convnext_base_ascend.yaml

# system
mode: 0
distribute: True
num_parallel_workers: 8
val_while_train: True

# dataset
dataset: 'imagenet'
data_dir: '/path/to/imagenet'
shuffle: True
dataset_download: False
batch_size: 16
drop_remainder: True

# augmentation
image_resize: 224
scale: [0.08, 1.0]
ratio: [0.75, 1.333]
re_value: 'random'
hflip: 0.5
interpolation: 'bicubic'
auto_augment: 'randaug-m9-mstd0.5-inc1'
re_prob: 0.25
crop_pct: 0.95
mixup: 0.8
cutmix: 1.0

# model
model: 'convnext_base'
num_classes: 1000
pretrained: False
ckpt_path: ''
keep_checkpoint_max: 10
ckpt_save_dir: './ckpt'
epoch_size: 450
drop_path_rate: 0.5
dataset_sink_mode: True
amp_level: 'O2'

# loss
loss: 'ce'
label_smoothing: 0.1

# lr scheduler
scheduler: 'cosine_decay'
lr: 0.002
min_lr: 0.0000003
decay_epochs: 430
warmup_factor: 0.0000175
warmup_epochs: 20

# optimizer
opt: 'adamw'
momentum: 0.9
weight_decay: 0.05
loss_scale_type: 'auto'
use_nesterov: False