utils.events INFO:  eta: 5:34:05  iteration: 246699/375342  consumed_samples: 252620800  total_loss: 3.312  time: 0.3435 s/iter  data_time: 0.2201 s/iter total_throughput: 2981.02 samples/s lr: 2.70e-04  
[09/23 03:04:16] lb.utils.events INFO:  eta: 5:33:47  iteration: 246799/375342  consumed_samples: 252723200  total_loss: 3.315  time: 0.3435 s/iter  data_time: 0.2156 s/iter total_throughput: 2981.01 samples/s lr: 2.70e-04  
[09/23 03:04:51] lb.utils.events INFO:  eta: 5:33:37  iteration: 246899/375342  consumed_samples: 252825600  total_loss: 3.325  time: 0.3435 s/iter  data_time: 0.2316 s/iter total_throughput: 2980.99 samples/s lr: 2.70e-04  
[09/23 03:05:26] lb.utils.events INFO:  eta: 5:33:22  iteration: 246999/375342  consumed_samples: 252928000  total_loss: 3.328  time: 0.3435 s/iter  data_time: 0.2278 s/iter total_throughput: 2980.98 samples/s lr: 2.69e-04  
[09/23 03:06:01] lb.utils.events INFO:  eta: 5:33:05  iteration: 247099/375342  consumed_samples: 253030400  total_loss: 3.343  time: 0.3435 s/iter  data_time: 0.2287 s/iter total_throughput: 2980.96 samples/s lr: 2.69e-04  
[09/23 03:06:35] lb.utils.events INFO:  eta: 5:32:36  iteration: 247199/375342  consumed_samples: 253132800  total_loss: 3.35  time: 0.3435 s/iter  data_time: 0.2122 s/iter total_throughput: 2980.96 samples/s lr: 2.68e-04  
[09/23 03:07:10] lb.utils.events INFO:  eta: 5:32:29  iteration: 247299/375342  consumed_samples: 253235200  total_loss: 3.349  time: 0.3435 s/iter  data_time: 0.2304 s/iter total_throughput: 2980.95 samples/s lr: 2.68e-04  
[09/23 03:07:44] lb.utils.events INFO:  eta: 5:31:17  iteration: 247399/375342  consumed_samples: 253337600  total_loss: 3.336  time: 0.3435 s/iter  data_time: 0.2176 s/iter total_throughput: 2980.94 samples/s lr: 2.68e-04  
[09/23 03:08:19] lb.utils.events INFO:  eta: 5:31:41  iteration: 247499/375342  consumed_samples: 253440000  total_loss: 3.337  time: 0.3435 s/iter  data_time: 0.2276 s/iter total_throughput: 2980.93 samples/s lr: 2.67e-04  
[09/23 03:08:54] lb.utils.events INFO:  eta: 5:31:31  iteration: 247599/375342  consumed_samples: 253542400  total_loss: 3.338  time: 0.3435 s/iter  data_time: 0.2257 s/iter total_throughput: 2980.91 samples/s lr: 2.67e-04  
[09/23 03:09:28] lb.utils.events INFO:  eta: 5:31:31  iteration: 247699/375342  consumed_samples: 253644800  total_loss: 3.319  time: 0.3435 s/iter  data_time: 0.2152 s/iter total_throughput: 2980.91 samples/s lr: 2.67e-04  
[09/23 03:10:02] lb.utils.events INFO:  eta: 5:30:58  iteration: 247799/375342  consumed_samples: 253747200  total_loss: 3.291  time: 0.3435 s/iter  data_time: 0.2117 s/iter total_throughput: 2980.91 samples/s lr: 2.66e-04  
[09/23 03:10:37] lb.utils.events INFO:  eta: 5:30:25  iteration: 247899/375342  consumed_samples: 253849600  total_loss: 3.328  time: 0.3435 s/iter  data_time: 0.2134 s/iter total_throughput: 2980.91 samples/s lr: 2.66e-04  
[09/23 03:11:12] lb.utils.events INFO:  eta: 5:30:17  iteration: 247999/375342  consumed_samples: 253952000  total_loss: 3.332  time: 0.3435 s/iter  data_time: 0.2227 s/iter total_throughput: 2980.90 samples/s lr: 2.66e-04  
[09/23 03:11:47] lb.utils.events INFO:  eta: 5:29:26  iteration: 248099/375342  consumed_samples: 254054400  total_loss: 3.294  time: 0.3435 s/iter  data_time: 0.2352 s/iter total_throughput: 2980.88 samples/s lr: 2.65e-04  
[09/23 03:12:21] lb.utils.events INFO:  eta: 5:29:28  iteration: 248199/375342  consumed_samples: 254156800  total_loss: 3.318  time: 0.3435 s/iter  data_time: 0.2290 s/iter total_throughput: 2980.87 samples/s lr: 2.65e-04  
[09/23 03:12:56] lb.utils.events INFO:  eta: 5:28:38  iteration: 248299/375342  consumed_samples: 254259200  total_loss: 3.344  time: 0.3435 s/iter  data_time: 0.2318 s/iter total_throughput: 2980.84 samples/s lr: 2.64e-04  
[09/23 03:13:31] lb.utils.events INFO:  eta: 5:28:35  iteration: 248399/375342  consumed_samples: 254361600  total_loss: 3.34  time: 0.3435 s/iter  data_time: 0.2114 s/iter total_throughput: 2980.84 samples/s lr: 2.64e-04  
[09/23 03:14:05] lb.utils.events INFO:  eta: 5:28:16  iteration: 248499/375342  consumed_samples: 254464000  total_loss: 3.312  time: 0.3435 s/iter  data_time: 0.2259 s/iter total_throughput: 2980.83 samples/s lr: 2.64e-04  
[09/23 03:14:40] lb.utils.events INFO:  eta: 5:27:59  iteration: 248599/375342  consumed_samples: 254566400  total_loss: 3.309  time: 0.3435 s/iter  data_time: 0.2104 s/iter total_throughput: 2980.83 samples/s lr: 2.63e-04  
[09/23 03:15:15] lb.utils.events INFO:  eta: 5:27:24  iteration: 248699/375342  consumed_samples: 254668800  total_loss: 3.328  time: 0.3435 s/iter  data_time: 0.2238 s/iter total_throughput: 2980.81 samples/s lr: 2.63e-04  
[09/23 03:15:49] lb.utils.events INFO:  eta: 5:27:03  iteration: 248799/375342  consumed_samples: 254771200  total_loss: 3.328  time: 0.3435 s/iter  data_time: 0.2251 s/iter total_throughput: 2980.80 samples/s lr: 2.63e-04  
[09/23 03:16:24] lb.utils.events INFO:  eta: 5:27:01  iteration: 248899/375342  consumed_samples: 254873600  total_loss: 3.32  time: 0.3435 s/iter  data_time: 0.2208 s/iter total_throughput: 2980.79 samples/s lr: 2.62e-04  
[09/23 03:16:59] lb.utils.events INFO:  eta: 5:26:25  iteration: 248999/375342  consumed_samples: 254976000  total_loss: 3.331  time: 0.3435 s/iter  data_time: 0.2215 s/iter total_throughput: 2980.78 samples/s lr: 2.62e-04  
[09/23 03:17:33] lb.utils.events INFO:  eta: 5:27:03  iteration: 249099/375342  consumed_samples: 255078400  total_loss: 3.34  time: 0.3435 s/iter  data_time: 0.2202 s/iter total_throughput: 2980.77 samples/s lr: 2.62e-04  
[09/23 03:18:08] lb.utils.events INFO:  eta: 5:26:58  iteration: 249199/375342  consumed_samples: 255180800  total_loss: 3.33  time: 0.3435 s/iter  data_time: 0.2092 s/iter total_throughput: 2980.76 samples/s lr: 2.61e-04  
[09/23 03:18:43] lb.utils.events INFO:  eta: 5:26:32  iteration: 249299/375342  consumed_samples: 255283200  total_loss: 3.321  time: 0.3435 s/iter  data_time: 0.2130 s/iter total_throughput: 2980.75 samples/s lr: 2.61e-04  
[09/23 03:19:17] lb.utils.events INFO:  eta: 5:26:29  iteration: 249399/375342  consumed_samples: 255385600  total_loss: 3.324  time: 0.3435 s/iter  data_time: 0.2120 s/iter total_throughput: 2980.74 samples/s lr: 2.60e-04  
[09/23 03:19:52] lb.utils.events INFO:  eta: 5:25:53  iteration: 249499/375342  consumed_samples: 255488000  total_loss: 3.32  time: 0.3435 s/iter  data_time: 0.2147 s/iter total_throughput: 2980.74 samples/s lr: 2.60e-04  
[09/23 03:20:26] lb.utils.events INFO:  eta: 5:25:37  iteration: 249599/375342  consumed_samples: 255590400  total_loss: 3.312  time: 0.3435 s/iter  data_time: 0.2163 s/iter total_throughput: 2980.73 samples/s lr: 2.60e-04  
[09/23 03:21:00] lb.utils.events INFO:  eta: 5:25:30  iteration: 249699/375342  consumed_samples: 255692800  total_loss: 3.32  time: 0.3435 s/iter  data_time: 0.2093 s/iter total_throughput: 2980.74 samples/s lr: 2.59e-04  
[09/23 03:21:35] lb.utils.events INFO:  eta: 5:25:15  iteration: 249799/375342  consumed_samples: 255795200  total_loss: 3.325  time: 0.3435 s/iter  data_time: 0.2252 s/iter total_throughput: 2980.73 samples/s lr: 2.59e-04  
[09/23 03:22:10] lb.utils.events INFO:  eta: 5:24:51  iteration: 249899/375342  consumed_samples: 255897600  total_loss: 3.333  time: 0.3435 s/iter  data_time: 0.2225 s/iter total_throughput: 2980.72 samples/s lr: 2.59e-04  
[09/23 03:22:45] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0249999
[09/23 03:22:45] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/23 03:22:45] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/23 03:22:50] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.1018 s/iter. Inference: 0.1634 s/iter. Eval: 0.0020 s/iter. Total: 0.2672 s/iter. ETA=0:00:09
[09/23 03:22:55] lb.evaluation.evaluator INFO: Inference done 28672/50000. Dataloading: 0.1162 s/iter. Inference: 0.1694 s/iter. Eval: 0.0021 s/iter. Total: 0.2877 s/iter. ETA=0:00:05
[09/23 03:23:00] lb.evaluation.evaluator INFO: Inference done 46080/50000. Dataloading: 0.1221 s/iter. Inference: 0.1672 s/iter. Eval: 0.0021 s/iter. Total: 0.2915 s/iter. ETA=0:00:00
[09/23 03:23:01] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/23 03:23:01] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.614043 (0.000252 s / iter per device, on 8 devices)
[09/23 03:23:01] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000148 s / iter per device, on 8 devices)
[09/23 03:23:01] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/23 03:23:01] lb.evaluation.utils INFO: copypaste: Acc@1=77.622
[09/23 03:23:01] lb.evaluation.utils INFO: copypaste: Acc@5=93.756
[09/23 03:23:01] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 77.62200, better than last best score 77.21000 @ iteration 244999.
[09/23 03:23:01] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/23 03:23:01] lb.utils.events INFO:  eta: 5:24:28  iteration: 249999/375342  consumed_samples: 256000000  total_loss: 3.316  time: 0.3435 s/iter  data_time: 0.2350 s/iter total_throughput: 2980.69 samples/s lr: 2.58e-04  
[09/23 03:23:34] lb.utils.events INFO:  eta: 5:25:51  iteration: 250099/375342  consumed_samples: 256102400  total_loss: 3.312  time: 0.3435 s/iter  data_time: 0.2340 s/iter total_throughput: 2980.75 samples/s lr: 2.58e-04  
[09/23 03:24:09] lb.utils.events INFO:  eta: 5:25:08  iteration: 250199/375342  consumed_samples: 256204800  total_loss: 3.32  time: 0.3435 s/iter  data_time: 0.2156 s/iter total_throughput: 2980.74 samples/s lr: 2.58e-04  
[09/23 03:24:43] lb.utils.events INFO:  eta: 5:25:37  iteration: 250299/375342  consumed_samples: 256307200  total_loss: 3.316  time: 0.3435 s/iter  data_time: 0.2084 s/iter total_throughput: 2980.75 samples/s lr: 2.57e-04  
[09/23 03:25:17] lb.utils.events INFO:  eta: 5:24:51  iteration: 250399/375342  consumed_samples: 256409600  total_loss: 3.303  time: 0.3435 s/iter  data_time: 0.2149 s/iter total_throughput: 2980.74 samples/s lr: 2.57e-04  
[09/23 03:25:52] lb.utils.events INFO:  eta: 5:24:47  iteration: 250499/375342  consumed_samples: 256512000  total_loss: 3.331  time: 0.3435 s/iter  data_time: 0.2127 s/iter total_throughput: 2980.74 samples/s lr: 2.57e-04  
[09/23 03:26:27] lb.utils.events INFO:  eta: 5:24:47  iteration: 250599/375342  consumed_samples: 256614400  total_loss: 3.313  time: 0.3435 s/iter  data_time: 0.2268 s/iter total_throughput: 2980.71 samples/s lr: 2.56e-04  
[09/23 03:27:02] lb.utils.events INFO:  eta: 5:24:15  iteration: 250699/375342  consumed_samples: 256716800  total_loss: 3.299  time: 0.3435 s/iter  data_time: 0.2382 s/iter total_throughput: 2980.70 samples/s lr: 2.56e-04  
[09/23 03:27:36] lb.utils.events INFO:  eta: 5:24:00  iteration: 250799/375342  consumed_samples: 256819200  total_loss: 3.305  time: 0.3435 s/iter  data_time: 0.2222 s/iter total_throughput: 2980.70 samples/s lr: 2.55e-04  
[09/23 03:28:11] lb.utils.events INFO:  eta: 5:23:38  iteration: 250899/375342  consumed_samples: 256921600  total_loss: 3.301  time: 0.3435 s/iter  data_time: 0.2211 s/iter total_throughput: 2980.69 samples/s lr: 2.55e-04  
[09/23 03:28:46] lb.utils.events INFO:  eta: 5:23:51  iteration: 250999/375342  consumed_samples: 257024000  total_loss: 3.309  time: 0.3435 s/iter  data_time: 0.2265 s/iter total_throughput: 2980.68 samples/s lr: 2.55e-04  
[09/23 03:29:20] lb.utils.events INFO:  eta: 5:21:57  iteration: 251099/375342  consumed_samples: 257126400  total_loss: 3.324  time: 0.3435 s/iter  data_time: 0.2175 s/iter total_throughput: 2980.67 samples/s lr: 2.54e-04  
[09/23 03:29:55] lb.utils.events INFO:  eta: 5:21:33  iteration: 251199/375342  consumed_samples: 257228800  total_loss: 3.319  time: 0.3435 s/iter  data_time: 0.2212 s/iter total_throughput: 2980.67 samples/s lr: 2.54e-04  
[09/23 03:30:29] lb.utils.events INFO:  eta: 5:21:07  iteration: 251299/375342  consumed_samples: 257331200  total_loss: 3.308  time: 0.3435 s/iter  data_time: 0.2248 s/iter total_throughput: 2980.65 samples/s lr: 2.54e-04  
[09/23 03:31:04] lb.utils.events INFO:  eta: 5:21:03  iteration: 251399/375342  consumed_samples: 257433600  total_loss: 3.322  time: 0.3435 s/iter  data_time: 0.2199 s/iter total_throughput: 2980.65 samples/s lr: 2.53e-04  
[09/23 03:31:38] lb.utils.events INFO:  eta: 5:20:19  iteration: 251499/375342  consumed_samples: 257536000  total_loss: 3.326  time: 0.3435 s/iter  data_time: 0.2160 s/iter total_throughput: 2980.65 samples/s lr: 2.53e-04  
[09/23 03:32:13] lb.utils.events INFO:  eta: 5:19:49  iteration: 251599/375342  consumed_samples: 257638400  total_loss: 3.307  time: 0.3435 s/iter  data_time: 0.2137 s/iter total_throughput: 2980.65 samples/s lr: 2.53e-04  
[09/23 03:32:47] lb.utils.events INFO:  eta: 5:20:13  iteration: 251699/375342  consumed_samples: 257740800  total_loss: 3.315  time: 0.3436 s/iter  data_time: 0.2132 s/iter total_throughput: 2980.64 samples/s lr: 2.52e-04  
[09/23 03:33:21] lb.utils.events INFO:  eta: 5:19:35  iteration: 251799/375342  consumed_samples: 257843200  total_loss: 3.318  time: 0.3435 s/iter  data_time: 0.2125 s/iter total_throughput: 2980.65 samples/s lr: 2.52e-04  
[09/23 03:33:55] lb.utils.events INFO:  eta: 5:20:06  iteration: 251899/375342  consumed_samples: 257945600  total_loss: 3.317  time: 0.3435 s/iter  data_time: 0.2070 s/iter total_throughput: 2980.66 samples/s lr: 2.52e-04  
[09/23 03:34:29] lb.utils.events INFO:  eta: 5:19:54  iteration: 251999/375342  consumed_samples: 258048000  total_loss: 3.311  time: 0.3435 s/iter  data_time: 0.2116 s/iter total_throughput: 2980.67 samples/s lr: 2.51e-04  
[09/23 03:35:04] lb.utils.events INFO:  eta: 5:19:35  iteration: 252099/375342  consumed_samples: 258150400  total_loss: 3.297  time: 0.3435 s/iter  data_time: 0.2364 s/iter total_throughput: 2980.65 samples/s lr: 2.51e-04  
[09/23 03:35:39] lb.utils.events INFO:  eta: 5:19:34  iteration: 252199/375342  consumed_samples: 258252800  total_loss: 3.286  time: 0.3436 s/iter  data_time: 0.2171 s/iter total_throughput: 2980.63 samples/s lr: 2.50e-04  
[09/23 03:36:14] lb.utils.events INFO:  eta: 5:19:19  iteration: 252299/375342  consumed_samples: 258355200  total_loss: 3.308  time: 0.3436 s/iter  data_time: 0.2375 s/iter total_throughput: 2980.61 samples/s lr: 2.50e-04  
[09/23 03:36:49] lb.utils.events INFO:  eta: 5:19:16  iteration: 252399/375342  consumed_samples: 258457600  total_loss: 3.317  time: 0.3436 s/iter  data_time: 0.2384 s/iter total_throughput: 2980.58 samples/s lr: 2.50e-04  
[09/23 03:37:24] lb.utils.events INFO:  eta: 5:19:10  iteration: 252499/375342  consumed_samples: 258560000  total_loss: 3.301  time: 0.3436 s/iter  data_time: 0.2193 s/iter total_throughput: 2980.56 samples/s lr: 2.49e-04  
[09/23 03:38:00] lb.utils.events INFO:  eta: 5:18:52  iteration: 252599/375342  consumed_samples: 258662400  total_loss: 3.282  time: 0.3436 s/iter  data_time: 0.2220 s/iter total_throughput: 2980.53 samples/s lr: 2.49e-04  
[09/23 03:38:35] lb.utils.events INFO:  eta: 5:18:02  iteration: 252699/375342  consumed_samples: 258764800  total_loss: 3.309  time: 0.3436 s/iter  data_time: 0.2435 s/iter total_throughput: 2980.49 samples/s lr: 2.49e-04  
[09/23 03:39:11] lb.utils.events INFO:  eta: 5:17:02  iteration: 252799/375342  consumed_samples: 258867200  total_loss: 3.312  time: 0.3436 s/iter  data_time: 0.2386 s/iter total_throughput: 2980.44 samples/s lr: 2.48e-04  
[09/23 03:39:46] lb.utils.events INFO:  eta: 5:16:30  iteration: 252899/375342  consumed_samples: 258969600  total_loss: 3.302  time: 0.3436 s/iter  data_time: 0.2306 s/iter total_throughput: 2980.42 samples/s lr: 2.48e-04  
[09/23 03:40:21] lb.utils.events INFO:  eta: 5:16:15  iteration: 252999/375342  consumed_samples: 259072000  total_loss: 3.297  time: 0.3436 s/iter  data_time: 0.2140 s/iter total_throughput: 2980.40 samples/s lr: 2.48e-04  
[09/23 03:40:56] lb.utils.events INFO:  eta: 5:16:10  iteration: 253099/375342  consumed_samples: 259174400  total_loss: 3.305  time: 0.3436 s/iter  data_time: 0.2266 s/iter total_throughput: 2980.38 samples/s lr: 2.47e-04  
[09/23 03:41:31] lb.utils.events INFO:  eta: 5:15:51  iteration: 253199/375342  consumed_samples: 259276800  total_loss: 3.316  time: 0.3436 s/iter  data_time: 0.2199 s/iter total_throughput: 2980.36 samples/s lr: 2.47e-04  
[09/23 03:42:05] lb.utils.events INFO:  eta: 5:15:48  iteration: 253299/375342  consumed_samples: 259379200  total_loss: 3.302  time: 0.3436 s/iter  data_time: 0.2154 s/iter total_throughput: 2980.35 samples/s lr: 2.47e-04  
[09/23 03:42:41] lb.utils.events INFO:  eta: 5:15:51  iteration: 253399/375342  consumed_samples: 259481600  total_loss: 3.293  time: 0.3436 s/iter  data_time: 0.2196 s/iter total_throughput: 2980.33 samples/s lr: 2.46e-04  
[09/23 03:43:16] lb.utils.events INFO:  eta: 5:14:46  iteration: 253499/375342  consumed_samples: 259584000  total_loss: 3.303  time: 0.3436 s/iter  data_time: 0.2230 s/iter total_throughput: 2980.29 samples/s lr: 2.46e-04  
[09/23 03:43:51] lb.utils.events INFO:  eta: 5:14:31  iteration: 253599/375342  consumed_samples: 259686400  total_loss: 3.297  time: 0.3436 s/iter  data_time: 0.2305 s/iter total_throughput: 2980.27 samples/s lr: 2.46e-04  
[09/23 03:44:26] lb.utils.events INFO:  eta: 5:14:39  iteration: 253699/375342  consumed_samples: 259788800  total_loss: 3.287  time: 0.3436 s/iter  data_time: 0.2247 s/iter total_throughput: 2980.25 samples/s lr: 2.45e-04  
[09/23 03:45:01] lb.utils.events INFO:  eta: 5:15:07  iteration: 253799/375342  consumed_samples: 259891200  total_loss: 3.292  time: 0.3436 s/iter  data_time: 0.2354 s/iter total_throughput: 2980.22 samples/s lr: 2.45e-04  
[09/23 03:45:37] lb.utils.events INFO:  eta: 5:13:46  iteration: 253899/375342  consumed_samples: 259993600  total_loss: 3.291  time: 0.3436 s/iter  data_time: 0.2243 s/iter total_throughput: 2980.18 samples/s lr: 2.44e-04  
[09/23 03:46:12] lb.utils.events INFO:  eta: 5:14:31  iteration: 253999/375342  consumed_samples: 260096000  total_loss: 3.292  time: 0.3436 s/iter  data_time: 0.2338 s/iter total_throughput: 2980.15 samples/s lr: 2.44e-04  
[09/23 03:46:48] lb.utils.events INFO:  eta: 5:13:39  iteration: 254099/375342  consumed_samples: 260198400  total_loss: 3.285  time: 0.3436 s/iter  data_time: 0.2342 s/iter total_throughput: 2980.10 samples/s lr: 2.44e-04  
[09/23 03:47:23] lb.utils.events INFO:  eta: 5:13:23  iteration: 254199/375342  consumed_samples: 260300800  total_loss: 3.286  time: 0.3436 s/iter  data_time: 0.2204 s/iter total_throughput: 2980.07 samples/s lr: 2.43e-04  
[09/23 03:47:58] lb.utils.events INFO:  eta: 5:12:43  iteration: 254299/375342  consumed_samples: 260403200  total_loss: 3.281  time: 0.3436 s/iter  data_time: 0.2165 s/iter total_throughput: 2980.06 samples/s lr: 2.43e-04  
[09/23 03:48:33] lb.utils.events INFO:  eta: 5:12:18  iteration: 254399/375342  consumed_samples: 260505600  total_loss: 3.273  time: 0.3436 s/iter  data_time: 0.2238 s/iter total_throughput: 2980.03 samples/s lr: 2.43e-04  
[09/23 03:49:08] lb.utils.events INFO:  eta: 5:12:38  iteration: 254499/375342  consumed_samples: 260608000  total_loss: 3.297  time: 0.3436 s/iter  data_time: 0.2148 s/iter total_throughput: 2980.02 samples/s lr: 2.42e-04  
[09/23 03:49:42] lb.utils.events INFO:  eta: 5:12:25  iteration: 254599/375342  consumed_samples: 260710400  total_loss: 3.274  time: 0.3436 s/iter  data_time: 0.2259 s/iter total_throughput: 2980.00 samples/s lr: 2.42e-04  
[09/23 03:50:17] lb.utils.events INFO:  eta: 5:12:33  iteration: 254699/375342  consumed_samples: 260812800  total_loss: 3.287  time: 0.3436 s/iter  data_time: 0.2216 s/iter total_throughput: 2979.99 samples/s lr: 2.42e-04  
[09/23 03:50:53] lb.utils.events INFO:  eta: 5:12:12  iteration: 254799/375342  consumed_samples: 260915200  total_loss: 3.308  time: 0.3436 s/iter  data_time: 0.2319 s/iter total_throughput: 2979.95 samples/s lr: 2.41e-04  
[09/23 03:51:27] lb.utils.events INFO:  eta: 5:12:20  iteration: 254899/375342  consumed_samples: 261017600  total_loss: 3.29  time: 0.3436 s/iter  data_time: 0.2206 s/iter total_throughput: 2979.95 samples/s lr: 2.41e-04  
[09/23 03:52:03] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0254999
[09/23 03:52:03] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/23 03:52:03] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/23 03:52:08] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.1086 s/iter. Inference: 0.1607 s/iter. Eval: 0.0022 s/iter. Total: 0.2716 s/iter. ETA=0:00:10
[09/23 03:52:13] lb.evaluation.evaluator INFO: Inference done 28672/50000. Dataloading: 0.1195 s/iter. Inference: 0.1687 s/iter. Eval: 0.0021 s/iter. Total: 0.2905 s/iter. ETA=0:00:05
[09/23 03:52:18] lb.evaluation.evaluator INFO: Inference done 47104/50000. Dataloading: 0.1248 s/iter. Inference: 0.1677 s/iter. Eval: 0.0021 s/iter. Total: 0.2947 s/iter. ETA=0:00:00
[09/23 03:52:19] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/23 03:52:19] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.590637 (0.000252 s / iter per device, on 8 devices)
[09/23 03:52:19] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000147 s / iter per device, on 8 devices)
[09/23 03:52:19] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/23 03:52:19] lb.evaluation.utils INFO: copypaste: Acc@1=77.45
[09/23 03:52:19] lb.evaluation.utils INFO: copypaste: Acc@5=93.732
[09/23 03:52:19] lb.engine.hooks INFO: Not saving as latest eval score for Acc@1 is 77.45000, not better than best score 77.62200 @ iteration 249999.
[09/23 03:52:19] lb.utils.events INFO:  eta: 5:11:27  iteration: 254999/375342  consumed_samples: 261120000  total_loss: 3.293  time: 0.3436 s/iter  data_time: 0.2375 s/iter total_throughput: 2979.91 samples/s lr: 2.41e-04  
[09/23 03:52:52] lb.utils.events INFO:  eta: 5:12:00  iteration: 255099/375342  consumed_samples: 261222400  total_loss: 3.299  time: 0.3436 s/iter  data_time: 0.2275 s/iter total_throughput: 2979.95 samples/s lr: 2.40e-04  
[09/23 03:53:27] lb.utils.events INFO:  eta: 5:11:39  iteration: 255199/375342  consumed_samples: 261324800  total_loss: 3.309  time: 0.3436 s/iter  data_time: 0.2324 s/iter total_throughput: 2979.91 samples/s lr: 2.40e-04  
[09/23 03:54:03] lb.utils.events INFO:  eta: 5:11:06  iteration: 255299/375342  consumed_samples: 261427200  total_loss: 3.303  time: 0.3436 s/iter  data_time: 0.2184 s/iter total_throughput: 2979.87 samples/s lr: 2.40e-04  
[09/23 03:54:38] lb.utils.events INFO:  eta: 5:10:15  iteration: 255399/375342  consumed_samples: 261529600  total_loss: 3.312  time: 0.3436 s/iter  data_time: 0.2363 s/iter total_throughput: 2979.84 samples/s lr: 2.39e-04  
[09/23 03:55:13] lb.utils.events INFO:  eta: 5:10:23  iteration: 255499/375342  consumed_samples: 261632000  total_loss: 3.301  time: 0.3436 s/iter  data_time: 0.2148 s/iter total_throughput: 2979.82 samples/s lr: 2.39e-04  
[09/23 03:55:48] lb.utils.events INFO:  eta: 5:10:21  iteration: 255599/375342  consumed_samples: 261734400  total_loss: 3.285  time: 0.3436 s/iter  data_time: 0.2242 s/iter total_throughput: 2979.81 samples/s lr: 2.38e-04  
[09/23 03:56:23] lb.utils.events INFO:  eta: 5:10:16  iteration: 255699/375342  consumed_samples: 261836800  total_loss: 3.296  time: 0.3436 s/iter  data_time: 0.2265 s/iter total_throughput: 2979.79 samples/s lr: 2.38e-04  
[09/23 03:56:58] lb.utils.events INFO:  eta: 5:10:30  iteration: 255799/375342  consumed_samples: 261939200  total_loss: 3.292  time: 0.3437 s/iter  data_time: 0.2277 s/iter total_throughput: 2979.77 samples/s lr: 2.38e-04  
[09/23 03:57:32] lb.utils.events INFO:  eta: 5:10:18  iteration: 255899/375342  consumed_samples: 262041600  total_loss: 3.291  time: 0.3437 s/iter  data_time: 0.2274 s/iter total_throughput: 2979.76 samples/s lr: 2.37e-04  
[09/23 03:58:07] lb.utils.events INFO:  eta: 5:10:02  iteration: 255999/375342  consumed_samples: 262144000  total_loss: 3.293  time: 0.3437 s/iter  data_time: 0.2326 s/iter total_throughput: 2979.74 samples/s lr: 2.37e-04  
[09/23 03:58:42] lb.utils.events INFO:  eta: 5:08:36  iteration: 256099/375342  consumed_samples: 262246400  total_loss: 3.301  time: 0.3437 s/iter  data_time: 0.2175 s/iter total_throughput: 2979.72 samples/s lr: 2.37e-04  
[09/23 03:59:17] lb.utils.events INFO:  eta: 5:08:24  iteration: 256199/375342  consumed_samples: 262348800  total_loss: 3.297  time: 0.3437 s/iter  data_time: 0.2229 s/iter total_throughput: 2979.70 samples/s lr: 2.36e-04  
[09/23 03:59:52] lb.utils.events INFO:  eta: 5:09:02  iteration: 256299/375342  consumed_samples: 262451200  total_loss: 3.305  time: 0.3437 s/iter  data_time: 0.2151 s/iter total_throughput: 2979.69 samples/s lr: 2.36e-04  
[09/23 04:00:27] lb.utils.events INFO:  eta: 5:09:01  iteration: 256399/375342  consumed_samples: 262553600  total_loss: 3.305  time: 0.3437 s/iter  data_time: 0.2117 s/iter total_throughput: 2979.67 samples/s lr: 2.36e-04  
[09/23 04:01:02] lb.utils.events INFO:  eta: 5:08:48  iteration: 256499/375342  consumed_samples: 262656000  total_loss: 3.28  time: 0.3437 s/iter  data_time: 0.2289 s/iter total_throughput: 2979.65 samples/s lr: 2.35e-04  
[09/23 04:01:37] lb.utils.events INFO:  eta: 5:08:30  iteration: 256599/375342  consumed_samples: 262758400  total_loss: 3.27  time: 0.3437 s/iter  data_time: 0.2228 s/iter total_throughput: 2979.62 samples/s lr: 2.35e-04  
[09/23 04:02:12] lb.utils.events INFO:  eta: 5:07:49  iteration: 256699/375342  consumed_samples: 262860800  total_loss: 3.277  time: 0.3437 s/iter  data_time: 0.2272 s/iter total_throughput: 2979.60 samples/s lr: 2.35e-04  
[09/23 04:02:47] lb.utils.events INFO:  eta: 5:07:06  iteration: 256799/375342  consumed_samples: 262963200  total_loss: 3.288  time: 0.3437 s/iter  data_time: 0.2212 s/iter total_throughput: 2979.59 samples/s lr: 2.34e-04  
[09/23 04:03:22] lb.utils.events INFO:  eta: 5:06:45  iteration: 256899/375342  consumed_samples: 263065600  total_loss: 3.279  time: 0.3437 s/iter  data_time: 0.2271 s/iter total_throughput: 2979.57 samples/s lr: 2.34e-04  
[09/23 04:03:57] lb.utils.events INFO:  eta: 5:06:36  iteration: 256999/375342  consumed_samples: 263168000  total_loss: 3.301  time: 0.3437 s/iter  data_time: 0.2196 s/iter total_throughput: 2979.54 samples/s lr: 2.34e-04  
[09/23 04:04:32] lb.utils.events INFO:  eta: 5:06:14  iteration: 257099/375342  consumed_samples: 263270400  total_loss: 3.302  time: 0.3437 s/iter  data_time: 0.2226 s/iter total_throughput: 2979.52 samples/s lr: 2.33e-04  
[09/23 04:05:06] lb.utils.events INFO:  eta: 5:06:35  iteration: 257199/375342  consumed_samples: 263372800  total_loss: 3.293  time: 0.3437 s/iter  data_time: 0.2199 s/iter total_throughput: 2979.51 samples/s lr: 2.33e-04  
[09/23 04:05:42] lb.utils.events INFO:  eta: 5:05:34  iteration: 257299/375342  consumed_samples: 263475200  total_loss: 3.296  time: 0.3437 s/iter  data_time: 0.2207 s/iter total_throughput: 2979.48 samples/s lr: 2.33e-04  
[09/23 04:06:17] lb.utils.events INFO:  eta: 5:05:09  iteration: 257399/375342  consumed_samples: 263577600  total_loss: 3.287  time: 0.3437 s/iter  data_time: 0.2225 s/iter total_throughput: 2979.45 samples/s lr: 2.32e-04  
[09/23 04:06:53] lb.utils.events INFO:  eta: 5:04:28  iteration: 257499/375342  consumed_samples: 263680000  total_loss: 3.284  time: 0.3437 s/iter  data_time: 0.2258 s/iter total_throughput: 2979.41 samples/s lr: 2.32e-04  
[09/23 04:07:27] lb.utils.events INFO:  eta: 5:04:58  iteration: 257599/375342  consumed_samples: 263782400  total_loss: 3.287  time: 0.3437 s/iter  data_time: 0.2237 s/iter total_throughput: 2979.40 samples/s lr: 2.32e-04  
[09/23 04:08:02] lb.utils.events INFO:  eta: 5:04:43  iteration: 257699/375342  consumed_samples: 263884800  total_loss: 3.286  time: 0.3437 s/iter  data_time: 0.2247 s/iter total_throughput: 2979.38 samples/s lr: 2.31e-04  
[09/23 04:08:37] lb.utils.events INFO:  eta: 5:04:44  iteration: 257799/375342  consumed_samples: 263987200  total_loss: 3.283  time: 0.3437 s/iter  data_time: 0.2190 s/iter total_throughput: 2979.38 samples/s lr: 2.31e-04  
[09/23 04:09:12] lb.utils.events INFO:  eta: 5:03:45  iteration: 257899/375342  consumed_samples: 264089600  total_loss: 3.27  time: 0.3437 s/iter  data_time: 0.2254 s/iter total_throughput: 2979.36 samples/s lr: 2.31e-04  
[09/23 04:09:47] lb.utils.events INFO:  eta: 5:04:15  iteration: 257999/375342  consumed_samples: 264192000  total_loss: 3.278  time: 0.3437 s/iter  data_time: 0.2178 s/iter total_throughput: 2979.34 samples/s lr: 2.30e-04  
[09/23 04:10:21] lb.utils.events INFO:  eta: 5:04:18  iteration: 258099/375342  consumed_samples: 264294400  total_loss: 3.284  time: 0.3437 s/iter  data_time: 0.2323 s/iter total_throughput: 2979.33 samples/s lr: 2.30e-04  
[09/23 04:10:56] lb.utils.events INFO:  eta: 5:03:44  iteration: 258199/375342  consumed_samples: 264396800  total_loss: 3.271  time: 0.3437 s/iter  data_time: 0.2194 s/iter total_throughput: 2979.31 samples/s lr: 2.29e-04  
[09/23 04:11:31] lb.utils.events INFO:  eta: 5:03:44  iteration: 258299/375342  consumed_samples: 264499200  total_loss: 3.27  time: 0.3437 s/iter  data_time: 0.2202 s/iter total_throughput: 2979.29 samples/s lr: 2.29e-04  
[09/23 04:12:06] lb.utils.events INFO:  eta: 5:03:31  iteration: 258399/375342  consumed_samples: 264601600  total_loss: 3.295  time: 0.3437 s/iter  data_time: 0.2351 s/iter total_throughput: 2979.27 samples/s lr: 2.29e-04  
[09/23 04:12:41] lb.utils.events INFO:  eta: 5:04:12  iteration: 258499/375342  consumed_samples: 264704000  total_loss: 3.301  time: 0.3437 s/iter  data_time: 0.2180 s/iter total_throughput: 2979.25 samples/s lr: 2.28e-04  
[09/23 04:13:17] lb.utils.events INFO:  eta: 5:02:45  iteration: 258599/375342  consumed_samples: 264806400  total_loss: 3.296  time: 0.3437 s/iter  data_time: 0.2282 s/iter total_throughput: 2979.22 samples/s lr: 2.28e-04  
[09/23 04:13:51] lb.utils.events INFO:  eta: 5:02:49  iteration: 258699/375342  consumed_samples: 264908800  total_loss: 3.273  time: 0.3437 s/iter  data_time: 0.2151 s/iter total_throughput: 2979.21 samples/s lr: 2.28e-04  
[09/23 04:14:26] lb.utils.events INFO:  eta: 5:02:30  iteration: 258799/375342  consumed_samples: 265011200  total_loss: 3.269  time: 0.3437 s/iter  data_time: 0.2088 s/iter total_throughput: 2979.19 samples/s lr: 2.27e-04  
[09/23 04:15:01] lb.utils.events INFO:  eta: 5:03:29  iteration: 258899/375342  consumed_samples: 265113600  total_loss: 3.277  time: 0.3437 s/iter  data_time: 0.2183 s/iter total_throughput: 2979.18 samples/s lr: 2.27e-04  
[09/23 04:15:36] lb.utils.events INFO:  eta: 5:03:13  iteration: 258999/375342  consumed_samples: 265216000  total_loss: 3.281  time: 0.3437 s/iter  data_time: 0.2070 s/iter total_throughput: 2979.17 samples/s lr: 2.27e-04  
[09/23 04:16:10] lb.utils.events INFO:  eta: 5:02:04  iteration: 259099/375342  consumed_samples: 265318400  total_loss: 3.276  time: 0.3437 s/iter  data_time: 0.2249 s/iter total_throughput: 2979.15 samples/s lr: 2.26e-04  
[09/23 04:16:46] lb.utils.events INFO:  eta: 5:01:44  iteration: 259199/375342  consumed_samples: 265420800  total_loss: 3.267  time: 0.3437 s/iter  data_time: 0.2242 s/iter total_throughput: 2979.12 samples/s lr: 2.26e-04  
[09/23 04:17:21] lb.utils.events INFO:  eta: 5:01:33  iteration: 259299/375342  consumed_samples: 265523200  total_loss: 3.266  time: 0.3437 s/iter  data_time: 0.2215 s/iter total_throughput: 2979.10 samples/s lr: 2.26e-04  
[09/23 04:17:56] lb.utils.events INFO:  eta: 5:01:10  iteration: 259399/375342  consumed_samples: 265625600  total_loss: 3.253  time: 0.3437 s/iter  data_time: 0.2159 s/iter total_throughput: 2979.08 samples/s lr: 2.25e-04  
[09/23 04:18:31] lb.utils.events INFO:  eta: 5:00:33  iteration: 259499/375342  consumed_samples: 265728000  total_loss: 3.281  time: 0.3437 s/iter  data_time: 0.2142 s/iter total_throughput: 2979.06 samples/s lr: 2.25e-04  
[09/23 04:19:06] lb.utils.events INFO:  eta: 5:00:36  iteration: 259599/375342  consumed_samples: 265830400  total_loss: 3.287  time: 0.3437 s/iter  data_time: 0.2243 s/iter total_throughput: 2979.04 samples/s lr: 2.25e-04  
[09/23 04:19:41] lb.utils.events INFO:  eta: 5:00:10  iteration: 259699/375342  consumed_samples: 265932800  total_loss: 3.27  time: 0.3437 s/iter  data_time: 0.2284 s/iter total_throughput: 2979.00 samples/s lr: 2.24e-04  
[09/23 04:20:16] lb.utils.events INFO:  eta: 4:59:53  iteration: 259799/375342  consumed_samples: 266035200  total_loss: 3.274  time: 0.3437 s/iter  data_time: 0.2232 s/iter total_throughput: 2978.99 samples/s lr: 2.24e-04  
[09/23 04:20:51] lb.utils.events INFO:  eta: 4:58:57  iteration: 259899/375342  consumed_samples: 266137600  total_loss: 3.283  time: 0.3437 s/iter  data_time: 0.2281 s/iter total_throughput: 2978.97 samples/s lr: 2.24e-04  
[09/23 04:21:26] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0259999
[09/23 04:21:27] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/23 04:21:27] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/23 04:21:31] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.1012 s/iter. Inference: 0.1631 s/iter. Eval: 0.0021 s/iter. Total: 0.2664 s/iter. ETA=0:00:09
[09/23 04:21:36] lb.evaluation.evaluator INFO: Inference done 28672/50000. Dataloading: 0.1198 s/iter. Inference: 0.1663 s/iter. Eval: 0.0020 s/iter. Total: 0.2882 s/iter. ETA=0:00:05
[09/23 04:21:41] lb.evaluation.evaluator INFO: Inference done 46080/50000. Dataloading: 0.1268 s/iter. Inference: 0.1638 s/iter. Eval: 0.0020 s/iter. Total: 0.2926 s/iter. ETA=0:00:00
[09/23 04:21:42] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/23 04:21:42] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.660901 (0.000253 s / iter per device, on 8 devices)
[09/23 04:21:42] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000144 s / iter per device, on 8 devices)
[09/23 04:21:42] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/23 04:21:42] lb.evaluation.utils INFO: copypaste: Acc@1=77.704
[09/23 04:21:42] lb.evaluation.utils INFO: copypaste: Acc@5=93.72399999999999
[09/23 04:21:42] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 77.70400, better than last best score 77.62200 @ iteration 249999.
[09/23 04:21:42] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/23 04:21:43] lb.utils.events INFO:  eta: 4:57:50  iteration: 259999/375342  consumed_samples: 266240000  total_loss: 3.295  time: 0.3437 s/iter  data_time: 0.2238 s/iter total_throughput: 2978.96 samples/s lr: 2.23e-04  
[09/23 04:22:15] lb.utils.events INFO:  eta: 4:59:38  iteration: 260099/375342  consumed_samples: 266342400  total_loss: 3.281  time: 0.3437 s/iter  data_time: 0.2373 s/iter total_throughput: 2979.02 samples/s lr: 2.23e-04  
[09/23 04:22:50] lb.utils.events INFO:  eta: 4:59:07  iteration: 260199/375342  consumed_samples: 266444800  total_loss: 3.277  time: 0.3437 s/iter  data_time: 0.2229 s/iter total_throughput: 2979.00 samples/s lr: 2.23e-04  
[09/23 04:23:25] lb.utils.events INFO:  eta: 4:58:33  iteration: 260299/375342  consumed_samples: 266547200  total_loss: 3.276  time: 0.3437 s/iter  data_time: 0.2244 s/iter total_throughput: 2979.00 samples/s lr: 2.22e-04  
[09/23 04:24:00] lb.utils.events INFO:  eta: 4:58:15  iteration: 260399/375342  consumed_samples: 266649600  total_loss: 3.259  time: 0.3437 s/iter  data_time: 0.2250 s/iter total_throughput: 2978.97 samples/s lr: 2.22e-04  
[09/23 04:24:35] lb.utils.events INFO:  eta: 4:58:19  iteration: 260499/375342  consumed_samples: 266752000  total_loss: 3.258  time: 0.3437 s/iter  data_time: 0.2238 s/iter total_throughput: 2978.95 samples/s lr: 2.22e-04  
[09/23 04:25:09] lb.utils.events INFO:  eta: 4:57:55  iteration: 260599/375342  consumed_samples: 266854400  total_loss: 3.266  time: 0.3437 s/iter  data_time: 0.2281 s/iter total_throughput: 2978.95 samples/s lr: 2.21e-04  
[09/23 04:25:44] lb.utils.events INFO:  eta: 4:58:12  iteration: 260699/375342  consumed_samples: 266956800  total_loss: 3.276  time: 0.3437 s/iter  data_time: 0.2311 s/iter total_throughput: 2978.94 samples/s lr: 2.21e-04  
[09/23 04:26:18] lb.utils.events INFO:  eta: 4:57:40  iteration: 260799/375342  consumed_samples: 267059200  total_loss: 3.273  time: 0.3437 s/iter  data_time: 0.2162 s/iter total_throughput: 2978.93 samples/s lr: 2.21e-04  
[09/23 04:26:53] lb.utils.events INFO:  eta: 4:57:30  iteration: 260899/375342  consumed_samples: 267161600  total_loss: 3.271  time: 0.3437 s/iter  data_time: 0.2145 s/iter total_throughput: 2978.93 samples/s lr: 2.20e-04  
[09/23 04:27:27] lb.utils.events INFO:  eta: 4:57:41  iteration: 260999/375342  consumed_samples: 267264000  total_loss: 3.303  time: 0.3437 s/iter  data_time: 0.2118 s/iter total_throughput: 2978.92 samples/s lr: 2.20e-04  
[09/23 04:28:02] lb.utils.events INFO:  eta: 4:56:10  iteration: 261099/375342  consumed_samples: 267366400  total_loss: 3.305  time: 0.3438 s/iter  data_time: 0.2236 s/iter total_throughput: 2978.90 samples/s lr: 2.20e-04  
[09/23 04:28:37] lb.utils.events INFO:  eta: 4:56:18  iteration: 261199/375342  consumed_samples: 267468800  total_loss: 3.285  time: 0.3438 s/iter  data_time: 0.2148 s/iter total_throughput: 2978.89 samples/s lr: 2.19e-04  
[09/23 04:29:12] lb.utils.events INFO:  eta: 4:56:03  iteration: 261299/375342  consumed_samples: 267571200  total_loss: 3.27  time: 0.3438 s/iter  data_time: 0.2215 s/iter total_throughput: 2978.87 samples/s lr: 2.19e-04  
[09/23 04:29:47] lb.utils.events INFO:  eta: 4:55:47  iteration: 261399/375342  consumed_samples: 267673600  total_loss: 3.263  time: 0.3438 s/iter  data_time: 0.2160 s/iter total_throughput: 2978.87 samples/s lr: 2.19e-04  
[09/23 04:30:22] lb.utils.events INFO:  eta: 4:55:31  iteration: 261499/375342  consumed_samples: 267776000  total_loss: 3.273  time: 0.3438 s/iter  data_time: 0.2297 s/iter total_throughput: 2978.85 samples/s lr: 2.18e-04  
[09/23 04:30:57] lb.utils.events INFO:  eta: 4:55:02  iteration: 261599/375342  consumed_samples: 267878400  total_loss: 3.273  time: 0.3438 s/iter  data_time: 0.2234 s/iter total_throughput: 2978.83 samples/s lr: 2.18e-04  
[09/23 04:31:31] lb.utils.events INFO:  eta: 4:54:15  iteration: 261699/375342  consumed_samples: 267980800  total_loss: 3.262  time: 0.3438 s/iter  data_time: 0.2183 s/iter total_throughput: 2978.82 samples/s lr: 2.18e-04  
[09/23 04:32:06] lb.utils.events INFO:  eta: 4:54:03  iteration: 261799/375342  consumed_samples: 268083200  total_loss: 3.263  time: 0.3438 s/iter  data_time: 0.2271 s/iter total_throughput: 2978.81 samples/s lr: 2.17e-04  
[09/23 04:32:40] lb.utils.events INFO:  eta: 4:53:44  iteration: 261899/375342  consumed_samples: 268185600  total_loss: 3.259  time: 0.3438 s/iter  data_time: 0.2141 s/iter total_throughput: 2978.81 samples/s lr: 2.17e-04  
[09/23 04:33:16] lb.utils.events INFO:  eta: 4:52:03  iteration: 261999/375342  consumed_samples: 268288000  total_loss: 3.25  time: 0.3438 s/iter  data_time: 0.2321 s/iter total_throughput: 2978.78 samples/s lr: 2.17e-04  
[09/23 04:33:50] lb.utils.events INFO:  eta: 4:52:23  iteration: 262099/375342  consumed_samples: 268390400  total_loss: 3.253  time: 0.3438 s/iter  data_time: 0.2214 s/iter total_throughput: 2978.77 samples/s lr: 2.16e-04  
[09/23 04:34:25] lb.utils.events INFO:  eta: 4:52:05  iteration: 262199/375342  consumed_samples: 268492800  total_loss: 3.268  time: 0.3438 s/iter  data_time: 0.2239 s/iter total_throughput: 2978.74 samples/s lr: 2.16e-04  
[09/23 04:35:00] lb.utils.events INFO:  eta: 4:52:02  iteration: 262299/375342  consumed_samples: 268595200  total_loss: 3.273  time: 0.3438 s/iter  data_time: 0.2210 s/iter total_throughput: 2978.73 samples/s lr: 2.16e-04  
[09/23 04:35:35] lb.utils.events INFO:  eta: 4:51:31  iteration: 262399/375342  consumed_samples: 268697600  total_loss: 3.265  time: 0.3438 s/iter  data_time: 0.2315 s/iter total_throughput: 2978.72 samples/s lr: 2.15e-04  
[09/23 04:36:10] lb.utils.events INFO:  eta: 4:51:31  iteration: 262499/375342  consumed_samples: 268800000  total_loss: 3.267  time: 0.3438 s/iter  data_time: 0.2152 s/iter total_throughput: 2978.71 samples/s lr: 2.15e-04  
[09/23 04:36:45] lb.utils.events INFO:  eta: 4:50:56  iteration: 262599/375342  consumed_samples: 268902400  total_loss: 3.267  time: 0.3438 s/iter  data_time: 0.2230 s/iter total_throughput: 2978.69 samples/s lr: 2.15e-04  
[09/23 04:37:20] lb.utils.events INFO:  eta: 4:50:47  iteration: 262699/375342  consumed_samples: 269004800  total_loss: 3.24  time: 0.3438 s/iter  data_time: 0.2262 s/iter total_throughput: 2978.67 samples/s lr: 2.14e-04  
[09/23 04:37:55] lb.utils.events INFO:  eta: 4:50:45  iteration: 262799/375342  consumed_samples: 269107200  total_loss: 3.234  time: 0.3438 s/iter  data_time: 0.2211 s/iter total_throughput: 2978.65 samples/s lr: 2.14e-04  
[09/23 04:38:29] lb.utils.events INFO:  eta: 4:50:14  iteration: 262899/375342  consumed_samples: 269209600  total_loss: 3.248  time: 0.3438 s/iter  data_time: 0.2240 s/iter total_throughput: 2978.65 samples/s lr: 2.14e-04  
[09/23 04:39:04] lb.utils.events INFO:  eta: 4:49:50  iteration: 262999/375342  consumed_samples: 269312000  total_loss: 3.273  time: 0.3438 s/iter  data_time: 0.2284 s/iter total_throughput: 2978.63 samples/s lr: 2.13e-04  
[09/23 04:39:38] lb.utils.events INFO:  eta: 4:49:55  iteration: 263099/375342  consumed_samples: 269414400  total_loss: 3.264  time: 0.3438 s/iter  data_time: 0.2199 s/iter total_throughput: 2978.64 samples/s lr: 2.13e-04  
[09/23 04:40:13] lb.utils.events INFO:  eta: 4:49:56  iteration: 263199/375342  consumed_samples: 269516800  total_loss: 3.25  time: 0.3438 s/iter  data_time: 0.2201 s/iter total_throughput: 2978.61 samples/s lr: 2.13e-04  
[09/23 04:40:47] lb.utils.events INFO:  eta: 4:49:53  iteration: 263299/375342  consumed_samples: 269619200  total_loss: 3.251  time: 0.3438 s/iter  data_time: 0.2254 s/iter total_throughput: 2978.62 samples/s lr: 2.12e-04  
[09/23 04:41:22] lb.utils.events INFO:  eta: 4:50:33  iteration: 263399/375342  consumed_samples: 269721600  total_loss: 3.254  time: 0.3438 s/iter  data_time: 0.2171 s/iter total_throughput: 2978.61 samples/s lr: 2.12e-04  
[09/23 04:41:56] lb.utils.events INFO:  eta: 4:50:40  iteration: 263499/375342  consumed_samples: 269824000  total_loss: 3.266  time: 0.3438 s/iter  data_time: 0.2093 s/iter total_throughput: 2978.61 samples/s lr: 2.12e-04  
[09/23 04:42:31] lb.utils.events INFO:  eta: 4:50:33  iteration: 263599/375342  consumed_samples: 269926400  total_loss: 3.275  time: 0.3438 s/iter  data_time: 0.2100 s/iter total_throughput: 2978.60 samples/s lr: 2.11e-04  
[09/23 04:43:06] lb.utils.events INFO:  eta: 4:49:56  iteration: 263699/375342  consumed_samples: 270028800  total_loss: 3.264  time: 0.3438 s/iter  data_time: 0.2096 s/iter total_throughput: 2978.60 samples/s lr: 2.11e-04  
[09/23 04:43:40] lb.utils.events INFO:  eta: 4:50:02  iteration: 263799/375342  consumed_samples: 270131200  total_loss: 3.272  time: 0.3438 s/iter  data_time: 0.2188 s/iter total_throughput: 2978.60 samples/s lr: 2.11e-04  
[09/23 04:44:15] lb.utils.events INFO:  eta: 4:50:03  iteration: 263899/375342  consumed_samples: 270233600  total_loss: 3.283  time: 0.3438 s/iter  data_time: 0.2190 s/iter total_throughput: 2978.60 samples/s lr: 2.10e-04  
[09/23 04:44:49] lb.utils.events INFO:  eta: 4:50:45  iteration: 263999/375342  consumed_samples: 270336000  total_loss: 3.281  time: 0.3438 s/iter  data_time: 0.2108 s/iter total_throughput: 2978.60 samples/s lr: 2.10e-04  
[09/23 04:45:23] lb.utils.events INFO:  eta: 4:49:51  iteration: 264099/375342  consumed_samples: 270438400  total_loss: 3.275  time: 0.3438 s/iter  data_time: 0.2193 s/iter total_throughput: 2978.59 samples/s lr: 2.10e-04  
[09/23 04:45:58] lb.utils.events INFO:  eta: 4:49:43  iteration: 264199/375342  consumed_samples: 270540800  total_loss: 3.254  time: 0.3438 s/iter  data_time: 0.2282 s/iter total_throughput: 2978.58 samples/s lr: 2.09e-04  
[09/23 04:46:33] lb.utils.events INFO:  eta: 4:49:05  iteration: 264299/375342  consumed_samples: 270643200  total_loss: 3.238  time: 0.3438 s/iter  data_time: 0.2186 s/iter total_throughput: 2978.57 samples/s lr: 2.09e-04  
[09/23 04:47:07] lb.utils.events INFO:  eta: 4:48:45  iteration: 264399/375342  consumed_samples: 270745600  total_loss: 3.227  time: 0.3438 s/iter  data_time: 0.2220 s/iter total_throughput: 2978.57 samples/s lr: 2.09e-04  
[09/23 04:47:42] lb.utils.events INFO:  eta: 4:47:45  iteration: 264499/375342  consumed_samples: 270848000  total_loss: 3.241  time: 0.3438 s/iter  data_time: 0.2193 s/iter total_throughput: 2978.56 samples/s lr: 2.08e-04  
[09/23 04:48:17] lb.utils.events INFO:  eta: 4:46:58  iteration: 264599/375342  consumed_samples: 270950400  total_loss: 3.281  time: 0.3438 s/iter  data_time: 0.2239 s/iter total_throughput: 2978.54 samples/s lr: 2.08e-04  
[09/23 04:48:52] lb.utils.events INFO:  eta: 4:47:26  iteration: 264699/375342  consumed_samples: 271052800  total_loss: 3.274  time: 0.3438 s/iter  data_time: 0.2187 s/iter total_throughput: 2978.53 samples/s lr: 2.08e-04  
[09/23 04:49:26] lb.utils.events INFO:  eta: 4:47:11  iteration: 264799/375342  consumed_samples: 271155200  total_loss: 3.261  time: 0.3438 s/iter  data_time: 0.2198 s/iter total_throughput: 2978.52 samples/s lr: 2.07e-04  
[09/23 04:50:01] lb.utils.events INFO:  eta: 4:46:28  iteration: 264899/375342  consumed_samples: 271257600  total_loss: 3.252  time: 0.3438 s/iter  data_time: 0.2296 s/iter total_throughput: 2978.51 samples/s lr: 2.07e-04  
[09/23 04:50:36] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0264999
[09/23 04:50:36] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/23 04:50:36] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/23 04:50:41] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0893 s/iter. Inference: 0.1611 s/iter. Eval: 0.0020 s/iter. Total: 0.2524 s/iter. ETA=0:00:09
[09/23 04:50:46] lb.evaluation.evaluator INFO: Inference done 29696/50000. Dataloading: 0.1378 s/iter. Inference: 0.1628 s/iter. Eval: 0.0020 s/iter. Total: 0.3027 s/iter. ETA=0:00:05
[09/23 04:50:52] lb.evaluation.evaluator INFO: Inference done 50000/50000. Dataloading: 0.1223 s/iter. Inference: 0.1625 s/iter. Eval: 0.0020 s/iter. Total: 0.2869 s/iter. ETA=0:00:00
[09/23 04:50:52] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/23 04:50:52] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.628936 (0.000253 s / iter per device, on 8 devices)
[09/23 04:50:52] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000143 s / iter per device, on 8 devices)
[09/23 04:50:52] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/23 04:50:52] lb.evaluation.utils INFO: copypaste: Acc@1=77.9
[09/23 04:50:52] lb.evaluation.utils INFO: copypaste: Acc@5=93.72399999999999
[09/23 04:50:52] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 77.90000, better than last best score 77.70400 @ iteration 259999.
[09/23 04:50:52] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/23 04:50:52] lb.utils.events INFO:  eta: 4:45:16  iteration: 264999/375342  consumed_samples: 271360000  total_loss: 3.256  time: 0.3438 s/iter  data_time: 0.2297 s/iter total_throughput: 2978.50 samples/s lr: 2.07e-04  
[09/23 04:51:25] lb.utils.events INFO:  eta: 4:46:53  iteration: 265099/375342  consumed_samples: 271462400  total_loss: 3.273  time: 0.3438 s/iter  data_time: 0.2352 s/iter total_throughput: 2978.57 samples/s lr: 2.06e-04  
[09/23 04:51:59] lb.utils.events INFO:  eta: 4:45:55  iteration: 265199/375342  consumed_samples: 271564800  total_loss: 3.271  time: 0.3438 s/iter  data_time: 0.2254 s/iter total_throughput: 2978.56 samples/s lr: 2.06e-04  
[09/23 04:52:33] lb.utils.events INFO:  eta: 4:45:45  iteration: 265299/375342  consumed_samples: 271667200  total_loss: 3.258  time: 0.3438 s/iter  data_time: 0.2080 s/iter total_throughput: 2978.57 samples/s lr: 2.06e-04  
[09/23 04:53:08] lb.utils.events INFO:  eta: 4:45:42  iteration: 265399/375342  consumed_samples: 271769600  total_loss: 3.234  time: 0.3438 s/iter  data_time: 0.2240 s/iter total_throughput: 2978.58 samples/s lr: 2.05e-04  
[09/23 04:53:42] lb.utils.events INFO:  eta: 4:46:03  iteration: 265499/375342  consumed_samples: 271872000  total_loss: 3.25  time: 0.3438 s/iter  data_time: 0.2086 s/iter total_throughput: 2978.59 samples/s lr: 2.05e-04  
[09/23 04:54:16] lb.utils.events INFO:  eta: 4:46:18  iteration: 265599/375342  consumed_samples: 271974400  total_loss: 3.247  time: 0.3438 s/iter  data_time: 0.2178 s/iter total_throughput: 2978.59 samples/s lr: 2.05e-04  
[09/23 04:54:51] lb.utils.events INFO:  eta: 4:45:30  iteration: 265699/375342  consumed_samples: 272076800  total_loss: 3.24  time: 0.3438 s/iter  data_time: 0.2201 s/iter total_throughput: 2978.58 samples/s lr: 2.04e-04  
[09/23 04:55:25] lb.utils.events INFO:  eta: 4:46:09  iteration: 265799/375342  consumed_samples: 272179200  total_loss: 3.244  time: 0.3438 s/iter  data_time: 0.2236 s/iter total_throughput: 2978.60 samples/s lr: 2.04e-04  
[09/23 04:55:59] lb.utils.events INFO:  eta: 4:46:39  iteration: 265899/375342  consumed_samples: 272281600  total_loss: 3.246  time: 0.3438 s/iter  data_time: 0.2257 s/iter total_throughput: 2978.60 samples/s lr: 2.04e-04  
[09/23 04:56:33] lb.utils.events INFO:  eta: 4:46:36  iteration: 265999/375342  consumed_samples: 272384000  total_loss: 3.25  time: 0.3438 s/iter  data_time: 0.2240 s/iter total_throughput: 2978.59 samples/s lr: 2.03e-04  
[09/23 04:57:08] lb.utils.events INFO:  eta: 4:43:55  iteration: 266099/375342  consumed_samples: 272486400  total_loss: 3.233  time: 0.3438 s/iter  data_time: 0.2118 s/iter total_throughput: 2978.58 samples/s lr: 2.03e-04  
[09/23 04:57:43] lb.utils.events INFO:  eta: 4:44:40  iteration: 266199/375342  consumed_samples: 272588800  total_loss: 3.231  time: 0.3438 s/iter  data_time: 0.2256 s/iter total_throughput: 2978.57 samples/s lr: 2.03e-04  
[09/23 04:58:18] lb.utils.events INFO:  eta: 4:43:43  iteration: 266299/375342  consumed_samples: 272691200  total_loss: 3.247  time: 0.3438 s/iter  data_time: 0.2163 s/iter total_throughput: 2978.56 samples/s lr: 2.02e-04  
[09/23 04:58:53] lb.utils.events INFO:  eta: 4:42:29  iteration: 266399/375342  consumed_samples: 272793600  total_loss: 3.262  time: 0.3438 s/iter  data_time: 0.2290 s/iter total_throughput: 2978.52 samples/s lr: 2.02e-04  
[09/23 04:59:29] lb.utils.events INFO:  eta: 4:41:53  iteration: 266499/375342  consumed_samples: 272896000  total_loss: 3.258  time: 0.3438 s/iter  data_time: 0.2323 s/iter total_throughput: 2978.49 samples/s lr: 2.02e-04  
[09/23 05:00:04] lb.utils.events INFO:  eta: 4:40:56  iteration: 266599/375342  consumed_samples: 272998400  total_loss: 3.265  time: 0.3438 s/iter  data_time: 0.2349 s/iter total_throughput: 2978.44 samples/s lr: 2.01e-04  
[09/23 05:00:40] lb.utils.events INFO:  eta: 4:41:22  iteration: 266699/375342  consumed_samples: 273100800  total_loss: 3.247  time: 0.3438 s/iter  data_time: 0.2244 s/iter total_throughput: 2978.41 samples/s lr: 2.01e-04  
[09/23 05:01:15] lb.utils.events INFO:  eta: 4:39:56  iteration: 266799/375342  consumed_samples: 273203200  total_loss: 3.228  time: 0.3438 s/iter  data_time: 0.2306 s/iter total_throughput: 2978.38 samples/s lr: 2.01e-04  
[09/23 05:01:50] lb.utils.events INFO:  eta: 4:39:05  iteration: 266899/375342  consumed_samples: 273305600  total_loss: 3.243  time: 0.3438 s/iter  data_time: 0.2295 s/iter total_throughput: 2978.36 samples/s lr: 2.00e-04  
[09/23 05:02:25] lb.utils.events INFO:  eta: 4:38:42  iteration: 266999/375342  consumed_samples: 273408000  total_loss: 3.245  time: 0.3438 s/iter  data_time: 0.2203 s/iter total_throughput: 2978.33 samples/s lr: 2.00e-04  
[09/23 05:03:01] lb.utils.events INFO:  eta: 4:38:27  iteration: 267099/375342  consumed_samples: 273510400  total_loss: 3.227  time: 0.3438 s/iter  data_time: 0.2223 s/iter total_throughput: 2978.30 samples/s lr: 2.00e-04  
[09/23 05:03:36] lb.utils.events INFO:  eta: 4:38:10  iteration: 267199/375342  consumed_samples: 273612800  total_loss: 3.233  time: 0.3438 s/iter  data_time: 0.2323 s/iter total_throughput: 2978.27 samples/s lr: 1.99e-04  
[09/23 05:04:11] lb.utils.events INFO:  eta: 4:38:12  iteration: 267299/375342  consumed_samples: 273715200  total_loss: 3.25  time: 0.3438 s/iter  data_time: 0.2149 s/iter total_throughput: 2978.27 samples/s lr: 1.99e-04  
[09/23 05:04:46] lb.utils.events INFO:  eta: 4:38:41  iteration: 267399/375342  consumed_samples: 273817600  total_loss: 3.241  time: 0.3438 s/iter  data_time: 0.2138 s/iter total_throughput: 2978.25 samples/s lr: 1.99e-04  
[09/23 05:05:21] lb.utils.events INFO:  eta: 4:38:26  iteration: 267499/375342  consumed_samples: 273920000  total_loss: 3.24  time: 0.3438 s/iter  data_time: 0.2239 s/iter total_throughput: 2978.22 samples/s lr: 1.98e-04  
[09/23 05:05:56] lb.utils.events INFO:  eta: 4:38:22  iteration: 267599/375342  consumed_samples: 274022400  total_loss: 3.248  time: 0.3438 s/iter  data_time: 0.2212 s/iter total_throughput: 2978.19 samples/s lr: 1.98e-04  
[09/23 05:06:31] lb.utils.events INFO:  eta: 4:37:38  iteration: 267699/375342  consumed_samples: 274124800  total_loss: 3.252  time: 0.3438 s/iter  data_time: 0.2152 s/iter total_throughput: 2978.17 samples/s lr: 1.98e-04  
[09/23 05:07:06] lb.utils.events INFO:  eta: 4:36:44  iteration: 267799/375342  consumed_samples: 274227200  total_loss: 3.255  time: 0.3438 s/iter  data_time: 0.2318 s/iter total_throughput: 2978.14 samples/s lr: 1.97e-04  
[09/23 05:07:41] lb.utils.events INFO:  eta: 4:36:16  iteration: 267899/375342  consumed_samples: 274329600  total_loss: 3.252  time: 0.3438 s/iter  data_time: 0.2240 s/iter total_throughput: 2978.13 samples/s lr: 1.97e-04  
[09/23 05:08:16] lb.utils.events INFO:  eta: 4:36:41  iteration: 267999/375342  consumed_samples: 274432000  total_loss: 3.237  time: 0.3438 s/iter  data_time: 0.2192 s/iter total_throughput: 2978.11 samples/s lr: 1.97e-04  
[09/23 05:08:51] lb.utils.events INFO:  eta: 4:36:40  iteration: 268099/375342  consumed_samples: 274534400  total_loss: 3.233  time: 0.3438 s/iter  data_time: 0.2130 s/iter total_throughput: 2978.11 samples/s lr: 1.96e-04  
[09/23 05:09:26] lb.utils.events INFO:  eta: 4:36:18  iteration: 268199/375342  consumed_samples: 274636800  total_loss: 3.234  time: 0.3438 s/iter  data_time: 0.2198 s/iter total_throughput: 2978.09 samples/s lr: 1.96e-04  
[09/23 05:10:01] lb.utils.events INFO:  eta: 4:35:39  iteration: 268299/375342  consumed_samples: 274739200  total_loss: 3.229  time: 0.3438 s/iter  data_time: 0.2185 s/iter total_throughput: 2978.06 samples/s lr: 1.96e-04  
[09/23 05:10:36] lb.utils.events INFO:  eta: 4:35:10  iteration: 268399/375342  consumed_samples: 274841600  total_loss: 3.245  time: 0.3439 s/iter  data_time: 0.2625 s/iter total_throughput: 2978.02 samples/s lr: 1.95e-04  
[09/23 05:11:11] lb.utils.events INFO:  eta: 4:34:46  iteration: 268499/375342  consumed_samples: 274944000  total_loss: 3.252  time: 0.3439 s/iter  data_time: 0.2156 s/iter total_throughput: 2978.01 samples/s lr: 1.95e-04  
[09/23 05:11:46] lb.utils.events INFO:  eta: 4:35:10  iteration: 268599/375342  consumed_samples: 275046400  total_loss: 3.255  time: 0.3439 s/iter  data_time: 0.2127 s/iter total_throughput: 2978.01 samples/s lr: 1.95e-04  
[09/23 05:12:20] lb.utils.events INFO:  eta: 4:35:52  iteration: 268699/375342  consumed_samples: 275148800  total_loss: 3.248  time: 0.3439 s/iter  data_time: 0.2130 s/iter total_throughput: 2978.00 samples/s lr: 1.94e-04  
[09/23 05:12:55] lb.utils.events INFO:  eta: 4:35:58  iteration: 268799/375342  consumed_samples: 275251200  total_loss: 3.254  time: 0.3439 s/iter  data_time: 0.2234 s/iter total_throughput: 2977.98 samples/s lr: 1.94e-04  
[09/23 05:13:30] lb.utils.events INFO:  eta: 4:35:18  iteration: 268899/375342  consumed_samples: 275353600  total_loss: 3.255  time: 0.3439 s/iter  data_time: 0.2350 s/iter total_throughput: 2977.96 samples/s lr: 1.94e-04  
[09/23 05:14:05] lb.utils.events INFO:  eta: 4:34:37  iteration: 268999/375342  consumed_samples: 275456000  total_loss: 3.242  time: 0.3439 s/iter  data_time: 0.2169 s/iter total_throughput: 2977.95 samples/s lr: 1.93e-04  
[09/23 05:14:40] lb.utils.events INFO:  eta: 4:34:22  iteration: 269099/375342  consumed_samples: 275558400  total_loss: 3.221  time: 0.3439 s/iter  data_time: 0.2136 s/iter total_throughput: 2977.93 samples/s lr: 1.93e-04  
[09/23 05:15:15] lb.utils.events INFO:  eta: 4:34:22  iteration: 269199/375342  consumed_samples: 275660800  total_loss: 3.226  time: 0.3439 s/iter  data_time: 0.2133 s/iter total_throughput: 2977.92 samples/s lr: 1.93e-04  
[09/23 05:15:50] lb.utils.events INFO:  eta: 4:34:27  iteration: 269299/375342  consumed_samples: 275763200  total_loss: 3.248  time: 0.3439 s/iter  data_time: 0.2179 s/iter total_throughput: 2977.90 samples/s lr: 1.93e-04  
[09/23 05:16:25] lb.utils.events INFO:  eta: 4:33:47  iteration: 269399/375342  consumed_samples: 275865600  total_loss: 3.233  time: 0.3439 s/iter  data_time: 0.2287 s/iter total_throughput: 2977.86 samples/s lr: 1.92e-04  
[09/23 05:17:00] lb.utils.events INFO:  eta: 4:33:35  iteration: 269499/375342  consumed_samples: 275968000  total_loss: 3.235  time: 0.3439 s/iter  data_time: 0.2182 s/iter total_throughput: 2977.85 samples/s lr: 1.92e-04  
[09/23 05:17:35] lb.utils.events INFO:  eta: 4:33:03  iteration: 269599/375342  consumed_samples: 276070400  total_loss: 3.259  time: 0.3439 s/iter  data_time: 0.2218 s/iter total_throughput: 2977.83 samples/s lr: 1.92e-04  
[09/23 05:18:10] lb.utils.events INFO:  eta: 4:32:32  iteration: 269699/375342  consumed_samples: 276172800  total_loss: 3.23  time: 0.3439 s/iter  data_time: 0.2154 s/iter total_throughput: 2977.82 samples/s lr: 1.91e-04  
[09/23 05:18:45] lb.utils.events INFO:  eta: 4:32:07  iteration: 269799/375342  consumed_samples: 276275200  total_loss: 3.228  time: 0.3439 s/iter  data_time: 0.2311 s/iter total_throughput: 2977.79 samples/s lr: 1.91e-04  
[09/23 05:19:21] lb.utils.events INFO:  eta: 4:32:41  iteration: 269899/375342  consumed_samples: 276377600  total_loss: 3.24  time: 0.3439 s/iter  data_time: 0.2334 s/iter total_throughput: 2977.76 samples/s lr: 1.91e-04  
[09/23 05:19:56] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0269999
[09/23 05:19:57] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/23 05:19:57] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/23 05:20:01] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0947 s/iter. Inference: 0.1652 s/iter. Eval: 0.0022 s/iter. Total: 0.2621 s/iter. ETA=0:00:09
[09/23 05:20:06] lb.evaluation.evaluator INFO: Inference done 29696/50000. Dataloading: 0.1282 s/iter. Inference: 0.1676 s/iter. Eval: 0.0021 s/iter. Total: 0.2980 s/iter. ETA=0:00:05
[09/23 05:20:12] lb.evaluation.evaluator INFO: Inference done 49152/50000. Dataloading: 0.1203 s/iter. Inference: 0.1634 s/iter. Eval: 0.0021 s/iter. Total: 0.2858 s/iter. ETA=0:00:00
[09/23 05:20:12] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/23 05:20:12] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.484810 (0.000250 s / iter per device, on 8 devices)
[09/23 05:20:12] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000144 s / iter per device, on 8 devices)
[09/23 05:20:12] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/23 05:20:12] lb.evaluation.utils INFO: copypaste: Acc@1=78.164
[09/23 05:20:12] lb.evaluation.utils INFO: copypaste: Acc@5=93.864
[09/23 05:20:12] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 78.16400, better than last best score 77.90000 @ iteration 264999.
[09/23 05:20:12] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/23 05:20:13] lb.utils.events INFO:  eta: 4:32:17  iteration: 269999/375342  consumed_samples: 276480000  total_loss: 3.246  time: 0.3439 s/iter  data_time: 0.2300 s/iter total_throughput: 2977.73 samples/s lr: 1.90e-04  
[09/23 05:20:45] lb.utils.events INFO:  eta: 4:33:36  iteration: 270099/375342  consumed_samples: 276582400  total_loss: 3.244  time: 0.3439 s/iter  data_time: 0.2328 s/iter total_throughput: 2977.78 samples/s lr: 1.90e-04  
[09/23 05:21:20] lb.utils.events INFO:  eta: 4:33:18  iteration: 270199/375342  consumed_samples: 276684800  total_loss: 3.227  time: 0.3439 s/iter  data_time: 0.2289 s/iter total_throughput: 2977.76 samples/s lr: 1.90e-04  
[09/23 05:21:55] lb.utils.events INFO:  eta: 4:33:40  iteration: 270299/375342  consumed_samples: 276787200  total_loss: 3.239  time: 0.3439 s/iter  data_time: 0.2155 s/iter total_throughput: 2977.75 samples/s lr: 1.89e-04  
[09/23 05:22:30] lb.utils.events INFO:  eta: 4:33:24  iteration: 270399/375342  consumed_samples: 276889600  total_loss: 3.229  time: 0.3439 s/iter  data_time: 0.2351 s/iter total_throughput: 2977.73 samples/s lr: 1.89e-04  
[09/23 05:23:05] lb.utils.events INFO:  eta: 4:33:35  iteration: 270499/375342  consumed_samples: 276992000  total_loss: 3.227  time: 0.3439 s/iter  data_time: 0.2144 s/iter total_throughput: 2977.73 samples/s lr: 1.89e-04  
[09/23 05:23:39] lb.utils.events INFO:  eta: 4:34:05  iteration: 270599/375342  consumed_samples: 277094400  total_loss: 3.251  time: 0.3439 s/iter  data_time: 0.2098 s/iter total_throughput: 2977.72 samples/s lr: 1.88e-04  
[09/23 05:24:14] lb.utils.events INFO:  eta: 4:33:47  iteration: 270699/375342  consumed_samples: 277196800  total_loss: 3.237  time: 0.3439 s/iter  data_time: 0.2295 s/iter total_throughput: 2977.69 samples/s lr: 1.88e-04  
[09/23 05:24:49] lb.utils.events INFO:  eta: 4:34:11  iteration: 270799/375342  consumed_samples: 277299200  total_loss: 3.233  time: 0.3439 s/iter  data_time: 0.2205 s/iter total_throughput: 2977.69 samples/s lr: 1.88e-04  
[09/23 05:25:24] lb.utils.events INFO:  eta: 4:34:49  iteration: 270899/375342  consumed_samples: 277401600  total_loss: 3.248  time: 0.3439 s/iter  data_time: 0.2258 s/iter total_throughput: 2977.68 samples/s lr: 1.87e-04  
[09/23 05:25:59] lb.utils.events INFO:  eta: 4:34:28  iteration: 270999/375342  consumed_samples: 277504000  total_loss: 3.253  time: 0.3439 s/iter  data_time: 0.2202 s/iter total_throughput: 2977.66 samples/s lr: 1.87e-04  
[09/23 05:26:34] lb.utils.events INFO:  eta: 4:32:34  iteration: 271099/375342  consumed_samples: 277606400  total_loss: 3.234  time: 0.3439 s/iter  data_time: 0.2227 s/iter total_throughput: 2977.64 samples/s lr: 1.87e-04  
[09/23 05:27:09] lb.utils.events INFO:  eta: 4:32:07  iteration: 271199/375342  consumed_samples: 277708800  total_loss: 3.229  time: 0.3439 s/iter  data_time: 0.2276 s/iter total_throughput: 2977.62 samples/s lr: 1.86e-04  
[09/23 05:27:43] lb.utils.events INFO:  eta: 4:31:14  iteration: 271299/375342  consumed_samples: 277811200  total_loss: 3.23  time: 0.3439 s/iter  data_time: 0.2138 s/iter total_throughput: 2977.62 samples/s lr: 1.86e-04  
[09/23 05:28:18] lb.utils.events INFO:  eta: 4:30:50  iteration: 271399/375342  consumed_samples: 277913600  total_loss: 3.232  time: 0.3439 s/iter  data_time: 0.2219 s/iter total_throughput: 2977.61 samples/s lr: 1.86e-04  
[09/23 05:28:53] lb.utils.events INFO:  eta: 4:30:03  iteration: 271499/375342  consumed_samples: 278016000  total_loss: 3.23  time: 0.3439 s/iter  data_time: 0.2349 s/iter total_throughput: 2977.59 samples/s lr: 1.85e-04  
[09/23 05:29:28] lb.utils.events INFO:  eta: 4:29:46  iteration: 271599/375342  consumed_samples: 278118400  total_loss: 3.209  time: 0.3439 s/iter  data_time: 0.2307 s/iter total_throughput: 2977.57 samples/s lr: 1.85e-04  
[09/23 05:30:03] lb.utils.events INFO:  eta: 4:29:32  iteration: 271699/375342  consumed_samples: 278220800  total_loss: 3.201  time: 0.3439 s/iter  data_time: 0.2148 s/iter total_throughput: 2977.56 samples/s lr: 1.85e-04  
[09/23 05:30:37] lb.utils.events INFO:  eta: 4:29:48  iteration: 271799/375342  consumed_samples: 278323200  total_loss: 3.23  time: 0.3439 s/iter  data_time: 0.2144 s/iter total_throughput: 2977.56 samples/s lr: 1.85e-04  
[09/23 05:31:12] lb.utils.events INFO:  eta: 4:28:31  iteration: 271899/375342  consumed_samples: 278425600  total_loss: 3.246  time: 0.3439 s/iter  data_time: 0.2273 s/iter total_throughput: 2977.53 samples/s lr: 1.84e-04  
[09/23 05:31:46] lb.utils.events INFO:  eta: 4:28:49  iteration: 271999/375342  consumed_samples: 278528000  total_loss: 3.231  time: 0.3439 s/iter  data_time: 0.2153 s/iter total_throughput: 2977.54 samples/s lr: 1.84e-04  
[09/23 05:32:21] lb.utils.events INFO:  eta: 4:28:33  iteration: 272099/375342  consumed_samples: 278630400  total_loss: 3.229  time: 0.3439 s/iter  data_time: 0.2238 s/iter total_throughput: 2977.53 samples/s lr: 1.84e-04  
[09/23 05:32:56] lb.utils.events INFO:  eta: 4:28:56  iteration: 272199/375342  consumed_samples: 278732800  total_loss: 3.229  time: 0.3439 s/iter  data_time: 0.2164 s/iter total_throughput: 2977.52 samples/s lr: 1.83e-04  
[09/23 05:33:31] lb.utils.events INFO:  eta: 4:28:42  iteration: 272299/375342  consumed_samples: 278835200  total_loss: 3.215  time: 0.3439 s/iter  data_time: 0.2171 s/iter total_throughput: 2977.51 samples/s lr: 1.83e-04  
[09/23 05:34:05] lb.utils.events INFO:  eta: 4:29:11  iteration: 272399/375342  consumed_samples: 278937600  total_loss: 3.227  time: 0.3439 s/iter  data_time: 0.2150 s/iter total_throughput: 2977.50 samples/s lr: 1.83e-04  
[09/23 05:34:40] lb.utils.events INFO:  eta: 4:29:23  iteration: 272499/375342  consumed_samples: 279040000  total_loss: 3.244  time: 0.3439 s/iter  data_time: 0.2242 s/iter total_throughput: 2977.48 samples/s lr: 1.82e-04  
[09/23 05:35:16] lb.utils.events INFO:  eta: 4:28:29  iteration: 272599/375342  consumed_samples: 279142400  total_loss: 3.222  time: 0.3439 s/iter  data_time: 0.2144 s/iter total_throughput: 2977.45 samples/s lr: 1.82e-04  
[09/23 05:35:50] lb.utils.events INFO:  eta: 4:27:44  iteration: 272699/375342  consumed_samples: 279244800  total_loss: 3.234  time: 0.3439 s/iter  data_time: 0.2237 s/iter total_throughput: 2977.45 samples/s lr: 1.82e-04  
[09/23 05:36:25] lb.utils.events INFO:  eta: 4:26:49  iteration: 272799/375342  consumed_samples: 279347200  total_loss: 3.229  time: 0.3439 s/iter  data_time: 0.2157 s/iter total_throughput: 2977.43 samples/s lr: 1.81e-04  
[09/23 05:37:00] lb.utils.events INFO:  eta: 4:26:53  iteration: 272899/375342  consumed_samples: 279449600  total_loss: 3.217  time: 0.3439 s/iter  data_time: 0.2202 s/iter total_throughput: 2977.42 samples/s lr: 1.81e-04  
[09/23 05:37:34] lb.utils.events INFO:  eta: 4:25:43  iteration: 272999/375342  consumed_samples: 279552000  total_loss: 3.236  time: 0.3439 s/iter  data_time: 0.2253 s/iter total_throughput: 2977.42 samples/s lr: 1.81e-04  
[09/23 05:38:09] lb.utils.events INFO:  eta: 4:25:16  iteration: 273099/375342  consumed_samples: 279654400  total_loss: 3.233  time: 0.3439 s/iter  data_time: 0.2351 s/iter total_throughput: 2977.40 samples/s lr: 1.80e-04  
[09/23 05:38:44] lb.utils.events INFO:  eta: 4:24:28  iteration: 273199/375342  consumed_samples: 279756800  total_loss: 3.232  time: 0.3439 s/iter  data_time: 0.2108 s/iter total_throughput: 2977.39 samples/s lr: 1.80e-04  
[09/23 05:39:18] lb.utils.events INFO:  eta: 4:24:20  iteration: 273299/375342  consumed_samples: 279859200  total_loss: 3.231  time: 0.3439 s/iter  data_time: 0.2170 s/iter total_throughput: 2977.39 samples/s lr: 1.80e-04  
[09/23 05:39:53] lb.utils.events INFO:  eta: 4:24:01  iteration: 273399/375342  consumed_samples: 279961600  total_loss: 3.227  time: 0.3439 s/iter  data_time: 0.2203 s/iter total_throughput: 2977.38 samples/s lr: 1.80e-04  
[09/23 05:40:28] lb.utils.events INFO:  eta: 4:24:02  iteration: 273499/375342  consumed_samples: 280064000  total_loss: 3.229  time: 0.3439 s/iter  data_time: 0.2329 s/iter total_throughput: 2977.38 samples/s lr: 1.79e-04  
[09/23 05:41:03] lb.utils.events INFO:  eta: 4:24:02  iteration: 273599/375342  consumed_samples: 280166400  total_loss: 3.229  time: 0.3439 s/iter  data_time: 0.2137 s/iter total_throughput: 2977.36 samples/s lr: 1.79e-04  
[09/23 05:41:38] lb.utils.events INFO:  eta: 4:23:51  iteration: 273699/375342  consumed_samples: 280268800  total_loss: 3.236  time: 0.3439 s/iter  data_time: 0.2259 s/iter total_throughput: 2977.33 samples/s lr: 1.79e-04  
[09/23 05:42:13] lb.utils.events INFO:  eta: 4:23:10  iteration: 273799/375342  consumed_samples: 280371200  total_loss: 3.229  time: 0.3439 s/iter  data_time: 0.2358 s/iter total_throughput: 2977.30 samples/s lr: 1.78e-04  
[09/23 05:42:48] lb.utils.events INFO:  eta: 4:23:28  iteration: 273899/375342  consumed_samples: 280473600  total_loss: 3.216  time: 0.3439 s/iter  data_time: 0.2198 s/iter total_throughput: 2977.30 samples/s lr: 1.78e-04  
[09/23 05:43:23] lb.utils.events INFO:  eta: 4:22:39  iteration: 273999/375342  consumed_samples: 280576000  total_loss: 3.201  time: 0.3439 s/iter  data_time: 0.2264 s/iter total_throughput: 2977.28 samples/s lr: 1.78e-04  
[09/23 05:43:57] lb.utils.events INFO:  eta: 4:22:44  iteration: 274099/375342  consumed_samples: 280678400  total_loss: 3.189  time: 0.3439 s/iter  data_time: 0.2114 s/iter total_throughput: 2977.27 samples/s lr: 1.77e-04  
[09/23 05:44:32] lb.utils.events INFO:  eta: 4:22:32  iteration: 274199/375342  consumed_samples: 280780800  total_loss: 3.209  time: 0.3439 s/iter  data_time: 0.2223 s/iter total_throughput: 2977.26 samples/s lr: 1.77e-04  
[09/23 05:45:07] lb.utils.events INFO:  eta: 4:22:09  iteration: 274299/375342  consumed_samples: 280883200  total_loss: 3.224  time: 0.3439 s/iter  data_time: 0.2197 s/iter total_throughput: 2977.25 samples/s lr: 1.77e-04  
[09/23 05:45:41] lb.utils.events INFO:  eta: 4:21:50  iteration: 274399/375342  consumed_samples: 280985600  total_loss: 3.203  time: 0.3439 s/iter  data_time: 0.2139 s/iter total_throughput: 2977.25 samples/s lr: 1.76e-04  
[09/23 05:46:16] lb.utils.events INFO:  eta: 4:21:04  iteration: 274499/375342  consumed_samples: 281088000  total_loss: 3.206  time: 0.3439 s/iter  data_time: 0.2315 s/iter total_throughput: 2977.22 samples/s lr: 1.76e-04  
[09/23 05:46:51] lb.utils.events INFO:  eta: 4:20:41  iteration: 274599/375342  consumed_samples: 281190400  total_loss: 3.217  time: 0.3439 s/iter  data_time: 0.2251 s/iter total_throughput: 2977.21 samples/s lr: 1.76e-04  
[09/23 05:47:26] lb.utils.events INFO:  eta: 4:21:01  iteration: 274699/375342  consumed_samples: 281292800  total_loss: 3.217  time: 0.3439 s/iter  data_time: 0.2172 s/iter total_throughput: 2977.21 samples/s lr: 1.75e-04  
[09/23 05:48:01] lb.utils.events INFO:  eta: 4:21:00  iteration: 274799/375342  consumed_samples: 281395200  total_loss: 3.219  time: 0.3439 s/iter  data_time: 0.2313 s/iter total_throughput: 2977.18 samples/s lr: 1.75e-04  
[09/23 05:48:36] lb.utils.events INFO:  eta: 4:20:33  iteration: 274899/375342  consumed_samples: 281497600  total_loss: 3.22  time: 0.3440 s/iter  data_time: 0.2218 s/iter total_throughput: 2977.16 samples/s lr: 1.75e-04  
[09/23 05:49:12] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0274999
[09/23 05:49:12] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/23 05:49:12] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/23 05:49:16] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.1004 s/iter. Inference: 0.1689 s/iter. Eval: 0.0020 s/iter. Total: 0.2714 s/iter. ETA=0:00:10
[09/23 05:49:22] lb.evaluation.evaluator INFO: Inference done 29696/50000. Dataloading: 0.1386 s/iter. Inference: 0.1643 s/iter. Eval: 0.0020 s/iter. Total: 0.3050 s/iter. ETA=0:00:05
[09/23 05:49:27] lb.evaluation.evaluator INFO: Inference done 49152/50000. Dataloading: 0.1226 s/iter. Inference: 0.1627 s/iter. Eval: 0.0020 s/iter. Total: 0.2874 s/iter. ETA=0:00:00
[09/23 05:49:28] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/23 05:49:28] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.806459 (0.000256 s / iter per device, on 8 devices)
[09/23 05:49:28] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000144 s / iter per device, on 8 devices)
[09/23 05:49:28] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/23 05:49:28] lb.evaluation.utils INFO: copypaste: Acc@1=78.358
[09/23 05:49:28] lb.evaluation.utils INFO: copypaste: Acc@5=93.978
[09/23 05:49:28] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 78.35800, better than last best score 78.16400 @ iteration 269999.
[09/23 05:49:28] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/23 05:49:28] lb.utils.events INFO:  eta: 4:20:29  iteration: 274999/375342  consumed_samples: 281600000  total_loss: 3.215  time: 0.3440 s/iter  data_time: 0.2311 s/iter total_throughput: 2977.13 samples/s lr: 1.75e-04  
[09/23 05:50:01] lb.utils.events INFO:  eta: 4:21:01  iteration: 275099/375342  consumed_samples: 281702400  total_loss: 3.203  time: 0.3439 s/iter  data_time: 0.2144 s/iter total_throughput: 2977.20 samples/s lr: 1.74e-04  
[09/23 05:50:36] lb.utils.events INFO:  eta: 4:20:55  iteration: 275199/375342  consumed_samples: 281804800  total_loss: 3.197  time: 0.3439 s/iter  data_time: 0.2097 s/iter total_throughput: 2977.18 samples/s lr: 1.74e-04  
[09/23 05:51:11] lb.utils.events INFO:  eta: 4:20:39  iteration: 275299/375342  consumed_samples: 281907200  total_loss: 3.188  time: 0.3440 s/iter  data_time: 0.2270 s/iter total_throughput: 2977.15 samples/s lr: 1.74e-04  
[09/23 05:51:45] lb.utils.events INFO:  eta: 4:20:42  iteration: 275399/375342  consumed_samples: 282009600  total_loss: 3.193  time: 0.3440 s/iter  data_time: 0.2143 s/iter total_throughput: 2977.15 samples/s lr: 1.73e-04  
[09/23 05:52:20] lb.utils.events INFO:  eta: 4:21:24  iteration: 275499/375342  consumed_samples: 282112000  total_loss: 3.213  time: 0.3440 s/iter  data_time: 0.2169 s/iter total_throughput: 2977.14 samples/s lr: 1.73e-04  
[09/23 05:52:55] lb.utils.events INFO:  eta: 4:21:08  iteration: 275599/375342  consumed_samples: 282214400  total_loss: 3.223  time: 0.3440 s/iter  data_time: 0.2216 s/iter total_throughput: 2977.13 samples/s lr: 1.73e-04  
[09/23 05:53:30] lb.utils.events INFO:  eta: 4:20:30  iteration: 275699/375342  consumed_samples: 282316800  total_loss: 3.208  time: 0.3440 s/iter  data_time: 0.2209 s/iter total_throughput: 2977.12 samples/s lr: 1.72e-04  
[09/23 05:54:05] lb.utils.events INFO:  eta: 4:19:36  iteration: 275799/375342  consumed_samples: 282419200  total_loss: 3.207  time: 0.3440 s/iter  data_time: 0.2317 s/iter total_throughput: 2977.09 samples/s lr: 1.72e-04  
[09/23 05:54:40] lb.utils.events INFO:  eta: 4:18:49  iteration: 275899/375342  consumed_samples: 282521600  total_loss: 3.22  time: 0.3440 s/iter  data_time: 0.2325 s/iter total_throughput: 2977.08 samples/s lr: 1.72e-04  
[09/23 05:55:15] lb.utils.events INFO:  eta: 4:18:40  iteration: 275999/375342  consumed_samples: 282624000  total_loss: 3.229  time: 0.3440 s/iter  data_time: 0.2330 s/iter total_throughput: 2977.06 samples/s lr: 1.71e-04  
[09/23 05:55:50] lb.utils.events INFO:  eta: 4:17:17  iteration: 276099/375342  consumed_samples: 282726400  total_loss: 3.229  time: 0.3440 s/iter  data_time: 0.2350 s/iter total_throughput: 2977.04 samples/s lr: 1.71e-04  
[09/23 05:56:24] lb.utils.events INFO:  eta: 4:16:46  iteration: 276199/375342  consumed_samples: 282828800  total_loss: 3.218  time: 0.3440 s/iter  data_time: 0.2261 s/iter total_throughput: 2977.03 samples/s lr: 1.71e-04  
[09/23 05:56:59] lb.utils.events INFO:  eta: 4:16:14  iteration: 276299/375342  consumed_samples: 282931200  total_loss: 3.204  time: 0.3440 s/iter  data_time: 0.2228 s/iter total_throughput: 2977.03 samples/s lr: 1.71e-04  
[09/23 05:57:33] lb.utils.events INFO:  eta: 4:16:12  iteration: 276399/375342  consumed_samples: 283033600  total_loss: 3.206  time: 0.3440 s/iter  data_time: 0.2075 s/iter total_throughput: 2977.04 samples/s lr: 1.70e-04  
[09/23 05:58:08] lb.utils.events INFO:  eta: 4:15:46  iteration: 276499/375342  consumed_samples: 283136000  total_loss: 3.203  time: 0.3440 s/iter  data_time: 0.2363 s/iter total_throughput: 2977.02 samples/s lr: 1.70e-04  
[09/23 05:58:43] lb.utils.events INFO:  eta: 4:15:28  iteration: 276599/375342  consumed_samples: 283238400  total_loss: 3.209  time: 0.3440 s/iter  data_time: 0.2264 s/iter total_throughput: 2977.01 samples/s lr: 1.70e-04  
[09/23 05:59:18] lb.utils.events INFO:  eta: 4:14:50  iteration: 276699/375342  consumed_samples: 283340800  total_loss: 3.192  time: 0.3440 s/iter  data_time: 0.2310 s/iter total_throughput: 2976.99 samples/s lr: 1.69e-04  
[09/23 05:59:53] lb.utils.events INFO:  eta: 4:15:12  iteration: 276799/375342  consumed_samples: 283443200  total_loss: 3.185  time: 0.3440 s/iter  data_time: 0.2240 s/iter total_throughput: 2976.98 samples/s lr: 1.69e-04  
[09/23 06:00:27] lb.utils.events INFO:  eta: 4:15:26  iteration: 276899/375342  consumed_samples: 283545600  total_loss: 3.202  time: 0.3440 s/iter  data_time: 0.2232 s/iter total_throughput: 2976.97 samples/s lr: 1.69e-04  
[09/23 06:01:02] lb.utils.events INFO:  eta: 4:15:13  iteration: 276999/375342  consumed_samples: 283648000  total_loss: 3.203  time: 0.3440 s/iter  data_time: 0.2182 s/iter total_throughput: 2976.96 samples/s lr: 1.68e-04  
[09/23 06:01:36] lb.utils.events INFO:  eta: 4:15:14  iteration: 277099/375342  consumed_samples: 283750400  total_loss: 3.223  time: 0.3440 s/iter  data_time: 0.2156 s/iter total_throughput: 2976.97 samples/s lr: 1.68e-04  
[09/23 06:02:10] lb.utils.events INFO:  eta: 4:15:18  iteration: 277199/375342  consumed_samples: 283852800  total_loss: 3.222  time: 0.3440 s/iter  data_time: 0.2089 s/iter total_throughput: 2976.98 samples/s lr: 1.68e-04  
[09/23 06:02:44] lb.utils.events INFO:  eta: 4:15:35  iteration: 277299/375342  consumed_samples: 283955200  total_loss: 3.219  time: 0.3440 s/iter  data_time: 0.2198 s/iter total_throughput: 2976.98 samples/s lr: 1.68e-04  
[09/23 06:03:19] lb.utils.events INFO:  eta: 4:15:01  iteration: 277399/375342  consumed_samples: 284057600  total_loss: 3.225  time: 0.3440 s/iter  data_time: 0.2430 s/iter total_throughput: 2976.97 samples/s lr: 1.67e-04  
[09/23 06:03:54] lb.utils.events INFO:  eta: 4:14:58  iteration: 277499/375342  consumed_samples: 284160000  total_loss: 3.21  time: 0.3440 s/iter  data_time: 0.2114 s/iter total_throughput: 2976.96 samples/s lr: 1.67e-04  
[09/23 06:04:29] lb.utils.events INFO:  eta: 4:14:37  iteration: 277599/375342  consumed_samples: 284262400  total_loss: 3.2  time: 0.3440 s/iter  data_time: 0.2078 s/iter total_throughput: 2976.95 samples/s lr: 1.67e-04  
[09/23 06:05:03] lb.utils.events INFO:  eta: 4:14:26  iteration: 277699/375342  consumed_samples: 284364800  total_loss: 3.207  time: 0.3440 s/iter  data_time: 0.2250 s/iter total_throughput: 2976.95 samples/s lr: 1.66e-04  
[09/23 06:05:38] lb.utils.events INFO:  eta: 4:13:51  iteration: 277799/375342  consumed_samples: 284467200  total_loss: 3.22  time: 0.3440 s/iter  data_time: 0.2193 s/iter total_throughput: 2976.93 samples/s lr: 1.66e-04  
[09/23 06:06:13] lb.utils.events INFO:  eta: 4:13:24  iteration: 277899/375342  consumed_samples: 284569600  total_loss: 3.197  time: 0.3440 s/iter  data_time: 0.2119 s/iter total_throughput: 2976.92 samples/s lr: 1.66e-04  
[09/23 06:06:47] lb.utils.events INFO:  eta: 4:13:47  iteration: 277999/375342  consumed_samples: 284672000  total_loss: 3.179  time: 0.3440 s/iter  data_time: 0.2168 s/iter total_throughput: 2976.93 samples/s lr: 1.65e-04  
[09/23 06:07:22] lb.utils.events INFO:  eta: 4:13:17  iteration: 278099/375342  consumed_samples: 284774400  total_loss: 3.196  time: 0.3440 s/iter  data_time: 0.2223 s/iter total_throughput: 2976.91 samples/s lr: 1.65e-04  
[09/23 06:07:57] lb.utils.events INFO:  eta: 4:12:28  iteration: 278199/375342  consumed_samples: 284876800  total_loss: 3.198  time: 0.3440 s/iter  data_time: 0.2080 s/iter total_throughput: 2976.91 samples/s lr: 1.65e-04  
[09/23 06:08:32] lb.utils.events INFO:  eta: 4:11:11  iteration: 278299/375342  consumed_samples: 284979200  total_loss: 3.195  time: 0.3440 s/iter  data_time: 0.2425 s/iter total_throughput: 2976.87 samples/s lr: 1.65e-04  
[09/23 06:09:07] lb.utils.events INFO:  eta: 4:10:47  iteration: 278399/375342  consumed_samples: 285081600  total_loss: 3.206  time: 0.3440 s/iter  data_time: 0.2336 s/iter total_throughput: 2976.86 samples/s lr: 1.64e-04  
[09/23 06:09:41] lb.utils.events INFO:  eta: 4:11:01  iteration: 278499/375342  consumed_samples: 285184000  total_loss: 3.224  time: 0.3440 s/iter  data_time: 0.2093 s/iter total_throughput: 2976.87 samples/s lr: 1.64e-04  
[09/23 06:10:16] lb.utils.events INFO:  eta: 4:11:15  iteration: 278599/375342  consumed_samples: 285286400  total_loss: 3.225  time: 0.3440 s/iter  data_time: 0.2161 s/iter total_throughput: 2976.86 samples/s lr: 1.64e-04  
[09/23 06:10:50] lb.utils.events INFO:  eta: 4:10:55  iteration: 278699/375342  consumed_samples: 285388800  total_loss: 3.214  time: 0.3440 s/iter  data_time: 0.2215 s/iter total_throughput: 2976.86 samples/s lr: 1.63e-04  
[09/23 06:11:25] lb.utils.events INFO:  eta: 4:10:50  iteration: 278799/375342  consumed_samples: 285491200  total_loss: 3.202  time: 0.3440 s/iter  data_time: 0.2216 s/iter total_throughput: 2976.85 samples/s lr: 1.63e-04  
[09/23 06:11:59] lb.utils.events INFO:  eta: 4:11:29  iteration: 278899/375342  consumed_samples: 285593600  total_loss: 3.199  time: 0.3440 s/iter  data_time: 0.2174 s/iter total_throughput: 2976.85 samples/s lr: 1.63e-04  
[09/23 06:12:33] lb.utils.events INFO:  eta: 4:10:19  iteration: 278999/375342  consumed_samples: 285696000  total_loss: 3.203  time: 0.3440 s/iter  data_time: 0.2090 s/iter total_throughput: 2976.87 samples/s lr: 1.62e-04  
[09/23 06:13:07] lb.utils.events INFO:  eta: 4:10:24  iteration: 279099/375342  consumed_samples: 285798400  total_loss: 3.182  time: 0.3440 s/iter  data_time: 0.2083 s/iter total_throughput: 2976.88 samples/s lr: 1.62e-04  
[09/23 06:13:41] lb.utils.events INFO:  eta: 4:10:47  iteration: 279199/375342  consumed_samples: 285900800  total_loss: 3.174  time: 0.3440 s/iter  data_time: 0.2216 s/iter total_throughput: 2976.88 samples/s lr: 1.62e-04  
[09/23 06:14:16] lb.utils.events INFO:  eta: 4:10:16  iteration: 279299/375342  consumed_samples: 286003200  total_loss: 3.186  time: 0.3440 s/iter  data_time: 0.2247 s/iter total_throughput: 2976.87 samples/s lr: 1.62e-04  
[09/23 06:14:51] lb.utils.events INFO:  eta: 4:10:22  iteration: 279399/375342  consumed_samples: 286105600  total_loss: 3.195  time: 0.3440 s/iter  data_time: 0.2256 s/iter total_throughput: 2976.87 samples/s lr: 1.61e-04  
[09/23 06:15:25] lb.utils.events INFO:  eta: 4:10:07  iteration: 279499/375342  consumed_samples: 286208000  total_loss: 3.201  time: 0.3440 s/iter  data_time: 0.2147 s/iter total_throughput: 2976.87 samples/s lr: 1.61e-04  
[09/23 06:15:59] lb.utils.events INFO:  eta: 4:09:49  iteration: 279599/375342  consumed_samples: 286310400  total_loss: 3.199  time: 0.3440 s/iter  data_time: 0.2164 s/iter total_throughput: 2976.88 samples/s lr: 1.61e-04  
[09/23 06:16:33] lb.utils.events INFO:  eta: 4:09:41  iteration: 279699/375342  consumed_samples: 286412800  total_loss: 3.186  time: 0.3440 s/iter  data_time: 0.2221 s/iter total_throughput: 2976.89 samples/s lr: 1.60e-04  
[09/23 06:17:08] lb.utils.events INFO:  eta: 4:09:26  iteration: 279799/375342  consumed_samples: 286515200  total_loss: 3.202  time: 0.3440 s/iter  data_time: 0.2210 s/iter total_throughput: 2976.89 samples/s lr: 1.60e-04  
[09/23 06:17:42] lb.utils.events INFO:  eta: 4:08:42  iteration: 279899/375342  consumed_samples: 286617600  total_loss: 3.202  time: 0.3440 s/iter  data_time: 0.2210 s/iter total_throughput: 2976.89 samples/s lr: 1.60e-04  
[09/23 06:18:16] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0279999
[09/23 06:18:16] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/23 06:18:16] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/23 06:18:21] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.1043 s/iter. Inference: 0.1641 s/iter. Eval: 0.0021 s/iter. Total: 0.2705 s/iter. ETA=0:00:10
[09/23 06:18:26] lb.evaluation.evaluator INFO: Inference done 28672/50000. Dataloading: 0.1248 s/iter. Inference: 0.1632 s/iter. Eval: 0.0020 s/iter. Total: 0.2901 s/iter. ETA=0:00:05
[09/23 06:18:31] lb.evaluation.evaluator INFO: Inference done 46080/50000. Dataloading: 0.1293 s/iter. Inference: 0.1626 s/iter. Eval: 0.0020 s/iter. Total: 0.2941 s/iter. ETA=0:00:00
[09/23 06:18:32] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/23 06:18:32] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.700771 (0.000254 s / iter per device, on 8 devices)
[09/23 06:18:32] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000143 s / iter per device, on 8 devices)
[09/23 06:18:32] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/23 06:18:32] lb.evaluation.utils INFO: copypaste: Acc@1=78.35600000000001
[09/23 06:18:32] lb.evaluation.utils INFO: copypaste: Acc@5=94.002
[09/23 06:18:32] lb.engine.hooks INFO: Not saving as latest eval score for Acc@1 is 78.35600, not better than best score 78.35800 @ iteration 274999.
[09/23 06:18:32] lb.utils.events INFO:  eta: 4:08:34  iteration: 279999/375342  consumed_samples: 286720000  total_loss: 3.194  time: 0.3440 s/iter  data_time: 0.2119 s/iter total_throughput: 2976.91 samples/s lr: 1.59e-04  
[09/23 06:19:04] lb.utils.events INFO:  eta: 4:08:35  iteration: 280099/375342  consumed_samples: 286822400  total_loss: 3.204  time: 0.3440 s/iter  data_time: 0.2149 s/iter total_throughput: 2976.97 samples/s lr: 1.59e-04  
[09/23 06:19:39] lb.utils.events INFO:  eta: 4:08:26  iteration: 280199/375342  consumed_samples: 286924800  total_loss: 3.209  time: 0.3440 s/iter  data_time: 0.2192 s/iter total_throughput: 2976.97 samples/s lr: 1.59e-04  
[09/23 06:20:13] lb.utils.events INFO:  eta: 4:08:14  iteration: 280299/375342  consumed_samples: 287027200  total_loss: 3.204  time: 0.3440 s/iter  data_time: 0.2198 s/iter total_throughput: 2976.96 samples/s lr: 1.59e-04  
[09/23 06:20:48] lb.utils.events INFO:  eta: 4:07:31  iteration: 280399/375342  consumed_samples: 287129600  total_loss: 3.179  time: 0.3440 s/iter  data_time: 0.2216 s/iter total_throughput: 2976.94 samples/s lr: 1.58e-04  
[09/23 06:21:23] lb.utils.events INFO:  eta: 4:07:09  iteration: 280499/375342  consumed_samples: 287232000  total_loss: 3.174  time: 0.3440 s/iter  data_time: 0.2161 s/iter total_throughput: 2976.92 samples/s lr: 1.58e-04  
[09/23 06:21:59] lb.utils.events INFO:  eta: 4:06:52  iteration: 280599/375342  consumed_samples: 287334400  total_loss: 3.17  time: 0.3440 s/iter  data_time: 0.2297 s/iter total_throughput: 2976.90 samples/s lr: 1.58e-04  
[09/23 06:22:34] lb.utils.events INFO:  eta: 4:06:24  iteration: 280699/375342  consumed_samples: 287436800  total_loss: 3.18  time: 0.3440 s/iter  data_time: 0.2301 s/iter total_throughput: 2976.87 samples/s lr: 1.57e-04  
[09/23 06:23:09] lb.utils.events INFO:  eta: 4:05:19  iteration: 280799/375342  consumed_samples: 287539200  total_loss: 3.192  time: 0.3440 s/iter  data_time: 0.2304 s/iter total_throughput: 2976.84 samples/s lr: 1.57e-04  
[09/23 06:23:44] lb.utils.events INFO:  eta: 4:05:42  iteration: 280899/375342  consumed_samples: 287641600  total_loss: 3.198  time: 0.3440 s/iter  data_time: 0.2175 s/iter total_throughput: 2976.83 samples/s lr: 1.57e-04  
[09/23 06:24:19] lb.utils.events INFO:  eta: 4:05:38  iteration: 280999/375342  consumed_samples: 287744000  total_loss: 3.193  time: 0.3440 s/iter  data_time: 0.2083 s/iter total_throughput: 2976.83 samples/s lr: 1.56e-04  
[09/23 06:24:53] lb.utils.events INFO:  eta: 4:05:03  iteration: 281099/375342  consumed_samples: 287846400  total_loss: 3.178  time: 0.3440 s/iter  data_time: 0.2136 s/iter total_throughput: 2976.81 samples/s lr: 1.56e-04  
[09/23 06:25:28] lb.utils.events INFO:  eta: 4:04:21  iteration: 281199/375342  consumed_samples: 287948800  total_loss: 3.178  time: 0.3440 s/iter  data_time: 0.2190 s/iter total_throughput: 2976.81 samples/s lr: 1.56e-04  
[09/23 06:26:03] lb.utils.events INFO:  eta: 4:05:10  iteration: 281299/375342  consumed_samples: 288051200  total_loss: 3.184  time: 0.3440 s/iter  data_time: 0.2219 s/iter total_throughput: 2976.79 samples/s lr: 1.56e-04  
[09/23 06:26:38] lb.utils.events INFO:  eta: 4:05:51  iteration: 281399/375342  consumed_samples: 288153600  total_loss: 3.197  time: 0.3440 s/iter  data_time: 0.2162 s/iter total_throughput: 2976.77 samples/s lr: 1.55e-04  
[09/23 06:27:14] lb.utils.events INFO:  eta: 4:04:55  iteration: 281499/375342  consumed_samples: 288256000  total_loss: 3.202  time: 0.3440 s/iter  data_time: 0.2213 s/iter total_throughput: 2976.74 samples/s lr: 1.55e-04  
[09/23 06:27:49] lb.utils.events INFO:  eta: 4:04:12  iteration: 281599/375342  consumed_samples: 288358400  total_loss: 3.178  time: 0.3440 s/iter  data_time: 0.2244 s/iter total_throughput: 2976.72 samples/s lr: 1.55e-04  
[09/23 06:28:23] lb.utils.events INFO:  eta: 4:04:06  iteration: 281699/375342  consumed_samples: 288460800  total_loss: 3.169  time: 0.3440 s/iter  data_time: 0.2150 s/iter total_throughput: 2976.71 samples/s lr: 1.54e-04  
[09/23 06:28:59] lb.utils.events INFO:  eta: 4:04:52  iteration: 281799/375342  consumed_samples: 288563200  total_loss: 3.178  time: 0.3440 s/iter  data_time: 0.2502 s/iter total_throughput: 2976.67 samples/s lr: 1.54e-04  
[09/23 06:29:34] lb.utils.events INFO:  eta: 4:03:31  iteration: 281899/375342  consumed_samples: 288665600  total_loss: 3.192  time: 0.3440 s/iter  data_time: 0.2207 s/iter total_throughput: 2976.66 samples/s lr: 1.54e-04  
[09/23 06:30:09] lb.utils.events INFO:  eta: 4:02:57  iteration: 281999/375342  consumed_samples: 288768000  total_loss: 3.184  time: 0.3440 s/iter  data_time: 0.2236 s/iter total_throughput: 2976.64 samples/s lr: 1.54e-04  
[09/23 06:30:43] lb.utils.events INFO:  eta: 4:02:44  iteration: 282099/375342  consumed_samples: 288870400  total_loss: 3.179  time: 0.3440 s/iter  data_time: 0.2193 s/iter total_throughput: 2976.64 samples/s lr: 1.53e-04  
[09/23 06:31:18] lb.utils.events INFO:  eta: 4:02:57  iteration: 282199/375342  consumed_samples: 288972800  total_loss: 3.186  time: 0.3440 s/iter  data_time: 0.2295 s/iter total_throughput: 2976.62 samples/s lr: 1.53e-04  
[09/23 06:31:53] lb.utils.events INFO:  eta: 4:01:46  iteration: 282299/375342  consumed_samples: 289075200  total_loss: 3.184  time: 0.3440 s/iter  data_time: 0.2228 s/iter total_throughput: 2976.60 samples/s lr: 1.53e-04  
[09/23 06:32:28] lb.utils.events INFO:  eta: 4:00:30  iteration: 282399/375342  consumed_samples: 289177600  total_loss: 3.199  time: 0.3440 s/iter  data_time: 0.2184 s/iter total_throughput: 2976.58 samples/s lr: 1.52e-04  
[09/23 06:33:03] lb.utils.events INFO:  eta: 4:00:38  iteration: 282499/375342  consumed_samples: 289280000  total_loss: 3.2  time: 0.3440 s/iter  data_time: 0.2299 s/iter total_throughput: 2976.56 samples/s lr: 1.52e-04  
[09/23 06:33:38] lb.utils.events INFO:  eta: 4:00:23  iteration: 282599/375342  consumed_samples: 289382400  total_loss: 3.18  time: 0.3440 s/iter  data_time: 0.2136 s/iter total_throughput: 2976.55 samples/s lr: 1.52e-04  
[09/23 06:34:13] lb.utils.events INFO:  eta: 3:59:58  iteration: 282699/375342  consumed_samples: 289484800  total_loss: 3.18  time: 0.3440 s/iter  data_time: 0.2107 s/iter total_throughput: 2976.54 samples/s lr: 1.52e-04  
[09/23 06:34:48] lb.utils.events INFO:  eta: 4:00:14  iteration: 282799/375342  consumed_samples: 289587200  total_loss: 3.188  time: 0.3440 s/iter  data_time: 0.2280 s/iter total_throughput: 2976.53 samples/s lr: 1.51e-04  
[09/23 06:35:22] lb.utils.events INFO:  eta: 3:59:39  iteration: 282899/375342  consumed_samples: 289689600  total_loss: 3.186  time: 0.3440 s/iter  data_time: 0.2225 s/iter total_throughput: 2976.52 samples/s lr: 1.51e-04  
[09/23 06:35:57] lb.utils.events INFO:  eta: 3:58:56  iteration: 282999/375342  consumed_samples: 289792000  total_loss: 3.177  time: 0.3440 s/iter  data_time: 0.2281 s/iter total_throughput: 2976.50 samples/s lr: 1.51e-04  
[09/23 06:36:32] lb.utils.events INFO:  eta: 3:58:27  iteration: 283099/375342  consumed_samples: 289894400  total_loss: 3.174  time: 0.3440 s/iter  data_time: 0.2238 s/iter total_throughput: 2976.48 samples/s lr: 1.50e-04  
[09/23 06:37:08] lb.utils.events INFO:  eta: 3:58:04  iteration: 283199/375342  consumed_samples: 289996800  total_loss: 3.162  time: 0.3440 s/iter  data_time: 0.2309 s/iter total_throughput: 2976.46 samples/s lr: 1.50e-04  
[09/23 06:37:42] lb.utils.events INFO:  eta: 3:57:56  iteration: 283299/375342  consumed_samples: 290099200  total_loss: 3.165  time: 0.3440 s/iter  data_time: 0.2205 s/iter total_throughput: 2976.45 samples/s lr: 1.50e-04  
[09/23 06:38:17] lb.utils.events INFO:  eta: 3:57:57  iteration: 283399/375342  consumed_samples: 290201600  total_loss: 3.204  time: 0.3440 s/iter  data_time: 0.2172 s/iter total_throughput: 2976.43 samples/s lr: 1.49e-04  
[09/23 06:38:52] lb.utils.events INFO:  eta: 3:57:53  iteration: 283499/375342  consumed_samples: 290304000  total_loss: 3.187  time: 0.3440 s/iter  data_time: 0.2207 s/iter total_throughput: 2976.42 samples/s lr: 1.49e-04  
[09/23 06:39:27] lb.utils.events INFO:  eta: 3:57:22  iteration: 283599/375342  consumed_samples: 290406400  total_loss: 3.169  time: 0.3440 s/iter  data_time: 0.2152 s/iter total_throughput: 2976.41 samples/s lr: 1.49e-04  
[09/23 06:40:01] lb.utils.events INFO:  eta: 3:57:22  iteration: 283699/375342  consumed_samples: 290508800  total_loss: 3.19  time: 0.3440 s/iter  data_time: 0.2180 s/iter total_throughput: 2976.40 samples/s lr: 1.49e-04  
[09/23 06:40:36] lb.utils.events INFO:  eta: 3:57:15  iteration: 283799/375342  consumed_samples: 290611200  total_loss: 3.194  time: 0.3440 s/iter  data_time: 0.2175 s/iter total_throughput: 2976.40 samples/s lr: 1.48e-04  
[09/23 06:41:11] lb.utils.events INFO:  eta: 3:56:57  iteration: 283899/375342  consumed_samples: 290713600  total_loss: 3.186  time: 0.3440 s/iter  data_time: 0.2149 s/iter total_throughput: 2976.37 samples/s lr: 1.48e-04  
[09/23 06:41:47] lb.utils.events INFO:  eta: 3:57:06  iteration: 283999/375342  consumed_samples: 290816000  total_loss: 3.197  time: 0.3440 s/iter  data_time: 0.2312 s/iter total_throughput: 2976.34 samples/s lr: 1.48e-04  
[09/23 06:42:22] lb.utils.events INFO:  eta: 3:57:18  iteration: 284099/375342  consumed_samples: 290918400  total_loss: 3.192  time: 0.3440 s/iter  data_time: 0.2253 s/iter total_throughput: 2976.32 samples/s lr: 1.47e-04  
[09/23 06:42:57] lb.utils.events INFO:  eta: 3:56:48  iteration: 284199/375342  consumed_samples: 291020800  total_loss: 3.174  time: 0.3441 s/iter  data_time: 0.2190 s/iter total_throughput: 2976.30 samples/s lr: 1.47e-04  
[09/23 06:43:32] lb.utils.events INFO:  eta: 3:56:22  iteration: 284299/375342  consumed_samples: 291123200  total_loss: 3.176  time: 0.3441 s/iter  data_time: 0.2352 s/iter total_throughput: 2976.28 samples/s lr: 1.47e-04  
[09/23 06:44:07] lb.utils.events INFO:  eta: 3:56:28  iteration: 284399/375342  consumed_samples: 291225600  total_loss: 3.175  time: 0.3441 s/iter  data_time: 0.2353 s/iter total_throughput: 2976.27 samples/s lr: 1.47e-04  
[09/23 06:44:42] lb.utils.events INFO:  eta: 3:55:39  iteration: 284499/375342  consumed_samples: 291328000  total_loss: 3.182  time: 0.3441 s/iter  data_time: 0.2199 s/iter total_throughput: 2976.24 samples/s lr: 1.46e-04  
[09/23 06:45:17] lb.utils.events INFO:  eta: 3:55:45  iteration: 284599/375342  consumed_samples: 291430400  total_loss: 3.166  time: 0.3441 s/iter  data_time: 0.2222 s/iter total_throughput: 2976.23 samples/s lr: 1.46e-04  
[09/23 06:45:52] lb.utils.events INFO:  eta: 3:55:18  iteration: 284699/375342  consumed_samples: 291532800  total_loss: 3.166  time: 0.3441 s/iter  data_time: 0.2177 s/iter total_throughput: 2976.22 samples/s lr: 1.46e-04  
[09/23 06:46:26] lb.utils.events INFO:  eta: 3:55:06  iteration: 284799/375342  consumed_samples: 291635200  total_loss: 3.195  time: 0.3441 s/iter  data_time: 0.2194 s/iter total_throughput: 2976.21 samples/s lr: 1.45e-04  
[09/23 06:47:01] lb.utils.events INFO:  eta: 3:54:53  iteration: 284899/375342  consumed_samples: 291737600  total_loss: 3.195  time: 0.3441 s/iter  data_time: 0.2113 s/iter total_throughput: 2976.20 samples/s lr: 1.45e-04  
[09/23 06:47:36] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0284999
[09/23 06:47:37] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/23 06:47:37] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/23 06:47:41] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0811 s/iter. Inference: 0.1619 s/iter. Eval: 0.0020 s/iter. Total: 0.2450 s/iter. ETA=0:00:09
[09/23 06:47:47] lb.evaluation.evaluator INFO: Inference done 29696/50000. Dataloading: 0.1309 s/iter. Inference: 0.1677 s/iter. Eval: 0.0020 s/iter. Total: 0.3006 s/iter. ETA=0:00:05
[09/23 06:47:52] lb.evaluation.evaluator INFO: Inference done 50000/50000. Dataloading: 0.1193 s/iter. Inference: 0.1644 s/iter. Eval: 0.0020 s/iter. Total: 0.2858 s/iter. ETA=0:00:00
[09/23 06:47:52] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/23 06:47:52] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.578605 (0.000252 s / iter per device, on 8 devices)
[09/23 06:47:52] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000145 s / iter per device, on 8 devices)
[09/23 06:47:52] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/23 06:47:52] lb.evaluation.utils INFO: copypaste: Acc@1=78.71000000000001
[09/23 06:47:52] lb.evaluation.utils INFO: copypaste: Acc@5=94.184
[09/23 06:47:52] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 78.71000, better than last best score 78.35800 @ iteration 274999.
[09/23 06:47:52] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/23 06:47:53] lb.utils.events INFO:  eta: 3:54:13  iteration: 284999/375342  consumed_samples: 291840000  total_loss: 3.191  time: 0.3441 s/iter  data_time: 0.2424 s/iter total_throughput: 2976.18 samples/s lr: 1.45e-04  
[09/23 06:48:26] lb.utils.events INFO:  eta: 3:54:36  iteration: 285099/375342  consumed_samples: 291942400  total_loss: 3.186  time: 0.3441 s/iter  data_time: 0.2246 s/iter total_throughput: 2976.22 samples/s lr: 1.45e-04  
[09/23 06:49:01] lb.utils.events INFO:  eta: 3:54:31  iteration: 285199/375342  consumed_samples: 292044800  total_loss: 3.179  time: 0.3441 s/iter  data_time: 0.2298 s/iter total_throughput: 2976.20 samples/s lr: 1.44e-04  
[09/23 06:49:36] lb.utils.events INFO:  eta: 3:54:30  iteration: 285299/375342  consumed_samples: 292147200  total_loss: 3.173  time: 0.3441 s/iter  data_time: 0.2220 s/iter total_throughput: 2976.18 samples/s lr: 1.44e-04  
[09/23 06:50:11] lb.utils.events INFO:  eta: 3:54:10  iteration: 285399/375342  consumed_samples: 292249600  total_loss: 3.164  time: 0.3441 s/iter  data_time: 0.2226 s/iter total_throughput: 2976.17 samples/s lr: 1.44e-04  
[09/23 06:50:46] lb.utils.events INFO:  eta: 3:54:10  iteration: 285499/375342  consumed_samples: 292352000  total_loss: 3.182  time: 0.3441 s/iter  data_time: 0.2091 s/iter total_throughput: 2976.16 samples/s lr: 1.43e-04  
[09/23 06:51:21] lb.utils.events INFO:  eta: 3:53:47  iteration: 285599/375342  consumed_samples: 292454400  total_loss: 3.19  time: 0.3441 s/iter  data_time: 0.2204 s/iter total_throughput: 2976.14 samples/s lr: 1.43e-04  
[09/23 06:51:55] lb.utils.events INFO:  eta: 3:53:47  iteration: 285699/375342  consumed_samples: 292556800  total_loss: 3.178  time: 0.3441 s/iter  data_time: 0.2156 s/iter total_throughput: 2976.13 samples/s lr: 1.43e-04  
[09/23 06:52:30] lb.utils.events INFO:  eta: 3:53:43  iteration: 285799/375342  consumed_samples: 292659200  total_loss: 3.168  time: 0.3441 s/iter  data_time: 0.2184 s/iter total_throughput: 2976.13 samples/s lr: 1.43e-04  
[09/23 06:53:05] lb.utils.events INFO:  eta: 3:53:04  iteration: 285899/375342  consumed_samples: 292761600  total_loss: 3.177  time: 0.3441 s/iter  data_time: 0.2281 s/iter total_throughput: 2976.11 samples/s lr: 1.42e-04  
[09/23 06:53:40] lb.utils.events INFO:  eta: 3:52:27  iteration: 285999/375342  consumed_samples: 292864000  total_loss: 3.185  time: 0.3441 s/iter  data_time: 0.2226 s/iter total_throughput: 2976.10 samples/s lr: 1.42e-04  
[09/23 06:54:14] lb.utils.events INFO:  eta: 3:51:37  iteration: 286099/375342  consumed_samples: 292966400  total_loss: 3.164  time: 0.3441 s/iter  data_time: 0.2168 s/iter total_throughput: 2976.09 samples/s lr: 1.42e-04  
[09/23 06:54:49] lb.utils.events INFO:  eta: 3:51:16  iteration: 286199/375342  consumed_samples: 293068800  total_loss: 3.159  time: 0.3441 s/iter  data_time: 0.2329 s/iter total_throughput: 2976.07 samples/s lr: 1.42e-04  
[09/23 06:55:25] lb.utils.events INFO:  eta: 3:50:43  iteration: 286299/375342  consumed_samples: 293171200  total_loss: 3.177  time: 0.3441 s/iter  data_time: 0.2269 s/iter total_throughput: 2976.04 samples/s lr: 1.41e-04  
[09/23 06:55:59] lb.utils.events INFO:  eta: 3:50:35  iteration: 286399/375342  consumed_samples: 293273600  total_loss: 3.182  time: 0.3441 s/iter  data_time: 0.2185 s/iter total_throughput: 2976.04 samples/s lr: 1.41e-04  
[09/23 06:56:34] lb.utils.events INFO:  eta: 3:50:42  iteration: 286499/375342  consumed_samples: 293376000  total_loss: 3.166  time: 0.3441 s/iter  data_time: 0.2160 s/iter total_throughput: 2976.04 samples/s lr: 1.41e-04  
[09/23 06:57:09] lb.utils.events INFO:  eta: 3:50:32  iteration: 286599/375342  consumed_samples: 293478400  total_loss: 3.148  time: 0.3441 s/iter  data_time: 0.2291 s/iter total_throughput: 2976.02 samples/s lr: 1.40e-04  
[09/23 06:57:44] lb.utils.events INFO:  eta: 3:50:06  iteration: 286699/375342  consumed_samples: 293580800  total_loss: 3.146  time: 0.3441 s/iter  data_time: 0.2296 s/iter total_throughput: 2976.01 samples/s lr: 1.40e-04  
[09/23 06:58:19] lb.utils.events INFO:  eta: 3:49:39  iteration: 286799/375342  consumed_samples: 293683200  total_loss: 3.16  time: 0.3441 s/iter  data_time: 0.2317 s/iter total_throughput: 2976.00 samples/s lr: 1.40e-04  
[09/23 06:58:53] lb.utils.events INFO:  eta: 3:49:30  iteration: 286899/375342  consumed_samples: 293785600  total_loss: 3.167  time: 0.3441 s/iter  data_time: 0.2161 s/iter total_throughput: 2975.98 samples/s lr: 1.40e-04  
[09/23 06:59:28] lb.utils.events INFO:  eta: 3:49:55  iteration: 286999/375342  consumed_samples: 293888000  total_loss: 3.171  time: 0.3441 s/iter  data_time: 0.2138 s/iter total_throughput: 2975.98 samples/s lr: 1.39e-04  
[09/23 07:00:03] lb.utils.events INFO:  eta: 3:49:47  iteration: 287099/375342  consumed_samples: 293990400  total_loss: 3.152  time: 0.3441 s/iter  data_time: 0.2222 s/iter total_throughput: 2975.97 samples/s lr: 1.39e-04  
[09/23 07:00:38] lb.utils.events INFO:  eta: 3:49:37  iteration: 287199/375342  consumed_samples: 294092800  total_loss: 3.157  time: 0.3441 s/iter  data_time: 0.2211 s/iter total_throughput: 2975.95 samples/s lr: 1.39e-04  
[09/23 07:01:13] lb.utils.events INFO:  eta: 3:49:37  iteration: 287299/375342  consumed_samples: 294195200  total_loss: 3.178  time: 0.3441 s/iter  data_time: 0.2164 s/iter total_throughput: 2975.93 samples/s lr: 1.38e-04  
[09/23 07:01:48] lb.utils.events INFO:  eta: 3:49:05  iteration: 287399/375342  consumed_samples: 294297600  total_loss: 3.166  time: 0.3441 s/iter  data_time: 0.2197 s/iter total_throughput: 2975.91 samples/s lr: 1.38e-04  
[09/23 07:02:23] lb.utils.events INFO:  eta: 3:48:42  iteration: 287499/375342  consumed_samples: 294400000  total_loss: 3.151  time: 0.3441 s/iter  data_time: 0.2144 s/iter total_throughput: 2975.89 samples/s lr: 1.38e-04  
[09/23 07:02:58] lb.utils.events INFO:  eta: 3:48:49  iteration: 287599/375342  consumed_samples: 294502400  total_loss: 3.18  time: 0.3441 s/iter  data_time: 0.2194 s/iter total_throughput: 2975.87 samples/s lr: 1.38e-04  
[09/23 07:03:33] lb.utils.events INFO:  eta: 3:48:18  iteration: 287699/375342  consumed_samples: 294604800  total_loss: 3.185  time: 0.3441 s/iter  data_time: 0.2219 s/iter total_throughput: 2975.86 samples/s lr: 1.37e-04  
[09/23 07:04:08] lb.utils.events INFO:  eta: 3:48:03  iteration: 287799/375342  consumed_samples: 294707200  total_loss: 3.172  time: 0.3441 s/iter  data_time: 0.2242 s/iter total_throughput: 2975.84 samples/s lr: 1.37e-04  
[09/23 07:04:43] lb.utils.events INFO:  eta: 3:47:33  iteration: 287899/375342  consumed_samples: 294809600  total_loss: 3.136  time: 0.3441 s/iter  data_time: 0.2310 s/iter total_throughput: 2975.83 samples/s lr: 1.37e-04  
[09/23 07:05:18] lb.utils.events INFO:  eta: 3:46:51  iteration: 287999/375342  consumed_samples: 294912000  total_loss: 3.161  time: 0.3441 s/iter  data_time: 0.2190 s/iter total_throughput: 2975.81 samples/s lr: 1.36e-04  
[09/23 07:05:53] lb.utils.events INFO:  eta: 3:46:34  iteration: 288099/375342  consumed_samples: 295014400  total_loss: 3.181  time: 0.3441 s/iter  data_time: 0.2219 s/iter total_throughput: 2975.78 samples/s lr: 1.36e-04  
[09/23 07:06:28] lb.utils.events INFO:  eta: 3:46:28  iteration: 288199/375342  consumed_samples: 295116800  total_loss: 3.174  time: 0.3441 s/iter  data_time: 0.2354 s/iter total_throughput: 2975.77 samples/s lr: 1.36e-04  
[09/23 07:07:02] lb.utils.events INFO:  eta: 3:46:21  iteration: 288299/375342  consumed_samples: 295219200  total_loss: 3.167  time: 0.3441 s/iter  data_time: 0.2186 s/iter total_throughput: 2975.77 samples/s lr: 1.36e-04  
[09/23 07:07:37] lb.utils.events INFO:  eta: 3:45:51  iteration: 288399/375342  consumed_samples: 295321600  total_loss: 3.171  time: 0.3441 s/iter  data_time: 0.2162 s/iter total_throughput: 2975.75 samples/s lr: 1.35e-04  
[09/23 07:08:12] lb.utils.events INFO:  eta: 3:45:32  iteration: 288499/375342  consumed_samples: 295424000  total_loss: 3.153  time: 0.3441 s/iter  data_time: 0.2198 s/iter total_throughput: 2975.73 samples/s lr: 1.35e-04  
[09/23 07:08:47] lb.utils.events INFO:  eta: 3:45:04  iteration: 288599/375342  consumed_samples: 295526400  total_loss: 3.146  time: 0.3441 s/iter  data_time: 0.2188 s/iter total_throughput: 2975.72 samples/s lr: 1.35e-04  
[09/23 07:09:22] lb.utils.events INFO:  eta: 3:44:44  iteration: 288699/375342  consumed_samples: 295628800  total_loss: 3.151  time: 0.3441 s/iter  data_time: 0.2207 s/iter total_throughput: 2975.71 samples/s lr: 1.35e-04  
[09/23 07:09:57] lb.utils.events INFO:  eta: 3:44:36  iteration: 288799/375342  consumed_samples: 295731200  total_loss: 3.155  time: 0.3441 s/iter  data_time: 0.2144 s/iter total_throughput: 2975.69 samples/s lr: 1.34e-04  
[09/23 07:10:32] lb.utils.events INFO:  eta: 3:44:29  iteration: 288899/375342  consumed_samples: 295833600  total_loss: 3.151  time: 0.3441 s/iter  data_time: 0.2358 s/iter total_throughput: 2975.68 samples/s lr: 1.34e-04  
[09/23 07:11:06] lb.utils.events INFO:  eta: 3:44:27  iteration: 288999/375342  consumed_samples: 295936000  total_loss: 3.164  time: 0.3441 s/iter  data_time: 0.2204 s/iter total_throughput: 2975.69 samples/s lr: 1.34e-04  
[09/23 07:11:40] lb.utils.events INFO:  eta: 3:44:11  iteration: 289099/375342  consumed_samples: 296038400  total_loss: 3.169  time: 0.3441 s/iter  data_time: 0.2137 s/iter total_throughput: 2975.69 samples/s lr: 1.33e-04  
[09/23 07:12:15] lb.utils.events INFO:  eta: 3:43:48  iteration: 289199/375342  consumed_samples: 296140800  total_loss: 3.135  time: 0.3441 s/iter  data_time: 0.2334 s/iter total_throughput: 2975.67 samples/s lr: 1.33e-04  
[09/23 07:12:50] lb.utils.events INFO:  eta: 3:43:26  iteration: 289299/375342  consumed_samples: 296243200  total_loss: 3.152  time: 0.3441 s/iter  data_time: 0.2143 s/iter total_throughput: 2975.65 samples/s lr: 1.33e-04  
[09/23 07:13:25] lb.utils.events INFO:  eta: 3:43:22  iteration: 289399/375342  consumed_samples: 296345600  total_loss: 3.157  time: 0.3441 s/iter  data_time: 0.2157 s/iter total_throughput: 2975.65 samples/s lr: 1.33e-04  
[09/23 07:14:00] lb.utils.events INFO:  eta: 3:43:18  iteration: 289499/375342  consumed_samples: 296448000  total_loss: 3.146  time: 0.3441 s/iter  data_time: 0.2091 s/iter total_throughput: 2975.64 samples/s lr: 1.32e-04  
[09/23 07:14:34] lb.utils.events INFO:  eta: 3:43:26  iteration: 289599/375342  consumed_samples: 296550400  total_loss: 3.137  time: 0.3441 s/iter  data_time: 0.2244 s/iter total_throughput: 2975.63 samples/s lr: 1.32e-04  
[09/23 07:15:09] lb.utils.events INFO:  eta: 3:43:33  iteration: 289699/375342  consumed_samples: 296652800  total_loss: 3.141  time: 0.3441 s/iter  data_time: 0.2135 s/iter total_throughput: 2975.64 samples/s lr: 1.32e-04  
[09/23 07:15:43] lb.utils.events INFO:  eta: 3:42:27  iteration: 289799/375342  consumed_samples: 296755200  total_loss: 3.155  time: 0.3441 s/iter  data_time: 0.2083 s/iter total_throughput: 2975.64 samples/s lr: 1.32e-04  
[09/23 07:16:18] lb.utils.events INFO:  eta: 3:41:45  iteration: 289899/375342  consumed_samples: 296857600  total_loss: 3.147  time: 0.3441 s/iter  data_time: 0.2206 s/iter total_throughput: 2975.62 samples/s lr: 1.31e-04  
[09/23 07:16:53] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0289999
[09/23 07:16:54] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/23 07:16:54] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/23 07:16:58] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0969 s/iter. Inference: 0.1630 s/iter. Eval: 0.0022 s/iter. Total: 0.2621 s/iter. ETA=0:00:09
[09/23 07:17:04] lb.evaluation.evaluator INFO: Inference done 29696/50000. Dataloading: 0.1168 s/iter. Inference: 0.1763 s/iter. Eval: 0.0022 s/iter. Total: 0.2954 s/iter. ETA=0:00:05
[09/23 07:17:09] lb.evaluation.evaluator INFO: Inference done 48128/50000. Dataloading: 0.1216 s/iter. Inference: 0.1697 s/iter. Eval: 0.0022 s/iter. Total: 0.2936 s/iter. ETA=0:00:00
[09/23 07:17:09] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/23 07:17:09] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.680098 (0.000254 s / iter per device, on 8 devices)
[09/23 07:17:09] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000149 s / iter per device, on 8 devices)
[09/23 07:17:09] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/23 07:17:09] lb.evaluation.utils INFO: copypaste: Acc@1=78.922
[09/23 07:17:09] lb.evaluation.utils INFO: copypaste: Acc@5=94.192
[09/23 07:17:09] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 78.92200, better than last best score 78.71000 @ iteration 284999.
[09/23 07:17:09] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/23 07:17:10] lb.utils.events INFO:  eta: 3:40:56  iteration: 289999/375342  consumed_samples: 296960000  total_loss: 3.146  time: 0.3441 s/iter  data_time: 0.2307 s/iter total_throughput: 2975.60 samples/s lr: 1.31e-04  
[09/23 07:17:43] lb.utils.events INFO:  eta: 3:41:09  iteration: 290099/375342  consumed_samples: 297062400  total_loss: 3.149  time: 0.3441 s/iter  data_time: 0.2261 s/iter total_throughput: 2975.63 samples/s lr: 1.31e-04  
[09/23 07:18:18] lb.utils.events INFO:  eta: 3:40:58  iteration: 290199/375342  consumed_samples: 297164800  total_loss: 3.137  time: 0.3441 s/iter  data_time: 0.2123 s/iter total_throughput: 2975.63 samples/s lr: 1.30e-04  
[09/23 07:18:52] lb.utils.events INFO:  eta: 3:41:16  iteration: 290299/375342  consumed_samples: 297267200  total_loss: 3.119  time: 0.3441 s/iter  data_time: 0.2256 s/iter total_throughput: 2975.63 samples/s lr: 1.30e-04  
[09/23 07:19:27] lb.utils.events INFO:  eta: 3:40:37  iteration: 290399/375342  consumed_samples: 297369600  total_loss: 3.124  time: 0.3441 s/iter  data_time: 0.2148 s/iter total_throughput: 2975.62 samples/s lr: 1.30e-04  
[09/23 07:20:02] lb.utils.events INFO:  eta: 3:39:56  iteration: 290499/375342  consumed_samples: 297472000  total_loss: 3.155  time: 0.3441 s/iter  data_time: 0.2168 s/iter total_throughput: 2975.60 samples/s lr: 1.30e-04  
[09/23 07:20:37] lb.utils.events INFO:  eta: 3:39:40  iteration: 290599/375342  consumed_samples: 297574400  total_loss: 3.155  time: 0.3441 s/iter  data_time: 0.2171 s/iter total_throughput: 2975.58 samples/s lr: 1.29e-04  
[09/23 07:21:12] lb.utils.events INFO:  eta: 3:39:10  iteration: 290699/375342  consumed_samples: 297676800  total_loss: 3.144  time: 0.3441 s/iter  data_time: 0.2144 s/iter total_throughput: 2975.57 samples/s lr: 1.29e-04  
[09/23 07:21:47] lb.utils.events INFO:  eta: 3:39:47  iteration: 290799/375342  consumed_samples: 297779200  total_loss: 3.142  time: 0.3441 s/iter  data_time: 0.2172 s/iter total_throughput: 2975.56 samples/s lr: 1.29e-04  
[09/23 07:22:21] lb.utils.events INFO:  eta: 3:39:21  iteration: 290899/375342  consumed_samples: 297881600  total_loss: 3.157  time: 0.3441 s/iter  data_time: 0.2177 s/iter total_throughput: 2975.56 samples/s lr: 1.29e-04  
[09/23 07:22:56] lb.utils.events INFO:  eta: 3:39:56  iteration: 290999/375342  consumed_samples: 297984000  total_loss: 3.156  time: 0.3441 s/iter  data_time: 0.2192 s/iter total_throughput: 2975.56 samples/s lr: 1.28e-04  
[09/23 07:23:31] lb.utils.events INFO:  eta: 3:38:44  iteration: 291099/375342  consumed_samples: 298086400  total_loss: 3.155  time: 0.3441 s/iter  data_time: 0.2146 s/iter total_throughput: 2975.54 samples/s lr: 1.28e-04  
[09/23 07:24:06] lb.utils.events INFO:  eta: 3:37:57  iteration: 291199/375342  consumed_samples: 298188800  total_loss: 3.158  time: 0.3441 s/iter  data_time: 0.2314 s/iter total_throughput: 2975.52 samples/s lr: 1.28e-04  
[09/23 07:24:40] lb.utils.events INFO:  eta: 3:37:22  iteration: 291299/375342  consumed_samples: 298291200  total_loss: 3.163  time: 0.3441 s/iter  data_time: 0.2230 s/iter total_throughput: 2975.52 samples/s lr: 1.28e-04  
[09/23 07:25:15] lb.utils.events INFO:  eta: 3:37:12  iteration: 291399/375342  consumed_samples: 298393600  total_loss: 3.154  time: 0.3441 s/iter  data_time: 0.2224 s/iter total_throughput: 2975.50 samples/s lr: 1.27e-04  
[09/23 07:25:50] lb.utils.events INFO:  eta: 3:37:42  iteration: 291499/375342  consumed_samples: 298496000  total_loss: 3.151  time: 0.3441 s/iter  data_time: 0.2203 s/iter total_throughput: 2975.50 samples/s lr: 1.27e-04  
[09/23 07:26:24] lb.utils.events INFO:  eta: 3:37:48  iteration: 291599/375342  consumed_samples: 298598400  total_loss: 3.157  time: 0.3441 s/iter  data_time: 0.2240 s/iter total_throughput: 2975.49 samples/s lr: 1.27e-04  
[09/23 07:26:59] lb.utils.events INFO:  eta: 3:37:53  iteration: 291699/375342  consumed_samples: 298700800  total_loss: 3.159  time: 0.3441 s/iter  data_time: 0.2161 s/iter total_throughput: 2975.49 samples/s lr: 1.26e-04  
[09/23 07:27:33] lb.utils.events INFO:  eta: 3:37:12  iteration: 291799/375342  consumed_samples: 298803200  total_loss: 3.155  time: 0.3441 s/iter  data_time: 0.2207 s/iter total_throughput: 2975.49 samples/s lr: 1.26e-04  
[09/23 07:28:08] lb.utils.events INFO:  eta: 3:37:02  iteration: 291899/375342  consumed_samples: 298905600  total_loss: 3.137  time: 0.3441 s/iter  data_time: 0.2151 s/iter total_throughput: 2975.49 samples/s lr: 1.26e-04  
[09/23 07:28:42] lb.utils.events INFO:  eta: 3:37:00  iteration: 291999/375342  consumed_samples: 299008000  total_loss: 3.132  time: 0.3441 s/iter  data_time: 0.2014 s/iter total_throughput: 2975.49 samples/s lr: 1.26e-04  
[09/23 07:29:17] lb.utils.events INFO:  eta: 3:36:41  iteration: 292099/375342  consumed_samples: 299110400  total_loss: 3.152  time: 0.3441 s/iter  data_time: 0.2235 s/iter total_throughput: 2975.47 samples/s lr: 1.25e-04  
[09/23 07:29:52] lb.utils.events INFO:  eta: 3:36:34  iteration: 292199/375342  consumed_samples: 299212800  total_loss: 3.143  time: 0.3441 s/iter  data_time: 0.2094 s/iter total_throughput: 2975.46 samples/s lr: 1.25e-04  
[09/23 07:30:26] lb.utils.events INFO:  eta: 3:36:52  iteration: 292299/375342  consumed_samples: 299315200  total_loss: 3.135  time: 0.3441 s/iter  data_time: 0.2138 s/iter total_throughput: 2975.46 samples/s lr: 1.25e-04  
[09/23 07:31:00] lb.utils.events INFO:  eta: 3:36:46  iteration: 292399/375342  consumed_samples: 299417600  total_loss: 3.146  time: 0.3441 s/iter  data_time: 0.2136 s/iter total_throughput: 2975.48 samples/s lr: 1.25e-04  
[09/23 07:31:35] lb.utils.events INFO:  eta: 3:36:03  iteration: 292499/375342  consumed_samples: 299520000  total_loss: 3.148  time: 0.3441 s/iter  data_time: 0.2221 s/iter total_throughput: 2975.47 samples/s lr: 1.24e-04  
[09/23 07:32:10] lb.utils.events INFO:  eta: 3:35:45  iteration: 292599/375342  consumed_samples: 299622400  total_loss: 3.148  time: 0.3441 s/iter  data_time: 0.2291 s/iter total_throughput: 2975.46 samples/s lr: 1.24e-04  
[09/23 07:32:44] lb.utils.events INFO:  eta: 3:35:06  iteration: 292699/375342  consumed_samples: 299724800  total_loss: 3.145  time: 0.3441 s/iter  data_time: 0.2149 s/iter total_throughput: 2975.45 samples/s lr: 1.24e-04  
[09/23 07:33:18] lb.utils.events INFO:  eta: 3:34:55  iteration: 292799/375342  consumed_samples: 299827200  total_loss: 3.146  time: 0.3441 s/iter  data_time: 0.2191 s/iter total_throughput: 2975.46 samples/s lr: 1.24e-04  
[09/23 07:33:53] lb.utils.events INFO:  eta: 3:34:48  iteration: 292899/375342  consumed_samples: 299929600  total_loss: 3.15  time: 0.3441 s/iter  data_time: 0.2237 s/iter total_throughput: 2975.46 samples/s lr: 1.23e-04  
[09/23 07:34:28] lb.utils.events INFO:  eta: 3:34:15  iteration: 292999/375342  consumed_samples: 300032000  total_loss: 3.15  time: 0.3441 s/iter  data_time: 0.2207 s/iter total_throughput: 2975.45 samples/s lr: 1.23e-04  
[09/23 07:35:02] lb.utils.events INFO:  eta: 3:34:25  iteration: 293099/375342  consumed_samples: 300134400  total_loss: 3.155  time: 0.3441 s/iter  data_time: 0.2125 s/iter total_throughput: 2975.45 samples/s lr: 1.23e-04  
[09/23 07:35:37] lb.utils.events INFO:  eta: 3:34:01  iteration: 293199/375342  consumed_samples: 300236800  total_loss: 3.14  time: 0.3442 s/iter  data_time: 0.2247 s/iter total_throughput: 2975.44 samples/s lr: 1.22e-04  
[09/23 07:36:11] lb.utils.events INFO:  eta: 3:33:23  iteration: 293299/375342  consumed_samples: 300339200  total_loss: 3.141  time: 0.3441 s/iter  data_time: 0.2071 s/iter total_throughput: 2975.45 samples/s lr: 1.22e-04  
[09/23 07:36:45] lb.utils.events INFO:  eta: 3:32:46  iteration: 293399/375342  consumed_samples: 300441600  total_loss: 3.142  time: 0.3441 s/iter  data_time: 0.2132 s/iter total_throughput: 2975.46 samples/s lr: 1.22e-04  
[09/23 07:37:19] lb.utils.events INFO:  eta: 3:32:53  iteration: 293499/375342  consumed_samples: 300544000  total_loss: 3.136  time: 0.3441 s/iter  data_time: 0.2066 s/iter total_throughput: 2975.47 samples/s lr: 1.22e-04  
[09/23 07:37:53] lb.utils.events INFO:  eta: 3:32:54  iteration: 293599/375342  consumed_samples: 300646400  total_loss: 3.142  time: 0.3441 s/iter  data_time: 0.2182 s/iter total_throughput: 2975.48 samples/s lr: 1.21e-04  
[09/23 07:38:27] lb.utils.events INFO:  eta: 3:32:45  iteration: 293699/375342  consumed_samples: 300748800  total_loss: 3.131  time: 0.3441 s/iter  data_time: 0.2110 s/iter total_throughput: 2975.50 samples/s lr: 1.21e-04  
[09/23 07:39:01] lb.utils.events INFO:  eta: 3:32:34  iteration: 293799/375342  consumed_samples: 300851200  total_loss: 3.125  time: 0.3441 s/iter  data_time: 0.2168 s/iter total_throughput: 2975.51 samples/s lr: 1.21e-04  
[09/23 07:39:35] lb.utils.events INFO:  eta: 3:32:20  iteration: 293899/375342  consumed_samples: 300953600  total_loss: 3.137  time: 0.3441 s/iter  data_time: 0.2181 s/iter total_throughput: 2975.52 samples/s lr: 1.21e-04  
[09/23 07:40:10] lb.utils.events INFO:  eta: 3:32:03  iteration: 293999/375342  consumed_samples: 301056000  total_loss: 3.165  time: 0.3441 s/iter  data_time: 0.2179 s/iter total_throughput: 2975.51 samples/s lr: 1.20e-04  
[09/23 07:40:44] lb.utils.events INFO:  eta: 3:31:22  iteration: 294099/375342  consumed_samples: 301158400  total_loss: 3.161  time: 0.3441 s/iter  data_time: 0.2255 s/iter total_throughput: 2975.50 samples/s lr: 1.20e-04  
[09/23 07:41:19] lb.utils.events INFO:  eta: 3:31:09  iteration: 294199/375342  consumed_samples: 301260800  total_loss: 3.136  time: 0.3441 s/iter  data_time: 0.2166 s/iter total_throughput: 2975.50 samples/s lr: 1.20e-04  
[09/23 07:41:54] lb.utils.events INFO:  eta: 3:30:59  iteration: 294299/375342  consumed_samples: 301363200  total_loss: 3.125  time: 0.3441 s/iter  data_time: 0.2028 s/iter total_throughput: 2975.50 samples/s lr: 1.20e-04  
[09/23 07:42:29] lb.utils.events INFO:  eta: 3:30:31  iteration: 294399/375342  consumed_samples: 301465600  total_loss: 3.155  time: 0.3441 s/iter  data_time: 0.2233 s/iter total_throughput: 2975.48 samples/s lr: 1.19e-04  
[09/23 07:43:04] lb.utils.events INFO:  eta: 3:29:51  iteration: 294499/375342  consumed_samples: 301568000  total_loss: 3.156  time: 0.3441 s/iter  data_time: 0.2209 s/iter total_throughput: 2975.46 samples/s lr: 1.19e-04  
[09/23 07:43:39] lb.utils.events INFO:  eta: 3:29:19  iteration: 294599/375342  consumed_samples: 301670400  total_loss: 3.127  time: 0.3442 s/iter  data_time: 0.2298 s/iter total_throughput: 2975.43 samples/s lr: 1.19e-04  
[09/23 07:44:14] lb.utils.events INFO:  eta: 3:28:18  iteration: 294699/375342  consumed_samples: 301772800  total_loss: 3.116  time: 0.3442 s/iter  data_time: 0.2300 s/iter total_throughput: 2975.41 samples/s lr: 1.19e-04  
[09/23 07:44:50] lb.utils.events INFO:  eta: 3:27:14  iteration: 294799/375342  consumed_samples: 301875200  total_loss: 3.112  time: 0.3442 s/iter  data_time: 0.2418 s/iter total_throughput: 2975.39 samples/s lr: 1.18e-04  
[09/23 07:45:25] lb.utils.events INFO:  eta: 3:26:56  iteration: 294899/375342  consumed_samples: 301977600  total_loss: 3.133  time: 0.3442 s/iter  data_time: 0.2352 s/iter total_throughput: 2975.36 samples/s lr: 1.18e-04  
[09/23 07:46:00] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0294999
[09/23 07:46:01] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/23 07:46:01] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/23 07:46:05] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0993 s/iter. Inference: 0.1637 s/iter. Eval: 0.0023 s/iter. Total: 0.2653 s/iter. ETA=0:00:09
[09/23 07:46:10] lb.evaluation.evaluator INFO: Inference done 29696/50000. Dataloading: 0.1177 s/iter. Inference: 0.1752 s/iter. Eval: 0.0021 s/iter. Total: 0.2950 s/iter. ETA=0:00:05
[09/23 07:46:16] lb.evaluation.evaluator INFO: Inference done 48128/50000. Dataloading: 0.1192 s/iter. Inference: 0.1685 s/iter. Eval: 0.0021 s/iter. Total: 0.2898 s/iter. ETA=0:00:00
[09/23 07:46:16] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/23 07:46:16] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.534134 (0.000251 s / iter per device, on 8 devices)
[09/23 07:46:16] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000148 s / iter per device, on 8 devices)
[09/23 07:46:16] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/23 07:46:16] lb.evaluation.utils INFO: copypaste: Acc@1=78.9
[09/23 07:46:16] lb.evaluation.utils INFO: copypaste: Acc@5=94.25
[09/23 07:46:16] lb.engine.hooks INFO: Not saving as latest eval score for Acc@1 is 78.90000, not better than best score 78.92200 @ iteration 289999.
[09/23 07:46:16] lb.utils.events INFO:  eta: 3:26:43  iteration: 294999/375342  consumed_samples: 302080000  total_loss: 3.141  time: 0.3442 s/iter  data_time: 0.2157 s/iter total_throughput: 2975.33 samples/s lr: 1.18e-04  
[09/23 07:46:49] lb.utils.events INFO:  eta: 3:27:10  iteration: 295099/375342  consumed_samples: 302182400  total_loss: 3.127  time: 0.3442 s/iter  data_time: 0.2263 s/iter total_throughput: 2975.38 samples/s lr: 1.18e-04  
[09/23 07:47:24] lb.utils.events INFO:  eta: 3:26:45  iteration: 295199/375342  consumed_samples: 302284800  total_loss: 3.149  time: 0.3442 s/iter  data_time: 0.2157 s/iter total_throughput: 2975.36 samples/s lr: 1.17e-04  
[09/23 07:47:59] lb.utils.events INFO:  eta: 3:26:15  iteration: 295299/375342  consumed_samples: 302387200  total_loss: 3.157  time: 0.3442 s/iter  data_time: 0.2403 s/iter total_throughput: 2975.33 samples/s lr: 1.17e-04  
[09/23 07:48:34] lb.utils.events INFO:  eta: 3:26:22  iteration: 295399/375342  consumed_samples: 302489600  total_loss: 3.138  time: 0.3442 s/iter  data_time: 0.2187 s/iter total_throughput: 2975.31 samples/s lr: 1.17e-04  
[09/23 07:49:09] lb.utils.events INFO:  eta: 3:27:03  iteration: 295499/375342  consumed_samples: 302592000  total_loss: 3.133  time: 0.3442 s/iter  data_time: 0.2090 s/iter total_throughput: 2975.30 samples/s lr: 1.16e-04  
[09/23 07:49:44] lb.utils.events INFO:  eta: 3:27:01  iteration: 295599/375342  consumed_samples: 302694400  total_loss: 3.114  time: 0.3442 s/iter  data_time: 0.2242 s/iter total_throughput: 2975.28 samples/s lr: 1.16e-04  
[09/23 07:50:19] lb.utils.events INFO:  eta: 3:26:44  iteration: 295699/375342  consumed_samples: 302796800  total_loss: 3.102  time: 0.3442 s/iter  data_time: 0.2260 s/iter total_throughput: 2975.26 samples/s lr: 1.16e-04  
[09/23 07:50:54] lb.utils.events INFO:  eta: 3:26:31  iteration: 295799/375342  consumed_samples: 302899200  total_loss: 3.099  time: 0.3442 s/iter  data_time: 0.2349 s/iter total_throughput: 2975.25 samples/s lr: 1.16e-04  
[09/23 07:51:29] lb.utils.events INFO:  eta: 3:26:39  iteration: 295899/375342  consumed_samples: 303001600  total_loss: 3.116  time: 0.3442 s/iter  data_time: 0.2236 s/iter total_throughput: 2975.23 samples/s lr: 1.15e-04  
[09/23 07:52:04] lb.utils.events INFO:  eta: 3:25:54  iteration: 295999/375342  consumed_samples: 303104000  total_loss: 3.134  time: 0.3442 s/iter  data_time: 0.2194 s/iter total_throughput: 2975.21 samples/s lr: 1.15e-04  
[09/23 07:52:39] lb.utils.events INFO:  eta: 3:25:02  iteration: 296099/375342  consumed_samples: 303206400  total_loss: 3.127  time: 0.3442 s/iter  data_time: 0.2168 s/iter total_throughput: 2975.19 samples/s lr: 1.15e-04  
[09/23 07:53:14] lb.utils.events INFO:  eta: 3:25:12  iteration: 296199/375342  consumed_samples: 303308800  total_loss: 3.154  time: 0.3442 s/iter  data_time: 0.2146 s/iter total_throughput: 2975.18 samples/s lr: 1.15e-04  
[09/23 07:53:49] lb.utils.events INFO:  eta: 3:25:15  iteration: 296299/375342  consumed_samples: 303411200  total_loss: 3.138  time: 0.3442 s/iter  data_time: 0.2164 s/iter total_throughput: 2975.16 samples/s lr: 1.14e-04  
[09/23 07:54:24] lb.utils.events INFO:  eta: 3:24:39  iteration: 296399/375342  consumed_samples: 303513600  total_loss: 3.127  time: 0.3442 s/iter  data_time: 0.2242 s/iter total_throughput: 2975.14 samples/s lr: 1.14e-04  
[09/23 07:55:00] lb.utils.events INFO:  eta: 3:24:02  iteration: 296499/375342  consumed_samples: 303616000  total_loss: 3.127  time: 0.3442 s/iter  data_time: 0.2260 s/iter total_throughput: 2975.12 samples/s lr: 1.14e-04  
[09/23 07:55:35] lb.utils.events INFO:  eta: 3:23:36  iteration: 296599/375342  consumed_samples: 303718400  total_loss: 3.117  time: 0.3442 s/iter  data_time: 0.2369 s/iter total_throughput: 2975.09 samples/s lr: 1.14e-04  
[09/23 07:56:10] lb.utils.events INFO:  eta: 3:23:42  iteration: 296699/375342  consumed_samples: 303820800  total_loss: 3.111  time: 0.3442 s/iter  data_time: 0.2158 s/iter total_throughput: 2975.07 samples/s lr: 1.13e-04  
[09/23 07:56:45] lb.utils.events INFO:  eta: 3:23:26  iteration: 296799/375342  consumed_samples: 303923200  total_loss: 3.119  time: 0.3442 s/iter  data_time: 0.2232 s/iter total_throughput: 2975.05 samples/s lr: 1.13e-04  
[09/23 07:57:20] lb.utils.events INFO:  eta: 3:23:11  iteration: 296899/375342  consumed_samples: 304025600  total_loss: 3.109  time: 0.3442 s/iter  data_time: 0.2217 s/iter total_throughput: 2975.04 samples/s lr: 1.13e-04  
[09/23 07:57:55] lb.utils.events INFO:  eta: 3:22:53  iteration: 296999/375342  consumed_samples: 304128000  total_loss: 3.117  time: 0.3442 s/iter  data_time: 0.2252 s/iter total_throughput: 2975.01 samples/s lr: 1.13e-04  
[09/23 07:58:30] lb.utils.events INFO:  eta: 3:22:35  iteration: 297099/375342  consumed_samples: 304230400  total_loss: 3.144  time: 0.3442 s/iter  data_time: 0.2235 s/iter total_throughput: 2975.00 samples/s lr: 1.12e-04  
[09/23 07:59:05] lb.utils.events INFO:  eta: 3:22:18  iteration: 297199/375342  consumed_samples: 304332800  total_loss: 3.153  time: 0.3442 s/iter  data_time: 0.2257 s/iter total_throughput: 2974.99 samples/s lr: 1.12e-04  
[09/23 07:59:40] lb.utils.events INFO:  eta: 3:21:59  iteration: 297299/375342  consumed_samples: 304435200  total_loss: 3.13  time: 0.3442 s/iter  data_time: 0.2198 s/iter total_throughput: 2974.97 samples/s lr: 1.12e-04  
[09/23 08:00:16] lb.utils.events INFO:  eta: 3:21:40  iteration: 297399/375342  consumed_samples: 304537600  total_loss: 3.123  time: 0.3442 s/iter  data_time: 0.2206 s/iter total_throughput: 2974.94 samples/s lr: 1.12e-04  
[09/23 08:00:50] lb.utils.events INFO:  eta: 3:21:14  iteration: 297499/375342  consumed_samples: 304640000  total_loss: 3.124  time: 0.3442 s/iter  data_time: 0.2248 s/iter total_throughput: 2974.93 samples/s lr: 1.11e-04  
[09/23 08:01:25] lb.utils.events INFO:  eta: 3:21:05  iteration: 297599/375342  consumed_samples: 304742400  total_loss: 3.13  time: 0.3442 s/iter  data_time: 0.2201 s/iter total_throughput: 2974.92 samples/s lr: 1.11e-04  
[09/23 08:02:01] lb.utils.events INFO:  eta: 3:20:41  iteration: 297699/375342  consumed_samples: 304844800  total_loss: 3.113  time: 0.3442 s/iter  data_time: 0.2276 s/iter total_throughput: 2974.89 samples/s lr: 1.11e-04  
[09/23 08:02:36] lb.utils.events INFO:  eta: 3:20:08  iteration: 297799/375342  consumed_samples: 304947200  total_loss: 3.097  time: 0.3442 s/iter  data_time: 0.2264 s/iter total_throughput: 2974.87 samples/s lr: 1.11e-04  
[09/23 08:03:11] lb.utils.events INFO:  eta: 3:19:42  iteration: 297899/375342  consumed_samples: 305049600  total_loss: 3.109  time: 0.3442 s/iter  data_time: 0.2262 s/iter total_throughput: 2974.85 samples/s lr: 1.10e-04  
[09/23 08:03:46] lb.utils.events INFO:  eta: 3:19:45  iteration: 297999/375342  consumed_samples: 305152000  total_loss: 3.114  time: 0.3442 s/iter  data_time: 0.2200 s/iter total_throughput: 2974.84 samples/s lr: 1.10e-04  
[09/23 08:04:20] lb.utils.events INFO:  eta: 3:19:25  iteration: 298099/375342  consumed_samples: 305254400  total_loss: 3.124  time: 0.3442 s/iter  data_time: 0.2230 s/iter total_throughput: 2974.83 samples/s lr: 1.10e-04  
[09/23 08:04:56] lb.utils.events INFO:  eta: 3:18:52  iteration: 298199/375342  consumed_samples: 305356800  total_loss: 3.119  time: 0.3442 s/iter  data_time: 0.2271 s/iter total_throughput: 2974.81 samples/s lr: 1.10e-04  
[09/23 08:05:30] lb.utils.events INFO:  eta: 3:18:37  iteration: 298299/375342  consumed_samples: 305459200  total_loss: 3.107  time: 0.3442 s/iter  data_time: 0.2150 s/iter total_throughput: 2974.80 samples/s lr: 1.09e-04  
[09/23 08:06:05] lb.utils.events INFO:  eta: 3:18:52  iteration: 298399/375342  consumed_samples: 305561600  total_loss: 3.113  time: 0.3442 s/iter  data_time: 0.2303 s/iter total_throughput: 2974.78 samples/s lr: 1.09e-04  
[09/23 08:06:40] lb.utils.events INFO:  eta: 3:18:51  iteration: 298499/375342  consumed_samples: 305664000  total_loss: 3.113  time: 0.3442 s/iter  data_time: 0.2218 s/iter total_throughput: 2974.77 samples/s lr: 1.09e-04  
[09/23 08:07:15] lb.utils.events INFO:  eta: 3:18:34  iteration: 298599/375342  consumed_samples: 305766400  total_loss: 3.122  time: 0.3442 s/iter  data_time: 0.2170 s/iter total_throughput: 2974.76 samples/s lr: 1.09e-04  
[09/23 08:07:50] lb.utils.events INFO:  eta: 3:18:36  iteration: 298699/375342  consumed_samples: 305868800  total_loss: 3.137  time: 0.3442 s/iter  data_time: 0.2355 s/iter total_throughput: 2974.74 samples/s lr: 1.08e-04  
[09/23 08:08:25] lb.utils.events INFO:  eta: 3:18:41  iteration: 298799/375342  consumed_samples: 305971200  total_loss: 3.132  time: 0.3442 s/iter  data_time: 0.2340 s/iter total_throughput: 2974.73 samples/s lr: 1.08e-04  
[09/23 08:09:00] lb.utils.events INFO:  eta: 3:18:50  iteration: 298899/375342  consumed_samples: 306073600  total_loss: 3.104  time: 0.3442 s/iter  data_time: 0.2215 s/iter total_throughput: 2974.72 samples/s lr: 1.08e-04  
[09/23 08:09:35] lb.utils.events INFO:  eta: 3:18:40  iteration: 298999/375342  consumed_samples: 306176000  total_loss: 3.104  time: 0.3442 s/iter  data_time: 0.2218 s/iter total_throughput: 2974.71 samples/s lr: 1.08e-04  
[09/23 08:10:09] lb.utils.events INFO:  eta: 3:18:06  iteration: 299099/375342  consumed_samples: 306278400  total_loss: 3.121  time: 0.3442 s/iter  data_time: 0.2217 s/iter total_throughput: 2974.71 samples/s lr: 1.07e-04  
[09/23 08:10:44] lb.utils.events INFO:  eta: 3:17:48  iteration: 299199/375342  consumed_samples: 306380800  total_loss: 3.123  time: 0.3442 s/iter  data_time: 0.2212 s/iter total_throughput: 2974.69 samples/s lr: 1.07e-04  
[09/23 08:11:19] lb.utils.events INFO:  eta: 3:17:28  iteration: 299299/375342  consumed_samples: 306483200  total_loss: 3.131  time: 0.3442 s/iter  data_time: 0.2206 s/iter total_throughput: 2974.67 samples/s lr: 1.07e-04  
[09/23 08:11:55] lb.utils.events INFO:  eta: 3:16:59  iteration: 299399/375342  consumed_samples: 306585600  total_loss: 3.119  time: 0.3442 s/iter  data_time: 0.2252 s/iter total_throughput: 2974.64 samples/s lr: 1.07e-04  
[09/23 08:12:30] lb.utils.events INFO:  eta: 3:16:44  iteration: 299499/375342  consumed_samples: 306688000  total_loss: 3.123  time: 0.3442 s/iter  data_time: 0.2255 s/iter total_throughput: 2974.62 samples/s lr: 1.06e-04  
[09/23 08:13:05] lb.utils.events INFO:  eta: 3:16:08  iteration: 299599/375342  consumed_samples: 306790400  total_loss: 3.135  time: 0.3442 s/iter  data_time: 0.2368 s/iter total_throughput: 2974.60 samples/s lr: 1.06e-04  
[09/23 08:13:40] lb.utils.events INFO:  eta: 3:15:23  iteration: 299699/375342  consumed_samples: 306892800  total_loss: 3.122  time: 0.3443 s/iter  data_time: 0.2250 s/iter total_throughput: 2974.58 samples/s lr: 1.06e-04  
[09/23 08:14:15] lb.utils.events INFO:  eta: 3:14:45  iteration: 299799/375342  consumed_samples: 306995200  total_loss: 3.127  time: 0.3443 s/iter  data_time: 0.2136 s/iter total_throughput: 2974.56 samples/s lr: 1.06e-04  
[09/23 08:14:50] lb.utils.events INFO:  eta: 3:14:14  iteration: 299899/375342  consumed_samples: 307097600  total_loss: 3.11  time: 0.3443 s/iter  data_time: 0.2205 s/iter total_throughput: 2974.55 samples/s lr: 1.05e-04  
[09/23 08:15:25] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0299999
[09/23 08:15:26] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/23 08:15:26] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/23 08:15:30] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0996 s/iter. Inference: 0.1665 s/iter. Eval: 0.0020 s/iter. Total: 0.2681 s/iter. ETA=0:00:09
[09/23 08:15:35] lb.evaluation.evaluator INFO: Inference done 28672/50000. Dataloading: 0.1109 s/iter. Inference: 0.1751 s/iter. Eval: 0.0020 s/iter. Total: 0.2881 s/iter. ETA=0:00:05
[09/23 08:15:40] lb.evaluation.evaluator INFO: Inference done 47104/50000. Dataloading: 0.1206 s/iter. Inference: 0.1685 s/iter. Eval: 0.0020 s/iter. Total: 0.2912 s/iter. ETA=0:00:00
[09/23 08:15:41] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/23 08:15:41] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.553595 (0.000251 s / iter per device, on 8 devices)
[09/23 08:15:41] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000149 s / iter per device, on 8 devices)
[09/23 08:15:41] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/23 08:15:41] lb.evaluation.utils INFO: copypaste: Acc@1=79.158
[09/23 08:15:41] lb.evaluation.utils INFO: copypaste: Acc@5=94.326
[09/23 08:15:41] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 79.15800, better than last best score 78.92200 @ iteration 289999.
[09/23 08:15:41] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/23 08:15:42] lb.utils.events INFO:  eta: 3:13:42  iteration: 299999/375342  consumed_samples: 307200000  total_loss: 3.104  time: 0.3443 s/iter  data_time: 0.2373 s/iter total_throughput: 2974.54 samples/s lr: 1.05e-04  
[09/23 08:16:15] lb.utils.events INFO:  eta: 3:14:04  iteration: 300099/375342  consumed_samples: 307302400  total_loss: 3.106  time: 0.3443 s/iter  data_time: 0.2206 s/iter total_throughput: 2974.57 samples/s lr: 1.05e-04  
[09/23 08:16:50] lb.utils.events INFO:  eta: 3:13:58  iteration: 300199/375342  consumed_samples: 307404800  total_loss: 3.116  time: 0.3443 s/iter  data_time: 0.2239 s/iter total_throughput: 2974.55 samples/s lr: 1.05e-04  
[09/23 08:17:25] lb.utils.events INFO:  eta: 3:13:43  iteration: 300299/375342  consumed_samples: 307507200  total_loss: 3.125  time: 0.3443 s/iter  data_time: 0.2246 s/iter total_throughput: 2974.52 samples/s lr: 1.04e-04  
[09/23 08:18:00] lb.utils.events INFO:  eta: 3:13:29  iteration: 300399/375342  consumed_samples: 307609600  total_loss: 3.104  time: 0.3443 s/iter  data_time: 0.2155 s/iter total_throughput: 2974.51 samples/s lr: 1.04e-04  
[09/23 08:18:35] lb.utils.events INFO:  eta: 3:13:41  iteration: 300499/375342  consumed_samples: 307712000  total_loss: 3.1  time: 0.3443 s/iter  data_time: 0.2228 s/iter total_throughput: 2974.50 samples/s lr: 1.04e-04  
[09/23 08:19:10] lb.utils.events INFO:  eta: 3:13:22  iteration: 300599/375342  consumed_samples: 307814400  total_loss: 3.119  time: 0.3443 s/iter  data_time: 0.2241 s/iter total_throughput: 2974.48 samples/s lr: 1.04e-04  
[09/23 08:19:45] lb.utils.events INFO:  eta: 3:13:25  iteration: 300699/375342  consumed_samples: 307916800  total_loss: 3.106  time: 0.3443 s/iter  data_time: 0.2360 s/iter total_throughput: 2974.47 samples/s lr: 1.04e-04  
[09/23 08:20:20] lb.utils.events INFO:  eta: 3:12:54  iteration: 300799/375342  consumed_samples: 308019200  total_loss: 3.107  time: 0.3443 s/iter  data_time: 0.2192 s/iter total_throughput: 2974.46 samples/s lr: 1.03e-04  
[09/23 08:20:55] lb.utils.events INFO:  eta: 3:13:02  iteration: 300899/375342  consumed_samples: 308121600  total_loss: 3.12  time: 0.3443 s/iter  data_time: 0.2283 s/iter total_throughput: 2974.44 samples/s lr: 1.03e-04  
[09/23 08:21:30] lb.utils.events INFO:  eta: 3:12:31  iteration: 300999/375342  consumed_samples: 308224000  total_loss: 3.115  time: 0.3443 s/iter  data_time: 0.2285 s/iter total_throughput: 2974.42 samples/s lr: 1.03e-04  
[09/23 08:22:05] lb.utils.events INFO:  eta: 3:11:39  iteration: 301099/375342  consumed_samples: 308326400  total_loss: 3.098  time: 0.3443 s/iter  data_time: 0.2255 s/iter total_throughput: 2974.41 samples/s lr: 1.03e-04  
[09/23 08:22:40] lb.utils.events INFO:  eta: 3:11:13  iteration: 301199/375342  consumed_samples: 308428800  total_loss: 3.104  time: 0.3443 s/iter  data_time: 0.2196 s/iter total_throughput: 2974.40 samples/s lr: 1.02e-04  
[09/23 08:23:14] lb.utils.events INFO:  eta: 3:10:58  iteration: 301299/375342  consumed_samples: 308531200  total_loss: 3.121  time: 0.3443 s/iter  data_time: 0.2260 s/iter total_throughput: 2974.39 samples/s lr: 1.02e-04  
[09/23 08:23:49] lb.utils.events INFO:  eta: 3:11:18  iteration: 301399/375342  consumed_samples: 308633600  total_loss: 3.111  time: 0.3443 s/iter  data_time: 0.2189 s/iter total_throughput: 2974.38 samples/s lr: 1.02e-04  
[09/23 08:24:24] lb.utils.events INFO:  eta: 3:10:36  iteration: 301499/375342  consumed_samples: 308736000  total_loss: 3.105  time: 0.3443 s/iter  data_time: 0.2237 s/iter total_throughput: 2974.37 samples/s lr: 1.02e-04  
[09/23 08:24:59] lb.utils.events INFO:  eta: 3:10:11  iteration: 301599/375342  consumed_samples: 308838400  total_loss: 3.097  time: 0.3443 s/iter  data_time: 0.2510 s/iter total_throughput: 2974.34 samples/s lr: 1.01e-04  
[09/23 08:25:35] lb.utils.events INFO:  eta: 3:09:53  iteration: 301699/375342  consumed_samples: 308940800  total_loss: 3.097  time: 0.3443 s/iter  data_time: 0.2178 s/iter total_throughput: 2974.32 samples/s lr: 1.01e-04  
[09/23 08:26:10] lb.utils.events INFO:  eta: 3:09:46  iteration: 301799/375342  consumed_samples: 309043200  total_loss: 3.107  time: 0.3443 s/iter  data_time: 0.2240 s/iter total_throughput: 2974.29 samples/s lr: 1.01e-04  
[09/23 08:26:45] lb.utils.events INFO:  eta: 3:09:45  iteration: 301899/375342  consumed_samples: 309145600  total_loss: 3.109  time: 0.3443 s/iter  data_time: 0.2128 s/iter total_throughput: 2974.29 samples/s lr: 1.01e-04  
[09/23 08:27:19] lb.utils.events INFO:  eta: 3:10:05  iteration: 301999/375342  consumed_samples: 309248000  total_loss: 3.101  time: 0.3443 s/iter  data_time: 0.2294 s/iter total_throughput: 2974.27 samples/s lr: 1.00e-04  
[09/23 08:27:54] lb.utils.events INFO:  eta: 3:09:58  iteration: 302099/375342  consumed_samples: 309350400  total_loss: 3.097  time: 0.3443 s/iter  data_time: 0.2166 s/iter total_throughput: 2974.26 samples/s lr: 1.00e-04  
[09/23 08:28:29] lb.utils.events INFO:  eta: 3:09:44  iteration: 302199/375342  consumed_samples: 309452800  total_loss: 3.108  time: 0.3443 s/iter  data_time: 0.2215 s/iter total_throughput: 2974.25 samples/s lr: 9.99e-05  
[09/23 08:29:04] lb.utils.events INFO:  eta: 3:09:33  iteration: 302299/375342  consumed_samples: 309555200  total_loss: 3.112  time: 0.3443 s/iter  data_time: 0.2353 s/iter total_throughput: 2974.23 samples/s lr: 9.97e-05  
[09/23 08:29:39] lb.utils.events INFO:  eta: 3:09:03  iteration: 302399/375342  consumed_samples: 309657600  total_loss: 3.1  time: 0.3443 s/iter  data_time: 0.2188 s/iter total_throughput: 2974.23 samples/s lr: 9.94e-05  
[09/23 08:30:14] lb.utils.events INFO:  eta: 3:08:47  iteration: 302499/375342  consumed_samples: 309760000  total_loss: 3.094  time: 0.3443 s/iter  data_time: 0.2312 s/iter total_throughput: 2974.22 samples/s lr: 9.92e-05  
[09/23 08:30:49] lb.utils.events INFO:  eta: 3:08:37  iteration: 302599/375342  consumed_samples: 309862400  total_loss: 3.082  time: 0.3443 s/iter  data_time: 0.2159 s/iter total_throughput: 2974.20 samples/s lr: 9.89e-05  
[09/23 08:31:24] lb.utils.events INFO:  eta: 3:08:36  iteration: 302699/375342  consumed_samples: 309964800  total_loss: 3.095  time: 0.3443 s/iter  data_time: 0.2163 s/iter total_throughput: 2974.19 samples/s lr: 9.87e-05  
[09/23 08:31:58] lb.utils.events INFO:  eta: 3:08:38  iteration: 302799/375342  consumed_samples: 310067200  total_loss: 3.102  time: 0.3443 s/iter  data_time: 0.2227 s/iter total_throughput: 2974.18 samples/s lr: 9.85e-05  
[09/23 08:32:33] lb.utils.events INFO:  eta: 3:07:52  iteration: 302899/375342  consumed_samples: 310169600  total_loss: 3.109  time: 0.3443 s/iter  data_time: 0.2229 s/iter total_throughput: 2974.17 samples/s lr: 9.82e-05  
[09/23 08:33:08] lb.utils.events INFO:  eta: 3:07:31  iteration: 302999/375342  consumed_samples: 310272000  total_loss: 3.118  time: 0.3443 s/iter  data_time: 0.2230 s/iter total_throughput: 2974.15 samples/s lr: 9.80e-05  
[09/23 08:33:43] lb.utils.events INFO:  eta: 3:07:11  iteration: 303099/375342  consumed_samples: 310374400  total_loss: 3.112  time: 0.3443 s/iter  data_time: 0.2247 s/iter total_throughput: 2974.14 samples/s lr: 9.78e-05  
[09/23 08:34:18] lb.utils.events INFO:  eta: 3:06:56  iteration: 303199/375342  consumed_samples: 310476800  total_loss: 3.114  time: 0.3443 s/iter  data_time: 0.2250 s/iter total_throughput: 2974.13 samples/s lr: 9.75e-05  
[09/23 08:34:52] lb.utils.events INFO:  eta: 3:06:40  iteration: 303299/375342  consumed_samples: 310579200  total_loss: 3.109  time: 0.3443 s/iter  data_time: 0.2204 s/iter total_throughput: 2974.13 samples/s lr: 9.73e-05  
[09/23 08:35:27] lb.utils.events INFO:  eta: 3:06:09  iteration: 303399/375342  consumed_samples: 310681600  total_loss: 3.104  time: 0.3443 s/iter  data_time: 0.2134 s/iter total_throughput: 2974.13 samples/s lr: 9.71e-05  
[09/23 08:36:01] lb.utils.events INFO:  eta: 3:06:22  iteration: 303499/375342  consumed_samples: 310784000  total_loss: 3.095  time: 0.3443 s/iter  data_time: 0.2113 s/iter total_throughput: 2974.12 samples/s lr: 9.68e-05  
[09/23 08:36:36] lb.utils.events INFO:  eta: 3:06:13  iteration: 303599/375342  consumed_samples: 310886400  total_loss: 3.09  time: 0.3443 s/iter  data_time: 0.2187 s/iter total_throughput: 2974.12 samples/s lr: 9.66e-05  
[09/23 08:37:10] lb.utils.events INFO:  eta: 3:05:54  iteration: 303699/375342  consumed_samples: 310988800  total_loss: 3.098  time: 0.3443 s/iter  data_time: 0.2105 s/iter total_throughput: 2974.12 samples/s lr: 9.64e-05  
[09/23 08:37:45] lb.utils.events INFO:  eta: 3:05:28  iteration: 303799/375342  consumed_samples: 311091200  total_loss: 3.086  time: 0.3443 s/iter  data_time: 0.2287 s/iter total_throughput: 2974.11 samples/s lr: 9.61e-05  
[09/23 08:38:19] lb.utils.events INFO:  eta: 3:05:08  iteration: 303899/375342  consumed_samples: 311193600  total_loss: 3.092  time: 0.3443 s/iter  data_time: 0.2216 s/iter total_throughput: 2974.11 samples/s lr: 9.59e-05  
[09/23 08:38:54] lb.utils.events INFO:  eta: 3:04:39  iteration: 303999/375342  consumed_samples: 311296000  total_loss: 3.101  time: 0.3443 s/iter  data_time: 0.2147 s/iter total_throughput: 2974.11 samples/s lr: 9.57e-05  
[09/23 08:39:28] lb.utils.events INFO:  eta: 3:04:27  iteration: 304099/375342  consumed_samples: 311398400  total_loss: 3.09  time: 0.3443 s/iter  data_time: 0.2093 s/iter total_throughput: 2974.11 samples/s lr: 9.54e-05  
[09/23 08:40:03] lb.utils.events INFO:  eta: 3:04:27  iteration: 304199/375342  consumed_samples: 311500800  total_loss: 3.102  time: 0.3443 s/iter  data_time: 0.2203 s/iter total_throughput: 2974.10 samples/s lr: 9.52e-05  
[09/23 08:40:38] lb.utils.events INFO:  eta: 3:04:17  iteration: 304299/375342  consumed_samples: 311603200  total_loss: 3.094  time: 0.3443 s/iter  data_time: 0.2209 s/iter total_throughput: 2974.10 samples/s lr: 9.50e-05  
[09/23 08:41:12] lb.utils.events INFO:  eta: 3:04:21  iteration: 304399/375342  consumed_samples: 311705600  total_loss: 3.076  time: 0.3443 s/iter  data_time: 0.2264 s/iter total_throughput: 2974.10 samples/s lr: 9.47e-05  
[09/23 08:41:47] lb.utils.events INFO:  eta: 3:03:30  iteration: 304499/375342  consumed_samples: 311808000  total_loss: 3.088  time: 0.3443 s/iter  data_time: 0.2203 s/iter total_throughput: 2974.10 samples/s lr: 9.45e-05  
[09/23 08:42:21] lb.utils.events INFO:  eta: 3:03:02  iteration: 304599/375342  consumed_samples: 311910400  total_loss: 3.096  time: 0.3443 s/iter  data_time: 0.2183 s/iter total_throughput: 2974.08 samples/s lr: 9.43e-05  
[09/23 08:42:56] lb.utils.events INFO:  eta: 3:02:43  iteration: 304699/375342  consumed_samples: 312012800  total_loss: 3.085  time: 0.3443 s/iter  data_time: 0.2171 s/iter total_throughput: 2974.08 samples/s lr: 9.40e-05  
[09/23 08:43:30] lb.utils.events INFO:  eta: 3:02:25  iteration: 304799/375342  consumed_samples: 312115200  total_loss: 3.098  time: 0.3443 s/iter  data_time: 0.2246 s/iter total_throughput: 2974.08 samples/s lr: 9.38e-05  
[09/23 08:44:05] lb.utils.events INFO:  eta: 3:02:24  iteration: 304899/375342  consumed_samples: 312217600  total_loss: 3.112  time: 0.3443 s/iter  data_time: 0.2161 s/iter total_throughput: 2974.08 samples/s lr: 9.36e-05  
[09/23 08:44:39] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0304999
[09/23 08:44:40] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/23 08:44:40] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/23 08:44:44] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0853 s/iter. Inference: 0.1618 s/iter. Eval: 0.0024 s/iter. Total: 0.2495 s/iter. ETA=0:00:09
[09/23 08:44:50] lb.evaluation.evaluator INFO: Inference done 29696/50000. Dataloading: 0.1360 s/iter. Inference: 0.1632 s/iter. Eval: 0.0021 s/iter. Total: 0.3013 s/iter. ETA=0:00:05
[09/23 08:44:55] lb.evaluation.evaluator INFO: Inference done 49152/50000. Dataloading: 0.1197 s/iter. Inference: 0.1626 s/iter. Eval: 0.0021 s/iter. Total: 0.2845 s/iter. ETA=0:00:00
[09/23 08:44:55] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/23 08:44:55] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.608791 (0.000252 s / iter per device, on 8 devices)
[09/23 08:44:55] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000144 s / iter per device, on 8 devices)
[09/23 08:44:55] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/23 08:44:55] lb.evaluation.utils INFO: copypaste: Acc@1=79.202
[09/23 08:44:55] lb.evaluation.utils INFO: copypaste: Acc@5=94.3
[09/23 08:44:55] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 79.20200, better than last best score 79.15800 @ iteration 299999.
[09/23 08:44:55] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/23 08:44:56] lb.utils.events INFO:  eta: 3:02:21  iteration: 304999/375342  consumed_samples: 312320000  total_loss: 3.095  time: 0.3443 s/iter  data_time: 0.2030 s/iter total_throughput: 2974.09 samples/s lr: 9.33e-05  
[09/23 08:45:27] lb.utils.events INFO:  eta: 3:03:15  iteration: 305099/375342  consumed_samples: 312422400  total_loss: 3.084  time: 0.3443 s/iter  data_time: 0.2155 s/iter total_throughput: 2974.17 samples/s lr: 9.31e-05  
[09/23 08:46:02] lb.utils.events INFO:  eta: 3:03:11  iteration: 305199/375342  consumed_samples: 312524800  total_loss: 3.083  time: 0.3443 s/iter  data_time: 0.2163 s/iter total_throughput: 2974.16 samples/s lr: 9.29e-05  
[09/23 08:46:36] lb.utils.events INFO:  eta: 3:03:11  iteration: 305299/375342  consumed_samples: 312627200  total_loss: 3.082  time: 0.3443 s/iter  data_time: 0.2190 s/iter total_throughput: 2974.17 samples/s lr: 9.27e-05  
[09/23 08:47:10] lb.utils.events INFO:  eta: 3:03:21  iteration: 305399/375342  consumed_samples: 312729600  total_loss: 3.085  time: 0.3443 s/iter  data_time: 0.2088 s/iter total_throughput: 2974.19 samples/s lr: 9.24e-05  
[09/23 08:47:44] lb.utils.events INFO:  eta: 3:03:15  iteration: 305499/375342  consumed_samples: 312832000  total_loss: 3.089  time: 0.3443 s/iter  data_time: 0.2128 s/iter total_throughput: 2974.20 samples/s lr: 9.22e-05  
[09/23 08:48:19] lb.utils.events INFO:  eta: 3:03:02  iteration: 305599/375342  consumed_samples: 312934400  total_loss: 3.095  time: 0.3443 s/iter  data_time: 0.2171 s/iter total_throughput: 2974.19 samples/s lr: 9.20e-05  
[09/23 08:48:53] lb.utils.events INFO:  eta: 3:02:42  iteration: 305699/375342  consumed_samples: 313036800  total_loss: 3.098  time: 0.3443 s/iter  data_time: 0.2222 s/iter total_throughput: 2974.19 samples/s lr: 9.17e-05  
[09/23 08:49:28] lb.utils.events INFO:  eta: 3:02:37  iteration: 305799/375342  consumed_samples: 313139200  total_loss: 3.081  time: 0.3443 s/iter  data_time: 0.2132 s/iter total_throughput: 2974.19 samples/s lr: 9.15e-05  
[09/23 08:50:02] lb.utils.events INFO:  eta: 3:02:23  iteration: 305899/375342  consumed_samples: 313241600  total_loss: 3.066  time: 0.3443 s/iter  data_time: 0.2155 s/iter total_throughput: 2974.21 samples/s lr: 9.13e-05  
[09/23 08:50:36] lb.utils.events INFO:  eta: 3:02:03  iteration: 305999/375342  consumed_samples: 313344000  total_loss: 3.077  time: 0.3443 s/iter  data_time: 0.2193 s/iter total_throughput: 2974.21 samples/s lr: 9.11e-05  
[09/23 08:51:10] lb.utils.events INFO:  eta: 3:01:02  iteration: 306099/375342  consumed_samples: 313446400  total_loss: 3.117  time: 0.3443 s/iter  data_time: 0.2279 s/iter total_throughput: 2974.22 samples/s lr: 9.08e-05  
[09/23 08:51:45] lb.utils.events INFO:  eta: 3:00:18  iteration: 306199/375342  consumed_samples: 313548800  total_loss: 3.082  time: 0.3443 s/iter  data_time: 0.2144 s/iter total_throughput: 2974.21 samples/s lr: 9.06e-05  
[09/23 08:52:19] lb.utils.events INFO:  eta: 2:59:32  iteration: 306299/375342  consumed_samples: 313651200  total_loss: 3.063  time: 0.3443 s/iter  data_time: 0.2063 s/iter total_throughput: 2974.23 samples/s lr: 9.04e-05  
[09/23 08:52:53] lb.utils.events INFO:  eta: 2:58:58  iteration: 306399/375342  consumed_samples: 313753600  total_loss: 3.066  time: 0.3443 s/iter  data_time: 0.2186 s/iter total_throughput: 2974.23 samples/s lr: 9.02e-05  
[09/23 08:53:27] lb.utils.events INFO:  eta: 2:59:00  iteration: 306499/375342  consumed_samples: 313856000  total_loss: 3.079  time: 0.3443 s/iter  data_time: 0.2202 s/iter total_throughput: 2974.24 samples/s lr: 8.99e-05  
[09/23 08:54:01] lb.utils.events INFO:  eta: 2:58:54  iteration: 306599/375342  consumed_samples: 313958400  total_loss: 3.082  time: 0.3443 s/iter  data_time: 0.2039 s/iter total_throughput: 2974.26 samples/s lr: 8.97e-05  
[09/23 08:54:34] lb.utils.events INFO:  eta: 2:59:15  iteration: 306699/375342  consumed_samples: 314060800  total_loss: 3.062  time: 0.3443 s/iter  data_time: 0.2015 s/iter total_throughput: 2974.28 samples/s lr: 8.95e-05  
[09/23 08:55:09] lb.utils.events INFO:  eta: 2:58:46  iteration: 306799/375342  consumed_samples: 314163200  total_loss: 3.071  time: 0.3443 s/iter  data_time: 0.2141 s/iter total_throughput: 2974.29 samples/s lr: 8.93e-05  
[09/23 08:55:43] lb.utils.events INFO:  eta: 2:58:27  iteration: 306899/375342  consumed_samples: 314265600  total_loss: 3.096  time: 0.3443 s/iter  data_time: 0.2158 s/iter total_throughput: 2974.30 samples/s lr: 8.90e-05  
[09/23 08:56:16] lb.utils.events INFO:  eta: 2:58:38  iteration: 306999/375342  consumed_samples: 314368000  total_loss: 3.085  time: 0.3443 s/iter  data_time: 0.2150 s/iter total_throughput: 2974.32 samples/s lr: 8.88e-05  
[09/23 08:56:50] lb.utils.events INFO:  eta: 2:58:31  iteration: 307099/375342  consumed_samples: 314470400  total_loss: 3.086  time: 0.3443 s/iter  data_time: 0.2072 s/iter total_throughput: 2974.34 samples/s lr: 8.86e-05  
[09/23 08:57:24] lb.utils.events INFO:  eta: 2:58:44  iteration: 307199/375342  consumed_samples: 314572800  total_loss: 3.074  time: 0.3443 s/iter  data_time: 0.1995 s/iter total_throughput: 2974.35 samples/s lr: 8.84e-05  
[09/23 08:57:58] lb.utils.events INFO:  eta: 2:58:40  iteration: 307299/375342  consumed_samples: 314675200  total_loss: 3.074  time: 0.3443 s/iter  data_time: 0.2040 s/iter total_throughput: 2974.37 samples/s lr: 8.81e-05  
[09/23 08:58:32] lb.utils.events INFO:  eta: 2:58:09  iteration: 307399/375342  consumed_samples: 314777600  total_loss: 3.093  time: 0.3443 s/iter  data_time: 0.2040 s/iter total_throughput: 2974.39 samples/s lr: 8.79e-05  
[09/23 08:59:06] lb.utils.events INFO:  eta: 2:57:35  iteration: 307499/375342  consumed_samples: 314880000  total_loss: 3.086  time: 0.3443 s/iter  data_time: 0.2202 s/iter total_throughput: 2974.40 samples/s lr: 8.77e-05  
[09/23 08:59:39] lb.utils.events INFO:  eta: 2:57:37  iteration: 307599/375342  consumed_samples: 314982400  total_loss: 3.098  time: 0.3443 s/iter  data_time: 0.2082 s/iter total_throughput: 2974.42 samples/s lr: 8.75e-05  
[09/23 09:00:13] lb.utils.events INFO:  eta: 2:56:57  iteration: 307699/375342  consumed_samples: 315084800  total_loss: 3.104  time: 0.3443 s/iter  data_time: 0.2138 s/iter total_throughput: 2974.44 samples/s lr: 8.72e-05  
[09/23 09:00:47] lb.utils.events INFO:  eta: 2:56:35  iteration: 307799/375342  consumed_samples: 315187200  total_loss: 3.077  time: 0.3443 s/iter  data_time: 0.2110 s/iter total_throughput: 2974.45 samples/s lr: 8.70e-05  
[09/23 09:01:21] lb.utils.events INFO:  eta: 2:56:20  iteration: 307899/375342  consumed_samples: 315289600  total_loss: 3.055  time: 0.3443 s/iter  data_time: 0.2085 s/iter total_throughput: 2974.47 samples/s lr: 8.68e-05  
[09/23 09:01:55] lb.utils.events INFO:  eta: 2:55:32  iteration: 307999/375342  consumed_samples: 315392000  total_loss: 3.061  time: 0.3443 s/iter  data_time: 0.2101 s/iter total_throughput: 2974.48 samples/s lr: 8.66e-05  
[09/23 09:02:29] lb.utils.events INFO:  eta: 2:54:55  iteration: 308099/375342  consumed_samples: 315494400  total_loss: 3.086  time: 0.3443 s/iter  data_time: 0.2218 s/iter total_throughput: 2974.48 samples/s lr: 8.64e-05  
[09/23 09:03:04] lb.utils.events INFO:  eta: 2:54:09  iteration: 308199/375342  consumed_samples: 315596800  total_loss: 3.086  time: 0.3443 s/iter  data_time: 0.2067 s/iter total_throughput: 2974.49 samples/s lr: 8.61e-05  
[09/23 09:03:38] lb.utils.events INFO:  eta: 2:53:47  iteration: 308299/375342  consumed_samples: 315699200  total_loss: 3.082  time: 0.3443 s/iter  data_time: 0.2143 s/iter total_throughput: 2974.48 samples/s lr: 8.59e-05  
[09/23 09:04:12] lb.utils.events INFO:  eta: 2:53:26  iteration: 308399/375342  consumed_samples: 315801600  total_loss: 3.097  time: 0.3443 s/iter  data_time: 0.2353 s/iter total_throughput: 2974.49 samples/s lr: 8.57e-05  
[09/23 09:04:47] lb.utils.events INFO:  eta: 2:52:54  iteration: 308499/375342  consumed_samples: 315904000  total_loss: 3.1  time: 0.3443 s/iter  data_time: 0.2239 s/iter total_throughput: 2974.48 samples/s lr: 8.55e-05  
[09/23 09:05:22] lb.utils.events INFO:  eta: 2:52:16  iteration: 308599/375342  consumed_samples: 316006400  total_loss: 3.093  time: 0.3443 s/iter  data_time: 0.2253 s/iter total_throughput: 2974.47 samples/s lr: 8.53e-05  
[09/23 09:05:57] lb.utils.events INFO:  eta: 2:51:56  iteration: 308699/375342  consumed_samples: 316108800  total_loss: 3.092  time: 0.3443 s/iter  data_time: 0.2170 s/iter total_throughput: 2974.46 samples/s lr: 8.50e-05  
[09/23 09:06:32] lb.utils.events INFO:  eta: 2:51:47  iteration: 308799/375342  consumed_samples: 316211200  total_loss: 3.07  time: 0.3443 s/iter  data_time: 0.2177 s/iter total_throughput: 2974.44 samples/s lr: 8.48e-05  
[09/23 09:07:07] lb.utils.events INFO:  eta: 2:51:35  iteration: 308899/375342  consumed_samples: 316313600  total_loss: 3.07  time: 0.3443 s/iter  data_time: 0.2235 s/iter total_throughput: 2974.43 samples/s lr: 8.46e-05  
[09/23 09:07:42] lb.utils.events INFO:  eta: 2:51:37  iteration: 308999/375342  consumed_samples: 316416000  total_loss: 3.09  time: 0.3443 s/iter  data_time: 0.2254 s/iter total_throughput: 2974.41 samples/s lr: 8.44e-05  
[09/23 09:08:16] lb.utils.events INFO:  eta: 2:52:14  iteration: 309099/375342  consumed_samples: 316518400  total_loss: 3.088  time: 0.3443 s/iter  data_time: 0.2079 s/iter total_throughput: 2974.43 samples/s lr: 8.42e-05  
[09/23 09:08:50] lb.utils.events INFO:  eta: 2:52:19  iteration: 309199/375342  consumed_samples: 316620800  total_loss: 3.086  time: 0.3443 s/iter  data_time: 0.2124 s/iter total_throughput: 2974.43 samples/s lr: 8.39e-05  
[09/23 09:09:25] lb.utils.events INFO:  eta: 2:52:01  iteration: 309299/375342  consumed_samples: 316723200  total_loss: 3.065  time: 0.3443 s/iter  data_time: 0.2310 s/iter total_throughput: 2974.42 samples/s lr: 8.37e-05  
[09/23 09:10:00] lb.utils.events INFO:  eta: 2:51:48  iteration: 309399/375342  consumed_samples: 316825600  total_loss: 3.062  time: 0.3443 s/iter  data_time: 0.2339 s/iter total_throughput: 2974.40 samples/s lr: 8.35e-05  
[09/23 09:10:35] lb.utils.events INFO:  eta: 2:51:36  iteration: 309499/375342  consumed_samples: 316928000  total_loss: 3.082  time: 0.3443 s/iter  data_time: 0.2252 s/iter total_throughput: 2974.39 samples/s lr: 8.33e-05  
[09/23 09:11:09] lb.utils.events INFO:  eta: 2:51:46  iteration: 309599/375342  consumed_samples: 317030400  total_loss: 3.093  time: 0.3443 s/iter  data_time: 0.2090 s/iter total_throughput: 2974.39 samples/s lr: 8.31e-05  
[09/23 09:11:44] lb.utils.events INFO:  eta: 2:51:31  iteration: 309699/375342  consumed_samples: 317132800  total_loss: 3.07  time: 0.3443 s/iter  data_time: 0.2242 s/iter total_throughput: 2974.38 samples/s lr: 8.29e-05  
[09/23 09:12:19] lb.utils.events INFO:  eta: 2:51:12  iteration: 309799/375342  consumed_samples: 317235200  total_loss: 3.071  time: 0.3443 s/iter  data_time: 0.2129 s/iter total_throughput: 2974.37 samples/s lr: 8.26e-05  
[09/23 09:12:53] lb.utils.events INFO:  eta: 2:50:59  iteration: 309899/375342  consumed_samples: 317337600  total_loss: 3.084  time: 0.3443 s/iter  data_time: 0.2172 s/iter total_throughput: 2974.37 samples/s lr: 8.24e-05  
[09/23 09:13:28] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0309999
[09/23 09:13:29] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/23 09:13:29] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/23 09:13:33] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0975 s/iter. Inference: 0.1603 s/iter. Eval: 0.0021 s/iter. Total: 0.2599 s/iter. ETA=0:00:09
[09/23 09:13:38] lb.evaluation.evaluator INFO: Inference done 29696/50000. Dataloading: 0.1214 s/iter. Inference: 0.1724 s/iter. Eval: 0.0020 s/iter. Total: 0.2959 s/iter. ETA=0:00:05
[09/23 09:13:43] lb.evaluation.evaluator INFO: Inference done 49152/50000. Dataloading: 0.1145 s/iter. Inference: 0.1666 s/iter. Eval: 0.0020 s/iter. Total: 0.2832 s/iter. ETA=0:00:00
[09/23 09:13:44] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/23 09:13:44] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.487346 (0.000250 s / iter per device, on 8 devices)
[09/23 09:13:44] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000147 s / iter per device, on 8 devices)
[09/23 09:13:44] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/23 09:13:44] lb.evaluation.utils INFO: copypaste: Acc@1=79.308
[09/23 09:13:44] lb.evaluation.utils INFO: copypaste: Acc@5=94.274
[09/23 09:13:44] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 79.30800, better than last best score 79.20200 @ iteration 304999.
[09/23 09:13:44] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/23 09:13:44] lb.utils.events INFO:  eta: 2:50:22  iteration: 309999/375342  consumed_samples: 317440000  total_loss: 3.087  time: 0.3443 s/iter  data_time: 0.2160 s/iter total_throughput: 2974.36 samples/s lr: 8.22e-05  
[09/23 09:14:17] lb.utils.events INFO:  eta: 2:50:52  iteration: 310099/375342  consumed_samples: 317542400  total_loss: 3.076  time: 0.3443 s/iter  data_time: 0.2200 s/iter total_throughput: 2974.41 samples/s lr: 8.20e-05  
[09/23 09:14:52] lb.utils.events INFO:  eta: 2:50:27  iteration: 310199/375342  consumed_samples: 317644800  total_loss: 3.086  time: 0.3443 s/iter  data_time: 0.2229 s/iter total_throughput: 2974.40 samples/s lr: 8.18e-05  
[09/23 09:15:27] lb.utils.events INFO:  eta: 2:50:33  iteration: 310299/375342  consumed_samples: 317747200  total_loss: 3.077  time: 0.3443 s/iter  data_time: 0.2224 s/iter total_throughput: 2974.39 samples/s lr: 8.16e-05  
[09/23 09:16:01] lb.utils.events INFO:  eta: 2:50:26  iteration: 310399/375342  consumed_samples: 317849600  total_loss: 3.069  time: 0.3443 s/iter  data_time: 0.2173 s/iter total_throughput: 2974.38 samples/s lr: 8.13e-05  
[09/23 09:16:36] lb.utils.events INFO:  eta: 2:49:48  iteration: 310499/375342  consumed_samples: 317952000  total_loss: 3.079  time: 0.3443 s/iter  data_time: 0.2118 s/iter total_throughput: 2974.38 samples/s lr: 8.11e-05  
[09/23 09:17:11] lb.utils.events INFO:  eta: 2:49:22  iteration: 310599/375342  consumed_samples: 318054400  total_loss: 3.071  time: 0.3443 s/iter  data_time: 0.2188 s/iter total_throughput: 2974.37 samples/s lr: 8.09e-05  
[09/23 09:17:46] lb.utils.events INFO:  eta: 2:48:39  iteration: 310699/375342  consumed_samples: 318156800  total_loss: 3.061  time: 0.3443 s/iter  data_time: 0.2239 s/iter total_throughput: 2974.36 samples/s lr: 8.07e-05  
[09/23 09:18:20] lb.utils.events INFO:  eta: 2:48:35  iteration: 310799/375342  consumed_samples: 318259200  total_loss: 3.065  time: 0.3443 s/iter  data_time: 0.2214 s/iter total_throughput: 2974.35 samples/s lr: 8.05e-05  
[09/23 09:18:55] lb.utils.events INFO:  eta: 2:48:26  iteration: 310899/375342  consumed_samples: 318361600  total_loss: 3.074  time: 0.3443 s/iter  data_time: 0.2211 s/iter total_throughput: 2974.34 samples/s lr: 8.03e-05  
[09/23 09:19:30] lb.utils.events INFO:  eta: 2:48:17  iteration: 310999/375342  consumed_samples: 318464000  total_loss: 3.068  time: 0.3443 s/iter  data_time: 0.2269 s/iter total_throughput: 2974.34 samples/s lr: 8.01e-05  
[09/23 09:20:04] lb.utils.events INFO:  eta: 2:47:23  iteration: 311099/375342  consumed_samples: 318566400  total_loss: 3.064  time: 0.3443 s/iter  data_time: 0.2177 s/iter total_throughput: 2974.35 samples/s lr: 7.99e-05  
[09/23 09:20:38] lb.utils.events INFO:  eta: 2:47:09  iteration: 311199/375342  consumed_samples: 318668800  total_loss: 3.063  time: 0.3443 s/iter  data_time: 0.2115 s/iter total_throughput: 2974.35 samples/s lr: 7.96e-05  
[09/23 09:21:13] lb.utils.events INFO:  eta: 2:46:55  iteration: 311299/375342  consumed_samples: 318771200  total_loss: 3.071  time: 0.3443 s/iter  data_time: 0.2115 s/iter total_throughput: 2974.34 samples/s lr: 7.94e-05  
[09/23 09:21:48] lb.utils.events INFO:  eta: 2:46:38  iteration: 311399/375342  consumed_samples: 318873600  total_loss: 3.079  time: 0.3443 s/iter  data_time: 0.2254 s/iter total_throughput: 2974.32 samples/s lr: 7.92e-05  
[09/23 09:22:22] lb.utils.events INFO:  eta: 2:46:29  iteration: 311499/375342  consumed_samples: 318976000  total_loss: 3.075  time: 0.3443 s/iter  data_time: 0.2169 s/iter total_throughput: 2974.32 samples/s lr: 7.90e-05  
[09/23 09:22:57] lb.utils.events INFO:  eta: 2:46:27  iteration: 311599/375342  consumed_samples: 319078400  total_loss: 3.068  time: 0.3443 s/iter  data_time: 0.2318 s/iter total_throughput: 2974.32 samples/s lr: 7.88e-05  
[09/23 09:23:32] lb.utils.events INFO:  eta: 2:46:24  iteration: 311699/375342  consumed_samples: 319180800  total_loss: 3.058  time: 0.3443 s/iter  data_time: 0.2173 s/iter total_throughput: 2974.30 samples/s lr: 7.86e-05  
[09/23 09:24:06] lb.utils.events INFO:  eta: 2:46:20  iteration: 311799/375342  consumed_samples: 319283200  total_loss: 3.06  time: 0.3443 s/iter  data_time: 0.2118 s/iter total_throughput: 2974.31 samples/s lr: 7.84e-05  
[09/23 09:24:41] lb.utils.events INFO:  eta: 2:46:08  iteration: 311899/375342  consumed_samples: 319385600  total_loss: 3.059  time: 0.3443 s/iter  data_time: 0.2212 s/iter total_throughput: 2974.30 samples/s lr: 7.82e-05  
[09/23 09:25:15] lb.utils.events INFO:  eta: 2:45:46  iteration: 311999/375342  consumed_samples: 319488000  total_loss: 3.064  time: 0.3443 s/iter  data_time: 0.2258 s/iter total_throughput: 2974.30 samples/s lr: 7.80e-05  
[09/23 09:25:49] lb.utils.events INFO:  eta: 2:45:17  iteration: 312099/375342  consumed_samples: 319590400  total_loss: 3.07  time: 0.3443 s/iter  data_time: 0.2131 s/iter total_throughput: 2974.31 samples/s lr: 7.77e-05  
[09/23 09:26:24] lb.utils.events INFO:  eta: 2:44:54  iteration: 312199/375342  consumed_samples: 319692800  total_loss: 3.06  time: 0.3443 s/iter  data_time: 0.2267 s/iter total_throughput: 2974.30 samples/s lr: 7.75e-05  
[09/23 09:26:59] lb.utils.events INFO:  eta: 2:44:18  iteration: 312299/375342  consumed_samples: 319795200  total_loss: 3.057  time: 0.3443 s/iter  data_time: 0.2145 s/iter total_throughput: 2974.29 samples/s lr: 7.73e-05  
[09/23 09:27:33] lb.utils.events INFO:  eta: 2:44:24  iteration: 312399/375342  consumed_samples: 319897600  total_loss: 3.062  time: 0.3443 s/iter  data_time: 0.2129 s/iter total_throughput: 2974.30 samples/s lr: 7.71e-05  
[09/23 09:28:08] lb.utils.events INFO:  eta: 2:44:07  iteration: 312499/375342  consumed_samples: 320000000  total_loss: 3.061  time: 0.3443 s/iter  data_time: 0.2241 s/iter total_throughput: 2974.29 samples/s lr: 7.69e-05  
[09/23 09:28:42] lb.utils.events INFO:  eta: 2:43:53  iteration: 312599/375342  consumed_samples: 320102400  total_loss: 3.069  time: 0.3443 s/iter  data_time: 0.2163 s/iter total_throughput: 2974.29 samples/s lr: 7.67e-05  
[09/23 09:29:17] lb.utils.events INFO:  eta: 2:43:52  iteration: 312699/375342  consumed_samples: 320204800  total_loss: 3.069  time: 0.3443 s/iter  data_time: 0.2169 s/iter total_throughput: 2974.29 samples/s lr: 7.65e-05  
[09/23 09:29:51] lb.utils.events INFO:  eta: 2:43:44  iteration: 312799/375342  consumed_samples: 320307200  total_loss: 3.056  time: 0.3443 s/iter  data_time: 0.2115 s/iter total_throughput: 2974.29 samples/s lr: 7.63e-05  
[09/23 09:30:26] lb.utils.events INFO:  eta: 2:43:14  iteration: 312899/375342  consumed_samples: 320409600  total_loss: 3.062  time: 0.3443 s/iter  data_time: 0.2243 s/iter total_throughput: 2974.29 samples/s lr: 7.61e-05  
[09/23 09:31:00] lb.utils.events INFO:  eta: 2:42:58  iteration: 312999/375342  consumed_samples: 320512000  total_loss: 3.064  time: 0.3443 s/iter  data_time: 0.2100 s/iter total_throughput: 2974.29 samples/s lr: 7.59e-05  
[09/23 09:31:35] lb.utils.events INFO:  eta: 2:42:47  iteration: 313099/375342  consumed_samples: 320614400  total_loss: 3.066  time: 0.3443 s/iter  data_time: 0.2088 s/iter total_throughput: 2974.29 samples/s lr: 7.57e-05  
[09/23 09:32:09] lb.utils.events INFO:  eta: 2:42:37  iteration: 313199/375342  consumed_samples: 320716800  total_loss: 3.057  time: 0.3443 s/iter  data_time: 0.2126 s/iter total_throughput: 2974.29 samples/s lr: 7.55e-05  
[09/23 09:32:43] lb.utils.events INFO:  eta: 2:42:22  iteration: 313299/375342  consumed_samples: 320819200  total_loss: 3.048  time: 0.3443 s/iter  data_time: 0.2127 s/iter total_throughput: 2974.29 samples/s lr: 7.53e-05  
[09/23 09:33:18] lb.utils.events INFO:  eta: 2:41:59  iteration: 313399/375342  consumed_samples: 320921600  total_loss: 3.044  time: 0.3443 s/iter  data_time: 0.2203 s/iter total_throughput: 2974.28 samples/s lr: 7.51e-05  
[09/23 09:33:53] lb.utils.events INFO:  eta: 2:41:37  iteration: 313499/375342  consumed_samples: 321024000  total_loss: 3.047  time: 0.3443 s/iter  data_time: 0.2259 s/iter total_throughput: 2974.27 samples/s lr: 7.48e-05  
[09/23 09:34:28] lb.utils.events INFO:  eta: 2:40:46  iteration: 313599/375342  consumed_samples: 321126400  total_loss: 3.064  time: 0.3443 s/iter  data_time: 0.2251 s/iter total_throughput: 2974.26 samples/s lr: 7.46e-05  
[09/23 09:35:03] lb.utils.events INFO:  eta: 2:40:00  iteration: 313699/375342  consumed_samples: 321228800  total_loss: 3.072  time: 0.3443 s/iter  data_time: 0.2231 s/iter total_throughput: 2974.25 samples/s lr: 7.44e-05  
[09/23 09:35:37] lb.utils.events INFO:  eta: 2:39:36  iteration: 313799/375342  consumed_samples: 321331200  total_loss: 3.068  time: 0.3443 s/iter  data_time: 0.2141 s/iter total_throughput: 2974.24 samples/s lr: 7.42e-05  
[09/23 09:36:12] lb.utils.events INFO:  eta: 2:39:11  iteration: 313899/375342  consumed_samples: 321433600  total_loss: 3.071  time: 0.3443 s/iter  data_time: 0.2198 s/iter total_throughput: 2974.24 samples/s lr: 7.40e-05  
[09/23 09:36:46] lb.utils.events INFO:  eta: 2:39:11  iteration: 313999/375342  consumed_samples: 321536000  total_loss: 3.059  time: 0.3443 s/iter  data_time: 0.2194 s/iter total_throughput: 2974.23 samples/s lr: 7.38e-05  
[09/23 09:37:21] lb.utils.events INFO:  eta: 2:38:52  iteration: 314099/375342  consumed_samples: 321638400  total_loss: 3.045  time: 0.3443 s/iter  data_time: 0.2198 s/iter total_throughput: 2974.22 samples/s lr: 7.36e-05  
[09/23 09:37:56] lb.utils.events INFO:  eta: 2:38:43  iteration: 314199/375342  consumed_samples: 321740800  total_loss: 3.044  time: 0.3443 s/iter  data_time: 0.2236 s/iter total_throughput: 2974.22 samples/s lr: 7.34e-05  
[09/23 09:38:30] lb.utils.events INFO:  eta: 2:38:24  iteration: 314299/375342  consumed_samples: 321843200  total_loss: 3.041  time: 0.3443 s/iter  data_time: 0.2226 s/iter total_throughput: 2974.22 samples/s lr: 7.32e-05  
[09/23 09:39:05] lb.utils.events INFO:  eta: 2:38:23  iteration: 314399/375342  consumed_samples: 321945600  total_loss: 3.05  time: 0.3443 s/iter  data_time: 0.2064 s/iter total_throughput: 2974.22 samples/s lr: 7.30e-05  
[09/23 09:39:39] lb.utils.events INFO:  eta: 2:37:50  iteration: 314499/375342  consumed_samples: 322048000  total_loss: 3.055  time: 0.3443 s/iter  data_time: 0.2380 s/iter total_throughput: 2974.22 samples/s lr: 7.28e-05  
[09/23 09:40:14] lb.utils.events INFO:  eta: 2:37:56  iteration: 314599/375342  consumed_samples: 322150400  total_loss: 3.056  time: 0.3443 s/iter  data_time: 0.2179 s/iter total_throughput: 2974.22 samples/s lr: 7.26e-05  
[09/23 09:40:48] lb.utils.events INFO:  eta: 2:38:05  iteration: 314699/375342  consumed_samples: 322252800  total_loss: 3.059  time: 0.3443 s/iter  data_time: 0.2100 s/iter total_throughput: 2974.22 samples/s lr: 7.24e-05  
[09/23 09:41:22] lb.utils.events INFO:  eta: 2:37:59  iteration: 314799/375342  consumed_samples: 322355200  total_loss: 3.061  time: 0.3443 s/iter  data_time: 0.2128 s/iter total_throughput: 2974.23 samples/s lr: 7.22e-05  
[09/23 09:41:56] lb.utils.events INFO:  eta: 2:37:56  iteration: 314899/375342  consumed_samples: 322457600  total_loss: 3.051  time: 0.3443 s/iter  data_time: 0.2204 s/iter total_throughput: 2974.23 samples/s lr: 7.20e-05  
[09/23 09:42:31] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0314999
[09/23 09:42:32] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/23 09:42:32] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/23 09:42:36] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.1129 s/iter. Inference: 0.1611 s/iter. Eval: 0.0021 s/iter. Total: 0.2761 s/iter. ETA=0:00:10
[09/23 09:42:41] lb.evaluation.evaluator INFO: Inference done 29696/50000. Dataloading: 0.1274 s/iter. Inference: 0.1677 s/iter. Eval: 0.0022 s/iter. Total: 0.2974 s/iter. ETA=0:00:05
[09/23 09:42:46] lb.evaluation.evaluator INFO: Inference done 48128/50000. Dataloading: 0.1244 s/iter. Inference: 0.1645 s/iter. Eval: 0.0021 s/iter. Total: 0.2911 s/iter. ETA=0:00:00
[09/23 09:42:47] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/23 09:42:47] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.578217 (0.000252 s / iter per device, on 8 devices)
[09/23 09:42:47] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000145 s / iter per device, on 8 devices)
[09/23 09:42:47] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/23 09:42:47] lb.evaluation.utils INFO: copypaste: Acc@1=79.51
[09/23 09:42:47] lb.evaluation.utils INFO: copypaste: Acc@5=94.338
[09/23 09:42:47] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 79.51000, better than last best score 79.30800 @ iteration 309999.
[09/23 09:42:47] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/23 09:42:47] lb.utils.events INFO:  eta: 2:37:41  iteration: 314999/375342  consumed_samples: 322560000  total_loss: 3.051  time: 0.3443 s/iter  data_time: 0.2245 s/iter total_throughput: 2974.23 samples/s lr: 7.18e-05  
[09/23 09:43:20] lb.utils.events INFO:  eta: 2:38:15  iteration: 315099/375342  consumed_samples: 322662400  total_loss: 3.053  time: 0.3443 s/iter  data_time: 0.2313 s/iter total_throughput: 2974.29 samples/s lr: 7.16e-05  
[09/23 09:43:54] lb.utils.events INFO:  eta: 2:37:44  iteration: 315199/375342  consumed_samples: 322764800  total_loss: 3.043  time: 0.3443 s/iter  data_time: 0.2207 s/iter total_throughput: 2974.29 samples/s lr: 7.14e-05  
[09/23 09:44:29] lb.utils.events INFO:  eta: 2:37:55  iteration: 315299/375342  consumed_samples: 322867200  total_loss: 3.057  time: 0.3443 s/iter  data_time: 0.2159 s/iter total_throughput: 2974.28 samples/s lr: 7.12e-05  
[09/23 09:45:04] lb.utils.events INFO:  eta: 2:37:43  iteration: 315399/375342  consumed_samples: 322969600  total_loss: 3.059  time: 0.3443 s/iter  data_time: 0.2129 s/iter total_throughput: 2974.28 samples/s lr: 7.10e-05  
[09/23 09:45:38] lb.utils.events INFO:  eta: 2:37:39  iteration: 315499/375342  consumed_samples: 323072000  total_loss: 3.048  time: 0.3443 s/iter  data_time: 0.2242 s/iter total_throughput: 2974.28 samples/s lr: 7.08e-05  
[09/23 09:46:12] lb.utils.events INFO:  eta: 2:37:29  iteration: 315599/375342  consumed_samples: 323174400  total_loss: 3.044  time: 0.3443 s/iter  data_time: 0.2111 s/iter total_throughput: 2974.29 samples/s lr: 7.06e-05  
[09/23 09:46:47] lb.utils.events INFO:  eta: 2:37:15  iteration: 315699/375342  consumed_samples: 323276800  total_loss: 3.065  time: 0.3443 s/iter  data_time: 0.2153 s/iter total_throughput: 2974.29 samples/s lr: 7.04e-05  
[09/23 09:47:21] lb.utils.events INFO:  eta: 2:36:47  iteration: 315799/375342  consumed_samples: 323379200  total_loss: 3.049  time: 0.3443 s/iter  data_time: 0.2123 s/iter total_throughput: 2974.30 samples/s lr: 7.02e-05  
[09/23 09:47:55] lb.utils.events INFO:  eta: 2:36:19  iteration: 315899/375342  consumed_samples: 323481600  total_loss: 3.05  time: 0.3443 s/iter  data_time: 0.2236 s/iter total_throughput: 2974.29 samples/s lr: 7.00e-05  
[09/23 09:48:30] lb.utils.events INFO:  eta: 2:35:57  iteration: 315999/375342  consumed_samples: 323584000  total_loss: 3.06  time: 0.3443 s/iter  data_time: 0.2287 s/iter total_throughput: 2974.30 samples/s lr: 6.98e-05  
[09/23 09:49:05] lb.utils.events INFO:  eta: 2:35:08  iteration: 316099/375342  consumed_samples: 323686400  total_loss: 3.047  time: 0.3443 s/iter  data_time: 0.2310 s/iter total_throughput: 2974.28 samples/s lr: 6.96e-05  
[09/23 09:49:39] lb.utils.events INFO:  eta: 2:34:51  iteration: 316199/375342  consumed_samples: 323788800  total_loss: 3.044  time: 0.3443 s/iter  data_time: 0.2071 s/iter total_throughput: 2974.28 samples/s lr: 6.94e-05  
[09/23 09:50:13] lb.utils.events INFO:  eta: 2:34:37  iteration: 316299/375342  consumed_samples: 323891200  total_loss: 3.048  time: 0.3443 s/iter  data_time: 0.2051 s/iter total_throughput: 2974.29 samples/s lr: 6.92e-05  
[09/23 09:50:47] lb.utils.events INFO:  eta: 2:34:16  iteration: 316399/375342  consumed_samples: 323993600  total_loss: 3.062  time: 0.3443 s/iter  data_time: 0.2093 s/iter total_throughput: 2974.30 samples/s lr: 6.90e-05  
[09/23 09:51:22] lb.utils.events INFO:  eta: 2:33:41  iteration: 316499/375342  consumed_samples: 324096000  total_loss: 3.05  time: 0.3443 s/iter  data_time: 0.2297 s/iter total_throughput: 2974.28 samples/s lr: 6.88e-05  
[09/23 09:51:57] lb.utils.events INFO:  eta: 2:33:22  iteration: 316599/375342  consumed_samples: 324198400  total_loss: 3.036  time: 0.3443 s/iter  data_time: 0.2196 s/iter total_throughput: 2974.28 samples/s lr: 6.86e-05  
[09/23 09:52:31] lb.utils.events INFO:  eta: 2:33:10  iteration: 316699/375342  consumed_samples: 324300800  total_loss: 3.038  time: 0.3443 s/iter  data_time: 0.2259 s/iter total_throughput: 2974.27 samples/s lr: 6.84e-05  
[09/23 09:53:06] lb.utils.events INFO:  eta: 2:32:43  iteration: 316799/375342  consumed_samples: 324403200  total_loss: 3.037  time: 0.3443 s/iter  data_time: 0.2193 s/iter total_throughput: 2974.28 samples/s lr: 6.82e-05  
[09/23 09:53:40] lb.utils.events INFO:  eta: 2:32:17  iteration: 316899/375342  consumed_samples: 324505600  total_loss: 3.047  time: 0.3443 s/iter  data_time: 0.2104 s/iter total_throughput: 2974.28 samples/s lr: 6.81e-05  
[09/23 09:54:14] lb.utils.events INFO:  eta: 2:32:12  iteration: 316999/375342  consumed_samples: 324608000  total_loss: 3.049  time: 0.3443 s/iter  data_time: 0.2171 s/iter total_throughput: 2974.28 samples/s lr: 6.79e-05  
[09/23 09:54:49] lb.utils.events INFO:  eta: 2:31:52  iteration: 317099/375342  consumed_samples: 324710400  total_loss: 3.029  time: 0.3443 s/iter  data_time: 0.2135 s/iter total_throughput: 2974.29 samples/s lr: 6.77e-05  
[09/23 09:55:23] lb.utils.events INFO:  eta: 2:31:48  iteration: 317199/375342  consumed_samples: 324812800  total_loss: 3.017  time: 0.3443 s/iter  data_time: 0.2235 s/iter total_throughput: 2974.28 samples/s lr: 6.75e-05  
[09/23 09:55:57] lb.utils.events INFO:  eta: 2:31:30  iteration: 317299/375342  consumed_samples: 324915200  total_loss: 3.033  time: 0.3443 s/iter  data_time: 0.2177 s/iter total_throughput: 2974.29 samples/s lr: 6.73e-05  
[09/23 09:56:32] lb.utils.events INFO:  eta: 2:31:16  iteration: 317399/375342  consumed_samples: 325017600  total_loss: 3.046  time: 0.3443 s/iter  data_time: 0.2208 s/iter total_throughput: 2974.29 samples/s lr: 6.71e-05  
[09/23 09:57:06] lb.utils.events INFO:  eta: 2:31:01  iteration: 317499/375342  consumed_samples: 325120000  total_loss: 3.046  time: 0.3443 s/iter  data_time: 0.2175 s/iter total_throughput: 2974.29 samples/s lr: 6.69e-05  
[09/23 09:57:41] lb.utils.events INFO:  eta: 2:30:26  iteration: 317599/375342  consumed_samples: 325222400  total_loss: 3.051  time: 0.3443 s/iter  data_time: 0.2112 s/iter total_throughput: 2974.30 samples/s lr: 6.67e-05  
[09/23 09:58:15] lb.utils.events INFO:  eta: 2:30:05  iteration: 317699/375342  consumed_samples: 325324800  total_loss: 3.06  time: 0.3443 s/iter  data_time: 0.2197 s/iter total_throughput: 2974.31 samples/s lr: 6.65e-05  
[09/23 09:58:49] lb.utils.events INFO:  eta: 2:30:15  iteration: 317799/375342  consumed_samples: 325427200  total_loss: 3.04  time: 0.3443 s/iter  data_time: 0.2058 s/iter total_throughput: 2974.32 samples/s lr: 6.63e-05  
[09/23 09:59:23] lb.utils.events INFO:  eta: 2:30:32  iteration: 317899/375342  consumed_samples: 325529600  total_loss: 3.021  time: 0.3443 s/iter  data_time: 0.2055 s/iter total_throughput: 2974.33 samples/s lr: 6.61e-05  
[09/23 09:59:57] lb.utils.events INFO:  eta: 2:29:59  iteration: 317999/375342  consumed_samples: 325632000  total_loss: 3.038  time: 0.3443 s/iter  data_time: 0.2085 s/iter total_throughput: 2974.33 samples/s lr: 6.59e-05  
[09/23 10:00:32] lb.utils.events INFO:  eta: 2:29:50  iteration: 318099/375342  consumed_samples: 325734400  total_loss: 3.039  time: 0.3443 s/iter  data_time: 0.2161 s/iter total_throughput: 2974.33 samples/s lr: 6.57e-05  
[09/23 10:01:06] lb.utils.events INFO:  eta: 2:29:28  iteration: 318199/375342  consumed_samples: 325836800  total_loss: 3.047  time: 0.3443 s/iter  data_time: 0.2134 s/iter total_throughput: 2974.32 samples/s lr: 6.55e-05  
[09/23 10:01:41] lb.utils.events INFO:  eta: 2:29:13  iteration: 318299/375342  consumed_samples: 325939200  total_loss: 3.064  time: 0.3443 s/iter  data_time: 0.2347 s/iter total_throughput: 2974.32 samples/s lr: 6.54e-05  
[09/23 10:02:15] lb.utils.events INFO:  eta: 2:29:03  iteration: 318399/375342  consumed_samples: 326041600  total_loss: 3.04  time: 0.3443 s/iter  data_time: 0.2283 s/iter total_throughput: 2974.32 samples/s lr: 6.52e-05  
[09/23 10:02:50] lb.utils.events INFO:  eta: 2:28:36  iteration: 318499/375342  consumed_samples: 326144000  total_loss: 3.032  time: 0.3443 s/iter  data_time: 0.2295 s/iter total_throughput: 2974.30 samples/s lr: 6.50e-05  
[09/23 10:03:24] lb.utils.events INFO:  eta: 2:28:32  iteration: 318599/375342  consumed_samples: 326246400  total_loss: 3.047  time: 0.3443 s/iter  data_time: 0.2229 s/iter total_throughput: 2974.31 samples/s lr: 6.48e-05  
[09/23 10:03:59] lb.utils.events INFO:  eta: 2:28:22  iteration: 318699/375342  consumed_samples: 326348800  total_loss: 3.052  time: 0.3443 s/iter  data_time: 0.2094 s/iter total_throughput: 2974.32 samples/s lr: 6.46e-05  
[09/23 10:04:33] lb.utils.events INFO:  eta: 2:27:48  iteration: 318799/375342  consumed_samples: 326451200  total_loss: 3.054  time: 0.3443 s/iter  data_time: 0.2163 s/iter total_throughput: 2974.32 samples/s lr: 6.44e-05  
[09/23 10:05:07] lb.utils.events INFO:  eta: 2:27:04  iteration: 318899/375342  consumed_samples: 326553600  total_loss: 3.039  time: 0.3443 s/iter  data_time: 0.2145 s/iter total_throughput: 2974.32 samples/s lr: 6.42e-05  
[09/23 10:05:42] lb.utils.events INFO:  eta: 2:27:01  iteration: 318999/375342  consumed_samples: 326656000  total_loss: 3.037  time: 0.3443 s/iter  data_time: 0.2177 s/iter total_throughput: 2974.33 samples/s lr: 6.40e-05  
[09/23 10:06:16] lb.utils.events INFO:  eta: 2:26:34  iteration: 319099/375342  consumed_samples: 326758400  total_loss: 3.04  time: 0.3443 s/iter  data_time: 0.2156 s/iter total_throughput: 2974.33 samples/s lr: 6.38e-05  
[09/23 10:06:50] lb.utils.events INFO:  eta: 2:26:20  iteration: 319199/375342  consumed_samples: 326860800  total_loss: 3.047  time: 0.3443 s/iter  data_time: 0.2127 s/iter total_throughput: 2974.34 samples/s lr: 6.37e-05  
[09/23 10:07:25] lb.utils.events INFO:  eta: 2:25:49  iteration: 319299/375342  consumed_samples: 326963200  total_loss: 3.05  time: 0.3443 s/iter  data_time: 0.2196 s/iter total_throughput: 2974.33 samples/s lr: 6.35e-05  
[09/23 10:07:59] lb.utils.events INFO:  eta: 2:25:09  iteration: 319399/375342  consumed_samples: 327065600  total_loss: 3.036  time: 0.3443 s/iter  data_time: 0.2096 s/iter total_throughput: 2974.33 samples/s lr: 6.33e-05  
[09/23 10:08:33] lb.utils.events INFO:  eta: 2:25:21  iteration: 319499/375342  consumed_samples: 327168000  total_loss: 3.029  time: 0.3443 s/iter  data_time: 0.2092 s/iter total_throughput: 2974.34 samples/s lr: 6.31e-05  
[09/23 10:09:07] lb.utils.events INFO:  eta: 2:24:56  iteration: 319599/375342  consumed_samples: 327270400  total_loss: 3.035  time: 0.3443 s/iter  data_time: 0.2094 s/iter total_throughput: 2974.35 samples/s lr: 6.29e-05  
[09/23 10:09:42] lb.utils.events INFO:  eta: 2:24:25  iteration: 319699/375342  consumed_samples: 327372800  total_loss: 3.062  time: 0.3443 s/iter  data_time: 0.2130 s/iter total_throughput: 2974.36 samples/s lr: 6.27e-05  
[09/23 10:10:16] lb.utils.events INFO:  eta: 2:24:18  iteration: 319799/375342  consumed_samples: 327475200  total_loss: 3.046  time: 0.3443 s/iter  data_time: 0.2180 s/iter total_throughput: 2974.36 samples/s lr: 6.25e-05  
[09/23 10:10:50] lb.utils.events INFO:  eta: 2:23:54  iteration: 319899/375342  consumed_samples: 327577600  total_loss: 3.034  time: 0.3443 s/iter  data_time: 0.2162 s/iter total_throughput: 2974.36 samples/s lr: 6.23e-05  
[09/23 10:11:25] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0319999
[09/23 10:11:26] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/23 10:11:26] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/23 10:11:30] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.1020 s/iter. Inference: 0.1630 s/iter. Eval: 0.0020 s/iter. Total: 0.2669 s/iter. ETA=0:00:09
[09/23 10:11:35] lb.evaluation.evaluator INFO: Inference done 28672/50000. Dataloading: 0.1099 s/iter. Inference: 0.1773 s/iter. Eval: 0.0020 s/iter. Total: 0.2893 s/iter. ETA=0:00:05
[09/23 10:11:40] lb.evaluation.evaluator INFO: Inference done 47104/50000. Dataloading: 0.1183 s/iter. Inference: 0.1712 s/iter. Eval: 0.0020 s/iter. Total: 0.2916 s/iter. ETA=0:00:00
[09/23 10:11:41] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/23 10:11:41] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.457130 (0.000249 s / iter per device, on 8 devices)
[09/23 10:11:41] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000150 s / iter per device, on 8 devices)
[09/23 10:11:41] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/23 10:11:41] lb.evaluation.utils INFO: copypaste: Acc@1=79.56400000000001
[09/23 10:11:41] lb.evaluation.utils INFO: copypaste: Acc@5=94.39800000000001
[09/23 10:11:41] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 79.56400, better than last best score 79.51000 @ iteration 314999.
[09/23 10:11:41] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/23 10:11:41] lb.utils.events INFO:  eta: 2:23:24  iteration: 319999/375342  consumed_samples: 327680000  total_loss: 3.04  time: 0.3443 s/iter  data_time: 0.2119 s/iter total_throughput: 2974.36 samples/s lr: 6.22e-05  
[09/23 10:12:13] lb.utils.events INFO:  eta: 2:24:15  iteration: 320099/375342  consumed_samples: 327782400  total_loss: 3.021  time: 0.3443 s/iter  data_time: 0.2071 s/iter total_throughput: 2974.42 samples/s lr: 6.20e-05  
[09/23 10:12:48] lb.utils.events INFO:  eta: 2:23:52  iteration: 320199/375342  consumed_samples: 327884800  total_loss: 3.027  time: 0.3443 s/iter  data_time: 0.2149 s/iter total_throughput: 2974.42 samples/s lr: 6.18e-05  
[09/23 10:13:23] lb.utils.events INFO:  eta: 2:23:40  iteration: 320299/375342  consumed_samples: 327987200  total_loss: 3.055  time: 0.3443 s/iter  data_time: 0.2188 s/iter total_throughput: 2974.41 samples/s lr: 6.16e-05  
[09/23 10:13:57] lb.utils.events INFO:  eta: 2:23:35  iteration: 320399/375342  consumed_samples: 328089600  total_loss: 3.038  time: 0.3443 s/iter  data_time: 0.2071 s/iter total_throughput: 2974.42 samples/s lr: 6.14e-05  
[09/23 10:14:31] lb.utils.events INFO:  eta: 2:23:15  iteration: 320499/375342  consumed_samples: 328192000  total_loss: 3.032  time: 0.3443 s/iter  data_time: 0.2134 s/iter total_throughput: 2974.42 samples/s lr: 6.12e-05  
[09/23 10:15:05] lb.utils.events INFO:  eta: 2:23:26  iteration: 320599/375342  consumed_samples: 328294400  total_loss: 3.041  time: 0.3443 s/iter  data_time: 0.2050 s/iter total_throughput: 2974.43 samples/s lr: 6.11e-05  
[09/23 10:15:39] lb.utils.events INFO:  eta: 2:22:56  iteration: 320699/375342  consumed_samples: 328396800  total_loss: 3.049  time: 0.3443 s/iter  data_time: 0.2169 s/iter total_throughput: 2974.44 samples/s lr: 6.09e-05  
[09/23 10:16:14] lb.utils.events INFO:  eta: 2:22:16  iteration: 320799/375342  consumed_samples: 328499200  total_loss: 3.027  time: 0.3443 s/iter  data_time: 0.2182 s/iter total_throughput: 2974.43 samples/s lr: 6.07e-05  
[09/23 10:16:48] lb.utils.events INFO:  eta: 2:22:02  iteration: 320899/375342  consumed_samples: 328601600  total_loss: 3.019  time: 0.3443 s/iter  data_time: 0.2103 s/iter total_throughput: 2974.45 samples/s lr: 6.05e-05  
[09/23 10:17:22] lb.utils.events INFO:  eta: 2:22:23  iteration: 320999/375342  consumed_samples: 328704000  total_loss: 3.024  time: 0.3443 s/iter  data_time: 0.2116 s/iter total_throughput: 2974.47 samples/s lr: 6.03e-05  
[09/23 10:17:56] lb.utils.events INFO:  eta: 2:20:57  iteration: 321099/375342  consumed_samples: 328806400  total_loss: 3.031  time: 0.3443 s/iter  data_time: 0.2266 s/iter total_throughput: 2974.48 samples/s lr: 6.01e-05  
[09/23 10:18:30] lb.utils.events INFO:  eta: 2:20:44  iteration: 321199/375342  consumed_samples: 328908800  total_loss: 3.041  time: 0.3443 s/iter  data_time: 0.2263 s/iter total_throughput: 2974.48 samples/s lr: 6.00e-05  
[09/23 10:19:04] lb.utils.events INFO:  eta: 2:20:38  iteration: 321299/375342  consumed_samples: 329011200  total_loss: 3.039  time: 0.3443 s/iter  data_time: 0.2090 s/iter total_throughput: 2974.49 samples/s lr: 5.98e-05  
[09/23 10:19:38] lb.utils.events INFO:  eta: 2:20:13  iteration: 321399/375342  consumed_samples: 329113600  total_loss: 3.04  time: 0.3443 s/iter  data_time: 0.2092 s/iter total_throughput: 2974.50 samples/s lr: 5.96e-05  
[09/23 10:20:12] lb.utils.events INFO:  eta: 2:20:19  iteration: 321499/375342  consumed_samples: 329216000  total_loss: 3.039  time: 0.3443 s/iter  data_time: 0.2068 s/iter total_throughput: 2974.52 samples/s lr: 5.94e-05  
[09/23 10:20:46] lb.utils.events INFO:  eta: 2:20:03  iteration: 321599/375342  consumed_samples: 329318400  total_loss: 3.019  time: 0.3443 s/iter  data_time: 0.2112 s/iter total_throughput: 2974.53 samples/s lr: 5.92e-05  
[09/23 10:21:20] lb.utils.events INFO:  eta: 2:19:50  iteration: 321699/375342  consumed_samples: 329420800  total_loss: 3.008  time: 0.3443 s/iter  data_time: 0.2233 s/iter total_throughput: 2974.53 samples/s lr: 5.91e-05  
[09/23 10:21:54] lb.utils.events INFO:  eta: 2:19:47  iteration: 321799/375342  consumed_samples: 329523200  total_loss: 3.026  time: 0.3443 s/iter  data_time: 0.2165 s/iter total_throughput: 2974.55 samples/s lr: 5.89e-05  
[09/23 10:22:28] lb.utils.events INFO:  eta: 2:19:41  iteration: 321899/375342  consumed_samples: 329625600  total_loss: 3.018  time: 0.3443 s/iter  data_time: 0.2057 s/iter total_throughput: 2974.57 samples/s lr: 5.87e-05  
[09/23 10:23:02] lb.utils.events INFO:  eta: 2:19:18  iteration: 321999/375342  consumed_samples: 329728000  total_loss: 3.029  time: 0.3443 s/iter  data_time: 0.2234 s/iter total_throughput: 2974.57 samples/s lr: 5.85e-05  
[09/23 10:23:36] lb.utils.events INFO:  eta: 2:18:54  iteration: 322099/375342  consumed_samples: 329830400  total_loss: 3.048  time: 0.3443 s/iter  data_time: 0.2111 s/iter total_throughput: 2974.58 samples/s lr: 5.83e-05  
[09/23 10:24:11] lb.utils.events INFO:  eta: 2:18:35  iteration: 322199/375342  consumed_samples: 329932800  total_loss: 3.047  time: 0.3443 s/iter  data_time: 0.2167 s/iter total_throughput: 2974.58 samples/s lr: 5.82e-05  
[09/23 10:24:45] lb.utils.events INFO:  eta: 2:18:24  iteration: 322299/375342  consumed_samples: 330035200  total_loss: 3.06  time: 0.3443 s/iter  data_time: 0.2194 s/iter total_throughput: 2974.58 samples/s lr: 5.80e-05  
[09/23 10:25:20] lb.utils.events INFO:  eta: 2:18:05  iteration: 322399/375342  consumed_samples: 330137600  total_loss: 3.046  time: 0.3443 s/iter  data_time: 0.2198 s/iter total_throughput: 2974.58 samples/s lr: 5.78e-05  
[09/23 10:25:54] lb.utils.events INFO:  eta: 2:17:41  iteration: 322499/375342  consumed_samples: 330240000  total_loss: 3.033  time: 0.3443 s/iter  data_time: 0.2245 s/iter total_throughput: 2974.57 samples/s lr: 5.76e-05  
[09/23 10:26:30] lb.utils.events INFO:  eta: 2:16:59  iteration: 322599/375342  consumed_samples: 330342400  total_loss: 3.035  time: 0.3443 s/iter  data_time: 0.2218 s/iter total_throughput: 2974.55 samples/s lr: 5.75e-05  
[09/23 10:27:05] lb.utils.events INFO:  eta: 2:16:46  iteration: 322699/375342  consumed_samples: 330444800  total_loss: 3.031  time: 0.3443 s/iter  data_time: 0.2281 s/iter total_throughput: 2974.53 samples/s lr: 5.73e-05  
[09/23 10:27:40] lb.utils.events INFO:  eta: 2:16:31  iteration: 322799/375342  consumed_samples: 330547200  total_loss: 3.025  time: 0.3443 s/iter  data_time: 0.2217 s/iter total_throughput: 2974.52 samples/s lr: 5.71e-05  
[09/23 10:28:14] lb.utils.events INFO:  eta: 2:16:11  iteration: 322899/375342  consumed_samples: 330649600  total_loss: 3.025  time: 0.3443 s/iter  data_time: 0.2329 s/iter total_throughput: 2974.51 samples/s lr: 5.69e-05  
[09/23 10:28:49] lb.utils.events INFO:  eta: 2:16:04  iteration: 322999/375342  consumed_samples: 330752000  total_loss: 3.017  time: 0.3443 s/iter  data_time: 0.2225 s/iter total_throughput: 2974.51 samples/s lr: 5.67e-05  
[09/23 10:29:23] lb.utils.events INFO:  eta: 2:16:14  iteration: 323099/375342  consumed_samples: 330854400  total_loss: 3.021  time: 0.3443 s/iter  data_time: 0.2148 s/iter total_throughput: 2974.51 samples/s lr: 5.66e-05  
[09/23 10:29:58] lb.utils.events INFO:  eta: 2:16:07  iteration: 323199/375342  consumed_samples: 330956800  total_loss: 3.028  time: 0.3443 s/iter  data_time: 0.2225 s/iter total_throughput: 2974.51 samples/s lr: 5.64e-05  
[09/23 10:30:33] lb.utils.events INFO:  eta: 2:15:42  iteration: 323299/375342  consumed_samples: 331059200  total_loss: 3.021  time: 0.3443 s/iter  data_time: 0.2276 s/iter total_throughput: 2974.50 samples/s lr: 5.62e-05  
[09/23 10:31:08] lb.utils.events INFO:  eta: 2:15:43  iteration: 323399/375342  consumed_samples: 331161600  total_loss: 3.028  time: 0.3443 s/iter  data_time: 0.2278 s/iter total_throughput: 2974.48 samples/s lr: 5.60e-05  
[09/23 10:31:42] lb.utils.events INFO:  eta: 2:15:21  iteration: 323499/375342  consumed_samples: 331264000  total_loss: 3.026  time: 0.3443 s/iter  data_time: 0.2314 s/iter total_throughput: 2974.48 samples/s lr: 5.59e-05  
[09/23 10:32:17] lb.utils.events INFO:  eta: 2:15:17  iteration: 323599/375342  consumed_samples: 331366400  total_loss: 3.021  time: 0.3443 s/iter  data_time: 0.2214 s/iter total_throughput: 2974.48 samples/s lr: 5.57e-05  
[09/23 10:32:51] lb.utils.events INFO:  eta: 2:15:01  iteration: 323699/375342  consumed_samples: 331468800  total_loss: 3.014  time: 0.3443 s/iter  data_time: 0.2215 s/iter total_throughput: 2974.47 samples/s lr: 5.55e-05  
[09/23 10:33:26] lb.utils.events INFO:  eta: 2:15:07  iteration: 323799/375342  consumed_samples: 331571200  total_loss: 3.008  time: 0.3443 s/iter  data_time: 0.2178 s/iter total_throughput: 2974.46 samples/s lr: 5.54e-05  
[09/23 10:34:01] lb.utils.events INFO:  eta: 2:14:31  iteration: 323899/375342  consumed_samples: 331673600  total_loss: 3.008  time: 0.3443 s/iter  data_time: 0.2331 s/iter total_throughput: 2974.45 samples/s lr: 5.52e-05  
[09/23 10:34:36] lb.utils.events INFO:  eta: 2:14:03  iteration: 323999/375342  consumed_samples: 331776000  total_loss: 3.023  time: 0.3443 s/iter  data_time: 0.2204 s/iter total_throughput: 2974.44 samples/s lr: 5.50e-05  
[09/23 10:35:10] lb.utils.events INFO:  eta: 2:13:28  iteration: 324099/375342  consumed_samples: 331878400  total_loss: 3.041  time: 0.3443 s/iter  data_time: 0.2201 s/iter total_throughput: 2974.43 samples/s lr: 5.48e-05  
[09/23 10:35:45] lb.utils.events INFO:  eta: 2:12:53  iteration: 324199/375342  consumed_samples: 331980800  total_loss: 3.032  time: 0.3443 s/iter  data_time: 0.2186 s/iter total_throughput: 2974.42 samples/s lr: 5.47e-05  
[09/23 10:36:20] lb.utils.events INFO:  eta: 2:12:41  iteration: 324299/375342  consumed_samples: 332083200  total_loss: 3.023  time: 0.3443 s/iter  data_time: 0.2243 s/iter total_throughput: 2974.42 samples/s lr: 5.45e-05  
[09/23 10:36:55] lb.utils.events INFO:  eta: 2:12:11  iteration: 324399/375342  consumed_samples: 332185600  total_loss: 3.011  time: 0.3443 s/iter  data_time: 0.2184 s/iter total_throughput: 2974.41 samples/s lr: 5.43e-05  
[09/23 10:37:30] lb.utils.events INFO:  eta: 2:11:50  iteration: 324499/375342  consumed_samples: 332288000  total_loss: 3.011  time: 0.3443 s/iter  data_time: 0.2248 s/iter total_throughput: 2974.39 samples/s lr: 5.41e-05  
[09/23 10:38:05] lb.utils.events INFO:  eta: 2:11:29  iteration: 324599/375342  consumed_samples: 332390400  total_loss: 3.035  time: 0.3443 s/iter  data_time: 0.2245 s/iter total_throughput: 2974.38 samples/s lr: 5.40e-05  
[09/23 10:38:39] lb.utils.events INFO:  eta: 2:11:20  iteration: 324699/375342  consumed_samples: 332492800  total_loss: 3.017  time: 0.3443 s/iter  data_time: 0.2288 s/iter total_throughput: 2974.38 samples/s lr: 5.38e-05  
[09/23 10:39:14] lb.utils.events INFO:  eta: 2:10:43  iteration: 324799/375342  consumed_samples: 332595200  total_loss: 3.012  time: 0.3443 s/iter  data_time: 0.2266 s/iter total_throughput: 2974.36 samples/s lr: 5.36e-05  
[09/23 10:39:49] lb.utils.events INFO:  eta: 2:10:26  iteration: 324899/375342  consumed_samples: 332697600  total_loss: 3.03  time: 0.3443 s/iter  data_time: 0.2277 s/iter total_throughput: 2974.35 samples/s lr: 5.35e-05  
[09/23 10:40:24] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0324999
[09/23 10:40:24] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/23 10:40:24] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/23 10:40:28] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0867 s/iter. Inference: 0.1613 s/iter. Eval: 0.0022 s/iter. Total: 0.2502 s/iter. ETA=0:00:09
[09/23 10:40:34] lb.evaluation.evaluator INFO: Inference done 29696/50000. Dataloading: 0.1354 s/iter. Inference: 0.1666 s/iter. Eval: 0.0022 s/iter. Total: 0.3042 s/iter. ETA=0:00:05
[09/23 10:40:40] lb.evaluation.evaluator INFO: Inference done 50000/50000. Dataloading: 0.1214 s/iter. Inference: 0.1645 s/iter. Eval: 0.0021 s/iter. Total: 0.2881 s/iter. ETA=0:00:00
[09/23 10:40:40] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/23 10:40:40] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.682062 (0.000254 s / iter per device, on 8 devices)
[09/23 10:40:40] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000145 s / iter per device, on 8 devices)
[09/23 10:40:40] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/23 10:40:40] lb.evaluation.utils INFO: copypaste: Acc@1=79.674
[09/23 10:40:40] lb.evaluation.utils INFO: copypaste: Acc@5=94.498
[09/23 10:40:40] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 79.67400, better than last best score 79.56400 @ iteration 319999.
[09/23 10:40:40] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/23 10:40:40] lb.utils.events INFO:  eta: 2:10:17  iteration: 324999/375342  consumed_samples: 332800000  total_loss: 3.027  time: 0.3443 s/iter  data_time: 0.2150 s/iter total_throughput: 2974.35 samples/s lr: 5.33e-05  
[09/23 10:41:13] lb.utils.events INFO:  eta: 2:10:26  iteration: 325099/375342  consumed_samples: 332902400  total_loss: 3.021  time: 0.3443 s/iter  data_time: 0.2154 s/iter total_throughput: 2974.40 samples/s lr: 5.31e-05  
[09/23 10:41:47] lb.utils.events INFO:  eta: 2:10:47  iteration: 325199/375342  consumed_samples: 333004800  total_loss: 3.019  time: 0.3443 s/iter  data_time: 0.2207 s/iter total_throughput: 2974.40 samples/s lr: 5.30e-05  
[09/23 10:42:22] lb.utils.events INFO:  eta: 2:10:36  iteration: 325299/375342  consumed_samples: 333107200  total_loss: 3.01  time: 0.3443 s/iter  data_time: 0.2171 s/iter total_throughput: 2974.39 samples/s lr: 5.28e-05  
[09/23 10:42:57] lb.utils.events INFO:  eta: 2:10:11  iteration: 325399/375342  consumed_samples: 333209600  total_loss: 3.002  time: 0.3443 s/iter  data_time: 0.2313 s/iter total_throughput: 2974.38 samples/s lr: 5.26e-05  
[09/23 10:43:32] lb.utils.events INFO:  eta: 2:09:53  iteration: 325499/375342  consumed_samples: 333312000  total_loss: 3.008  time: 0.3443 s/iter  data_time: 0.2234 s/iter total_throughput: 2974.37 samples/s lr: 5.25e-05  
[09/23 10:44:07] lb.utils.events INFO:  eta: 2:09:42  iteration: 325599/375342  consumed_samples: 333414400  total_loss: 3.013  time: 0.3443 s/iter  data_time: 0.2258 s/iter total_throughput: 2974.36 samples/s lr: 5.23e-05  
[09/23 10:44:41] lb.utils.events INFO:  eta: 2:09:25  iteration: 325699/375342  consumed_samples: 333516800  total_loss: 3.026  time: 0.3443 s/iter  data_time: 0.2194 s/iter total_throughput: 2974.36 samples/s lr: 5.21e-05  
[09/23 10:45:16] lb.utils.events INFO:  eta: 2:09:33  iteration: 325799/375342  consumed_samples: 333619200  total_loss: 3.023  time: 0.3443 s/iter  data_time: 0.2322 s/iter total_throughput: 2974.34 samples/s lr: 5.20e-05  
[09/23 10:45:50] lb.utils.events INFO:  eta: 2:09:46  iteration: 325899/375342  consumed_samples: 333721600  total_loss: 3.004  time: 0.3443 s/iter  data_time: 0.2224 s/iter total_throughput: 2974.34 samples/s lr: 5.18e-05  
[09/23 10:46:25] lb.utils.events INFO:  eta: 2:09:27  iteration: 325999/375342  consumed_samples: 333824000  total_loss: 3.014  time: 0.3443 s/iter  data_time: 0.2270 s/iter total_throughput: 2974.33 samples/s lr: 5.16e-05  
[09/23 10:47:00] lb.utils.events INFO:  eta: 2:08:54  iteration: 326099/375342  consumed_samples: 333926400  total_loss: 3.016  time: 0.3443 s/iter  data_time: 0.2166 s/iter total_throughput: 2974.34 samples/s lr: 5.15e-05  
[09/23 10:47:34] lb.utils.events INFO:  eta: 2:08:25  iteration: 326199/375342  consumed_samples: 334028800  total_loss: 3.004  time: 0.3443 s/iter  data_time: 0.2207 s/iter total_throughput: 2974.33 samples/s lr: 5.13e-05  
[09/23 10:48:09] lb.utils.events INFO:  eta: 2:07:52  iteration: 326299/375342  consumed_samples: 334131200  total_loss: 3.021  time: 0.3443 s/iter  data_time: 0.2256 s/iter total_throughput: 2974.33 samples/s lr: 5.11e-05  
[09/23 10:48:43] lb.utils.events INFO:  eta: 2:07:48  iteration: 326399/375342  consumed_samples: 334233600  total_loss: 3.014  time: 0.3443 s/iter  data_time: 0.2136 s/iter total_throughput: 2974.33 samples/s lr: 5.10e-05  
[09/23 10:49:18] lb.utils.events INFO:  eta: 2:07:45  iteration: 326499/375342  consumed_samples: 334336000  total_loss: 3.008  time: 0.3443 s/iter  data_time: 0.2197 s/iter total_throughput: 2974.33 samples/s lr: 5.08e-05  
[09/23 10:49:52] lb.utils.events INFO:  eta: 2:07:37  iteration: 326599/375342  consumed_samples: 334438400  total_loss: 3.003  time: 0.3443 s/iter  data_time: 0.2211 s/iter total_throughput: 2974.32 samples/s lr: 5.06e-05  
[09/23 10:50:27] lb.utils.events INFO:  eta: 2:07:24  iteration: 326699/375342  consumed_samples: 334540800  total_loss: 2.999  time: 0.3443 s/iter  data_time: 0.2088 s/iter total_throughput: 2974.31 samples/s lr: 5.05e-05  
[09/23 10:51:03] lb.utils.events INFO:  eta: 2:07:05  iteration: 326799/375342  consumed_samples: 334643200  total_loss: 3.002  time: 0.3443 s/iter  data_time: 0.2263 s/iter total_throughput: 2974.29 samples/s lr: 5.03e-05  
[09/23 10:51:37] lb.utils.events INFO:  eta: 2:06:29  iteration: 326899/375342  consumed_samples: 334745600  total_loss: 3.002  time: 0.3443 s/iter  data_time: 0.2230 s/iter total_throughput: 2974.28 samples/s lr: 5.01e-05  
[09/23 10:52:12] lb.utils.events INFO:  eta: 2:06:26  iteration: 326999/375342  consumed_samples: 334848000  total_loss: 3.003  time: 0.3443 s/iter  data_time: 0.2219 s/iter total_throughput: 2974.28 samples/s lr: 5.00e-05  
[09/23 10:52:47] lb.utils.events INFO:  eta: 2:05:39  iteration: 327099/375342  consumed_samples: 334950400  total_loss: 2.992  time: 0.3443 s/iter  data_time: 0.2177 s/iter total_throughput: 2974.27 samples/s lr: 4.98e-05  
[09/23 10:53:21] lb.utils.events INFO:  eta: 2:05:24  iteration: 327199/375342  consumed_samples: 335052800  total_loss: 3.009  time: 0.3443 s/iter  data_time: 0.2292 s/iter total_throughput: 2974.27 samples/s lr: 4.96e-05  
[09/23 10:53:56] lb.utils.events INFO:  eta: 2:05:08  iteration: 327299/375342  consumed_samples: 335155200  total_loss: 3.031  time: 0.3443 s/iter  data_time: 0.2243 s/iter total_throughput: 2974.25 samples/s lr: 4.95e-05  
[09/23 10:54:31] lb.utils.events INFO:  eta: 2:04:49  iteration: 327399/375342  consumed_samples: 335257600  total_loss: 3.01  time: 0.3443 s/iter  data_time: 0.2229 s/iter total_throughput: 2974.23 samples/s lr: 4.93e-05  
[09/23 10:55:06] lb.utils.events INFO:  eta: 2:04:30  iteration: 327499/375342  consumed_samples: 335360000  total_loss: 2.995  time: 0.3443 s/iter  data_time: 0.2103 s/iter total_throughput: 2974.23 samples/s lr: 4.92e-05  
[09/23 10:55:40] lb.utils.events INFO:  eta: 2:04:10  iteration: 327599/375342  consumed_samples: 335462400  total_loss: 3.017  time: 0.3443 s/iter  data_time: 0.2172 s/iter total_throughput: 2974.23 samples/s lr: 4.90e-05  
[09/23 10:56:15] lb.utils.events INFO:  eta: 2:03:55  iteration: 327699/375342  consumed_samples: 335564800  total_loss: 3.033  time: 0.3443 s/iter  data_time: 0.2141 s/iter total_throughput: 2974.23 samples/s lr: 4.88e-05  
[09/23 10:56:49] lb.utils.events INFO:  eta: 2:03:46  iteration: 327799/375342  consumed_samples: 335667200  total_loss: 3.024  time: 0.3443 s/iter  data_time: 0.2115 s/iter total_throughput: 2974.23 samples/s lr: 4.87e-05  
[09/23 10:57:24] lb.utils.events INFO:  eta: 2:03:34  iteration: 327899/375342  consumed_samples: 335769600  total_loss: 3.023  time: 0.3443 s/iter  data_time: 0.2120 s/iter total_throughput: 2974.23 samples/s lr: 4.85e-05  
[09/23 10:57:58] lb.utils.events INFO:  eta: 2:03:17  iteration: 327999/375342  consumed_samples: 335872000  total_loss: 3.027  time: 0.3443 s/iter  data_time: 0.2274 s/iter total_throughput: 2974.22 samples/s lr: 4.84e-05  
[09/23 10:58:34] lb.utils.events INFO:  eta: 2:03:06  iteration: 328099/375342  consumed_samples: 335974400  total_loss: 3.002  time: 0.3443 s/iter  data_time: 0.2226 s/iter total_throughput: 2974.20 samples/s lr: 4.82e-05  
[09/23 10:59:08] lb.utils.events INFO:  eta: 2:03:08  iteration: 328199/375342  consumed_samples: 336076800  total_loss: 3.009  time: 0.3443 s/iter  data_time: 0.2091 s/iter total_throughput: 2974.20 samples/s lr: 4.80e-05  
[09/23 10:59:43] lb.utils.events INFO:  eta: 2:02:47  iteration: 328299/375342  consumed_samples: 336179200  total_loss: 3.021  time: 0.3443 s/iter  data_time: 0.2280 s/iter total_throughput: 2974.19 samples/s lr: 4.79e-05  
[09/23 11:00:18] lb.utils.events INFO:  eta: 2:02:37  iteration: 328399/375342  consumed_samples: 336281600  total_loss: 3.011  time: 0.3443 s/iter  data_time: 0.2225 s/iter total_throughput: 2974.18 samples/s lr: 4.77e-05  
[09/23 11:00:52] lb.utils.events INFO:  eta: 2:02:30  iteration: 328499/375342  consumed_samples: 336384000  total_loss: 3.004  time: 0.3443 s/iter  data_time: 0.2092 s/iter total_throughput: 2974.18 samples/s lr: 4.76e-05  
[09/23 11:01:26] lb.utils.events INFO:  eta: 2:02:00  iteration: 328599/375342  consumed_samples: 336486400  total_loss: 3.009  time: 0.3443 s/iter  data_time: 0.2115 s/iter total_throughput: 2974.18 samples/s lr: 4.74e-05  
[09/23 11:02:01] lb.utils.events INFO:  eta: 2:01:42  iteration: 328699/375342  consumed_samples: 336588800  total_loss: 3.025  time: 0.3443 s/iter  data_time: 0.2126 s/iter total_throughput: 2974.18 samples/s lr: 4.72e-05  
[09/23 11:02:35] lb.utils.events INFO:  eta: 2:01:22  iteration: 328799/375342  consumed_samples: 336691200  total_loss: 3.004  time: 0.3443 s/iter  data_time: 0.2181 s/iter total_throughput: 2974.18 samples/s lr: 4.71e-05  
[09/23 11:03:09] lb.utils.events INFO:  eta: 2:01:17  iteration: 328899/375342  consumed_samples: 336793600  total_loss: 2.998  time: 0.3443 s/iter  data_time: 0.2038 s/iter total_throughput: 2974.19 samples/s lr: 4.69e-05  
[09/23 11:03:44] lb.utils.events INFO:  eta: 2:01:11  iteration: 328999/375342  consumed_samples: 336896000  total_loss: 3.014  time: 0.3443 s/iter  data_time: 0.2239 s/iter total_throughput: 2974.19 samples/s lr: 4.68e-05  
[09/23 11:04:18] lb.utils.events INFO:  eta: 2:01:14  iteration: 329099/375342  consumed_samples: 336998400  total_loss: 3.008  time: 0.3443 s/iter  data_time: 0.2321 s/iter total_throughput: 2974.19 samples/s lr: 4.66e-05  
[09/23 11:04:53] lb.utils.events INFO:  eta: 2:00:44  iteration: 329199/375342  consumed_samples: 337100800  total_loss: 3  time: 0.3443 s/iter  data_time: 0.2091 s/iter total_throughput: 2974.18 samples/s lr: 4.65e-05  
[09/23 11:05:27] lb.utils.events INFO:  eta: 2:00:43  iteration: 329299/375342  consumed_samples: 337203200  total_loss: 2.993  time: 0.3443 s/iter  data_time: 0.2229 s/iter total_throughput: 2974.19 samples/s lr: 4.63e-05  
[09/23 11:06:02] lb.utils.events INFO:  eta: 2:00:31  iteration: 329399/375342  consumed_samples: 337305600  total_loss: 3.008  time: 0.3443 s/iter  data_time: 0.2151 s/iter total_throughput: 2974.19 samples/s lr: 4.61e-05  
[09/23 11:06:36] lb.utils.events INFO:  eta: 2:00:03  iteration: 329499/375342  consumed_samples: 337408000  total_loss: 3.01  time: 0.3443 s/iter  data_time: 0.2210 s/iter total_throughput: 2974.18 samples/s lr: 4.60e-05  
[09/23 11:07:11] lb.utils.events INFO:  eta: 1:59:53  iteration: 329599/375342  consumed_samples: 337510400  total_loss: 3.009  time: 0.3443 s/iter  data_time: 0.2170 s/iter total_throughput: 2974.18 samples/s lr: 4.58e-05  
[09/23 11:07:46] lb.utils.events INFO:  eta: 1:59:52  iteration: 329699/375342  consumed_samples: 337612800  total_loss: 2.984  time: 0.3443 s/iter  data_time: 0.2125 s/iter total_throughput: 2974.17 samples/s lr: 4.57e-05  
[09/23 11:08:20] lb.utils.events INFO:  eta: 1:59:35  iteration: 329799/375342  consumed_samples: 337715200  total_loss: 2.991  time: 0.3443 s/iter  data_time: 0.2200 s/iter total_throughput: 2974.17 samples/s lr: 4.55e-05  
[09/23 11:08:54] lb.utils.events INFO:  eta: 1:59:09  iteration: 329899/375342  consumed_samples: 337817600  total_loss: 3.005  time: 0.3443 s/iter  data_time: 0.2152 s/iter total_throughput: 2974.18 samples/s lr: 4.54e-05  
[09/23 11:09:29] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0329999
[09/23 11:09:29] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/23 11:09:29] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/23 11:09:34] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0922 s/iter. Inference: 0.1673 s/iter. Eval: 0.0023 s/iter. Total: 0.2619 s/iter. ETA=0:00:09
[09/23 11:09:39] lb.evaluation.evaluator INFO: Inference done 28672/50000. Dataloading: 0.0950 s/iter. Inference: 0.1894 s/iter. Eval: 0.0021 s/iter. Total: 0.2866 s/iter. ETA=0:00:05
[09/23 11:09:44] lb.evaluation.evaluator INFO: Inference done 46080/50000. Dataloading: 0.0976 s/iter. Inference: 0.1936 s/iter. Eval: 0.0021 s/iter. Total: 0.2934 s/iter. ETA=0:00:00
[09/23 11:09:45] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/23 11:09:45] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.655811 (0.000253 s / iter per device, on 8 devices)
[09/23 11:09:45] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:08 (0.000171 s / iter per device, on 8 devices)
[09/23 11:09:45] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/23 11:09:45] lb.evaluation.utils INFO: copypaste: Acc@1=79.744
[09/23 11:09:45] lb.evaluation.utils INFO: copypaste: Acc@5=94.50800000000001
[09/23 11:09:45] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 79.74400, better than last best score 79.67400 @ iteration 324999.
[09/23 11:09:45] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/23 11:09:45] lb.utils.events INFO:  eta: 1:58:49  iteration: 329999/375342  consumed_samples: 337920000  total_loss: 3.004  time: 0.3443 s/iter  data_time: 0.2127 s/iter total_throughput: 2974.18 samples/s lr: 4.52e-05  
[09/23 11:10:18] lb.utils.events INFO:  eta: 1:59:05  iteration: 330099/375342  consumed_samples: 338022400  total_loss: 3.004  time: 0.3443 s/iter  data_time: 0.2249 s/iter total_throughput: 2974.22 samples/s lr: 4.51e-05  
[09/23 11:10:52] lb.utils.events INFO:  eta: 1:58:48  iteration: 330199/375342  consumed_samples: 338124800  total_loss: 3.004  time: 0.3443 s/iter  data_time: 0.2159 s/iter total_throughput: 2974.23 samples/s lr: 4.49e-05  
[09/23 11:11:27] lb.utils.events INFO:  eta: 1:58:13  iteration: 330299/375342  consumed_samples: 338227200  total_loss: 3.02  time: 0.3443 s/iter  data_time: 0.2081 s/iter total_throughput: 2974.22 samples/s lr: 4.48e-05  
[09/23 11:12:01] lb.utils.events INFO:  eta: 1:58:11  iteration: 330399/375342  consumed_samples: 338329600  total_loss: 3.02  time: 0.3443 s/iter  data_time: 0.2200 s/iter total_throughput: 2974.23 samples/s lr: 4.46e-05  
[09/23 11:12:36] lb.utils.events INFO:  eta: 1:57:51  iteration: 330499/375342  consumed_samples: 338432000  total_loss: 3.001  time: 0.3443 s/iter  data_time: 0.2234 s/iter total_throughput: 2974.22 samples/s lr: 4.45e-05  
[09/23 11:13:10] lb.utils.events INFO:  eta: 1:57:48  iteration: 330599/375342  consumed_samples: 338534400  total_loss: 3.002  time: 0.3443 s/iter  data_time: 0.2101 s/iter total_throughput: 2974.22 samples/s lr: 4.43e-05  
[09/23 11:13:45] lb.utils.events INFO:  eta: 1:57:17  iteration: 330699/375342  consumed_samples: 338636800  total_loss: 3.004  time: 0.3443 s/iter  data_time: 0.2162 s/iter total_throughput: 2974.23 samples/s lr: 4.42e-05  
[09/23 11:14:19] lb.utils.events INFO:  eta: 1:57:13  iteration: 330799/375342  consumed_samples: 338739200  total_loss: 3.004  time: 0.3443 s/iter  data_time: 0.2194 s/iter total_throughput: 2974.22 samples/s lr: 4.40e-05  
[09/23 11:14:54] lb.utils.events INFO:  eta: 1:56:42  iteration: 330899/375342  consumed_samples: 338841600  total_loss: 3.008  time: 0.3443 s/iter  data_time: 0.2274 s/iter total_throughput: 2974.21 samples/s lr: 4.39e-05  
[09/23 11:15:28] lb.utils.events INFO:  eta: 1:56:22  iteration: 330999/375342  consumed_samples: 338944000  total_loss: 3.012  time: 0.3443 s/iter  data_time: 0.2251 s/iter total_throughput: 2974.21 samples/s lr: 4.37e-05  
[09/23 11:16:03] lb.utils.events INFO:  eta: 1:55:43  iteration: 331099/375342  consumed_samples: 339046400  total_loss: 3.011  time: 0.3443 s/iter  data_time: 0.2232 s/iter total_throughput: 2974.22 samples/s lr: 4.36e-05  
[09/23 11:16:37] lb.utils.events INFO:  eta: 1:55:27  iteration: 331199/375342  consumed_samples: 339148800  total_loss: 3.017  time: 0.3443 s/iter  data_time: 0.2081 s/iter total_throughput: 2974.22 samples/s lr: 4.34e-05  
[09/23 11:17:12] lb.utils.events INFO:  eta: 1:55:24  iteration: 331299/375342  consumed_samples: 339251200  total_loss: 3  time: 0.3443 s/iter  data_time: 0.2062 s/iter total_throughput: 2974.22 samples/s lr: 4.33e-05  
[09/23 11:17:46] lb.utils.events INFO:  eta: 1:55:06  iteration: 331399/375342  consumed_samples: 339353600  total_loss: 2.984  time: 0.3443 s/iter  data_time: 0.2174 s/iter total_throughput: 2974.21 samples/s lr: 4.31e-05  
[09/23 11:18:20] lb.utils.events INFO:  eta: 1:54:55  iteration: 331499/375342  consumed_samples: 339456000  total_loss: 2.994  time: 0.3443 s/iter  data_time: 0.2204 s/iter total_throughput: 2974.23 samples/s lr: 4.30e-05  
[09/23 11:18:55] lb.utils.events INFO:  eta: 1:54:26  iteration: 331599/375342  consumed_samples: 339558400  total_loss: 2.997  time: 0.3443 s/iter  data_time: 0.2164 s/iter total_throughput: 2974.22 samples/s lr: 4.28e-05  
[09/23 11:19:30] lb.utils.events INFO:  eta: 1:54:01  iteration: 331699/375342  consumed_samples: 339660800  total_loss: 2.993  time: 0.3443 s/iter  data_time: 0.2200 s/iter total_throughput: 2974.21 samples/s lr: 4.27e-05  
[09/23 11:20:04] lb.utils.events INFO:  eta: 1:53:26  iteration: 331799/375342  consumed_samples: 339763200  total_loss: 2.996  time: 0.3443 s/iter  data_time: 0.2292 s/iter total_throughput: 2974.21 samples/s lr: 4.25e-05  
[09/23 11:20:39] lb.utils.events INFO:  eta: 1:53:29  iteration: 331899/375342  consumed_samples: 339865600  total_loss: 2.991  time: 0.3443 s/iter  data_time: 0.2226 s/iter total_throughput: 2974.21 samples/s lr: 4.24e-05  
[09/23 11:21:13] lb.utils.events INFO:  eta: 1:53:15  iteration: 331999/375342  consumed_samples: 339968000  total_loss: 2.997  time: 0.3443 s/iter  data_time: 0.2241 s/iter total_throughput: 2974.21 samples/s lr: 4.22e-05  
[09/23 11:21:47] lb.utils.events INFO:  eta: 1:52:55  iteration: 332099/375342  consumed_samples: 340070400  total_loss: 3.013  time: 0.3443 s/iter  data_time: 0.2166 s/iter total_throughput: 2974.21 samples/s lr: 4.21e-05  
[09/23 11:22:22] lb.utils.events INFO:  eta: 1:52:41  iteration: 332199/375342  consumed_samples: 340172800  total_loss: 3.005  time: 0.3443 s/iter  data_time: 0.2171 s/iter total_throughput: 2974.21 samples/s lr: 4.19e-05  
[09/23 11:22:56] lb.utils.events INFO:  eta: 1:52:14  iteration: 332299/375342  consumed_samples: 340275200  total_loss: 3.002  time: 0.3443 s/iter  data_time: 0.2179 s/iter total_throughput: 2974.22 samples/s lr: 4.18e-05  
[09/23 11:23:31] lb.utils.events INFO:  eta: 1:51:45  iteration: 332399/375342  consumed_samples: 340377600  total_loss: 3.002  time: 0.3443 s/iter  data_time: 0.2125 s/iter total_throughput: 2974.22 samples/s lr: 4.16e-05  
[09/23 11:24:04] lb.utils.events INFO:  eta: 1:51:37  iteration: 332499/375342  consumed_samples: 340480000  total_loss: 3.006  time: 0.3443 s/iter  data_time: 0.2040 s/iter total_throughput: 2974.23 samples/s lr: 4.15e-05  
[09/23 11:24:39] lb.utils.events INFO:  eta: 1:51:17  iteration: 332599/375342  consumed_samples: 340582400  total_loss: 3.007  time: 0.3443 s/iter  data_time: 0.2128 s/iter total_throughput: 2974.23 samples/s lr: 4.13e-05  
[09/23 11:25:13] lb.utils.events INFO:  eta: 1:51:07  iteration: 332699/375342  consumed_samples: 340684800  total_loss: 3.002  time: 0.3443 s/iter  data_time: 0.2136 s/iter total_throughput: 2974.23 samples/s lr: 4.12e-05  
[09/23 11:25:48] lb.utils.events INFO:  eta: 1:51:08  iteration: 332799/375342  consumed_samples: 340787200  total_loss: 2.977  time: 0.3443 s/iter  data_time: 0.2229 s/iter total_throughput: 2974.23 samples/s lr: 4.11e-05  
[09/23 11:26:22] lb.utils.events INFO:  eta: 1:50:33  iteration: 332899/375342  consumed_samples: 340889600  total_loss: 2.978  time: 0.3443 s/iter  data_time: 0.2154 s/iter total_throughput: 2974.23 samples/s lr: 4.09e-05  
[09/23 11:26:57] lb.utils.events INFO:  eta: 1:50:09  iteration: 332999/375342  consumed_samples: 340992000  total_loss: 2.992  time: 0.3443 s/iter  data_time: 0.2189 s/iter total_throughput: 2974.22 samples/s lr: 4.08e-05  
[09/23 11:27:32] lb.utils.events INFO:  eta: 1:49:56  iteration: 333099/375342  consumed_samples: 341094400  total_loss: 2.985  time: 0.3443 s/iter  data_time: 0.2118 s/iter total_throughput: 2974.22 samples/s lr: 4.06e-05  
[09/23 11:28:06] lb.utils.events INFO:  eta: 1:49:36  iteration: 333199/375342  consumed_samples: 341196800  total_loss: 2.986  time: 0.3443 s/iter  data_time: 0.2231 s/iter total_throughput: 2974.22 samples/s lr: 4.05e-05  
[09/23 11:28:40] lb.utils.events INFO:  eta: 1:49:22  iteration: 333299/375342  consumed_samples: 341299200  total_loss: 2.989  time: 0.3443 s/iter  data_time: 0.2197 s/iter total_throughput: 2974.22 samples/s lr: 4.03e-05  
[09/23 11:29:15] lb.utils.events INFO:  eta: 1:49:40  iteration: 333399/375342  consumed_samples: 341401600  total_loss: 2.992  time: 0.3443 s/iter  data_time: 0.2221 s/iter total_throughput: 2974.22 samples/s lr: 4.02e-05  
[09/23 11:29:49] lb.utils.events INFO:  eta: 1:49:19  iteration: 333499/375342  consumed_samples: 341504000  total_loss: 2.989  time: 0.3443 s/iter  data_time: 0.2059 s/iter total_throughput: 2974.23 samples/s lr: 4.00e-05  
[09/23 11:30:23] lb.utils.events INFO:  eta: 1:49:22  iteration: 333599/375342  consumed_samples: 341606400  total_loss: 2.988  time: 0.3443 s/iter  data_time: 0.2077 s/iter total_throughput: 2974.24 samples/s lr: 3.99e-05  
[09/23 11:30:57] lb.utils.events INFO:  eta: 1:49:08  iteration: 333699/375342  consumed_samples: 341708800  total_loss: 3  time: 0.3443 s/iter  data_time: 0.2119 s/iter total_throughput: 2974.24 samples/s lr: 3.98e-05  
[09/23 11:31:31] lb.utils.events INFO:  eta: 1:49:06  iteration: 333799/375342  consumed_samples: 341811200  total_loss: 3  time: 0.3443 s/iter  data_time: 0.2182 s/iter total_throughput: 2974.25 samples/s lr: 3.96e-05  
[09/23 11:32:06] lb.utils.events INFO:  eta: 1:48:45  iteration: 333899/375342  consumed_samples: 341913600  total_loss: 2.992  time: 0.3443 s/iter  data_time: 0.2088 s/iter total_throughput: 2974.24 samples/s lr: 3.95e-05  
[09/23 11:32:41] lb.utils.events INFO:  eta: 1:48:42  iteration: 333999/375342  consumed_samples: 342016000  total_loss: 2.993  time: 0.3443 s/iter  data_time: 0.2157 s/iter total_throughput: 2974.24 samples/s lr: 3.93e-05  
[09/23 11:33:15] lb.utils.events INFO:  eta: 1:48:20  iteration: 334099/375342  consumed_samples: 342118400  total_loss: 3  time: 0.3443 s/iter  data_time: 0.2148 s/iter total_throughput: 2974.24 samples/s lr: 3.92e-05  
[09/23 11:33:49] lb.utils.events INFO:  eta: 1:48:02  iteration: 334199/375342  consumed_samples: 342220800  total_loss: 2.988  time: 0.3443 s/iter  data_time: 0.2153 s/iter total_throughput: 2974.24 samples/s lr: 3.91e-05  
[09/23 11:34:24] lb.utils.events INFO:  eta: 1:47:43  iteration: 334299/375342  consumed_samples: 342323200  total_loss: 2.982  time: 0.3443 s/iter  data_time: 0.2156 s/iter total_throughput: 2974.24 samples/s lr: 3.89e-05  
[09/23 11:34:58] lb.utils.events INFO:  eta: 1:46:59  iteration: 334399/375342  consumed_samples: 342425600  total_loss: 2.982  time: 0.3443 s/iter  data_time: 0.2216 s/iter total_throughput: 2974.25 samples/s lr: 3.88e-05  
[09/23 11:35:32] lb.utils.events INFO:  eta: 1:46:41  iteration: 334499/375342  consumed_samples: 342528000  total_loss: 2.985  time: 0.3443 s/iter  data_time: 0.2177 s/iter total_throughput: 2974.27 samples/s lr: 3.86e-05  
[09/23 11:36:06] lb.utils.events INFO:  eta: 1:46:20  iteration: 334599/375342  consumed_samples: 342630400  total_loss: 2.978  time: 0.3443 s/iter  data_time: 0.2130 s/iter total_throughput: 2974.27 samples/s lr: 3.85e-05  
[09/23 11:36:40] lb.utils.events INFO:  eta: 1:45:44  iteration: 334699/375342  consumed_samples: 342732800  total_loss: 2.98  time: 0.3443 s/iter  data_time: 0.2073 s/iter total_throughput: 2974.27 samples/s lr: 3.84e-05  
[09/23 11:37:15] lb.utils.events INFO:  eta: 1:45:09  iteration: 334799/375342  consumed_samples: 342835200  total_loss: 2.996  time: 0.3443 s/iter  data_time: 0.2186 s/iter total_throughput: 2974.28 samples/s lr: 3.82e-05  
[09/23 11:37:49] lb.utils.events INFO:  eta: 1:44:53  iteration: 334899/375342  consumed_samples: 342937600  total_loss: 2.987  time: 0.3443 s/iter  data_time: 0.2094 s/iter total_throughput: 2974.28 samples/s lr: 3.81e-05  
[09/23 11:38:23] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0334999
[09/23 11:38:24] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/23 11:38:24] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/23 11:38:28] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0975 s/iter. Inference: 0.1644 s/iter. Eval: 0.0023 s/iter. Total: 0.2642 s/iter. ETA=0:00:09
[09/23 11:38:33] lb.evaluation.evaluator INFO: Inference done 29696/50000. Dataloading: 0.1201 s/iter. Inference: 0.1753 s/iter. Eval: 0.0021 s/iter. Total: 0.2976 s/iter. ETA=0:00:05
[09/23 11:38:39] lb.evaluation.evaluator INFO: Inference done 48128/50000. Dataloading: 0.1204 s/iter. Inference: 0.1690 s/iter. Eval: 0.0021 s/iter. Total: 0.2915 s/iter. ETA=0:00:00
[09/23 11:38:39] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/23 11:38:39] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.595559 (0.000252 s / iter per device, on 8 devices)
[09/23 11:38:39] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000149 s / iter per device, on 8 devices)
[09/23 11:38:39] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/23 11:38:39] lb.evaluation.utils INFO: copypaste: Acc@1=79.738
[09/23 11:38:39] lb.evaluation.utils INFO: copypaste: Acc@5=94.428
[09/23 11:38:39] lb.engine.hooks INFO: Not saving as latest eval score for Acc@1 is 79.73800, not better than best score 79.74400 @ iteration 329999.
[09/23 11:38:39] lb.utils.events INFO:  eta: 1:44:29  iteration: 334999/375342  consumed_samples: 343040000  total_loss: 2.982  time: 0.3443 s/iter  data_time: 0.2177 s/iter total_throughput: 2974.29 samples/s lr: 3.80e-05  
[09/23 11:39:11] lb.utils.events INFO:  eta: 1:44:15  iteration: 335099/375342  consumed_samples: 343142400  total_loss: 2.999  time: 0.3443 s/iter  data_time: 0.2422 s/iter total_throughput: 2974.36 samples/s lr: 3.78e-05  
[09/23 11:39:45] lb.utils.events INFO:  eta: 1:44:02  iteration: 335199/375342  consumed_samples: 343244800  total_loss: 3.005  time: 0.3443 s/iter  data_time: 0.2095 s/iter total_throughput: 2974.37 samples/s lr: 3.77e-05  
[09/23 11:40:18] lb.utils.events INFO:  eta: 1:44:01  iteration: 335299/375342  consumed_samples: 343347200  total_loss: 2.984  time: 0.3443 s/iter  data_time: 0.2108 s/iter total_throughput: 2974.38 samples/s lr: 3.75e-05  
[09/23 11:40:53] lb.utils.events INFO:  eta: 1:43:56  iteration: 335399/375342  consumed_samples: 343449600  total_loss: 2.963  time: 0.3443 s/iter  data_time: 0.2126 s/iter total_throughput: 2974.38 samples/s lr: 3.74e-05  
[09/23 11:41:27] lb.utils.events INFO:  eta: 1:43:34  iteration: 335499/375342  consumed_samples: 343552000  total_loss: 2.965  time: 0.3443 s/iter  data_time: 0.2164 s/iter total_throughput: 2974.39 samples/s lr: 3.73e-05  
[09/23 11:42:01] lb.utils.events INFO:  eta: 1:43:06  iteration: 335599/375342  consumed_samples: 343654400  total_loss: 2.957  time: 0.3443 s/iter  data_time: 0.2107 s/iter total_throughput: 2974.40 samples/s lr: 3.71e-05  
[09/23 11:42:35] lb.utils.events INFO:  eta: 1:43:02  iteration: 335699/375342  consumed_samples: 343756800  total_loss: 2.96  time: 0.3443 s/iter  data_time: 0.2098 s/iter total_throughput: 2974.42 samples/s lr: 3.70e-05  
[09/23 11:43:09] lb.utils.events INFO:  eta: 1:42:41  iteration: 335799/375342  consumed_samples: 343859200  total_loss: 2.98  time: 0.3443 s/iter  data_time: 0.2088 s/iter total_throughput: 2974.43 samples/s lr: 3.69e-05  
[09/23 11:43:42] lb.utils.events INFO:  eta: 1:42:37  iteration: 335899/375342  consumed_samples: 343961600  total_loss: 2.985  time: 0.3443 s/iter  data_time: 0.2071 s/iter total_throughput: 2974.45 samples/s lr: 3.67e-05  
[09/23 11:44:17] lb.utils.events INFO:  eta: 1:42:29  iteration: 335999/375342  consumed_samples: 344064000  total_loss: 2.977  time: 0.3443 s/iter  data_time: 0.2118 s/iter total_throughput: 2974.46 samples/s lr: 3.66e-05  
[09/23 11:44:51] lb.utils.events INFO:  eta: 1:42:02  iteration: 336099/375342  consumed_samples: 344166400  total_loss: 3.001  time: 0.3443 s/iter  data_time: 0.2212 s/iter total_throughput: 2974.46 samples/s lr: 3.65e-05  
[09/23 11:45:26] lb.utils.events INFO:  eta: 1:41:38  iteration: 336199/375342  consumed_samples: 344268800  total_loss: 3.005  time: 0.3443 s/iter  data_time: 0.2205 s/iter total_throughput: 2974.44 samples/s lr: 3.63e-05  
[09/23 11:46:01] lb.utils.events INFO:  eta: 1:41:18  iteration: 336299/375342  consumed_samples: 344371200  total_loss: 2.993  time: 0.3443 s/iter  data_time: 0.2232 s/iter total_throughput: 2974.44 samples/s lr: 3.62e-05  
[09/23 11:46:36] lb.utils.events INFO:  eta: 1:41:07  iteration: 336399/375342  consumed_samples: 344473600  total_loss: 2.994  time: 0.3443 s/iter  data_time: 0.2245 s/iter total_throughput: 2974.43 samples/s lr: 3.61e-05  
[09/23 11:47:10] lb.utils.events INFO:  eta: 1:40:51  iteration: 336499/375342  consumed_samples: 344576000  total_loss: 3.002  time: 0.3443 s/iter  data_time: 0.2251 s/iter total_throughput: 2974.42 samples/s lr: 3.59e-05  
[09/23 11:47:46] lb.utils.events INFO:  eta: 1:40:40  iteration: 336599/375342  consumed_samples: 344678400  total_loss: 2.986  time: 0.3443 s/iter  data_time: 0.2312 s/iter total_throughput: 2974.39 samples/s lr: 3.58e-05  
[09/23 11:48:21] lb.utils.events INFO:  eta: 1:40:22  iteration: 336699/375342  consumed_samples: 344780800  total_loss: 2.986  time: 0.3443 s/iter  data_time: 0.2354 s/iter total_throughput: 2974.37 samples/s lr: 3.57e-05  
[09/23 11:48:56] lb.utils.events INFO:  eta: 1:40:11  iteration: 336799/375342  consumed_samples: 344883200  total_loss: 2.98  time: 0.3443 s/iter  data_time: 0.2220 s/iter total_throughput: 2974.36 samples/s lr: 3.55e-05  
[09/23 11:49:31] lb.utils.events INFO:  eta: 1:39:55  iteration: 336899/375342  consumed_samples: 344985600  total_loss: 2.973  time: 0.3443 s/iter  data_time: 0.2110 s/iter total_throughput: 2974.35 samples/s lr: 3.54e-05  
[09/23 11:50:06] lb.utils.events INFO:  eta: 1:39:35  iteration: 336999/375342  consumed_samples: 345088000  total_loss: 2.973  time: 0.3443 s/iter  data_time: 0.2375 s/iter total_throughput: 2974.33 samples/s lr: 3.53e-05  
[09/23 11:50:41] lb.utils.events INFO:  eta: 1:39:20  iteration: 337099/375342  consumed_samples: 345190400  total_loss: 2.967  time: 0.3443 s/iter  data_time: 0.2267 s/iter total_throughput: 2974.31 samples/s lr: 3.51e-05  
[09/23 11:51:16] lb.utils.events INFO:  eta: 1:39:09  iteration: 337199/375342  consumed_samples: 345292800  total_loss: 2.97  time: 0.3443 s/iter  data_time: 0.2169 s/iter total_throughput: 2974.31 samples/s lr: 3.50e-05  
[09/23 11:51:50] lb.utils.events INFO:  eta: 1:38:59  iteration: 337299/375342  consumed_samples: 345395200  total_loss: 2.977  time: 0.3443 s/iter  data_time: 0.2291 s/iter total_throughput: 2974.31 samples/s lr: 3.49e-05  
[09/23 11:52:25] lb.utils.events INFO:  eta: 1:38:40  iteration: 337399/375342  consumed_samples: 345497600  total_loss: 2.975  time: 0.3443 s/iter  data_time: 0.2185 s/iter total_throughput: 2974.30 samples/s lr: 3.48e-05  
[09/23 11:53:00] lb.utils.events INFO:  eta: 1:38:26  iteration: 337499/375342  consumed_samples: 345600000  total_loss: 2.985  time: 0.3443 s/iter  data_time: 0.2270 s/iter total_throughput: 2974.29 samples/s lr: 3.46e-05  
[09/23 11:53:35] lb.utils.events INFO:  eta: 1:38:09  iteration: 337599/375342  consumed_samples: 345702400  total_loss: 2.989  time: 0.3443 s/iter  data_time: 0.2210 s/iter total_throughput: 2974.26 samples/s lr: 3.45e-05  
[09/23 11:54:11] lb.utils.events INFO:  eta: 1:37:52  iteration: 337699/375342  consumed_samples: 345804800  total_loss: 2.983  time: 0.3443 s/iter  data_time: 0.2215 s/iter total_throughput: 2974.24 samples/s lr: 3.44e-05  
[09/23 11:54:45] lb.utils.events INFO:  eta: 1:37:44  iteration: 337799/375342  consumed_samples: 345907200  total_loss: 2.973  time: 0.3443 s/iter  data_time: 0.2127 s/iter total_throughput: 2974.24 samples/s lr: 3.42e-05  
[09/23 11:55:20] lb.utils.events INFO:  eta: 1:37:27  iteration: 337899/375342  consumed_samples: 346009600  total_loss: 2.988  time: 0.3443 s/iter  data_time: 0.2198 s/iter total_throughput: 2974.24 samples/s lr: 3.41e-05  
[09/23 11:55:54] lb.utils.events INFO:  eta: 1:37:17  iteration: 337999/375342  consumed_samples: 346112000  total_loss: 2.979  time: 0.3443 s/iter  data_time: 0.2240 s/iter total_throughput: 2974.23 samples/s lr: 3.40e-05  
[09/23 11:56:29] lb.utils.events INFO:  eta: 1:37:14  iteration: 338099/375342  consumed_samples: 346214400  total_loss: 2.952  time: 0.3443 s/iter  data_time: 0.2162 s/iter total_throughput: 2974.23 samples/s lr: 3.39e-05  
[09/23 11:57:03] lb.utils.events INFO:  eta: 1:36:55  iteration: 338199/375342  consumed_samples: 346316800  total_loss: 2.967  time: 0.3443 s/iter  data_time: 0.2263 s/iter total_throughput: 2974.22 samples/s lr: 3.37e-05  
[09/23 11:57:38] lb.utils.events INFO:  eta: 1:36:26  iteration: 338299/375342  consumed_samples: 346419200  total_loss: 2.979  time: 0.3443 s/iter  data_time: 0.2174 s/iter total_throughput: 2974.22 samples/s lr: 3.36e-05  
[09/23 11:58:12] lb.utils.events INFO:  eta: 1:36:13  iteration: 338399/375342  consumed_samples: 346521600  total_loss: 2.965  time: 0.3443 s/iter  data_time: 0.2133 s/iter total_throughput: 2974.22 samples/s lr: 3.35e-05  
[09/23 11:58:47] lb.utils.events INFO:  eta: 1:36:03  iteration: 338499/375342  consumed_samples: 346624000  total_loss: 2.967  time: 0.3443 s/iter  data_time: 0.2179 s/iter total_throughput: 2974.22 samples/s lr: 3.33e-05  
[09/23 11:59:22] lb.utils.events INFO:  eta: 1:35:48  iteration: 338599/375342  consumed_samples: 346726400  total_loss: 2.973  time: 0.3443 s/iter  data_time: 0.2239 s/iter total_throughput: 2974.22 samples/s lr: 3.32e-05  
[09/23 11:59:56] lb.utils.events INFO:  eta: 1:35:34  iteration: 338699/375342  consumed_samples: 346828800  total_loss: 2.975  time: 0.3443 s/iter  data_time: 0.2128 s/iter total_throughput: 2974.20 samples/s lr: 3.31e-05  
[09/23 12:00:31] lb.utils.events INFO:  eta: 1:34:55  iteration: 338799/375342  consumed_samples: 346931200  total_loss: 2.977  time: 0.3443 s/iter  data_time: 0.2289 s/iter total_throughput: 2974.19 samples/s lr: 3.30e-05  
[09/23 12:01:06] lb.utils.events INFO:  eta: 1:34:39  iteration: 338899/375342  consumed_samples: 347033600  total_loss: 2.979  time: 0.3443 s/iter  data_time: 0.2142 s/iter total_throughput: 2974.19 samples/s lr: 3.28e-05  
[09/23 12:01:41] lb.utils.events INFO:  eta: 1:34:24  iteration: 338999/375342  consumed_samples: 347136000  total_loss: 2.985  time: 0.3443 s/iter  data_time: 0.2297 s/iter total_throughput: 2974.18 samples/s lr: 3.27e-05  
[09/23 12:02:16] lb.utils.events INFO:  eta: 1:33:55  iteration: 339099/375342  consumed_samples: 347238400  total_loss: 2.98  time: 0.3443 s/iter  data_time: 0.2254 s/iter total_throughput: 2974.16 samples/s lr: 3.26e-05  
[09/23 12:02:51] lb.utils.events INFO:  eta: 1:33:39  iteration: 339199/375342  consumed_samples: 347340800  total_loss: 2.969  time: 0.3443 s/iter  data_time: 0.2242 s/iter total_throughput: 2974.14 samples/s lr: 3.25e-05  
[09/23 12:03:26] lb.utils.events INFO:  eta: 1:33:17  iteration: 339299/375342  consumed_samples: 347443200  total_loss: 2.958  time: 0.3443 s/iter  data_time: 0.2283 s/iter total_throughput: 2974.13 samples/s lr: 3.24e-05  
[09/23 12:04:01] lb.utils.events INFO:  eta: 1:33:11  iteration: 339399/375342  consumed_samples: 347545600  total_loss: 2.984  time: 0.3443 s/iter  data_time: 0.2196 s/iter total_throughput: 2974.11 samples/s lr: 3.22e-05  
[09/23 12:04:36] lb.utils.events INFO:  eta: 1:32:40  iteration: 339499/375342  consumed_samples: 347648000  total_loss: 2.987  time: 0.3443 s/iter  data_time: 0.2121 s/iter total_throughput: 2974.10 samples/s lr: 3.21e-05  
[09/23 12:05:11] lb.utils.events INFO:  eta: 1:32:24  iteration: 339599/375342  consumed_samples: 347750400  total_loss: 2.978  time: 0.3443 s/iter  data_time: 0.2189 s/iter total_throughput: 2974.09 samples/s lr: 3.20e-05  
[09/23 12:05:46] lb.utils.events INFO:  eta: 1:32:09  iteration: 339699/375342  consumed_samples: 347852800  total_loss: 2.975  time: 0.3443 s/iter  data_time: 0.2228 s/iter total_throughput: 2974.08 samples/s lr: 3.19e-05  
[09/23 12:06:21] lb.utils.events INFO:  eta: 1:31:59  iteration: 339799/375342  consumed_samples: 347955200  total_loss: 2.978  time: 0.3443 s/iter  data_time: 0.2160 s/iter total_throughput: 2974.06 samples/s lr: 3.17e-05  
[09/23 12:06:56] lb.utils.events INFO:  eta: 1:31:38  iteration: 339899/375342  consumed_samples: 348057600  total_loss: 2.995  time: 0.3443 s/iter  data_time: 0.2258 s/iter total_throughput: 2974.04 samples/s lr: 3.16e-05  
[09/23 12:07:30] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0339999
[09/23 12:07:31] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/23 12:07:31] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/23 12:07:35] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.1016 s/iter. Inference: 0.1646 s/iter. Eval: 0.0022 s/iter. Total: 0.2683 s/iter. ETA=0:00:09
[09/23 12:07:40] lb.evaluation.evaluator INFO: Inference done 28672/50000. Dataloading: 0.0979 s/iter. Inference: 0.1878 s/iter. Eval: 0.0021 s/iter. Total: 0.2879 s/iter. ETA=0:00:05
[09/23 12:07:46] lb.evaluation.evaluator INFO: Inference done 47104/50000. Dataloading: 0.1088 s/iter. Inference: 0.1819 s/iter. Eval: 0.0021 s/iter. Total: 0.2929 s/iter. ETA=0:00:00
[09/23 12:07:46] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/23 12:07:46] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.530537 (0.000251 s / iter per device, on 8 devices)
[09/23 12:07:46] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000159 s / iter per device, on 8 devices)
[09/23 12:07:46] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/23 12:07:46] lb.evaluation.utils INFO: copypaste: Acc@1=79.838
[09/23 12:07:46] lb.evaluation.utils INFO: copypaste: Acc@5=94.42399999999999
[09/23 12:07:46] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 79.83800, better than last best score 79.74400 @ iteration 329999.
[09/23 12:07:46] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/23 12:07:47] lb.utils.events INFO:  eta: 1:31:28  iteration: 339999/375342  consumed_samples: 348160000  total_loss: 3  time: 0.3443 s/iter  data_time: 0.2158 s/iter total_throughput: 2974.05 samples/s lr: 3.15e-05  
[09/23 12:08:19] lb.utils.events INFO:  eta: 1:31:57  iteration: 340099/375342  consumed_samples: 348262400  total_loss: 2.979  time: 0.3443 s/iter  data_time: 0.2080 s/iter total_throughput: 2974.10 samples/s lr: 3.14e-05  
[09/23 12:08:54] lb.utils.events INFO:  eta: 1:31:42  iteration: 340199/375342  consumed_samples: 348364800  total_loss: 2.982  time: 0.3443 s/iter  data_time: 0.2229 s/iter total_throughput: 2974.08 samples/s lr: 3.13e-05  
[09/23 12:09:29] lb.utils.events INFO:  eta: 1:31:34  iteration: 340299/375342  consumed_samples: 348467200  total_loss: 2.969  time: 0.3443 s/iter  data_time: 0.2276 s/iter total_throughput: 2974.07 samples/s lr: 3.11e-05  
[09/23 12:10:04] lb.utils.events INFO:  eta: 1:31:11  iteration: 340399/375342  consumed_samples: 348569600  total_loss: 2.956  time: 0.3443 s/iter  data_time: 0.2225 s/iter total_throughput: 2974.05 samples/s lr: 3.10e-05  
[09/23 12:10:39] lb.utils.events INFO:  eta: 1:30:54  iteration: 340499/375342  consumed_samples: 348672000  total_loss: 2.951  time: 0.3443 s/iter  data_time: 0.2195 s/iter total_throughput: 2974.05 samples/s lr: 3.09e-05  
[09/23 12:11:13] lb.utils.events INFO:  eta: 1:30:53  iteration: 340599/375342  consumed_samples: 348774400  total_loss: 2.96  time: 0.3443 s/iter  data_time: 0.2172 s/iter total_throughput: 2974.05 samples/s lr: 3.08e-05  
[09/23 12:11:48] lb.utils.events INFO:  eta: 1:30:42  iteration: 340699/375342  consumed_samples: 348876800  total_loss: 2.974  time: 0.3443 s/iter  data_time: 0.2117 s/iter total_throughput: 2974.05 samples/s lr: 3.07e-05  
[09/23 12:12:22] lb.utils.events INFO:  eta: 1:30:50  iteration: 340799/375342  consumed_samples: 348979200  total_loss: 2.973  time: 0.3443 s/iter  data_time: 0.2165 s/iter total_throughput: 2974.05 samples/s lr: 3.05e-05  
[09/23 12:12:57] lb.utils.events INFO:  eta: 1:30:33  iteration: 340899/375342  consumed_samples: 349081600  total_loss: 2.985  time: 0.3443 s/iter  data_time: 0.2166 s/iter total_throughput: 2974.03 samples/s lr: 3.04e-05  
[09/23 12:13:32] lb.utils.events INFO:  eta: 1:30:14  iteration: 340999/375342  consumed_samples: 349184000  total_loss: 2.991  time: 0.3443 s/iter  data_time: 0.2056 s/iter total_throughput: 2974.03 samples/s lr: 3.03e-05  
[09/23 12:14:06] lb.utils.events INFO:  eta: 1:29:29  iteration: 341099/375342  consumed_samples: 349286400  total_loss: 2.979  time: 0.3443 s/iter  data_time: 0.2090 s/iter total_throughput: 2974.03 samples/s lr: 3.02e-05  
[09/23 12:14:41] lb.utils.events INFO:  eta: 1:29:13  iteration: 341199/375342  consumed_samples: 349388800  total_loss: 2.953  time: 0.3443 s/iter  data_time: 0.2073 s/iter total_throughput: 2974.03 samples/s lr: 3.01e-05  
[09/23 12:15:16] lb.utils.events INFO:  eta: 1:28:43  iteration: 341299/375342  consumed_samples: 349491200  total_loss: 2.955  time: 0.3443 s/iter  data_time: 0.2230 s/iter total_throughput: 2974.01 samples/s lr: 3.00e-05  
[09/23 12:15:51] lb.utils.events INFO:  eta: 1:28:23  iteration: 341399/375342  consumed_samples: 349593600  total_loss: 2.983  time: 0.3443 s/iter  data_time: 0.2219 s/iter total_throughput: 2974.01 samples/s lr: 2.98e-05  
[09/23 12:16:25] lb.utils.events INFO:  eta: 1:28:14  iteration: 341499/375342  consumed_samples: 349696000  total_loss: 2.989  time: 0.3443 s/iter  data_time: 0.2200 s/iter total_throughput: 2974.01 samples/s lr: 2.97e-05  
[09/23 12:17:00] lb.utils.events INFO:  eta: 1:27:45  iteration: 341599/375342  consumed_samples: 349798400  total_loss: 2.957  time: 0.3443 s/iter  data_time: 0.2254 s/iter total_throughput: 2974.00 samples/s lr: 2.96e-05  
[09/23 12:17:34] lb.utils.events INFO:  eta: 1:27:43  iteration: 341699/375342  consumed_samples: 349900800  total_loss: 2.954  time: 0.3443 s/iter  data_time: 0.2168 s/iter total_throughput: 2974.00 samples/s lr: 2.95e-05  
[09/23 12:18:09] lb.utils.events INFO:  eta: 1:27:13  iteration: 341799/375342  consumed_samples: 350003200  total_loss: 2.97  time: 0.3443 s/iter  data_time: 0.2210 s/iter total_throughput: 2973.99 samples/s lr: 2.94e-05  
[09/23 12:18:44] lb.utils.events INFO:  eta: 1:26:57  iteration: 341899/375342  consumed_samples: 350105600  total_loss: 2.968  time: 0.3443 s/iter  data_time: 0.2209 s/iter total_throughput: 2973.98 samples/s lr: 2.93e-05  
[09/23 12:19:18] lb.utils.events INFO:  eta: 1:26:42  iteration: 341999/375342  consumed_samples: 350208000  total_loss: 2.958  time: 0.3443 s/iter  data_time: 0.2216 s/iter total_throughput: 2973.98 samples/s lr: 2.92e-05  
[09/23 12:19:53] lb.utils.events INFO:  eta: 1:26:14  iteration: 342099/375342  consumed_samples: 350310400  total_loss: 2.966  time: 0.3443 s/iter  data_time: 0.2150 s/iter total_throughput: 2973.96 samples/s lr: 2.90e-05  
[09/23 12:20:28] lb.utils.events INFO:  eta: 1:26:00  iteration: 342199/375342  consumed_samples: 350412800  total_loss: 2.977  time: 0.3443 s/iter  data_time: 0.2234 s/iter total_throughput: 2973.96 samples/s lr: 2.89e-05  
[09/23 12:21:03] lb.utils.events INFO:  eta: 1:25:44  iteration: 342299/375342  consumed_samples: 350515200  total_loss: 2.979  time: 0.3443 s/iter  data_time: 0.2214 s/iter total_throughput: 2973.95 samples/s lr: 2.88e-05  
[09/23 12:21:38] lb.utils.events INFO:  eta: 1:25:24  iteration: 342399/375342  consumed_samples: 350617600  total_loss: 2.972  time: 0.3443 s/iter  data_time: 0.2191 s/iter total_throughput: 2973.94 samples/s lr: 2.87e-05  
[09/23 12:22:12] lb.utils.events INFO:  eta: 1:25:09  iteration: 342499/375342  consumed_samples: 350720000  total_loss: 2.995  time: 0.3443 s/iter  data_time: 0.2190 s/iter total_throughput: 2973.94 samples/s lr: 2.86e-05  
[09/23 12:22:47] lb.utils.events INFO:  eta: 1:24:44  iteration: 342599/375342  consumed_samples: 350822400  total_loss: 2.992  time: 0.3443 s/iter  data_time: 0.2200 s/iter total_throughput: 2973.92 samples/s lr: 2.85e-05  
[09/23 12:23:22] lb.utils.events INFO:  eta: 1:24:21  iteration: 342699/375342  consumed_samples: 350924800  total_loss: 2.979  time: 0.3443 s/iter  data_time: 0.2129 s/iter total_throughput: 2973.92 samples/s lr: 2.84e-05  
[09/23 12:23:56] lb.utils.events INFO:  eta: 1:24:06  iteration: 342799/375342  consumed_samples: 351027200  total_loss: 2.973  time: 0.3443 s/iter  data_time: 0.2291 s/iter total_throughput: 2973.92 samples/s lr: 2.82e-05  
[09/23 12:24:31] lb.utils.events INFO:  eta: 1:23:43  iteration: 342899/375342  consumed_samples: 351129600  total_loss: 2.963  time: 0.3443 s/iter  data_time: 0.2253 s/iter total_throughput: 2973.91 samples/s lr: 2.81e-05  
[09/23 12:25:06] lb.utils.events INFO:  eta: 1:23:19  iteration: 342999/375342  consumed_samples: 351232000  total_loss: 2.961  time: 0.3443 s/iter  data_time: 0.2118 s/iter total_throughput: 2973.91 samples/s lr: 2.80e-05  
[09/23 12:25:40] lb.utils.events INFO:  eta: 1:23:27  iteration: 343099/375342  consumed_samples: 351334400  total_loss: 2.98  time: 0.3443 s/iter  data_time: 0.2272 s/iter total_throughput: 2973.90 samples/s lr: 2.79e-05  
[09/23 12:26:15] lb.utils.events INFO:  eta: 1:23:12  iteration: 343199/375342  consumed_samples: 351436800  total_loss: 2.968  time: 0.3443 s/iter  data_time: 0.2308 s/iter total_throughput: 2973.89 samples/s lr: 2.78e-05  
[09/23 12:26:50] lb.utils.events INFO:  eta: 1:23:05  iteration: 343299/375342  consumed_samples: 351539200  total_loss: 2.96  time: 0.3443 s/iter  data_time: 0.2193 s/iter total_throughput: 2973.88 samples/s lr: 2.77e-05  
[09/23 12:27:25] lb.utils.events INFO:  eta: 1:22:52  iteration: 343399/375342  consumed_samples: 351641600  total_loss: 2.965  time: 0.3443 s/iter  data_time: 0.2171 s/iter total_throughput: 2973.86 samples/s lr: 2.76e-05  
[09/23 12:28:00] lb.utils.events INFO:  eta: 1:22:33  iteration: 343499/375342  consumed_samples: 351744000  total_loss: 2.949  time: 0.3443 s/iter  data_time: 0.2258 s/iter total_throughput: 2973.86 samples/s lr: 2.75e-05  
[09/23 12:28:35] lb.utils.events INFO:  eta: 1:22:26  iteration: 343599/375342  consumed_samples: 351846400  total_loss: 2.966  time: 0.3443 s/iter  data_time: 0.2218 s/iter total_throughput: 2973.84 samples/s lr: 2.74e-05  
[09/23 12:29:09] lb.utils.events INFO:  eta: 1:22:21  iteration: 343699/375342  consumed_samples: 351948800  total_loss: 2.975  time: 0.3443 s/iter  data_time: 0.2130 s/iter total_throughput: 2973.85 samples/s lr: 2.73e-05  
[09/23 12:29:43] lb.utils.events INFO:  eta: 1:22:00  iteration: 343799/375342  consumed_samples: 352051200  total_loss: 2.968  time: 0.3443 s/iter  data_time: 0.2080 s/iter total_throughput: 2973.85 samples/s lr: 2.72e-05  
[09/23 12:30:18] lb.utils.events INFO:  eta: 1:21:51  iteration: 343899/375342  consumed_samples: 352153600  total_loss: 2.974  time: 0.3443 s/iter  data_time: 0.2178 s/iter total_throughput: 2973.85 samples/s lr: 2.70e-05  
[09/23 12:30:52] lb.utils.events INFO:  eta: 1:21:35  iteration: 343999/375342  consumed_samples: 352256000  total_loss: 2.968  time: 0.3443 s/iter  data_time: 0.2117 s/iter total_throughput: 2973.85 samples/s lr: 2.69e-05  
[09/23 12:31:27] lb.utils.events INFO:  eta: 1:21:22  iteration: 344099/375342  consumed_samples: 352358400  total_loss: 2.949  time: 0.3443 s/iter  data_time: 0.2169 s/iter total_throughput: 2973.84 samples/s lr: 2.68e-05  
[09/23 12:32:02] lb.utils.events INFO:  eta: 1:21:05  iteration: 344199/375342  consumed_samples: 352460800  total_loss: 2.963  time: 0.3443 s/iter  data_time: 0.2262 s/iter total_throughput: 2973.84 samples/s lr: 2.67e-05  
[09/23 12:32:36] lb.utils.events INFO:  eta: 1:21:02  iteration: 344299/375342  consumed_samples: 352563200  total_loss: 2.969  time: 0.3443 s/iter  data_time: 0.2172 s/iter total_throughput: 2973.83 samples/s lr: 2.66e-05  
[09/23 12:33:11] lb.utils.events INFO:  eta: 1:20:44  iteration: 344399/375342  consumed_samples: 352665600  total_loss: 2.969  time: 0.3443 s/iter  data_time: 0.2241 s/iter total_throughput: 2973.84 samples/s lr: 2.65e-05  
[09/23 12:33:45] lb.utils.events INFO:  eta: 1:20:26  iteration: 344499/375342  consumed_samples: 352768000  total_loss: 2.972  time: 0.3443 s/iter  data_time: 0.2171 s/iter total_throughput: 2973.83 samples/s lr: 2.64e-05  
[09/23 12:34:19] lb.utils.events INFO:  eta: 1:20:02  iteration: 344599/375342  consumed_samples: 352870400  total_loss: 2.968  time: 0.3443 s/iter  data_time: 0.2108 s/iter total_throughput: 2973.84 samples/s lr: 2.63e-05  
[09/23 12:34:54] lb.utils.events INFO:  eta: 1:19:47  iteration: 344699/375342  consumed_samples: 352972800  total_loss: 2.961  time: 0.3443 s/iter  data_time: 0.2065 s/iter total_throughput: 2973.84 samples/s lr: 2.62e-05  
[09/23 12:35:28] lb.utils.events INFO:  eta: 1:19:32  iteration: 344799/375342  consumed_samples: 353075200  total_loss: 2.969  time: 0.3443 s/iter  data_time: 0.2238 s/iter total_throughput: 2973.84 samples/s lr: 2.61e-05  
[09/23 12:36:02] lb.utils.events INFO:  eta: 1:19:30  iteration: 344899/375342  consumed_samples: 353177600  total_loss: 2.965  time: 0.3443 s/iter  data_time: 0.2041 s/iter total_throughput: 2973.85 samples/s lr: 2.60e-05  
[09/23 12:36:36] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0344999
[09/23 12:36:37] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/23 12:36:37] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/23 12:36:41] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.1003 s/iter. Inference: 0.1610 s/iter. Eval: 0.0021 s/iter. Total: 0.2634 s/iter. ETA=0:00:09
[09/23 12:36:46] lb.evaluation.evaluator INFO: Inference done 28672/50000. Dataloading: 0.1164 s/iter. Inference: 0.1689 s/iter. Eval: 0.0021 s/iter. Total: 0.2875 s/iter. ETA=0:00:05
[09/23 12:36:51] lb.evaluation.evaluator INFO: Inference done 46080/50000. Dataloading: 0.1232 s/iter. Inference: 0.1664 s/iter. Eval: 0.0021 s/iter. Total: 0.2918 s/iter. ETA=0:00:00
[09/23 12:36:52] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/23 12:36:52] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.613401 (0.000252 s / iter per device, on 8 devices)
[09/23 12:36:52] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000147 s / iter per device, on 8 devices)
[09/23 12:36:52] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/23 12:36:52] lb.evaluation.utils INFO: copypaste: Acc@1=79.93599999999999
[09/23 12:36:52] lb.evaluation.utils INFO: copypaste: Acc@5=94.428
[09/23 12:36:52] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 79.93600, better than last best score 79.83800 @ iteration 339999.
[09/23 12:36:52] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/23 12:36:53] lb.utils.events INFO:  eta: 1:19:26  iteration: 344999/375342  consumed_samples: 353280000  total_loss: 2.962  time: 0.3443 s/iter  data_time: 0.2101 s/iter total_throughput: 2973.86 samples/s lr: 2.59e-05  
[09/23 12:37:26] lb.utils.events INFO:  eta: 1:19:14  iteration: 345099/375342  consumed_samples: 353382400  total_loss: 2.971  time: 0.3443 s/iter  data_time: 0.2284 s/iter total_throughput: 2973.90 samples/s lr: 2.58e-05  
[09/23 12:38:00] lb.utils.events INFO:  eta: 1:19:00  iteration: 345199/375342  consumed_samples: 353484800  total_loss: 2.96  time: 0.3443 s/iter  data_time: 0.2106 s/iter total_throughput: 2973.90 samples/s lr: 2.57e-05  
[09/23 12:38:34] lb.utils.events INFO:  eta: 1:18:40  iteration: 345299/375342  consumed_samples: 353587200  total_loss: 2.951  time: 0.3443 s/iter  data_time: 0.2166 s/iter total_throughput: 2973.91 samples/s lr: 2.56e-05  
[09/23 12:39:08] lb.utils.events INFO:  eta: 1:18:40  iteration: 345399/375342  consumed_samples: 353689600  total_loss: 2.963  time: 0.3443 s/iter  data_time: 0.2146 s/iter total_throughput: 2973.92 samples/s lr: 2.55e-05  
[09/23 12:39:43] lb.utils.events INFO:  eta: 1:18:36  iteration: 345499/375342  consumed_samples: 353792000  total_loss: 2.963  time: 0.3443 s/iter  data_time: 0.2123 s/iter total_throughput: 2973.93 samples/s lr: 2.54e-05  
[09/23 12:40:17] lb.utils.events INFO:  eta: 1:18:34  iteration: 345599/375342  consumed_samples: 353894400  total_loss: 2.97  time: 0.3443 s/iter  data_time: 0.2200 s/iter total_throughput: 2973.93 samples/s lr: 2.53e-05  
[09/23 12:40:52] lb.utils.events INFO:  eta: 1:18:17  iteration: 345699/375342  consumed_samples: 353996800  total_loss: 2.964  time: 0.3443 s/iter  data_time: 0.2188 s/iter total_throughput: 2973.92 samples/s lr: 2.52e-05  
[09/23 12:41:26] lb.utils.events INFO:  eta: 1:18:04  iteration: 345799/375342  consumed_samples: 354099200  total_loss: 2.955  time: 0.3443 s/iter  data_time: 0.2212 s/iter total_throughput: 2973.91 samples/s lr: 2.51e-05  
[09/23 12:42:01] lb.utils.events INFO:  eta: 1:17:33  iteration: 345899/375342  consumed_samples: 354201600  total_loss: 2.969  time: 0.3443 s/iter  data_time: 0.2192 s/iter total_throughput: 2973.92 samples/s lr: 2.50e-05  
[09/23 12:42:36] lb.utils.events INFO:  eta: 1:17:13  iteration: 345999/375342  consumed_samples: 354304000  total_loss: 2.972  time: 0.3443 s/iter  data_time: 0.2249 s/iter total_throughput: 2973.91 samples/s lr: 2.49e-05  
[09/23 12:43:10] lb.utils.events INFO:  eta: 1:16:38  iteration: 346099/375342  consumed_samples: 354406400  total_loss: 2.97  time: 0.3443 s/iter  data_time: 0.2133 s/iter total_throughput: 2973.90 samples/s lr: 2.48e-05  
[09/23 12:43:44] lb.utils.events INFO:  eta: 1:16:32  iteration: 346199/375342  consumed_samples: 354508800  total_loss: 2.947  time: 0.3443 s/iter  data_time: 0.2157 s/iter total_throughput: 2973.91 samples/s lr: 2.47e-05  
[09/23 12:44:19] lb.utils.events INFO:  eta: 1:16:06  iteration: 346299/375342  consumed_samples: 354611200  total_loss: 2.959  time: 0.3443 s/iter  data_time: 0.2127 s/iter total_throughput: 2973.91 samples/s lr: 2.46e-05  
[09/23 12:44:53] lb.utils.events INFO:  eta: 1:15:41  iteration: 346399/375342  consumed_samples: 354713600  total_loss: 2.98  time: 0.3443 s/iter  data_time: 0.2186 s/iter total_throughput: 2973.91 samples/s lr: 2.45e-05  
[09/23 12:45:28] lb.utils.events INFO:  eta: 1:15:23  iteration: 346499/375342  consumed_samples: 354816000  total_loss: 2.977  time: 0.3443 s/iter  data_time: 0.2229 s/iter total_throughput: 2973.91 samples/s lr: 2.44e-05  
[09/23 12:46:02] lb.utils.events INFO:  eta: 1:14:52  iteration: 346599/375342  consumed_samples: 354918400  total_loss: 2.96  time: 0.3443 s/iter  data_time: 0.2042 s/iter total_throughput: 2973.92 samples/s lr: 2.43e-05  
[09/23 12:46:37] lb.utils.events INFO:  eta: 1:14:47  iteration: 346699/375342  consumed_samples: 355020800  total_loss: 2.971  time: 0.3443 s/iter  data_time: 0.2078 s/iter total_throughput: 2973.91 samples/s lr: 2.42e-05  
[09/23 12:47:11] lb.utils.events INFO:  eta: 1:14:36  iteration: 346799/375342  consumed_samples: 355123200  total_loss: 2.965  time: 0.3443 s/iter  data_time: 0.2097 s/iter total_throughput: 2973.92 samples/s lr: 2.41e-05  
[09/23 12:47:45] lb.utils.events INFO:  eta: 1:14:22  iteration: 346899/375342  consumed_samples: 355225600  total_loss: 2.98  time: 0.3443 s/iter  data_time: 0.2116 s/iter total_throughput: 2973.92 samples/s lr: 2.40e-05  
[09/23 12:48:20] lb.utils.events INFO:  eta: 1:13:46  iteration: 346999/375342  consumed_samples: 355328000  total_loss: 2.988  time: 0.3443 s/iter  data_time: 0.2152 s/iter total_throughput: 2973.92 samples/s lr: 2.39e-05  
[09/23 12:48:54] lb.utils.events INFO:  eta: 1:13:34  iteration: 347099/375342  consumed_samples: 355430400  total_loss: 2.953  time: 0.3443 s/iter  data_time: 0.2242 s/iter total_throughput: 2973.92 samples/s lr: 2.38e-05  
[09/23 12:49:29] lb.utils.events INFO:  eta: 1:13:10  iteration: 347199/375342  consumed_samples: 355532800  total_loss: 2.951  time: 0.3443 s/iter  data_time: 0.2190 s/iter total_throughput: 2973.91 samples/s lr: 2.37e-05  
[09/23 12:50:03] lb.utils.events INFO:  eta: 1:12:57  iteration: 347299/375342  consumed_samples: 355635200  total_loss: 2.964  time: 0.3443 s/iter  data_time: 0.2250 s/iter total_throughput: 2973.91 samples/s lr: 2.36e-05  
[09/23 12:50:38] lb.utils.events INFO:  eta: 1:12:45  iteration: 347399/375342  consumed_samples: 355737600  total_loss: 2.954  time: 0.3443 s/iter  data_time: 0.2214 s/iter total_throughput: 2973.91 samples/s lr: 2.35e-05  
[09/23 12:51:12] lb.utils.events INFO:  eta: 1:12:33  iteration: 347499/375342  consumed_samples: 355840000  total_loss: 2.953  time: 0.3443 s/iter  data_time: 0.2153 s/iter total_throughput: 2973.91 samples/s lr: 2.34e-05  
[09/23 12:51:47] lb.utils.events INFO:  eta: 1:12:18  iteration: 347599/375342  consumed_samples: 355942400  total_loss: 2.964  time: 0.3443 s/iter  data_time: 0.2217 s/iter total_throughput: 2973.91 samples/s lr: 2.33e-05  
[09/23 12:52:21] lb.utils.events INFO:  eta: 1:11:54  iteration: 347699/375342  consumed_samples: 356044800  total_loss: 2.967  time: 0.3443 s/iter  data_time: 0.2087 s/iter total_throughput: 2973.91 samples/s lr: 2.32e-05  
[09/23 12:52:55] lb.utils.events INFO:  eta: 1:11:38  iteration: 347799/375342  consumed_samples: 356147200  total_loss: 2.968  time: 0.3443 s/iter  data_time: 0.2156 s/iter total_throughput: 2973.92 samples/s lr: 2.31e-05  
[09/23 12:53:30] lb.utils.events INFO:  eta: 1:11:14  iteration: 347899/375342  consumed_samples: 356249600  total_loss: 2.952  time: 0.3443 s/iter  data_time: 0.2173 s/iter total_throughput: 2973.92 samples/s lr: 2.30e-05  
[09/23 12:54:04] lb.utils.events INFO:  eta: 1:11:07  iteration: 347999/375342  consumed_samples: 356352000  total_loss: 2.95  time: 0.3443 s/iter  data_time: 0.2134 s/iter total_throughput: 2973.92 samples/s lr: 2.29e-05  
[09/23 12:54:38] lb.utils.events INFO:  eta: 1:11:02  iteration: 348099/375342  consumed_samples: 356454400  total_loss: 2.968  time: 0.3443 s/iter  data_time: 0.2221 s/iter total_throughput: 2973.93 samples/s lr: 2.28e-05  
[09/23 12:55:12] lb.utils.events INFO:  eta: 1:10:50  iteration: 348199/375342  consumed_samples: 356556800  total_loss: 2.953  time: 0.3443 s/iter  data_time: 0.2274 s/iter total_throughput: 2973.93 samples/s lr: 2.27e-05  
[09/23 12:55:47] lb.utils.events INFO:  eta: 1:10:37  iteration: 348299/375342  consumed_samples: 356659200  total_loss: 2.939  time: 0.3443 s/iter  data_time: 0.2272 s/iter total_throughput: 2973.93 samples/s lr: 2.26e-05  
[09/23 12:56:21] lb.utils.events INFO:  eta: 1:10:20  iteration: 348399/375342  consumed_samples: 356761600  total_loss: 2.955  time: 0.3443 s/iter  data_time: 0.2184 s/iter total_throughput: 2973.93 samples/s lr: 2.25e-05  
[09/23 12:56:55] lb.utils.events INFO:  eta: 1:10:01  iteration: 348499/375342  consumed_samples: 356864000  total_loss: 2.941  time: 0.3443 s/iter  data_time: 0.2300 s/iter total_throughput: 2973.94 samples/s lr: 2.24e-05  
[09/23 12:57:30] lb.utils.events INFO:  eta: 1:09:41  iteration: 348599/375342  consumed_samples: 356966400  total_loss: 2.942  time: 0.3443 s/iter  data_time: 0.2072 s/iter total_throughput: 2973.95 samples/s lr: 2.23e-05  
[09/23 12:58:04] lb.utils.events INFO:  eta: 1:09:22  iteration: 348699/375342  consumed_samples: 357068800  total_loss: 2.962  time: 0.3443 s/iter  data_time: 0.2109 s/iter total_throughput: 2973.95 samples/s lr: 2.23e-05  
[09/23 12:58:38] lb.utils.events INFO:  eta: 1:09:02  iteration: 348799/375342  consumed_samples: 357171200  total_loss: 2.973  time: 0.3443 s/iter  data_time: 0.2116 s/iter total_throughput: 2973.96 samples/s lr: 2.22e-05  
[09/23 12:59:12] lb.utils.events INFO:  eta: 1:08:54  iteration: 348899/375342  consumed_samples: 357273600  total_loss: 2.965  time: 0.3443 s/iter  data_time: 0.2127 s/iter total_throughput: 2973.98 samples/s lr: 2.21e-05  
[09/23 12:59:46] lb.utils.events INFO:  eta: 1:08:41  iteration: 348999/375342  consumed_samples: 357376000  total_loss: 2.964  time: 0.3443 s/iter  data_time: 0.2059 s/iter total_throughput: 2973.98 samples/s lr: 2.20e-05  
[09/23 13:00:19] lb.utils.events INFO:  eta: 1:08:25  iteration: 349099/375342  consumed_samples: 357478400  total_loss: 2.973  time: 0.3443 s/iter  data_time: 0.2061 s/iter total_throughput: 2974.00 samples/s lr: 2.19e-05  
[09/23 13:00:53] lb.utils.events INFO:  eta: 1:08:05  iteration: 349199/375342  consumed_samples: 357580800  total_loss: 2.958  time: 0.3443 s/iter  data_time: 0.2178 s/iter total_throughput: 2974.02 samples/s lr: 2.18e-05  
[09/23 13:01:27] lb.utils.events INFO:  eta: 1:07:55  iteration: 349299/375342  consumed_samples: 357683200  total_loss: 2.945  time: 0.3443 s/iter  data_time: 0.2037 s/iter total_throughput: 2974.02 samples/s lr: 2.17e-05  
[09/23 13:02:01] lb.utils.events INFO:  eta: 1:07:42  iteration: 349399/375342  consumed_samples: 357785600  total_loss: 2.956  time: 0.3443 s/iter  data_time: 0.2098 s/iter total_throughput: 2974.04 samples/s lr: 2.16e-05  
[09/23 13:02:35] lb.utils.events INFO:  eta: 1:07:32  iteration: 349499/375342  consumed_samples: 357888000  total_loss: 2.971  time: 0.3443 s/iter  data_time: 0.2219 s/iter total_throughput: 2974.05 samples/s lr: 2.15e-05  
[09/23 13:03:09] lb.utils.events INFO:  eta: 1:07:24  iteration: 349599/375342  consumed_samples: 357990400  total_loss: 2.963  time: 0.3443 s/iter  data_time: 0.2095 s/iter total_throughput: 2974.06 samples/s lr: 2.14e-05  
[09/23 13:03:43] lb.utils.events INFO:  eta: 1:07:09  iteration: 349699/375342  consumed_samples: 358092800  total_loss: 2.957  time: 0.3443 s/iter  data_time: 0.2172 s/iter total_throughput: 2974.07 samples/s lr: 2.14e-05  
[09/23 13:04:17] lb.utils.events INFO:  eta: 1:07:00  iteration: 349799/375342  consumed_samples: 358195200  total_loss: 2.951  time: 0.3443 s/iter  data_time: 0.2160 s/iter total_throughput: 2974.09 samples/s lr: 2.13e-05  
[09/23 13:04:51] lb.utils.events INFO:  eta: 1:06:38  iteration: 349899/375342  consumed_samples: 358297600  total_loss: 2.958  time: 0.3443 s/iter  data_time: 0.2161 s/iter total_throughput: 2974.10 samples/s lr: 2.12e-05  
[09/23 13:05:25] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0349999
[09/23 13:05:25] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/23 13:05:25] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/23 13:05:30] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0979 s/iter. Inference: 0.1624 s/iter. Eval: 0.0019 s/iter. Total: 0.2622 s/iter. ETA=0:00:09
[09/23 13:05:35] lb.evaluation.evaluator INFO: Inference done 28672/50000. Dataloading: 0.0961 s/iter. Inference: 0.1895 s/iter. Eval: 0.0021 s/iter. Total: 0.2877 s/iter. ETA=0:00:05
[09/23 13:05:40] lb.evaluation.evaluator INFO: Inference done 46080/50000. Dataloading: 0.1073 s/iter. Inference: 0.1836 s/iter. Eval: 0.0021 s/iter. Total: 0.2930 s/iter. ETA=0:00:00
[09/23 13:05:41] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/23 13:05:41] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.655478 (0.000253 s / iter per device, on 8 devices)
[09/23 13:05:41] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:08 (0.000161 s / iter per device, on 8 devices)
[09/23 13:05:41] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/23 13:05:41] lb.evaluation.utils INFO: copypaste: Acc@1=79.93400000000001
[09/23 13:05:41] lb.evaluation.utils INFO: copypaste: Acc@5=94.484
[09/23 13:05:41] lb.engine.hooks INFO: Not saving as latest eval score for Acc@1 is 79.93400, not better than best score 79.93600 @ iteration 344999.
[09/23 13:05:41] lb.utils.events INFO:  eta: 1:06:22  iteration: 349999/375342  consumed_samples: 358400000  total_loss: 2.968  time: 0.3443 s/iter  data_time: 0.2063 s/iter total_throughput: 2974.12 samples/s lr: 2.11e-05  
[09/23 13:06:12] lb.utils.events INFO:  eta: 1:06:10  iteration: 350099/375342  consumed_samples: 358502400  total_loss: 2.957  time: 0.3443 s/iter  data_time: 0.2113 s/iter total_throughput: 2974.18 samples/s lr: 2.10e-05  
[09/23 13:06:48] lb.utils.events INFO:  eta: 1:05:51  iteration: 350199/375342  consumed_samples: 358604800  total_loss: 2.942  time: 0.3443 s/iter  data_time: 0.2162 s/iter total_throughput: 2974.16 samples/s lr: 2.09e-05  
[09/23 13:07:22] lb.utils.events INFO:  eta: 1:05:35  iteration: 350299/375342  consumed_samples: 358707200  total_loss: 2.958  time: 0.3443 s/iter  data_time: 0.2119 s/iter total_throughput: 2974.16 samples/s lr: 2.08e-05  
[09/23 13:07:56] lb.utils.events INFO:  eta: 1:05:09  iteration: 350399/375342  consumed_samples: 358809600  total_loss: 2.962  time: 0.3443 s/iter  data_time: 0.2047 s/iter total_throughput: 2974.17 samples/s lr: 2.07e-05  
[09/23 13:08:31] lb.utils.events INFO:  eta: 1:04:44  iteration: 350499/375342  consumed_samples: 358912000  total_loss: 2.949  time: 0.3443 s/iter  data_time: 0.2297 s/iter total_throughput: 2974.16 samples/s lr: 2.07e-05  
[09/23 13:09:06] lb.utils.events INFO:  eta: 1:04:24  iteration: 350599/375342  consumed_samples: 359014400  total_loss: 2.944  time: 0.3443 s/iter  data_time: 0.2221 s/iter total_throughput: 2974.15 samples/s lr: 2.06e-05  
[09/23 13:09:41] lb.utils.events INFO:  eta: 1:04:08  iteration: 350699/375342  consumed_samples: 359116800  total_loss: 2.945  time: 0.3443 s/iter  data_time: 0.2196 s/iter total_throughput: 2974.14 samples/s lr: 2.05e-05  
[09/23 13:10:16] lb.utils.events INFO:  eta: 1:03:59  iteration: 350799/375342  consumed_samples: 359219200  total_loss: 2.961  time: 0.3443 s/iter  data_time: 0.2287 s/iter total_throughput: 2974.12 samples/s lr: 2.04e-05  
[09/23 13:10:51] lb.utils.events INFO:  eta: 1:03:43  iteration: 350899/375342  consumed_samples: 359321600  total_loss: 2.958  time: 0.3443 s/iter  data_time: 0.2204 s/iter total_throughput: 2974.11 samples/s lr: 2.03e-05  
[09/23 13:11:25] lb.utils.events INFO:  eta: 1:03:21  iteration: 350999/375342  consumed_samples: 359424000  total_loss: 2.962  time: 0.3443 s/iter  data_time: 0.2257 s/iter total_throughput: 2974.11 samples/s lr: 2.02e-05  
[09/23 13:12:01] lb.utils.events INFO:  eta: 1:03:01  iteration: 351099/375342  consumed_samples: 359526400  total_loss: 2.953  time: 0.3443 s/iter  data_time: 0.2334 s/iter total_throughput: 2974.09 samples/s lr: 2.02e-05  
[09/23 13:12:35] lb.utils.events INFO:  eta: 1:02:54  iteration: 351199/375342  consumed_samples: 359628800  total_loss: 2.943  time: 0.3443 s/iter  data_time: 0.2188 s/iter total_throughput: 2974.08 samples/s lr: 2.01e-05  
[09/23 13:13:10] lb.utils.events INFO:  eta: 1:02:38  iteration: 351299/375342  consumed_samples: 359731200  total_loss: 2.972  time: 0.3443 s/iter  data_time: 0.2277 s/iter total_throughput: 2974.08 samples/s lr: 2.00e-05  
[09/23 13:13:44] lb.utils.events INFO:  eta: 1:02:21  iteration: 351399/375342  consumed_samples: 359833600  total_loss: 2.966  time: 0.3443 s/iter  data_time: 0.2149 s/iter total_throughput: 2974.08 samples/s lr: 1.99e-05  
[09/23 13:14:19] lb.utils.events INFO:  eta: 1:02:10  iteration: 351499/375342  consumed_samples: 359936000  total_loss: 2.961  time: 0.3443 s/iter  data_time: 0.2366 s/iter total_throughput: 2974.07 samples/s lr: 1.98e-05  
[09/23 13:14:54] lb.utils.events INFO:  eta: 1:02:02  iteration: 351599/375342  consumed_samples: 360038400  total_loss: 2.947  time: 0.3443 s/iter  data_time: 0.2111 s/iter total_throughput: 2974.06 samples/s lr: 1.97e-05  
[09/23 13:15:29] lb.utils.events INFO:  eta: 1:01:42  iteration: 351699/375342  consumed_samples: 360140800  total_loss: 2.944  time: 0.3443 s/iter  data_time: 0.2162 s/iter total_throughput: 2974.05 samples/s lr: 1.97e-05  
[09/23 13:16:03] lb.utils.events INFO:  eta: 1:01:23  iteration: 351799/375342  consumed_samples: 360243200  total_loss: 2.94  time: 0.3443 s/iter  data_time: 0.2112 s/iter total_throughput: 2974.05 samples/s lr: 1.96e-05  
[09/23 13:16:38] lb.utils.events INFO:  eta: 1:01:06  iteration: 351899/375342  consumed_samples: 360345600  total_loss: 2.946  time: 0.3443 s/iter  data_time: 0.2262 s/iter total_throughput: 2974.04 samples/s lr: 1.95e-05  
[09/23 13:17:13] lb.utils.events INFO:  eta: 1:01:06  iteration: 351999/375342  consumed_samples: 360448000  total_loss: 2.947  time: 0.3443 s/iter  data_time: 0.2154 s/iter total_throughput: 2974.04 samples/s lr: 1.94e-05  
[09/23 13:17:47] lb.utils.events INFO:  eta: 1:00:45  iteration: 352099/375342  consumed_samples: 360550400  total_loss: 2.938  time: 0.3443 s/iter  data_time: 0.2051 s/iter total_throughput: 2974.04 samples/s lr: 1.93e-05  
[09/23 13:18:22] lb.utils.events INFO:  eta: 1:00:40  iteration: 352199/375342  consumed_samples: 360652800  total_loss: 2.938  time: 0.3443 s/iter  data_time: 0.2091 s/iter total_throughput: 2974.03 samples/s lr: 1.93e-05  
[09/23 13:18:56] lb.utils.events INFO:  eta: 1:00:25  iteration: 352299/375342  consumed_samples: 360755200  total_loss: 2.952  time: 0.3443 s/iter  data_time: 0.2211 s/iter total_throughput: 2974.03 samples/s lr: 1.92e-05  
[09/23 13:19:31] lb.utils.events INFO:  eta: 1:00:11  iteration: 352399/375342  consumed_samples: 360857600  total_loss: 2.956  time: 0.3443 s/iter  data_time: 0.2209 s/iter total_throughput: 2974.02 samples/s lr: 1.91e-05  
[09/23 13:20:06] lb.utils.events INFO:  eta: 0:59:55  iteration: 352499/375342  consumed_samples: 360960000  total_loss: 2.96  time: 0.3443 s/iter  data_time: 0.2161 s/iter total_throughput: 2974.02 samples/s lr: 1.90e-05  
[09/23 13:20:40] lb.utils.events INFO:  eta: 0:59:40  iteration: 352599/375342  consumed_samples: 361062400  total_loss: 2.96  time: 0.3443 s/iter  data_time: 0.2095 s/iter total_throughput: 2974.01 samples/s lr: 1.89e-05  
[09/23 13:21:15] lb.utils.events INFO:  eta: 0:59:32  iteration: 352699/375342  consumed_samples: 361164800  total_loss: 2.951  time: 0.3443 s/iter  data_time: 0.2199 s/iter total_throughput: 2974.01 samples/s lr: 1.89e-05  
[09/23 13:21:50] lb.utils.events INFO:  eta: 0:59:17  iteration: 352799/375342  consumed_samples: 361267200  total_loss: 2.948  time: 0.3443 s/iter  data_time: 0.2222 s/iter total_throughput: 2974.00 samples/s lr: 1.88e-05  
[09/23 13:22:24] lb.utils.events INFO:  eta: 0:59:06  iteration: 352899/375342  consumed_samples: 361369600  total_loss: 2.943  time: 0.3443 s/iter  data_time: 0.2209 s/iter total_throughput: 2973.99 samples/s lr: 1.87e-05  
[09/23 13:22:59] lb.utils.events INFO:  eta: 0:58:46  iteration: 352999/375342  consumed_samples: 361472000  total_loss: 2.943  time: 0.3443 s/iter  data_time: 0.2098 s/iter total_throughput: 2973.99 samples/s lr: 1.86e-05  
[09/23 13:23:34] lb.utils.events INFO:  eta: 0:58:31  iteration: 353099/375342  consumed_samples: 361574400  total_loss: 2.946  time: 0.3443 s/iter  data_time: 0.2221 s/iter total_throughput: 2973.99 samples/s lr: 1.86e-05  
[09/23 13:24:08] lb.utils.events INFO:  eta: 0:58:17  iteration: 353199/375342  consumed_samples: 361676800  total_loss: 2.963  time: 0.3443 s/iter  data_time: 0.2116 s/iter total_throughput: 2973.98 samples/s lr: 1.85e-05  
[09/23 13:24:42] lb.utils.events INFO:  eta: 0:57:59  iteration: 353299/375342  consumed_samples: 361779200  total_loss: 2.956  time: 0.3443 s/iter  data_time: 0.2105 s/iter total_throughput: 2973.99 samples/s lr: 1.84e-05  
[09/23 13:25:17] lb.utils.events INFO:  eta: 0:57:37  iteration: 353399/375342  consumed_samples: 361881600  total_loss: 2.924  time: 0.3443 s/iter  data_time: 0.2210 s/iter total_throughput: 2973.98 samples/s lr: 1.83e-05  
[09/23 13:25:52] lb.utils.events INFO:  eta: 0:57:24  iteration: 353499/375342  consumed_samples: 361984000  total_loss: 2.933  time: 0.3443 s/iter  data_time: 0.2104 s/iter total_throughput: 2973.97 samples/s lr: 1.82e-05  
[09/23 13:26:27] lb.utils.events INFO:  eta: 0:56:54  iteration: 353599/375342  consumed_samples: 362086400  total_loss: 2.949  time: 0.3443 s/iter  data_time: 0.2230 s/iter total_throughput: 2973.96 samples/s lr: 1.82e-05  
[09/23 13:27:01] lb.utils.events INFO:  eta: 0:56:36  iteration: 353699/375342  consumed_samples: 362188800  total_loss: 2.952  time: 0.3443 s/iter  data_time: 0.2096 s/iter total_throughput: 2973.96 samples/s lr: 1.81e-05  
[09/23 13:27:36] lb.utils.events INFO:  eta: 0:56:21  iteration: 353799/375342  consumed_samples: 362291200  total_loss: 2.973  time: 0.3443 s/iter  data_time: 0.2148 s/iter total_throughput: 2973.96 samples/s lr: 1.80e-05  
[09/23 13:28:10] lb.utils.events INFO:  eta: 0:56:07  iteration: 353899/375342  consumed_samples: 362393600  total_loss: 2.975  time: 0.3443 s/iter  data_time: 0.2053 s/iter total_throughput: 2973.96 samples/s lr: 1.80e-05  
[09/23 13:28:45] lb.utils.events INFO:  eta: 0:55:51  iteration: 353999/375342  consumed_samples: 362496000  total_loss: 2.942  time: 0.3443 s/iter  data_time: 0.2105 s/iter total_throughput: 2973.96 samples/s lr: 1.79e-05  
[09/23 13:29:19] lb.utils.events INFO:  eta: 0:55:36  iteration: 354099/375342  consumed_samples: 362598400  total_loss: 2.943  time: 0.3443 s/iter  data_time: 0.2187 s/iter total_throughput: 2973.96 samples/s lr: 1.78e-05  
[09/23 13:29:54] lb.utils.events INFO:  eta: 0:55:16  iteration: 354199/375342  consumed_samples: 362700800  total_loss: 2.957  time: 0.3443 s/iter  data_time: 0.2318 s/iter total_throughput: 2973.95 samples/s lr: 1.77e-05  
[09/23 13:30:29] lb.utils.events INFO:  eta: 0:54:55  iteration: 354299/375342  consumed_samples: 362803200  total_loss: 2.949  time: 0.3443 s/iter  data_time: 0.2151 s/iter total_throughput: 2973.94 samples/s lr: 1.77e-05  
[09/23 13:31:04] lb.utils.events INFO:  eta: 0:54:46  iteration: 354399/375342  consumed_samples: 362905600  total_loss: 2.953  time: 0.3443 s/iter  data_time: 0.2375 s/iter total_throughput: 2973.93 samples/s lr: 1.76e-05  
[09/23 13:31:39] lb.utils.events INFO:  eta: 0:54:20  iteration: 354499/375342  consumed_samples: 363008000  total_loss: 2.95  time: 0.3443 s/iter  data_time: 0.2196 s/iter total_throughput: 2973.92 samples/s lr: 1.75e-05  
[09/23 13:32:13] lb.utils.events INFO:  eta: 0:54:04  iteration: 354599/375342  consumed_samples: 363110400  total_loss: 2.951  time: 0.3443 s/iter  data_time: 0.2274 s/iter total_throughput: 2973.91 samples/s lr: 1.74e-05  
[09/23 13:32:48] lb.utils.events INFO:  eta: 0:53:47  iteration: 354699/375342  consumed_samples: 363212800  total_loss: 2.955  time: 0.3443 s/iter  data_time: 0.2117 s/iter total_throughput: 2973.91 samples/s lr: 1.74e-05  
[09/23 13:33:23] lb.utils.events INFO:  eta: 0:53:30  iteration: 354799/375342  consumed_samples: 363315200  total_loss: 2.95  time: 0.3443 s/iter  data_time: 0.2171 s/iter total_throughput: 2973.90 samples/s lr: 1.73e-05  
[09/23 13:33:58] lb.utils.events INFO:  eta: 0:53:12  iteration: 354899/375342  consumed_samples: 363417600  total_loss: 2.95  time: 0.3443 s/iter  data_time: 0.2195 s/iter total_throughput: 2973.89 samples/s lr: 1.72e-05  
[09/23 13:34:32] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0354999
[09/23 13:34:32] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/23 13:34:32] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/23 13:34:37] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.1027 s/iter. Inference: 0.1629 s/iter. Eval: 0.0023 s/iter. Total: 0.2678 s/iter. ETA=0:00:09
[09/23 13:34:42] lb.evaluation.evaluator INFO: Inference done 28672/50000. Dataloading: 0.1108 s/iter. Inference: 0.1756 s/iter. Eval: 0.0020 s/iter. Total: 0.2886 s/iter. ETA=0:00:05
[09/23 13:34:47] lb.evaluation.evaluator INFO: Inference done 47104/50000. Dataloading: 0.1218 s/iter. Inference: 0.1683 s/iter. Eval: 0.0020 s/iter. Total: 0.2921 s/iter. ETA=0:00:00
[09/23 13:34:48] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/23 13:34:48] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.582567 (0.000252 s / iter per device, on 8 devices)
[09/23 13:34:48] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000148 s / iter per device, on 8 devices)
[09/23 13:34:48] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/23 13:34:48] lb.evaluation.utils INFO: copypaste: Acc@1=79.984
[09/23 13:34:48] lb.evaluation.utils INFO: copypaste: Acc@5=94.464
[09/23 13:34:48] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 79.98400, better than last best score 79.93600 @ iteration 344999.
[09/23 13:34:48] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/23 13:34:48] lb.utils.events INFO:  eta: 0:52:57  iteration: 354999/375342  consumed_samples: 363520000  total_loss: 2.94  time: 0.3443 s/iter  data_time: 0.2109 s/iter total_throughput: 2973.90 samples/s lr: 1.72e-05  
[09/23 13:35:21] lb.utils.events INFO:  eta: 0:52:48  iteration: 355099/375342  consumed_samples: 363622400  total_loss: 2.947  time: 0.3443 s/iter  data_time: 0.2119 s/iter total_throughput: 2973.94 samples/s lr: 1.71e-05  
[09/23 13:35:56] lb.utils.events INFO:  eta: 0:52:33  iteration: 355199/375342  consumed_samples: 363724800  total_loss: 2.948  time: 0.3443 s/iter  data_time: 0.2161 s/iter total_throughput: 2973.94 samples/s lr: 1.70e-05  
[09/23 13:36:31] lb.utils.events INFO:  eta: 0:52:17  iteration: 355299/375342  consumed_samples: 363827200  total_loss: 2.955  time: 0.3443 s/iter  data_time: 0.2143 s/iter total_throughput: 2973.92 samples/s lr: 1.69e-05  
[09/23 13:37:05] lb.utils.events INFO:  eta: 0:52:03  iteration: 355399/375342  consumed_samples: 363929600  total_loss: 2.962  time: 0.3443 s/iter  data_time: 0.2008 s/iter total_throughput: 2973.92 samples/s lr: 1.69e-05  
[09/23 13:37:40] lb.utils.events INFO:  eta: 0:51:55  iteration: 355499/375342  consumed_samples: 364032000  total_loss: 2.959  time: 0.3443 s/iter  data_time: 0.2153 s/iter total_throughput: 2973.91 samples/s lr: 1.68e-05  
[09/23 13:38:15] lb.utils.events INFO:  eta: 0:51:41  iteration: 355599/375342  consumed_samples: 364134400  total_loss: 2.956  time: 0.3443 s/iter  data_time: 0.2308 s/iter total_throughput: 2973.90 samples/s lr: 1.67e-05  
[09/23 13:38:49] lb.utils.events INFO:  eta: 0:51:20  iteration: 355699/375342  consumed_samples: 364236800  total_loss: 2.949  time: 0.3443 s/iter  data_time: 0.2169 s/iter total_throughput: 2973.90 samples/s lr: 1.67e-05  
[09/23 13:39:24] lb.utils.events INFO:  eta: 0:51:09  iteration: 355799/375342  consumed_samples: 364339200  total_loss: 2.947  time: 0.3443 s/iter  data_time: 0.2116 s/iter total_throughput: 2973.90 samples/s lr: 1.66e-05  
[09/23 13:39:59] lb.utils.events INFO:  eta: 0:50:57  iteration: 355899/375342  consumed_samples: 364441600  total_loss: 2.951  time: 0.3443 s/iter  data_time: 0.2191 s/iter total_throughput: 2973.89 samples/s lr: 1.65e-05  
[09/23 13:40:33] lb.utils.events INFO:  eta: 0:50:38  iteration: 355999/375342  consumed_samples: 364544000  total_loss: 2.972  time: 0.3443 s/iter  data_time: 0.2146 s/iter total_throughput: 2973.89 samples/s lr: 1.65e-05  
[09/23 13:41:07] lb.utils.events INFO:  eta: 0:50:11  iteration: 356099/375342  consumed_samples: 364646400  total_loss: 2.965  time: 0.3443 s/iter  data_time: 0.2102 s/iter total_throughput: 2973.89 samples/s lr: 1.64e-05  
[09/23 13:41:42] lb.utils.events INFO:  eta: 0:49:59  iteration: 356199/375342  consumed_samples: 364748800  total_loss: 2.953  time: 0.3443 s/iter  data_time: 0.2078 s/iter total_throughput: 2973.90 samples/s lr: 1.63e-05  
[09/23 13:42:16] lb.utils.events INFO:  eta: 0:49:51  iteration: 356299/375342  consumed_samples: 364851200  total_loss: 2.955  time: 0.3443 s/iter  data_time: 0.2140 s/iter total_throughput: 2973.90 samples/s lr: 1.63e-05  
[09/23 13:42:50] lb.utils.events INFO:  eta: 0:49:32  iteration: 356399/375342  consumed_samples: 364953600  total_loss: 2.967  time: 0.3443 s/iter  data_time: 0.2081 s/iter total_throughput: 2973.90 samples/s lr: 1.62e-05  
[09/23 13:43:25] lb.utils.events INFO:  eta: 0:49:05  iteration: 356499/375342  consumed_samples: 365056000  total_loss: 2.969  time: 0.3443 s/iter  data_time: 0.2257 s/iter total_throughput: 2973.89 samples/s lr: 1.61e-05  
[09/23 13:44:00] lb.utils.events INFO:  eta: 0:48:57  iteration: 356599/375342  consumed_samples: 365158400  total_loss: 2.957  time: 0.3443 s/iter  data_time: 0.2141 s/iter total_throughput: 2973.89 samples/s lr: 1.61e-05  
[09/23 13:44:34] lb.utils.events INFO:  eta: 0:48:47  iteration: 356699/375342  consumed_samples: 365260800  total_loss: 2.954  time: 0.3443 s/iter  data_time: 0.2065 s/iter total_throughput: 2973.90 samples/s lr: 1.60e-05  
[09/23 13:45:09] lb.utils.events INFO:  eta: 0:48:31  iteration: 356799/375342  consumed_samples: 365363200  total_loss: 2.961  time: 0.3443 s/iter  data_time: 0.2232 s/iter total_throughput: 2973.89 samples/s lr: 1.59e-05  
[09/23 13:45:43] lb.utils.events INFO:  eta: 0:48:12  iteration: 356899/375342  consumed_samples: 365465600  total_loss: 2.974  time: 0.3443 s/iter  data_time: 0.2129 s/iter total_throughput: 2973.89 samples/s lr: 1.59e-05  
[09/23 13:46:17] lb.utils.events INFO:  eta: 0:47:53  iteration: 356999/375342  consumed_samples: 365568000  total_loss: 2.972  time: 0.3443 s/iter  data_time: 0.2225 s/iter total_throughput: 2973.89 samples/s lr: 1.58e-05  
[09/23 13:46:52] lb.utils.events INFO:  eta: 0:47:32  iteration: 357099/375342  consumed_samples: 365670400  total_loss: 2.951  time: 0.3443 s/iter  data_time: 0.2336 s/iter total_throughput: 2973.88 samples/s lr: 1.58e-05  
[09/23 13:47:27] lb.utils.events INFO:  eta: 0:47:17  iteration: 357199/375342  consumed_samples: 365772800  total_loss: 2.951  time: 0.3443 s/iter  data_time: 0.2250 s/iter total_throughput: 2973.87 samples/s lr: 1.57e-05  
[09/23 13:48:02] lb.utils.events INFO:  eta: 0:47:05  iteration: 357299/375342  consumed_samples: 365875200  total_loss: 2.958  time: 0.3443 s/iter  data_time: 0.2107 s/iter total_throughput: 2973.87 samples/s lr: 1.56e-05  
[09/23 13:48:36] lb.utils.events INFO:  eta: 0:46:50  iteration: 357399/375342  consumed_samples: 365977600  total_loss: 2.941  time: 0.3443 s/iter  data_time: 0.2103 s/iter total_throughput: 2973.86 samples/s lr: 1.56e-05  
[09/23 13:49:11] lb.utils.events INFO:  eta: 0:46:46  iteration: 357499/375342  consumed_samples: 366080000  total_loss: 2.949  time: 0.3443 s/iter  data_time: 0.2260 s/iter total_throughput: 2973.86 samples/s lr: 1.55e-05  
[09/23 13:49:45] lb.utils.events INFO:  eta: 0:46:29  iteration: 357599/375342  consumed_samples: 366182400  total_loss: 2.949  time: 0.3443 s/iter  data_time: 0.2141 s/iter total_throughput: 2973.87 samples/s lr: 1.54e-05  
[09/23 13:50:19] lb.utils.events INFO:  eta: 0:46:12  iteration: 357699/375342  consumed_samples: 366284800  total_loss: 2.92  time: 0.3443 s/iter  data_time: 0.2126 s/iter total_throughput: 2973.87 samples/s lr: 1.54e-05  
[09/23 13:50:53] lb.utils.events INFO:  eta: 0:46:03  iteration: 357799/375342  consumed_samples: 366387200  total_loss: 2.939  time: 0.3443 s/iter  data_time: 0.2040 s/iter total_throughput: 2973.88 samples/s lr: 1.53e-05  
[09/23 13:51:28] lb.utils.events INFO:  eta: 0:45:48  iteration: 357899/375342  consumed_samples: 366489600  total_loss: 2.953  time: 0.3443 s/iter  data_time: 0.2150 s/iter total_throughput: 2973.88 samples/s lr: 1.53e-05  
[09/23 13:52:03] lb.utils.events INFO:  eta: 0:45:34  iteration: 357999/375342  consumed_samples: 366592000  total_loss: 2.95  time: 0.3443 s/iter  data_time: 0.2254 s/iter total_throughput: 2973.87 samples/s lr: 1.52e-05  
[09/23 13:52:38] lb.utils.events INFO:  eta: 0:45:16  iteration: 358099/375342  consumed_samples: 366694400  total_loss: 2.948  time: 0.3443 s/iter  data_time: 0.2084 s/iter total_throughput: 2973.86 samples/s lr: 1.51e-05  
[09/23 13:53:12] lb.utils.events INFO:  eta: 0:44:52  iteration: 358199/375342  consumed_samples: 366796800  total_loss: 2.939  time: 0.3443 s/iter  data_time: 0.2187 s/iter total_throughput: 2973.85 samples/s lr: 1.51e-05  
[09/23 13:53:47] lb.utils.events INFO:  eta: 0:44:31  iteration: 358299/375342  consumed_samples: 366899200  total_loss: 2.942  time: 0.3443 s/iter  data_time: 0.2296 s/iter total_throughput: 2973.84 samples/s lr: 1.50e-05  
[09/23 13:54:22] lb.utils.events INFO:  eta: 0:44:16  iteration: 358399/375342  consumed_samples: 367001600  total_loss: 2.938  time: 0.3443 s/iter  data_time: 0.2132 s/iter total_throughput: 2973.84 samples/s lr: 1.50e-05  
[09/23 13:54:56] lb.utils.events INFO:  eta: 0:43:58  iteration: 358499/375342  consumed_samples: 367104000  total_loss: 2.954  time: 0.3443 s/iter  data_time: 0.2222 s/iter total_throughput: 2973.84 samples/s lr: 1.49e-05  
[09/23 13:55:31] lb.utils.events INFO:  eta: 0:43:42  iteration: 358599/375342  consumed_samples: 367206400  total_loss: 2.945  time: 0.3443 s/iter  data_time: 0.2284 s/iter total_throughput: 2973.83 samples/s lr: 1.49e-05  
[09/23 13:56:06] lb.utils.events INFO:  eta: 0:43:30  iteration: 358699/375342  consumed_samples: 367308800  total_loss: 2.928  time: 0.3443 s/iter  data_time: 0.2081 s/iter total_throughput: 2973.83 samples/s lr: 1.48e-05  
[09/23 13:56:40] lb.utils.events INFO:  eta: 0:43:07  iteration: 358799/375342  consumed_samples: 367411200  total_loss: 2.936  time: 0.3443 s/iter  data_time: 0.2199 s/iter total_throughput: 2973.82 samples/s lr: 1.47e-05  
[09/23 13:57:15] lb.utils.events INFO:  eta: 0:42:49  iteration: 358899/375342  consumed_samples: 367513600  total_loss: 2.933  time: 0.3443 s/iter  data_time: 0.2110 s/iter total_throughput: 2973.82 samples/s lr: 1.47e-05  
[09/23 13:57:49] lb.utils.events INFO:  eta: 0:42:35  iteration: 358999/375342  consumed_samples: 367616000  total_loss: 2.937  time: 0.3443 s/iter  data_time: 0.2141 s/iter total_throughput: 2973.83 samples/s lr: 1.46e-05  
[09/23 13:58:24] lb.utils.events INFO:  eta: 0:42:26  iteration: 359099/375342  consumed_samples: 367718400  total_loss: 2.938  time: 0.3443 s/iter  data_time: 0.2244 s/iter total_throughput: 2973.82 samples/s lr: 1.46e-05  
[09/23 13:58:58] lb.utils.events INFO:  eta: 0:42:14  iteration: 359199/375342  consumed_samples: 367820800  total_loss: 2.931  time: 0.3443 s/iter  data_time: 0.2221 s/iter total_throughput: 2973.82 samples/s lr: 1.45e-05  
[09/23 13:59:33] lb.utils.events INFO:  eta: 0:42:05  iteration: 359299/375342  consumed_samples: 367923200  total_loss: 2.938  time: 0.3443 s/iter  data_time: 0.2214 s/iter total_throughput: 2973.82 samples/s lr: 1.45e-05  
[09/23 14:00:07] lb.utils.events INFO:  eta: 0:41:45  iteration: 359399/375342  consumed_samples: 368025600  total_loss: 2.933  time: 0.3443 s/iter  data_time: 0.2127 s/iter total_throughput: 2973.82 samples/s lr: 1.44e-05  
[09/23 14:00:42] lb.utils.events INFO:  eta: 0:41:27  iteration: 359499/375342  consumed_samples: 368128000  total_loss: 2.924  time: 0.3443 s/iter  data_time: 0.2176 s/iter total_throughput: 2973.81 samples/s lr: 1.43e-05  
[09/23 14:01:17] lb.utils.events INFO:  eta: 0:41:12  iteration: 359599/375342  consumed_samples: 368230400  total_loss: 2.932  time: 0.3443 s/iter  data_time: 0.2135 s/iter total_throughput: 2973.81 samples/s lr: 1.43e-05  
[09/23 14:01:51] lb.utils.events INFO:  eta: 0:40:54  iteration: 359699/375342  consumed_samples: 368332800  total_loss: 2.942  time: 0.3443 s/iter  data_time: 0.2228 s/iter total_throughput: 2973.81 samples/s lr: 1.42e-05  
[09/23 14:02:25] lb.utils.events INFO:  eta: 0:40:38  iteration: 359799/375342  consumed_samples: 368435200  total_loss: 2.945  time: 0.3443 s/iter  data_time: 0.2150 s/iter total_throughput: 2973.82 samples/s lr: 1.42e-05  
[09/23 14:02:59] lb.utils.events INFO:  eta: 0:40:23  iteration: 359899/375342  consumed_samples: 368537600  total_loss: 2.932  time: 0.3443 s/iter  data_time: 0.2068 s/iter total_throughput: 2973.82 samples/s lr: 1.41e-05  
[09/23 14:03:34] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0359999
[09/23 14:03:34] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/23 14:03:34] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/23 14:03:39] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.1118 s/iter. Inference: 0.1694 s/iter. Eval: 0.0019 s/iter. Total: 0.2831 s/iter. ETA=0:00:10
[09/23 14:03:44] lb.evaluation.evaluator INFO: Inference done 28672/50000. Dataloading: 0.1218 s/iter. Inference: 0.1710 s/iter. Eval: 0.0020 s/iter. Total: 0.2948 s/iter. ETA=0:00:05
[09/23 14:03:49] lb.evaluation.evaluator INFO: Inference done 47104/50000. Dataloading: 0.1258 s/iter. Inference: 0.1683 s/iter. Eval: 0.0020 s/iter. Total: 0.2961 s/iter. ETA=0:00:00
[09/23 14:03:50] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/23 14:03:50] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.655341 (0.000253 s / iter per device, on 8 devices)
[09/23 14:03:50] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000148 s / iter per device, on 8 devices)
[09/23 14:03:50] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/23 14:03:50] lb.evaluation.utils INFO: copypaste: Acc@1=80.048
[09/23 14:03:50] lb.evaluation.utils INFO: copypaste: Acc@5=94.554
[09/23 14:03:50] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 80.04800, better than last best score 79.98400 @ iteration 354999.
[09/23 14:03:50] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/23 14:03:50] lb.utils.events INFO:  eta: 0:40:07  iteration: 359999/375342  consumed_samples: 368640000  total_loss: 2.931  time: 0.3443 s/iter  data_time: 0.2183 s/iter total_throughput: 2973.82 samples/s lr: 1.41e-05  
[09/23 14:04:23] lb.utils.events INFO:  eta: 0:39:53  iteration: 360099/375342  consumed_samples: 368742400  total_loss: 2.924  time: 0.3443 s/iter  data_time: 0.2053 s/iter total_throughput: 2973.88 samples/s lr: 1.40e-05  
[09/23 14:04:57] lb.utils.events INFO:  eta: 0:39:38  iteration: 360199/375342  consumed_samples: 368844800  total_loss: 2.936  time: 0.3443 s/iter  data_time: 0.2066 s/iter total_throughput: 2973.88 samples/s lr: 1.40e-05  
[09/23 14:05:31] lb.utils.events INFO:  eta: 0:39:23  iteration: 360299/375342  consumed_samples: 368947200  total_loss: 2.944  time: 0.3443 s/iter  data_time: 0.2211 s/iter total_throughput: 2973.89 samples/s lr: 1.39e-05  
[09/23 14:06:05] lb.utils.events INFO:  eta: 0:39:13  iteration: 360399/375342  consumed_samples: 369049600  total_loss: 2.937  time: 0.3443 s/iter  data_time: 0.2064 s/iter total_throughput: 2973.90 samples/s lr: 1.39e-05  
[09/23 14:06:40] lb.utils.events INFO:  eta: 0:39:03  iteration: 360499/375342  consumed_samples: 369152000  total_loss: 2.949  time: 0.3443 s/iter  data_time: 0.2120 s/iter total_throughput: 2973.90 samples/s lr: 1.38e-05  
[09/23 14:07:14] lb.utils.events INFO:  eta: 0:38:47  iteration: 360599/375342  consumed_samples: 369254400  total_loss: 2.953  time: 0.3443 s/iter  data_time: 0.2222 s/iter total_throughput: 2973.90 samples/s lr: 1.38e-05  
[09/23 14:07:48] lb.utils.events INFO:  eta: 0:38:34  iteration: 360699/375342  consumed_samples: 369356800  total_loss: 2.938  time: 0.3443 s/iter  data_time: 0.2091 s/iter total_throughput: 2973.90 samples/s lr: 1.37e-05  
[09/23 14:08:23] lb.utils.events INFO:  eta: 0:38:19  iteration: 360799/375342  consumed_samples: 369459200  total_loss: 2.936  time: 0.3443 s/iter  data_time: 0.2135 s/iter total_throughput: 2973.90 samples/s lr: 1.37e-05  
[09/23 14:08:57] lb.utils.events INFO:  eta: 0:38:06  iteration: 360899/375342  consumed_samples: 369561600  total_loss: 2.918  time: 0.3443 s/iter  data_time: 0.2237 s/iter total_throughput: 2973.90 samples/s lr: 1.36e-05  
[09/23 14:09:32] lb.utils.events INFO:  eta: 0:37:51  iteration: 360999/375342  consumed_samples: 369664000  total_loss: 2.914  time: 0.3443 s/iter  data_time: 0.2112 s/iter total_throughput: 2973.90 samples/s lr: 1.36e-05  
[09/23 14:10:06] lb.utils.events INFO:  eta: 0:37:29  iteration: 361099/375342  consumed_samples: 369766400  total_loss: 2.94  time: 0.3443 s/iter  data_time: 0.2156 s/iter total_throughput: 2973.90 samples/s lr: 1.35e-05  
[09/23 14:10:40] lb.utils.events INFO:  eta: 0:37:11  iteration: 361199/375342  consumed_samples: 369868800  total_loss: 2.936  time: 0.3443 s/iter  data_time: 0.2192 s/iter total_throughput: 2973.91 samples/s lr: 1.35e-05  
[09/23 14:11:14] lb.utils.events INFO:  eta: 0:36:49  iteration: 361299/375342  consumed_samples: 369971200  total_loss: 2.941  time: 0.3443 s/iter  data_time: 0.2117 s/iter total_throughput: 2973.92 samples/s lr: 1.34e-05  
[09/23 14:11:48] lb.utils.events INFO:  eta: 0:36:30  iteration: 361399/375342  consumed_samples: 370073600  total_loss: 2.94  time: 0.3443 s/iter  data_time: 0.2067 s/iter total_throughput: 2973.92 samples/s lr: 1.34e-05  
[09/23 14:12:23] lb.utils.events INFO:  eta: 0:36:13  iteration: 361499/375342  consumed_samples: 370176000  total_loss: 2.922  time: 0.3443 s/iter  data_time: 0.2296 s/iter total_throughput: 2973.93 samples/s lr: 1.33e-05  
[09/23 14:12:57] lb.utils.events INFO:  eta: 0:35:58  iteration: 361599/375342  consumed_samples: 370278400  total_loss: 2.922  time: 0.3443 s/iter  data_time: 0.2127 s/iter total_throughput: 2973.93 samples/s lr: 1.33e-05  
[09/23 14:13:31] lb.utils.events INFO:  eta: 0:35:40  iteration: 361699/375342  consumed_samples: 370380800  total_loss: 2.931  time: 0.3443 s/iter  data_time: 0.2039 s/iter total_throughput: 2973.94 samples/s lr: 1.32e-05  
[09/23 14:14:06] lb.utils.events INFO:  eta: 0:35:27  iteration: 361799/375342  consumed_samples: 370483200  total_loss: 2.931  time: 0.3443 s/iter  data_time: 0.2313 s/iter total_throughput: 2973.94 samples/s lr: 1.32e-05  
[09/23 14:14:40] lb.utils.events INFO:  eta: 0:35:11  iteration: 361899/375342  consumed_samples: 370585600  total_loss: 2.932  time: 0.3443 s/iter  data_time: 0.2195 s/iter total_throughput: 2973.93 samples/s lr: 1.31e-05  
[09/23 14:15:15] lb.utils.events INFO:  eta: 0:34:52  iteration: 361999/375342  consumed_samples: 370688000  total_loss: 2.94  time: 0.3443 s/iter  data_time: 0.2090 s/iter total_throughput: 2973.94 samples/s lr: 1.31e-05  
[09/23 14:15:49] lb.utils.events INFO:  eta: 0:34:34  iteration: 362099/375342  consumed_samples: 370790400  total_loss: 2.93  time: 0.3443 s/iter  data_time: 0.2205 s/iter total_throughput: 2973.93 samples/s lr: 1.30e-05  
[09/23 14:16:24] lb.utils.events INFO:  eta: 0:34:16  iteration: 362199/375342  consumed_samples: 370892800  total_loss: 2.914  time: 0.3443 s/iter  data_time: 0.2166 s/iter total_throughput: 2973.93 samples/s lr: 1.30e-05  
[09/23 14:16:58] lb.utils.events INFO:  eta: 0:34:02  iteration: 362299/375342  consumed_samples: 370995200  total_loss: 2.919  time: 0.3443 s/iter  data_time: 0.2184 s/iter total_throughput: 2973.94 samples/s lr: 1.29e-05  
[09/23 14:17:31] lb.utils.events INFO:  eta: 0:33:46  iteration: 362399/375342  consumed_samples: 371097600  total_loss: 2.927  time: 0.3443 s/iter  data_time: 0.2099 s/iter total_throughput: 2973.96 samples/s lr: 1.29e-05  
[09/23 14:18:05] lb.utils.events INFO:  eta: 0:33:30  iteration: 362499/375342  consumed_samples: 371200000  total_loss: 2.938  time: 0.3443 s/iter  data_time: 0.2076 s/iter total_throughput: 2973.97 samples/s lr: 1.29e-05  
[09/23 14:18:40] lb.utils.events INFO:  eta: 0:33:07  iteration: 362599/375342  consumed_samples: 371302400  total_loss: 2.946  time: 0.3443 s/iter  data_time: 0.2179 s/iter total_throughput: 2973.98 samples/s lr: 1.28e-05  
[09/23 14:19:14] lb.utils.events INFO:  eta: 0:32:50  iteration: 362699/375342  consumed_samples: 371404800  total_loss: 2.945  time: 0.3443 s/iter  data_time: 0.2203 s/iter total_throughput: 2973.98 samples/s lr: 1.28e-05  
[09/23 14:19:48] lb.utils.events INFO:  eta: 0:32:38  iteration: 362799/375342  consumed_samples: 371507200  total_loss: 2.94  time: 0.3443 s/iter  data_time: 0.2129 s/iter total_throughput: 2973.99 samples/s lr: 1.27e-05  
[09/23 14:20:22] lb.utils.events INFO:  eta: 0:32:21  iteration: 362899/375342  consumed_samples: 371609600  total_loss: 2.937  time: 0.3443 s/iter  data_time: 0.2126 s/iter total_throughput: 2973.99 samples/s lr: 1.27e-05  
[09/23 14:20:57] lb.utils.events INFO:  eta: 0:32:07  iteration: 362999/375342  consumed_samples: 371712000  total_loss: 2.926  time: 0.3443 s/iter  data_time: 0.2162 s/iter total_throughput: 2973.99 samples/s lr: 1.26e-05  
[09/23 14:21:31] lb.utils.events INFO:  eta: 0:32:00  iteration: 363099/375342  consumed_samples: 371814400  total_loss: 2.938  time: 0.3443 s/iter  data_time: 0.2073 s/iter total_throughput: 2974.00 samples/s lr: 1.26e-05  
[09/23 14:22:05] lb.utils.events INFO:  eta: 0:31:46  iteration: 363199/375342  consumed_samples: 371916800  total_loss: 2.937  time: 0.3443 s/iter  data_time: 0.2132 s/iter total_throughput: 2974.01 samples/s lr: 1.26e-05  
[09/23 14:22:39] lb.utils.events INFO:  eta: 0:31:26  iteration: 363299/375342  consumed_samples: 372019200  total_loss: 2.932  time: 0.3443 s/iter  data_time: 0.2067 s/iter total_throughput: 2974.02 samples/s lr: 1.25e-05  
[09/23 14:23:13] lb.utils.events INFO:  eta: 0:31:11  iteration: 363399/375342  consumed_samples: 372121600  total_loss: 2.938  time: 0.3443 s/iter  data_time: 0.2083 s/iter total_throughput: 2974.03 samples/s lr: 1.25e-05  
[09/23 14:23:47] lb.utils.events INFO:  eta: 0:30:52  iteration: 363499/375342  consumed_samples: 372224000  total_loss: 2.918  time: 0.3443 s/iter  data_time: 0.2239 s/iter total_throughput: 2974.04 samples/s lr: 1.24e-05  
[09/23 14:24:21] lb.utils.events INFO:  eta: 0:30:38  iteration: 363599/375342  consumed_samples: 372326400  total_loss: 2.914  time: 0.3443 s/iter  data_time: 0.2134 s/iter total_throughput: 2974.04 samples/s lr: 1.24e-05  
[09/23 14:24:55] lb.utils.events INFO:  eta: 0:30:21  iteration: 363699/375342  consumed_samples: 372428800  total_loss: 2.934  time: 0.3443 s/iter  data_time: 0.2131 s/iter total_throughput: 2974.06 samples/s lr: 1.23e-05  
[09/23 14:25:29] lb.utils.events INFO:  eta: 0:30:01  iteration: 363799/375342  consumed_samples: 372531200  total_loss: 2.964  time: 0.3443 s/iter  data_time: 0.2233 s/iter total_throughput: 2974.07 samples/s lr: 1.23e-05  
[09/23 14:26:02] lb.utils.events INFO:  eta: 0:29:47  iteration: 363899/375342  consumed_samples: 372633600  total_loss: 2.953  time: 0.3443 s/iter  data_time: 0.2063 s/iter total_throughput: 2974.09 samples/s lr: 1.23e-05  
[09/23 14:26:36] lb.utils.events INFO:  eta: 0:29:34  iteration: 363999/375342  consumed_samples: 372736000  total_loss: 2.946  time: 0.3443 s/iter  data_time: 0.2016 s/iter total_throughput: 2974.10 samples/s lr: 1.22e-05  
[09/23 14:27:10] lb.utils.events INFO:  eta: 0:29:14  iteration: 364099/375342  consumed_samples: 372838400  total_loss: 2.948  time: 0.3443 s/iter  data_time: 0.2076 s/iter total_throughput: 2974.11 samples/s lr: 1.22e-05  
[09/23 14:27:45] lb.utils.events INFO:  eta: 0:29:00  iteration: 364199/375342  consumed_samples: 372940800  total_loss: 2.936  time: 0.3443 s/iter  data_time: 0.2165 s/iter total_throughput: 2974.11 samples/s lr: 1.22e-05  
[09/23 14:28:20] lb.utils.events INFO:  eta: 0:28:43  iteration: 364299/375342  consumed_samples: 373043200  total_loss: 2.933  time: 0.3443 s/iter  data_time: 0.2154 s/iter total_throughput: 2974.11 samples/s lr: 1.21e-05  
[09/23 14:28:54] lb.utils.events INFO:  eta: 0:28:22  iteration: 364399/375342  consumed_samples: 373145600  total_loss: 2.939  time: 0.3443 s/iter  data_time: 0.2164 s/iter total_throughput: 2974.10 samples/s lr: 1.21e-05  
[09/23 14:29:28] lb.utils.events INFO:  eta: 0:28:04  iteration: 364499/375342  consumed_samples: 373248000  total_loss: 2.932  time: 0.3443 s/iter  data_time: 0.2203 s/iter total_throughput: 2974.10 samples/s lr: 1.20e-05  
[09/23 14:30:03] lb.utils.events INFO:  eta: 0:27:48  iteration: 364599/375342  consumed_samples: 373350400  total_loss: 2.912  time: 0.3443 s/iter  data_time: 0.2248 s/iter total_throughput: 2974.09 samples/s lr: 1.20e-05  
[09/23 14:30:38] lb.utils.events INFO:  eta: 0:27:32  iteration: 364699/375342  consumed_samples: 373452800  total_loss: 2.91  time: 0.3443 s/iter  data_time: 0.2280 s/iter total_throughput: 2974.08 samples/s lr: 1.20e-05  
[09/23 14:31:14] lb.utils.events INFO:  eta: 0:27:15  iteration: 364799/375342  consumed_samples: 373555200  total_loss: 2.928  time: 0.3443 s/iter  data_time: 0.2217 s/iter total_throughput: 2974.06 samples/s lr: 1.19e-05  
[09/23 14:31:49] lb.utils.events INFO:  eta: 0:27:00  iteration: 364899/375342  consumed_samples: 373657600  total_loss: 2.954  time: 0.3443 s/iter  data_time: 0.2230 s/iter total_throughput: 2974.05 samples/s lr: 1.19e-05  
[09/23 14:32:23] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0364999
[09/23 14:32:24] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/23 14:32:24] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/23 14:32:28] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.0918 s/iter. Inference: 0.1608 s/iter. Eval: 0.0022 s/iter. Total: 0.2549 s/iter. ETA=0:00:09
[09/23 14:32:33] lb.evaluation.evaluator INFO: Inference done 28672/50000. Dataloading: 0.1089 s/iter. Inference: 0.1750 s/iter. Eval: 0.0022 s/iter. Total: 0.2862 s/iter. ETA=0:00:05
[09/23 14:32:38] lb.evaluation.evaluator INFO: Inference done 46080/50000. Dataloading: 0.1212 s/iter. Inference: 0.1695 s/iter. Eval: 0.0022 s/iter. Total: 0.2929 s/iter. ETA=0:00:00
[09/23 14:32:39] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/23 14:32:39] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.655772 (0.000253 s / iter per device, on 8 devices)
[09/23 14:32:39] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000149 s / iter per device, on 8 devices)
[09/23 14:32:39] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/23 14:32:39] lb.evaluation.utils INFO: copypaste: Acc@1=80.048
[09/23 14:32:39] lb.evaluation.utils INFO: copypaste: Acc@5=94.50800000000001
[09/23 14:32:39] lb.engine.hooks INFO: Not saving as latest eval score for Acc@1 is 80.04800, not better than best score 80.04800 @ iteration 359999.
[09/23 14:32:39] lb.utils.events INFO:  eta: 0:26:46  iteration: 364999/375342  consumed_samples: 373760000  total_loss: 2.957  time: 0.3443 s/iter  data_time: 0.2297 s/iter total_throughput: 2974.05 samples/s lr: 1.19e-05  
[09/23 14:33:12] lb.utils.events INFO:  eta: 0:26:34  iteration: 365099/375342  consumed_samples: 373862400  total_loss: 2.945  time: 0.3443 s/iter  data_time: 0.2329 s/iter total_throughput: 2974.09 samples/s lr: 1.18e-05  
[09/23 14:33:46] lb.utils.events INFO:  eta: 0:26:20  iteration: 365199/375342  consumed_samples: 373964800  total_loss: 2.941  time: 0.3443 s/iter  data_time: 0.2156 s/iter total_throughput: 2974.09 samples/s lr: 1.18e-05  
[09/23 14:34:21] lb.utils.events INFO:  eta: 0:26:06  iteration: 365299/375342  consumed_samples: 374067200  total_loss: 2.936  time: 0.3443 s/iter  data_time: 0.2141 s/iter total_throughput: 2974.08 samples/s lr: 1.17e-05  
[09/23 14:34:56] lb.utils.events INFO:  eta: 0:25:50  iteration: 365399/375342  consumed_samples: 374169600  total_loss: 2.915  time: 0.3443 s/iter  data_time: 0.2120 s/iter total_throughput: 2974.07 samples/s lr: 1.17e-05  
[09/23 14:35:30] lb.utils.events INFO:  eta: 0:25:38  iteration: 365499/375342  consumed_samples: 374272000  total_loss: 2.919  time: 0.3443 s/iter  data_time: 0.2146 s/iter total_throughput: 2974.07 samples/s lr: 1.17e-05  
[09/23 14:36:05] lb.utils.events INFO:  eta: 0:25:25  iteration: 365599/375342  consumed_samples: 374374400  total_loss: 2.936  time: 0.3443 s/iter  data_time: 0.2213 s/iter total_throughput: 2974.07 samples/s lr: 1.16e-05  
[09/23 14:36:40] lb.utils.events INFO:  eta: 0:25:14  iteration: 365699/375342  consumed_samples: 374476800  total_loss: 2.936  time: 0.3443 s/iter  data_time: 0.2234 s/iter total_throughput: 2974.06 samples/s lr: 1.16e-05  
[09/23 14:37:15] lb.utils.events INFO:  eta: 0:25:01  iteration: 365799/375342  consumed_samples: 374579200  total_loss: 2.955  time: 0.3443 s/iter  data_time: 0.2222 s/iter total_throughput: 2974.04 samples/s lr: 1.16e-05  
[09/23 14:37:49] lb.utils.events INFO:  eta: 0:24:46  iteration: 365899/375342  consumed_samples: 374681600  total_loss: 2.93  time: 0.3443 s/iter  data_time: 0.2267 s/iter total_throughput: 2974.04 samples/s lr: 1.15e-05  
[09/23 14:38:24] lb.utils.events INFO:  eta: 0:24:25  iteration: 365999/375342  consumed_samples: 374784000  total_loss: 2.933  time: 0.3443 s/iter  data_time: 0.2257 s/iter total_throughput: 2974.03 samples/s lr: 1.15e-05  
[09/23 14:38:59] lb.utils.events INFO:  eta: 0:24:06  iteration: 366099/375342  consumed_samples: 374886400  total_loss: 2.945  time: 0.3443 s/iter  data_time: 0.2203 s/iter total_throughput: 2974.02 samples/s lr: 1.15e-05  
[09/23 14:39:34] lb.utils.events INFO:  eta: 0:23:43  iteration: 366199/375342  consumed_samples: 374988800  total_loss: 2.941  time: 0.3443 s/iter  data_time: 0.2160 s/iter total_throughput: 2974.01 samples/s lr: 1.14e-05  
[09/23 14:40:08] lb.utils.events INFO:  eta: 0:23:29  iteration: 366299/375342  consumed_samples: 375091200  total_loss: 2.943  time: 0.3443 s/iter  data_time: 0.2128 s/iter total_throughput: 2974.01 samples/s lr: 1.14e-05  
[09/23 14:40:43] lb.utils.events INFO:  eta: 0:23:15  iteration: 366399/375342  consumed_samples: 375193600  total_loss: 2.934  time: 0.3443 s/iter  data_time: 0.2216 s/iter total_throughput: 2974.01 samples/s lr: 1.14e-05  
[09/23 14:41:18] lb.utils.events INFO:  eta: 0:22:58  iteration: 366499/375342  consumed_samples: 375296000  total_loss: 2.934  time: 0.3443 s/iter  data_time: 0.2266 s/iter total_throughput: 2973.99 samples/s lr: 1.14e-05  
[09/23 14:41:52] lb.utils.events INFO:  eta: 0:22:45  iteration: 366599/375342  consumed_samples: 375398400  total_loss: 2.933  time: 0.3443 s/iter  data_time: 0.2237 s/iter total_throughput: 2974.00 samples/s lr: 1.13e-05  
[09/23 14:42:26] lb.utils.events INFO:  eta: 0:22:29  iteration: 366699/375342  consumed_samples: 375500800  total_loss: 2.939  time: 0.3443 s/iter  data_time: 0.2147 s/iter total_throughput: 2974.00 samples/s lr: 1.13e-05  
[09/23 14:43:01] lb.utils.events INFO:  eta: 0:22:13  iteration: 366799/375342  consumed_samples: 375603200  total_loss: 2.943  time: 0.3443 s/iter  data_time: 0.2065 s/iter total_throughput: 2974.01 samples/s lr: 1.13e-05  
[09/23 14:43:35] lb.utils.events INFO:  eta: 0:21:58  iteration: 366899/375342  consumed_samples: 375705600  total_loss: 2.939  time: 0.3443 s/iter  data_time: 0.1991 s/iter total_throughput: 2974.02 samples/s lr: 1.12e-05  
[09/23 14:44:10] lb.utils.events INFO:  eta: 0:21:42  iteration: 366999/375342  consumed_samples: 375808000  total_loss: 2.929  time: 0.3443 s/iter  data_time: 0.2189 s/iter total_throughput: 2974.01 samples/s lr: 1.12e-05  
[09/23 14:44:44] lb.utils.events INFO:  eta: 0:21:26  iteration: 367099/375342  consumed_samples: 375910400  total_loss: 2.927  time: 0.3443 s/iter  data_time: 0.2191 s/iter total_throughput: 2974.00 samples/s lr: 1.12e-05  
[09/23 14:45:19] lb.utils.events INFO:  eta: 0:21:16  iteration: 367199/375342  consumed_samples: 376012800  total_loss: 2.944  time: 0.3443 s/iter  data_time: 0.2161 s/iter total_throughput: 2974.00 samples/s lr: 1.11e-05  
[09/23 14:45:54] lb.utils.events INFO:  eta: 0:21:01  iteration: 367299/375342  consumed_samples: 376115200  total_loss: 2.941  time: 0.3443 s/iter  data_time: 0.2212 s/iter total_throughput: 2973.98 samples/s lr: 1.11e-05  
[09/23 14:46:29] lb.utils.events INFO:  eta: 0:20:47  iteration: 367399/375342  consumed_samples: 376217600  total_loss: 2.933  time: 0.3443 s/iter  data_time: 0.2130 s/iter total_throughput: 2973.97 samples/s lr: 1.11e-05  
[09/23 14:47:03] lb.utils.events INFO:  eta: 0:20:34  iteration: 367499/375342  consumed_samples: 376320000  total_loss: 2.922  time: 0.3443 s/iter  data_time: 0.2241 s/iter total_throughput: 2973.97 samples/s lr: 1.11e-05  
[09/23 14:47:38] lb.utils.events INFO:  eta: 0:20:16  iteration: 367599/375342  consumed_samples: 376422400  total_loss: 2.899  time: 0.3443 s/iter  data_time: 0.2204 s/iter total_throughput: 2973.96 samples/s lr: 1.10e-05  
[09/23 14:48:13] lb.utils.events INFO:  eta: 0:19:59  iteration: 367699/375342  consumed_samples: 376524800  total_loss: 2.902  time: 0.3443 s/iter  data_time: 0.2331 s/iter total_throughput: 2973.96 samples/s lr: 1.10e-05  
[09/23 14:48:47] lb.utils.events INFO:  eta: 0:19:43  iteration: 367799/375342  consumed_samples: 376627200  total_loss: 2.912  time: 0.3443 s/iter  data_time: 0.2158 s/iter total_throughput: 2973.96 samples/s lr: 1.10e-05  
[09/23 14:49:22] lb.utils.events INFO:  eta: 0:19:26  iteration: 367899/375342  consumed_samples: 376729600  total_loss: 2.93  time: 0.3443 s/iter  data_time: 0.2154 s/iter total_throughput: 2973.95 samples/s lr: 1.10e-05  
[09/23 14:49:56] lb.utils.events INFO:  eta: 0:19:13  iteration: 367999/375342  consumed_samples: 376832000  total_loss: 2.932  time: 0.3443 s/iter  data_time: 0.2173 s/iter total_throughput: 2973.95 samples/s lr: 1.09e-05  
[09/23 14:50:31] lb.utils.events INFO:  eta: 0:18:56  iteration: 368099/375342  consumed_samples: 376934400  total_loss: 2.931  time: 0.3443 s/iter  data_time: 0.2236 s/iter total_throughput: 2973.95 samples/s lr: 1.09e-05  
[09/23 14:51:06] lb.utils.events INFO:  eta: 0:18:36  iteration: 368199/375342  consumed_samples: 377036800  total_loss: 2.943  time: 0.3443 s/iter  data_time: 0.2201 s/iter total_throughput: 2973.94 samples/s lr: 1.09e-05  
[09/23 14:51:40] lb.utils.events INFO:  eta: 0:18:23  iteration: 368299/375342  consumed_samples: 377139200  total_loss: 2.941  time: 0.3443 s/iter  data_time: 0.2238 s/iter total_throughput: 2973.94 samples/s lr: 1.09e-05  
[09/23 14:52:15] lb.utils.events INFO:  eta: 0:18:05  iteration: 368399/375342  consumed_samples: 377241600  total_loss: 2.932  time: 0.3443 s/iter  data_time: 0.2267 s/iter total_throughput: 2973.94 samples/s lr: 1.08e-05  
[09/23 14:52:50] lb.utils.events INFO:  eta: 0:17:48  iteration: 368499/375342  consumed_samples: 377344000  total_loss: 2.92  time: 0.3443 s/iter  data_time: 0.2158 s/iter total_throughput: 2973.93 samples/s lr: 1.08e-05  
[09/23 14:53:25] lb.utils.events INFO:  eta: 0:17:31  iteration: 368599/375342  consumed_samples: 377446400  total_loss: 2.914  time: 0.3443 s/iter  data_time: 0.2332 s/iter total_throughput: 2973.92 samples/s lr: 1.08e-05  
[09/23 14:53:59] lb.utils.events INFO:  eta: 0:17:14  iteration: 368699/375342  consumed_samples: 377548800  total_loss: 2.912  time: 0.3443 s/iter  data_time: 0.2161 s/iter total_throughput: 2973.91 samples/s lr: 1.08e-05  
[09/23 14:54:34] lb.utils.events INFO:  eta: 0:17:00  iteration: 368799/375342  consumed_samples: 377651200  total_loss: 2.923  time: 0.3443 s/iter  data_time: 0.2204 s/iter total_throughput: 2973.91 samples/s lr: 1.07e-05  
[09/23 14:55:09] lb.utils.events INFO:  eta: 0:16:43  iteration: 368899/375342  consumed_samples: 377753600  total_loss: 2.933  time: 0.3443 s/iter  data_time: 0.2158 s/iter total_throughput: 2973.90 samples/s lr: 1.07e-05  
[09/23 14:55:43] lb.utils.events INFO:  eta: 0:16:28  iteration: 368999/375342  consumed_samples: 377856000  total_loss: 2.934  time: 0.3443 s/iter  data_time: 0.2178 s/iter total_throughput: 2973.90 samples/s lr: 1.07e-05  
[09/23 14:56:18] lb.utils.events INFO:  eta: 0:16:11  iteration: 369099/375342  consumed_samples: 377958400  total_loss: 2.905  time: 0.3443 s/iter  data_time: 0.2169 s/iter total_throughput: 2973.89 samples/s lr: 1.07e-05  
[09/23 14:56:52] lb.utils.events INFO:  eta: 0:15:56  iteration: 369199/375342  consumed_samples: 378060800  total_loss: 2.91  time: 0.3443 s/iter  data_time: 0.2194 s/iter total_throughput: 2973.89 samples/s lr: 1.07e-05  
[09/23 14:57:27] lb.utils.events INFO:  eta: 0:15:39  iteration: 369299/375342  consumed_samples: 378163200  total_loss: 2.932  time: 0.3443 s/iter  data_time: 0.2141 s/iter total_throughput: 2973.89 samples/s lr: 1.06e-05  
[09/23 14:58:01] lb.utils.events INFO:  eta: 0:15:23  iteration: 369399/375342  consumed_samples: 378265600  total_loss: 2.932  time: 0.3443 s/iter  data_time: 0.2231 s/iter total_throughput: 2973.89 samples/s lr: 1.06e-05  
[09/23 14:58:36] lb.utils.events INFO:  eta: 0:15:07  iteration: 369499/375342  consumed_samples: 378368000  total_loss: 2.922  time: 0.3443 s/iter  data_time: 0.2264 s/iter total_throughput: 2973.88 samples/s lr: 1.06e-05  
[09/23 14:59:11] lb.utils.events INFO:  eta: 0:14:52  iteration: 369599/375342  consumed_samples: 378470400  total_loss: 2.927  time: 0.3443 s/iter  data_time: 0.2140 s/iter total_throughput: 2973.88 samples/s lr: 1.06e-05  
[09/23 14:59:45] lb.utils.events INFO:  eta: 0:14:38  iteration: 369699/375342  consumed_samples: 378572800  total_loss: 2.937  time: 0.3443 s/iter  data_time: 0.2317 s/iter total_throughput: 2973.88 samples/s lr: 1.06e-05  
[09/23 15:00:19] lb.utils.events INFO:  eta: 0:14:22  iteration: 369799/375342  consumed_samples: 378675200  total_loss: 2.933  time: 0.3443 s/iter  data_time: 0.2114 s/iter total_throughput: 2973.88 samples/s lr: 1.05e-05  
[09/23 15:00:54] lb.utils.events INFO:  eta: 0:14:07  iteration: 369899/375342  consumed_samples: 378777600  total_loss: 2.922  time: 0.3443 s/iter  data_time: 0.2131 s/iter total_throughput: 2973.87 samples/s lr: 1.05e-05  
[09/23 15:01:29] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0369999
[09/23 15:01:30] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/23 15:01:30] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/23 15:01:34] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.1031 s/iter. Inference: 0.1624 s/iter. Eval: 0.0021 s/iter. Total: 0.2677 s/iter. ETA=0:00:09
[09/23 15:01:39] lb.evaluation.evaluator INFO: Inference done 29696/50000. Dataloading: 0.1263 s/iter. Inference: 0.1691 s/iter. Eval: 0.0020 s/iter. Total: 0.2975 s/iter. ETA=0:00:05
[09/23 15:01:44] lb.evaluation.evaluator INFO: Inference done 48128/50000. Dataloading: 0.1223 s/iter. Inference: 0.1651 s/iter. Eval: 0.0020 s/iter. Total: 0.2895 s/iter. ETA=0:00:00
[09/23 15:01:45] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/23 15:01:45] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.562763 (0.000251 s / iter per device, on 8 devices)
[09/23 15:01:45] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000146 s / iter per device, on 8 devices)
[09/23 15:01:45] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/23 15:01:45] lb.evaluation.utils INFO: copypaste: Acc@1=80.098
[09/23 15:01:45] lb.evaluation.utils INFO: copypaste: Acc@5=94.46
[09/23 15:01:45] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 80.09800, better than last best score 80.04800 @ iteration 359999.
[09/23 15:01:45] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/23 15:01:45] lb.utils.events INFO:  eta: 0:13:50  iteration: 369999/375342  consumed_samples: 378880000  total_loss: 2.918  time: 0.3443 s/iter  data_time: 0.2354 s/iter total_throughput: 2973.87 samples/s lr: 1.05e-05  
[09/23 15:02:18] lb.utils.events INFO:  eta: 0:13:39  iteration: 370099/375342  consumed_samples: 378982400  total_loss: 2.932  time: 0.3443 s/iter  data_time: 0.2078 s/iter total_throughput: 2973.92 samples/s lr: 1.05e-05  
[09/23 15:02:53] lb.utils.events INFO:  eta: 0:13:24  iteration: 370199/375342  consumed_samples: 379084800  total_loss: 2.929  time: 0.3443 s/iter  data_time: 0.2209 s/iter total_throughput: 2973.91 samples/s lr: 1.05e-05  
[09/23 15:03:27] lb.utils.events INFO:  eta: 0:13:09  iteration: 370299/375342  consumed_samples: 379187200  total_loss: 2.918  time: 0.3443 s/iter  data_time: 0.2207 s/iter total_throughput: 2973.91 samples/s lr: 1.04e-05  
[09/23 15:04:02] lb.utils.events INFO:  eta: 0:12:54  iteration: 370399/375342  consumed_samples: 379289600  total_loss: 2.926  time: 0.3443 s/iter  data_time: 0.2306 s/iter total_throughput: 2973.90 samples/s lr: 1.04e-05  
[09/23 15:04:37] lb.utils.events INFO:  eta: 0:12:39  iteration: 370499/375342  consumed_samples: 379392000  total_loss: 2.93  time: 0.3443 s/iter  data_time: 0.2169 s/iter total_throughput: 2973.89 samples/s lr: 1.04e-05  
[09/23 15:05:12] lb.utils.events INFO:  eta: 0:12:23  iteration: 370599/375342  consumed_samples: 379494400  total_loss: 2.922  time: 0.3443 s/iter  data_time: 0.2235 s/iter total_throughput: 2973.88 samples/s lr: 1.04e-05  
[09/23 15:05:46] lb.utils.events INFO:  eta: 0:12:05  iteration: 370699/375342  consumed_samples: 379596800  total_loss: 2.927  time: 0.3443 s/iter  data_time: 0.2380 s/iter total_throughput: 2973.87 samples/s lr: 1.04e-05  
[09/23 15:06:21] lb.utils.events INFO:  eta: 0:11:49  iteration: 370799/375342  consumed_samples: 379699200  total_loss: 2.94  time: 0.3443 s/iter  data_time: 0.2199 s/iter total_throughput: 2973.86 samples/s lr: 1.04e-05  
[09/23 15:06:56] lb.utils.events INFO:  eta: 0:11:34  iteration: 370899/375342  consumed_samples: 379801600  total_loss: 2.924  time: 0.3443 s/iter  data_time: 0.2184 s/iter total_throughput: 2973.86 samples/s lr: 1.03e-05  
[09/23 15:07:31] lb.utils.events INFO:  eta: 0:11:18  iteration: 370999/375342  consumed_samples: 379904000  total_loss: 2.921  time: 0.3443 s/iter  data_time: 0.2350 s/iter total_throughput: 2973.85 samples/s lr: 1.03e-05  
[09/23 15:08:06] lb.utils.events INFO:  eta: 0:10:59  iteration: 371099/375342  consumed_samples: 380006400  total_loss: 2.927  time: 0.3443 s/iter  data_time: 0.2270 s/iter total_throughput: 2973.84 samples/s lr: 1.03e-05  
[09/23 15:08:40] lb.utils.events INFO:  eta: 0:10:43  iteration: 371199/375342  consumed_samples: 380108800  total_loss: 2.939  time: 0.3443 s/iter  data_time: 0.2253 s/iter total_throughput: 2973.84 samples/s lr: 1.03e-05  
[09/23 15:09:15] lb.utils.events INFO:  eta: 0:10:27  iteration: 371299/375342  consumed_samples: 380211200  total_loss: 2.938  time: 0.3443 s/iter  data_time: 0.2228 s/iter total_throughput: 2973.83 samples/s lr: 1.03e-05  
[09/23 15:09:49] lb.utils.events INFO:  eta: 0:10:11  iteration: 371399/375342  consumed_samples: 380313600  total_loss: 2.938  time: 0.3443 s/iter  data_time: 0.2111 s/iter total_throughput: 2973.83 samples/s lr: 1.03e-05  
[09/23 15:10:24] lb.utils.events INFO:  eta: 0:09:56  iteration: 371499/375342  consumed_samples: 380416000  total_loss: 2.938  time: 0.3443 s/iter  data_time: 0.2145 s/iter total_throughput: 2973.82 samples/s lr: 1.03e-05  
[09/23 15:10:59] lb.utils.events INFO:  eta: 0:09:42  iteration: 371599/375342  consumed_samples: 380518400  total_loss: 2.928  time: 0.3443 s/iter  data_time: 0.2174 s/iter total_throughput: 2973.82 samples/s lr: 1.02e-05  
[09/23 15:11:34] lb.utils.events INFO:  eta: 0:09:26  iteration: 371699/375342  consumed_samples: 380620800  total_loss: 2.932  time: 0.3443 s/iter  data_time: 0.2313 s/iter total_throughput: 2973.80 samples/s lr: 1.02e-05  
[09/23 15:12:08] lb.utils.events INFO:  eta: 0:09:11  iteration: 371799/375342  consumed_samples: 380723200  total_loss: 2.949  time: 0.3443 s/iter  data_time: 0.2100 s/iter total_throughput: 2973.80 samples/s lr: 1.02e-05  
[09/23 15:12:43] lb.utils.events INFO:  eta: 0:08:56  iteration: 371899/375342  consumed_samples: 380825600  total_loss: 2.937  time: 0.3443 s/iter  data_time: 0.2129 s/iter total_throughput: 2973.80 samples/s lr: 1.02e-05  
[09/23 15:13:18] lb.utils.events INFO:  eta: 0:08:40  iteration: 371999/375342  consumed_samples: 380928000  total_loss: 2.921  time: 0.3443 s/iter  data_time: 0.2275 s/iter total_throughput: 2973.79 samples/s lr: 1.02e-05  
[09/23 15:13:52] lb.utils.events INFO:  eta: 0:08:24  iteration: 372099/375342  consumed_samples: 381030400  total_loss: 2.931  time: 0.3443 s/iter  data_time: 0.2222 s/iter total_throughput: 2973.78 samples/s lr: 1.02e-05  
[09/23 15:14:27] lb.utils.events INFO:  eta: 0:08:09  iteration: 372199/375342  consumed_samples: 381132800  total_loss: 2.942  time: 0.3443 s/iter  data_time: 0.2307 s/iter total_throughput: 2973.77 samples/s lr: 1.02e-05  
[09/23 15:15:02] lb.utils.events INFO:  eta: 0:07:54  iteration: 372299/375342  consumed_samples: 381235200  total_loss: 2.938  time: 0.3443 s/iter  data_time: 0.2116 s/iter total_throughput: 2973.77 samples/s lr: 1.02e-05  
[09/23 15:15:36] lb.utils.events INFO:  eta: 0:07:42  iteration: 372399/375342  consumed_samples: 381337600  total_loss: 2.904  time: 0.3443 s/iter  data_time: 0.2155 s/iter total_throughput: 2973.78 samples/s lr: 1.02e-05  
[09/23 15:16:10] lb.utils.events INFO:  eta: 0:07:24  iteration: 372499/375342  consumed_samples: 381440000  total_loss: 2.928  time: 0.3443 s/iter  data_time: 0.2184 s/iter total_throughput: 2973.79 samples/s lr: 1.01e-05  
[09/23 15:16:45] lb.utils.events INFO:  eta: 0:07:08  iteration: 372599/375342  consumed_samples: 381542400  total_loss: 2.93  time: 0.3443 s/iter  data_time: 0.2281 s/iter total_throughput: 2973.78 samples/s lr: 1.01e-05  
[09/23 15:17:19] lb.utils.events INFO:  eta: 0:06:52  iteration: 372699/375342  consumed_samples: 381644800  total_loss: 2.912  time: 0.3443 s/iter  data_time: 0.2070 s/iter total_throughput: 2973.78 samples/s lr: 1.01e-05  
[09/23 15:17:54] lb.utils.events INFO:  eta: 0:06:37  iteration: 372799/375342  consumed_samples: 381747200  total_loss: 2.916  time: 0.3443 s/iter  data_time: 0.2160 s/iter total_throughput: 2973.78 samples/s lr: 1.01e-05  
[09/23 15:18:28] lb.utils.events INFO:  eta: 0:06:21  iteration: 372899/375342  consumed_samples: 381849600  total_loss: 2.932  time: 0.3443 s/iter  data_time: 0.2190 s/iter total_throughput: 2973.78 samples/s lr: 1.01e-05  
[09/23 15:19:02] lb.utils.events INFO:  eta: 0:06:05  iteration: 372999/375342  consumed_samples: 381952000  total_loss: 2.918  time: 0.3443 s/iter  data_time: 0.2391 s/iter total_throughput: 2973.78 samples/s lr: 1.01e-05  
[09/23 15:19:37] lb.utils.events INFO:  eta: 0:05:49  iteration: 373099/375342  consumed_samples: 382054400  total_loss: 2.918  time: 0.3443 s/iter  data_time: 0.2084 s/iter total_throughput: 2973.78 samples/s lr: 1.01e-05  
[09/23 15:20:11] lb.utils.events INFO:  eta: 0:05:35  iteration: 373199/375342  consumed_samples: 382156800  total_loss: 2.927  time: 0.3443 s/iter  data_time: 0.2170 s/iter total_throughput: 2973.80 samples/s lr: 1.01e-05  
[09/23 15:20:45] lb.utils.events INFO:  eta: 0:05:19  iteration: 373299/375342  consumed_samples: 382259200  total_loss: 2.919  time: 0.3443 s/iter  data_time: 0.2266 s/iter total_throughput: 2973.79 samples/s lr: 1.01e-05  
[09/23 15:21:20] lb.utils.events INFO:  eta: 0:05:02  iteration: 373399/375342  consumed_samples: 382361600  total_loss: 2.935  time: 0.3443 s/iter  data_time: 0.2248 s/iter total_throughput: 2973.79 samples/s lr: 1.01e-05  
[09/23 15:21:54] lb.utils.events INFO:  eta: 0:04:48  iteration: 373499/375342  consumed_samples: 382464000  total_loss: 2.933  time: 0.3443 s/iter  data_time: 0.2047 s/iter total_throughput: 2973.80 samples/s lr: 1.01e-05  
[09/23 15:22:28] lb.utils.events INFO:  eta: 0:04:33  iteration: 373599/375342  consumed_samples: 382566400  total_loss: 2.918  time: 0.3443 s/iter  data_time: 0.2113 s/iter total_throughput: 2973.81 samples/s lr: 1.01e-05  
[09/23 15:23:02] lb.utils.events INFO:  eta: 0:04:17  iteration: 373699/375342  consumed_samples: 382668800  total_loss: 2.913  time: 0.3443 s/iter  data_time: 0.2126 s/iter total_throughput: 2973.81 samples/s lr: 1.00e-05  
[09/23 15:23:36] lb.utils.events INFO:  eta: 0:04:02  iteration: 373799/375342  consumed_samples: 382771200  total_loss: 2.931  time: 0.3443 s/iter  data_time: 0.2161 s/iter total_throughput: 2973.83 samples/s lr: 1.00e-05  
[09/23 15:24:10] lb.utils.events INFO:  eta: 0:03:46  iteration: 373899/375342  consumed_samples: 382873600  total_loss: 2.931  time: 0.3443 s/iter  data_time: 0.2278 s/iter total_throughput: 2973.83 samples/s lr: 1.00e-05  
[09/23 15:24:45] lb.utils.events INFO:  eta: 0:03:30  iteration: 373999/375342  consumed_samples: 382976000  total_loss: 2.929  time: 0.3443 s/iter  data_time: 0.2229 s/iter total_throughput: 2973.82 samples/s lr: 1.00e-05  
[09/23 15:25:20] lb.utils.events INFO:  eta: 0:03:15  iteration: 374099/375342  consumed_samples: 383078400  total_loss: 2.941  time: 0.3443 s/iter  data_time: 0.2145 s/iter total_throughput: 2973.82 samples/s lr: 1.00e-05  
[09/23 15:25:54] lb.utils.events INFO:  eta: 0:02:59  iteration: 374199/375342  consumed_samples: 383180800  total_loss: 2.927  time: 0.3443 s/iter  data_time: 0.2173 s/iter total_throughput: 2973.82 samples/s lr: 1.00e-05  
[09/23 15:26:28] lb.utils.events INFO:  eta: 0:02:43  iteration: 374299/375342  consumed_samples: 383283200  total_loss: 2.916  time: 0.3443 s/iter  data_time: 0.2217 s/iter total_throughput: 2973.82 samples/s lr: 1.00e-05  
[09/23 15:27:03] lb.utils.events INFO:  eta: 0:02:27  iteration: 374399/375342  consumed_samples: 383385600  total_loss: 2.914  time: 0.3443 s/iter  data_time: 0.2095 s/iter total_throughput: 2973.82 samples/s lr: 1.00e-05  
[09/23 15:27:38] lb.utils.events INFO:  eta: 0:02:11  iteration: 374499/375342  consumed_samples: 383488000  total_loss: 2.921  time: 0.3443 s/iter  data_time: 0.2131 s/iter total_throughput: 2973.81 samples/s lr: 1.00e-05  
[09/23 15:28:12] lb.utils.events INFO:  eta: 0:01:56  iteration: 374599/375342  consumed_samples: 383590400  total_loss: 2.906  time: 0.3443 s/iter  data_time: 0.2232 s/iter total_throughput: 2973.82 samples/s lr: 1.00e-05  
[09/23 15:28:46] lb.utils.events INFO:  eta: 0:01:40  iteration: 374699/375342  consumed_samples: 383692800  total_loss: 2.916  time: 0.3443 s/iter  data_time: 0.2211 s/iter total_throughput: 2973.82 samples/s lr: 1.00e-05  
[09/23 15:29:21] lb.utils.events INFO:  eta: 0:01:24  iteration: 374799/375342  consumed_samples: 383795200  total_loss: 2.918  time: 0.3443 s/iter  data_time: 0.2204 s/iter total_throughput: 2973.82 samples/s lr: 1.00e-05  
[09/23 15:29:55] lb.utils.events INFO:  eta: 0:01:09  iteration: 374899/375342  consumed_samples: 383897600  total_loss: 2.915  time: 0.3443 s/iter  data_time: 0.2083 s/iter total_throughput: 2973.82 samples/s lr: 1.00e-05  
[09/23 15:30:29] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_0374999
[09/23 15:30:30] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/23 15:30:30] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/23 15:30:34] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.1160 s/iter. Inference: 0.1623 s/iter. Eval: 0.0020 s/iter. Total: 0.2804 s/iter. ETA=0:00:10
[09/23 15:30:40] lb.evaluation.evaluator INFO: Inference done 29696/50000. Dataloading: 0.1319 s/iter. Inference: 0.1645 s/iter. Eval: 0.0020 s/iter. Total: 0.2984 s/iter. ETA=0:00:05
[09/23 15:30:45] lb.evaluation.evaluator INFO: Inference done 48128/50000. Dataloading: 0.1291 s/iter. Inference: 0.1628 s/iter. Eval: 0.0020 s/iter. Total: 0.2939 s/iter. ETA=0:00:00
[09/23 15:30:45] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/23 15:30:45] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.692443 (0.000254 s / iter per device, on 8 devices)
[09/23 15:30:45] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000144 s / iter per device, on 8 devices)
[09/23 15:30:45] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/23 15:30:45] lb.evaluation.utils INFO: copypaste: Acc@1=80.10000000000001
[09/23 15:30:45] lb.evaluation.utils INFO: copypaste: Acc@5=94.47
[09/23 15:30:45] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 80.10000, better than last best score 80.09800 @ iteration 369999.
[09/23 15:30:45] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best
[09/23 15:30:46] lb.utils.events INFO:  eta: 0:00:53  iteration: 374999/375342  consumed_samples: 384000000  total_loss: 2.935  time: 0.3443 s/iter  data_time: 0.2229 s/iter total_throughput: 2973.83 samples/s lr: 1.00e-05  
[09/23 15:31:19] lb.utils.events INFO:  eta: 0:00:37  iteration: 375099/375342  consumed_samples: 384102400  total_loss: 2.914  time: 0.3443 s/iter  data_time: 0.2244 s/iter total_throughput: 2973.87 samples/s lr: 1.00e-05  
[09/23 15:31:53] lb.utils.events INFO:  eta: 0:00:22  iteration: 375199/375342  consumed_samples: 384204800  total_loss: 2.898  time: 0.3443 s/iter  data_time: 0.2140 s/iter total_throughput: 2973.87 samples/s lr: 1.00e-05  
[09/23 15:32:27] lb.utils.events INFO:  eta: 0:00:06  iteration: 375299/375342  consumed_samples: 384307200  total_loss: 2.924  time: 0.3443 s/iter  data_time: 0.2054 s/iter total_throughput: 2973.88 samples/s lr: 1.00e-05  
[09/23 15:32:41] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_final
[09/23 15:32:42] lb.utils.events INFO:  eta: 0:00:00  iteration: 375341/375342  consumed_samples: 384350208  total_loss: 2.932  time: 0.3443 s/iter  data_time: 0.2227 s/iter total_throughput: 2973.89 samples/s lr: 1.00e-05  
[09/23 15:32:42] lb.engine.hooks INFO: Overall training speed: 375340 iterations in 1 day, 11:54:05 (0.3443 s / it)
[09/23 15:32:42] lb.engine.hooks INFO: Total training time: 1 day, 12:15:14 (0:21:09 on hooks)
[09/23 15:32:42] lb.evaluation.evaluator INFO: with eval_iter 100000.0, reset total samples 50000 to 50000
[09/23 15:32:42] lb.evaluation.evaluator INFO: Start inference on 50000 samples
[09/23 15:32:46] lb.evaluation.evaluator INFO: Inference done 11264/50000. Dataloading: 0.1042 s/iter. Inference: 0.1617 s/iter. Eval: 0.0020 s/iter. Total: 0.2679 s/iter. ETA=0:00:09
[09/23 15:32:52] lb.evaluation.evaluator INFO: Inference done 28672/50000. Dataloading: 0.1235 s/iter. Inference: 0.1638 s/iter. Eval: 0.0021 s/iter. Total: 0.2895 s/iter. ETA=0:00:05
[09/23 15:32:57] lb.evaluation.evaluator INFO: Inference done 47104/50000. Dataloading: 0.1279 s/iter. Inference: 0.1623 s/iter. Eval: 0.0021 s/iter. Total: 0.2924 s/iter. ETA=0:00:00
[09/23 15:32:57] lb.evaluation.evaluator INFO: Total valid samples: 50000
[09/23 15:32:57] lb.evaluation.evaluator INFO: Total inference time: 0:00:12.498202 (0.000250 s / iter per device, on 8 devices)
[09/23 15:32:57] lb.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.000143 s / iter per device, on 8 devices)
[09/23 15:32:57] lb.engine.default INFO: Evaluation results for ImageNetDataset in csv format:
[09/23 15:32:57] lb.evaluation.utils INFO: copypaste: Acc@1=80.166
[09/23 15:32:57] lb.evaluation.utils INFO: copypaste: Acc@5=94.536
[09/23 15:32:57] lb.engine.hooks INFO: Saved best model as latest eval score for Acc@1 is 80.16600, better than last best score 80.10000 @ iteration 374999.
[09/23 15:32:57] lb.utils.checkpoint INFO: Saving checkpoint to ./commit_swin/model_best