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INFO:root:07:59:53 Namespace(accumulate=None, batch_size=32, bert_dataset='book_corpus_wiki_en_uncased', bert_model='bert_12_768_12', dev_batch_size=8, dtype='float32', early_stop=None, epochs=5, epsilon=1e-06, gpu=0, log_interval=10, lr=2e-05, max_len=128, model_parameters=None, only_inference=False, optimizer='bertadam', output_dir='./output_dir', pad=False, pretrained_bert_parameters=None, seed=0, task_name='QQP', training_steps=None, warmup_ratio=0.1)
INFO:root:07:59:58 processing dataset...
WARNING:py.warnings:08:00:02 /home/ubuntu/.local/lib/python3.6/site-packages/gluonnlp/data/dataset.py:169: UserWarning: 21 incomplete samples in /home/ubuntu/.mxnet/datasets/glue_qqp/train.tsv
warnings.warn('%d incomplete samples in %s'%(num_missing, filename))
WARNING:py.warnings:08:00:50 /home/ubuntu/.local/lib/python3.6/site-packages/gluonnlp/data/dataset.py:169: UserWarning: 1 incomplete samples in /home/ubuntu/.mxnet/datasets/glue_qqp/dev.tsv
warnings.warn('%d incomplete samples in %s'%(num_missing, filename))
INFO:root:08:01:46 Now we are doing BERT classification training on gpu(0)!
INFO:root:08:01:46 training steps=56851
INFO:root:08:01:48 [Epoch 1 Batch 10/11375] loss=0.7393, lr=0.0000000, metrics:accuracy:0.5844,f1:0.0000
INFO:root:08:01:49 [Epoch 1 Batch 20/11375] loss=0.7918, lr=0.0000001, metrics:accuracy:0.5703,f1:0.0000
INFO:root:08:01:50 [Epoch 1 Batch 30/11375] loss=0.7012, lr=0.0000001, metrics:accuracy:0.5927,f1:0.0000
INFO:root:08:01:52 [Epoch 1 Batch 40/11375] loss=0.6737, lr=0.0000001, metrics:accuracy:0.6086,f1:0.0000
INFO:root:08:01:53 [Epoch 1 Batch 50/11375] loss=0.7787, lr=0.0000002, metrics:accuracy:0.5931,f1:0.0000
INFO:root:08:01:54 [Epoch 1 Batch 60/11375] loss=0.7384, lr=0.0000002, metrics:accuracy:0.5938,f1:0.0000
INFO:root:08:01:55 [Epoch 1 Batch 70/11375] loss=0.6794, lr=0.0000002, metrics:accuracy:0.5996,f1:0.0000
INFO:root:08:01:56 [Epoch 1 Batch 80/11375] loss=0.6859, lr=0.0000003, metrics:accuracy:0.6039,f1:0.0000
INFO:root:08:01:57 [Epoch 1 Batch 90/11375] loss=0.7225, lr=0.0000003, metrics:accuracy:0.6052,f1:0.0000
INFO:root:08:01:58 [Epoch 1 Batch 100/11375] loss=0.6854, lr=0.0000003, metrics:accuracy:0.6081,f1:0.0000
INFO:root:08:01:59 [Epoch 1 Batch 110/11375] loss=0.7419, lr=0.0000004, metrics:accuracy:0.6048,f1:0.0000
INFO:root:08:02:01 [Epoch 1 Batch 120/11375] loss=0.7615, lr=0.0000004, metrics:accuracy:0.6005,f1:0.0000
INFO:root:08:02:02 [Epoch 1 Batch 130/11375] loss=0.7036, lr=0.0000005, metrics:accuracy:0.6022,f1:0.0000
INFO:root:08:02:03 [Epoch 1 Batch 140/11375] loss=0.6355, lr=0.0000005, metrics:accuracy:0.6071,f1:0.0000
INFO:root:08:02:04 [Epoch 1 Batch 150/11375] loss=0.6627, lr=0.0000005, metrics:accuracy:0.6104,f1:0.0000
INFO:root:08:02:06 [Epoch 1 Batch 160/11375] loss=0.6478, lr=0.0000006, metrics:accuracy:0.6137,f1:0.0000
INFO:root:08:02:07 [Epoch 1 Batch 170/11375] loss=0.6717, lr=0.0000006, metrics:accuracy:0.6140,f1:0.0000
INFO:root:08:02:08 [Epoch 1 Batch 180/11375] loss=0.6282, lr=0.0000006, metrics:accuracy:0.6179,f1:0.0000
INFO:root:08:02:09 [Epoch 1 Batch 190/11375] loss=0.6706, lr=0.0000007, metrics:accuracy:0.6173,f1:0.0009
INFO:root:08:02:10 [Epoch 1 Batch 200/11375] loss=0.6989, lr=0.0000007, metrics:accuracy:0.6142,f1:0.0048
INFO:root:08:02:12 [Epoch 1 Batch 210/11375] loss=0.6114, lr=0.0000007, metrics:accuracy:0.6174,f1:0.0108
INFO:root:08:02:13 [Epoch 1 Batch 220/11375] loss=0.6464, lr=0.0000008, metrics:accuracy:0.6179,f1:0.0218
INFO:root:08:02:14 [Epoch 1 Batch 230/11375] loss=0.6304, lr=0.0000008, metrics:accuracy:0.6198,f1:0.0483
INFO:root:08:02:15 [Epoch 1 Batch 240/11375] loss=0.6179, lr=0.0000008, metrics:accuracy:0.6215,f1:0.0786
INFO:root:08:02:16 [Epoch 1 Batch 250/11375] loss=0.5959, lr=0.0000009, metrics:accuracy:0.6239,f1:0.0972
INFO:root:08:02:17 [Epoch 1 Batch 260/11375] loss=0.6058, lr=0.0000009, metrics:accuracy:0.6268,f1:0.1075
INFO:root:08:02:19 [Epoch 1 Batch 270/11375] loss=0.6050, lr=0.0000009, metrics:accuracy:0.6284,f1:0.1357
INFO:root:08:02:20 [Epoch 1 Batch 280/11375] loss=0.6219, lr=0.0000010, metrics:accuracy:0.6291,f1:0.1653
INFO:root:08:02:21 [Epoch 1 Batch 290/11375] loss=0.5768, lr=0.0000010, metrics:accuracy:0.6320,f1:0.1828
INFO:root:08:02:22 [Epoch 1 Batch 300/11375] loss=0.5755, lr=0.0000011, metrics:accuracy:0.6349,f1:0.1978
INFO:root:08:02:23 [Epoch 1 Batch 310/11375] loss=0.5597, lr=0.0000011, metrics:accuracy:0.6380,f1:0.2205
INFO:root:08:02:24 [Epoch 1 Batch 320/11375] loss=0.5612, lr=0.0000011, metrics:accuracy:0.6410,f1:0.2396
INFO:root:08:02:26 [Epoch 1 Batch 330/11375] loss=0.5484, lr=0.0000012, metrics:accuracy:0.6438,f1:0.2539
INFO:root:08:02:27 [Epoch 1 Batch 340/11375] loss=0.5688, lr=0.0000012, metrics:accuracy:0.6460,f1:0.2705
INFO:root:08:02:28 [Epoch 1 Batch 350/11375] loss=0.5322, lr=0.0000012, metrics:accuracy:0.6491,f1:0.2844
INFO:root:08:02:29 [Epoch 1 Batch 360/11375] loss=0.5654, lr=0.0000013, metrics:accuracy:0.6507,f1:0.2972
INFO:root:08:02:30 [Epoch 1 Batch 370/11375] loss=0.5750, lr=0.0000013, metrics:accuracy:0.6517,f1:0.3131
INFO:root:08:02:31 [Epoch 1 Batch 380/11375] loss=0.5521, lr=0.0000013, metrics:accuracy:0.6530,f1:0.3289
INFO:root:08:02:33 [Epoch 1 Batch 390/11375] loss=0.5523, lr=0.0000014, metrics:accuracy:0.6546,f1:0.3396
INFO:root:08:02:34 [Epoch 1 Batch 400/11375] loss=0.5196, lr=0.0000014, metrics:accuracy:0.6570,f1:0.3461
INFO:root:08:02:35 [Epoch 1 Batch 410/11375] loss=0.5010, lr=0.0000014, metrics:accuracy:0.6600,f1:0.3579
INFO:root:08:02:36 [Epoch 1 Batch 420/11375] loss=0.5374, lr=0.0000015, metrics:accuracy:0.6616,f1:0.3652
INFO:root:08:02:38 [Epoch 1 Batch 430/11375] loss=0.5114, lr=0.0000015, metrics:accuracy:0.6634,f1:0.3710
INFO:root:08:02:39 [Epoch 1 Batch 440/11375] loss=0.5175, lr=0.0000015, metrics:accuracy:0.6656,f1:0.3783
INFO:root:08:02:40 [Epoch 1 Batch 450/11375] loss=0.5304, lr=0.0000016, metrics:accuracy:0.6669,f1:0.3860
INFO:root:08:02:41 [Epoch 1 Batch 460/11375] loss=0.5219, lr=0.0000016, metrics:accuracy:0.6682,f1:0.3955
INFO:root:08:02:42 [Epoch 1 Batch 470/11375] loss=0.5200, lr=0.0000016, metrics:accuracy:0.6698,f1:0.4047
INFO:root:08:02:43 [Epoch 1 Batch 480/11375] loss=0.5268, lr=0.0000017, metrics:accuracy:0.6712,f1:0.4128
INFO:root:08:02:44 [Epoch 1 Batch 490/11375] loss=0.4889, lr=0.0000017, metrics:accuracy:0.6736,f1:0.4220
INFO:root:08:02:46 [Epoch 1 Batch 500/11375] loss=0.5016, lr=0.0000018, metrics:accuracy:0.6755,f1:0.4311
INFO:root:08:02:47 [Epoch 1 Batch 510/11375] loss=0.5109, lr=0.0000018, metrics:accuracy:0.6769,f1:0.4360
INFO:root:08:02:48 [Epoch 1 Batch 520/11375] loss=0.5098, lr=0.0000018, metrics:accuracy:0.6781,f1:0.4428
INFO:root:08:02:49 [Epoch 1 Batch 530/11375] loss=0.4744, lr=0.0000019, metrics:accuracy:0.6800,f1:0.4477
INFO:root:08:02:50 [Epoch 1 Batch 540/11375] loss=0.4938, lr=0.0000019, metrics:accuracy:0.6818,f1:0.4525
INFO:root:08:02:52 [Epoch 1 Batch 550/11375] loss=0.4939, lr=0.0000019, metrics:accuracy:0.6832,f1:0.4565
INFO:root:08:02:53 [Epoch 1 Batch 560/11375] loss=0.5102, lr=0.0000020, metrics:accuracy:0.6842,f1:0.4622
INFO:root:08:02:54 [Epoch 1 Batch 570/11375] loss=0.5337, lr=0.0000020, metrics:accuracy:0.6849,f1:0.4665
INFO:root:08:02:55 [Epoch 1 Batch 580/11375] loss=0.5096, lr=0.0000020, metrics:accuracy:0.6857,f1:0.4708
INFO:root:08:02:56 [Epoch 1 Batch 590/11375] loss=0.4893, lr=0.0000021, metrics:accuracy:0.6873,f1:0.4744
INFO:root:08:02:57 [Epoch 1 Batch 600/11375] loss=0.5070, lr=0.0000021, metrics:accuracy:0.6886,f1:0.4800
INFO:root:08:02:58 [Epoch 1 Batch 610/11375] loss=0.5097, lr=0.0000021, metrics:accuracy:0.6895,f1:0.4868
INFO:root:08:03:00 [Epoch 1 Batch 620/11375] loss=0.4584, lr=0.0000022, metrics:accuracy:0.6911,f1:0.4912
INFO:root:08:03:01 [Epoch 1 Batch 630/11375] loss=0.5318, lr=0.0000022, metrics:accuracy:0.6918,f1:0.4949
INFO:root:08:03:02 [Epoch 1 Batch 640/11375] loss=0.4806, lr=0.0000022, metrics:accuracy:0.6933,f1:0.5000
INFO:root:08:03:03 [Epoch 1 Batch 650/11375] loss=0.5283, lr=0.0000023, metrics:accuracy:0.6939,f1:0.5045
INFO:root:08:03:04 [Epoch 1 Batch 660/11375] loss=0.5298, lr=0.0000023, metrics:accuracy:0.6944,f1:0.5077
INFO:root:08:03:05 [Epoch 1 Batch 670/11375] loss=0.3984, lr=0.0000024, metrics:accuracy:0.6963,f1:0.5110
INFO:root:08:03:07 [Epoch 1 Batch 680/11375] loss=0.5267, lr=0.0000024, metrics:accuracy:0.6967,f1:0.5147
INFO:root:08:03:08 [Epoch 1 Batch 690/11375] loss=0.5241, lr=0.0000024, metrics:accuracy:0.6972,f1:0.5190
INFO:root:08:03:09 [Epoch 1 Batch 700/11375] loss=0.4995, lr=0.0000025, metrics:accuracy:0.6980,f1:0.5226
INFO:root:08:03:10 [Epoch 1 Batch 710/11375] loss=0.4868, lr=0.0000025, metrics:accuracy:0.6990,f1:0.5265
INFO:root:08:03:11 [Epoch 1 Batch 720/11375] loss=0.4555, lr=0.0000025, metrics:accuracy:0.7000,f1:0.5289
INFO:root:08:03:12 [Epoch 1 Batch 730/11375] loss=0.5426, lr=0.0000026, metrics:accuracy:0.7006,f1:0.5327
INFO:root:08:03:13 [Epoch 1 Batch 740/11375] loss=0.4657, lr=0.0000026, metrics:accuracy:0.7014,f1:0.5351
INFO:root:08:03:15 [Epoch 1 Batch 750/11375] loss=0.3802, lr=0.0000026, metrics:accuracy:0.7030,f1:0.5377
INFO:root:08:03:16 [Epoch 1 Batch 760/11375] loss=0.4392, lr=0.0000027, metrics:accuracy:0.7041,f1:0.5395
INFO:root:08:03:17 [Epoch 1 Batch 770/11375] loss=0.4773, lr=0.0000027, metrics:accuracy:0.7048,f1:0.5424
INFO:root:08:03:18 [Epoch 1 Batch 780/11375] loss=0.4221, lr=0.0000027, metrics:accuracy:0.7062,f1:0.5448
INFO:root:08:03:19 [Epoch 1 Batch 790/11375] loss=0.4984, lr=0.0000028, metrics:accuracy:0.7067,f1:0.5475
INFO:root:08:03:20 [Epoch 1 Batch 800/11375] loss=0.4410, lr=0.0000028, metrics:accuracy:0.7078,f1:0.5502
INFO:root:08:03:22 [Epoch 1 Batch 810/11375] loss=0.4830, lr=0.0000028, metrics:accuracy:0.7085,f1:0.5513
INFO:root:08:03:23 [Epoch 1 Batch 820/11375] loss=0.4762, lr=0.0000029, metrics:accuracy:0.7090,f1:0.5536
INFO:root:08:03:24 [Epoch 1 Batch 830/11375] loss=0.4921, lr=0.0000029, metrics:accuracy:0.7096,f1:0.5563
INFO:root:08:03:25 [Epoch 1 Batch 840/11375] loss=0.4473, lr=0.0000030, metrics:accuracy:0.7105,f1:0.5580
INFO:root:08:03:27 [Epoch 1 Batch 850/11375] loss=0.4099, lr=0.0000030, metrics:accuracy:0.7117,f1:0.5598
INFO:root:08:03:28 [Epoch 1 Batch 860/11375] loss=0.4126, lr=0.0000030, metrics:accuracy:0.7128,f1:0.5639
INFO:root:08:03:29 [Epoch 1 Batch 870/11375] loss=0.4837, lr=0.0000031, metrics:accuracy:0.7136,f1:0.5649
INFO:root:08:03:30 [Epoch 1 Batch 880/11375] loss=0.5023, lr=0.0000031, metrics:accuracy:0.7142,f1:0.5674
INFO:root:08:03:31 [Epoch 1 Batch 890/11375] loss=0.3969, lr=0.0000031, metrics:accuracy:0.7156,f1:0.5706
INFO:root:08:03:32 [Epoch 1 Batch 900/11375] loss=0.4414, lr=0.0000032, metrics:accuracy:0.7164,f1:0.5738
INFO:root:08:03:34 [Epoch 1 Batch 910/11375] loss=0.5024, lr=0.0000032, metrics:accuracy:0.7165,f1:0.5749
INFO:root:08:03:35 [Epoch 1 Batch 920/11375] loss=0.4213, lr=0.0000032, metrics:accuracy:0.7174,f1:0.5767
INFO:root:08:03:36 [Epoch 1 Batch 930/11375] loss=0.4969, lr=0.0000033, metrics:accuracy:0.7179,f1:0.5795
INFO:root:08:03:37 [Epoch 1 Batch 940/11375] loss=0.4134, lr=0.0000033, metrics:accuracy:0.7189,f1:0.5813
INFO:root:08:03:38 [Epoch 1 Batch 950/11375] loss=0.4303, lr=0.0000033, metrics:accuracy:0.7198,f1:0.5827
INFO:root:08:03:39 [Epoch 1 Batch 960/11375] loss=0.4759, lr=0.0000034, metrics:accuracy:0.7201,f1:0.5845
INFO:root:08:03:41 [Epoch 1 Batch 970/11375] loss=0.4370, lr=0.0000034, metrics:accuracy:0.7206,f1:0.5862
INFO:root:08:03:42 [Epoch 1 Batch 980/11375] loss=0.4407, lr=0.0000034, metrics:accuracy:0.7214,f1:0.5884
INFO:root:08:03:43 [Epoch 1 Batch 990/11375] loss=0.4542, lr=0.0000035, metrics:accuracy:0.7220,f1:0.5908
INFO:root:08:03:44 [Epoch 1 Batch 1000/11375] loss=0.4117, lr=0.0000035, metrics:accuracy:0.7227,f1:0.5925
INFO:root:08:03:45 [Epoch 1 Batch 1010/11375] loss=0.4562, lr=0.0000035, metrics:accuracy:0.7234,f1:0.5938
INFO:root:08:03:46 [Epoch 1 Batch 1020/11375] loss=0.4032, lr=0.0000036, metrics:accuracy:0.7244,f1:0.5954
INFO:root:08:03:48 [Epoch 1 Batch 1030/11375] loss=0.5043, lr=0.0000036, metrics:accuracy:0.7246,f1:0.5968
INFO:root:08:03:49 [Epoch 1 Batch 1040/11375] loss=0.4410, lr=0.0000037, metrics:accuracy:0.7252,f1:0.5984
INFO:root:08:03:50 [Epoch 1 Batch 1050/11375] loss=0.4934, lr=0.0000037, metrics:accuracy:0.7254,f1:0.6003
INFO:root:08:03:51 [Epoch 1 Batch 1060/11375] loss=0.4671, lr=0.0000037, metrics:accuracy:0.7257,f1:0.6007
INFO:root:08:03:52 [Epoch 1 Batch 1070/11375] loss=0.5103, lr=0.0000038, metrics:accuracy:0.7260,f1:0.6013
INFO:root:08:03:53 [Epoch 1 Batch 1080/11375] loss=0.4013, lr=0.0000038, metrics:accuracy:0.7268,f1:0.6021
INFO:root:08:03:54 [Epoch 1 Batch 1090/11375] loss=0.4801, lr=0.0000038, metrics:accuracy:0.7269,f1:0.6032
INFO:root:08:03:56 [Epoch 1 Batch 1100/11375] loss=0.4149, lr=0.0000039, metrics:accuracy:0.7276,f1:0.6044
INFO:root:08:03:57 [Epoch 1 Batch 1110/11375] loss=0.4269, lr=0.0000039, metrics:accuracy:0.7281,f1:0.6046
INFO:root:08:03:58 [Epoch 1 Batch 1120/11375] loss=0.4209, lr=0.0000039, metrics:accuracy:0.7288,f1:0.6056
INFO:root:08:03:59 [Epoch 1 Batch 1130/11375] loss=0.4123, lr=0.0000040, metrics:accuracy:0.7293,f1:0.6064
INFO:root:08:04:01 [Epoch 1 Batch 1140/11375] loss=0.4338, lr=0.0000040, metrics:accuracy:0.7300,f1:0.6074
INFO:root:08:04:02 [Epoch 1 Batch 1150/11375] loss=0.3523, lr=0.0000040, metrics:accuracy:0.7309,f1:0.6085
INFO:root:08:04:03 [Epoch 1 Batch 1160/11375] loss=0.3561, lr=0.0000041, metrics:accuracy:0.7318,f1:0.6096
INFO:root:08:04:04 [Epoch 1 Batch 1170/11375] loss=0.4944, lr=0.0000041, metrics:accuracy:0.7320,f1:0.6113
INFO:root:08:04:06 [Epoch 1 Batch 1180/11375] loss=0.4297, lr=0.0000041, metrics:accuracy:0.7324,f1:0.6123
INFO:root:08:04:07 [Epoch 1 Batch 1190/11375] loss=0.3660, lr=0.0000042, metrics:accuracy:0.7332,f1:0.6133
INFO:root:08:04:08 [Epoch 1 Batch 1200/11375] loss=0.4147, lr=0.0000042, metrics:accuracy:0.7337,f1:0.6143
INFO:root:08:04:09 [Epoch 1 Batch 1210/11375] loss=0.4585, lr=0.0000043, metrics:accuracy:0.7341,f1:0.6159
INFO:root:08:04:10 [Epoch 1 Batch 1220/11375] loss=0.5070, lr=0.0000043, metrics:accuracy:0.7342,f1:0.6160
INFO:root:08:04:12 [Epoch 1 Batch 1230/11375] loss=0.4361, lr=0.0000043, metrics:accuracy:0.7346,f1:0.6174
INFO:root:08:04:13 [Epoch 1 Batch 1240/11375] loss=0.4093, lr=0.0000044, metrics:accuracy:0.7353,f1:0.6186
INFO:root:08:04:14 [Epoch 1 Batch 1250/11375] loss=0.3950, lr=0.0000044, metrics:accuracy:0.7359,f1:0.6195
INFO:root:08:04:15 [Epoch 1 Batch 1260/11375] loss=0.4760, lr=0.0000044, metrics:accuracy:0.7360,f1:0.6207
INFO:root:08:04:16 [Epoch 1 Batch 1270/11375] loss=0.3964, lr=0.0000045, metrics:accuracy:0.7366,f1:0.6216
INFO:root:08:04:18 [Epoch 1 Batch 1280/11375] loss=0.4303, lr=0.0000045, metrics:accuracy:0.7369,f1:0.6221
INFO:root:08:04:19 [Epoch 1 Batch 1290/11375] loss=0.4378, lr=0.0000045, metrics:accuracy:0.7373,f1:0.6234
INFO:root:08:04:20 [Epoch 1 Batch 1300/11375] loss=0.4645, lr=0.0000046, metrics:accuracy:0.7378,f1:0.6241
INFO:root:08:04:21 [Epoch 1 Batch 1310/11375] loss=0.4226, lr=0.0000046, metrics:accuracy:0.7382,f1:0.6254
INFO:root:08:04:22 [Epoch 1 Batch 1320/11375] loss=0.4415, lr=0.0000046, metrics:accuracy:0.7386,f1:0.6260
INFO:root:08:04:24 [Epoch 1 Batch 1330/11375] loss=0.3822, lr=0.0000047, metrics:accuracy:0.7392,f1:0.6269
INFO:root:08:04:25 [Epoch 1 Batch 1340/11375] loss=0.4803, lr=0.0000047, metrics:accuracy:0.7396,f1:0.6281
INFO:root:08:04:26 [Epoch 1 Batch 1350/11375] loss=0.4409, lr=0.0000047, metrics:accuracy:0.7399,f1:0.6291
INFO:root:08:04:27 [Epoch 1 Batch 1360/11375] loss=0.4506, lr=0.0000048, metrics:accuracy:0.7401,f1:0.6298
INFO:root:08:04:28 [Epoch 1 Batch 1370/11375] loss=0.4378, lr=0.0000048, metrics:accuracy:0.7403,f1:0.6300
INFO:root:08:04:29 [Epoch 1 Batch 1380/11375] loss=0.4963, lr=0.0000049, metrics:accuracy:0.7403,f1:0.6310
INFO:root:08:04:31 [Epoch 1 Batch 1390/11375] loss=0.4302, lr=0.0000049, metrics:accuracy:0.7404,f1:0.6315
INFO:root:08:04:32 [Epoch 1 Batch 1400/11375] loss=0.4153, lr=0.0000049, metrics:accuracy:0.7408,f1:0.6325
INFO:root:08:04:33 [Epoch 1 Batch 1410/11375] loss=0.3135, lr=0.0000050, metrics:accuracy:0.7417,f1:0.6331
INFO:root:08:04:34 [Epoch 1 Batch 1420/11375] loss=0.3430, lr=0.0000050, metrics:accuracy:0.7424,f1:0.6343
INFO:root:08:04:36 [Epoch 1 Batch 1430/11375] loss=0.4444, lr=0.0000050, metrics:accuracy:0.7427,f1:0.6352
INFO:root:08:04:37 [Epoch 1 Batch 1440/11375] loss=0.4324, lr=0.0000051, metrics:accuracy:0.7433,f1:0.6363
INFO:root:08:04:38 [Epoch 1 Batch 1450/11375] loss=0.3753, lr=0.0000051, metrics:accuracy:0.7439,f1:0.6378
INFO:root:08:04:39 [Epoch 1 Batch 1460/11375] loss=0.4257, lr=0.0000051, metrics:accuracy:0.7441,f1:0.6383
INFO:root:08:04:40 [Epoch 1 Batch 1470/11375] loss=0.3679, lr=0.0000052, metrics:accuracy:0.7447,f1:0.6391
INFO:root:08:04:42 [Epoch 1 Batch 1480/11375] loss=0.3443, lr=0.0000052, metrics:accuracy:0.7453,f1:0.6395
INFO:root:08:04:43 [Epoch 1 Batch 1490/11375] loss=0.4398, lr=0.0000052, metrics:accuracy:0.7456,f1:0.6403
INFO:root:08:04:44 [Epoch 1 Batch 1500/11375] loss=0.4321, lr=0.0000053, metrics:accuracy:0.7460,f1:0.6413
INFO:root:08:04:45 [Epoch 1 Batch 1510/11375] loss=0.3622, lr=0.0000053, metrics:accuracy:0.7465,f1:0.6421
INFO:root:08:04:46 [Epoch 1 Batch 1520/11375] loss=0.4414, lr=0.0000053, metrics:accuracy:0.7468,f1:0.6426
INFO:root:08:04:48 [Epoch 1 Batch 1530/11375] loss=0.4085, lr=0.0000054, metrics:accuracy:0.7472,f1:0.6430
INFO:root:08:04:49 [Epoch 1 Batch 1540/11375] loss=0.4778, lr=0.0000054, metrics:accuracy:0.7474,f1:0.6438
INFO:root:08:04:50 [Epoch 1 Batch 1550/11375] loss=0.3740, lr=0.0000054, metrics:accuracy:0.7480,f1:0.6448
INFO:root:08:04:51 [Epoch 1 Batch 1560/11375] loss=0.4066, lr=0.0000055, metrics:accuracy:0.7485,f1:0.6456
INFO:root:08:04:52 [Epoch 1 Batch 1570/11375] loss=0.3710, lr=0.0000055, metrics:accuracy:0.7490,f1:0.6465
INFO:root:08:04:53 [Epoch 1 Batch 1580/11375] loss=0.3767, lr=0.0000056, metrics:accuracy:0.7495,f1:0.6476
INFO:root:08:04:54 [Epoch 1 Batch 1590/11375] loss=0.4965, lr=0.0000056, metrics:accuracy:0.7496,f1:0.6487
INFO:root:08:04:56 [Epoch 1 Batch 1600/11375] loss=0.3556, lr=0.0000056, metrics:accuracy:0.7501,f1:0.6495
INFO:root:08:04:57 [Epoch 1 Batch 1610/11375] loss=0.4023, lr=0.0000057, metrics:accuracy:0.7505,f1:0.6504
INFO:root:08:04:58 [Epoch 1 Batch 1620/11375] loss=0.4720, lr=0.0000057, metrics:accuracy:0.7508,f1:0.6516
INFO:root:08:04:59 [Epoch 1 Batch 1630/11375] loss=0.3762, lr=0.0000057, metrics:accuracy:0.7512,f1:0.6520
INFO:root:08:05:00 [Epoch 1 Batch 1640/11375] loss=0.4273, lr=0.0000058, metrics:accuracy:0.7512,f1:0.6526
INFO:root:08:05:01 [Epoch 1 Batch 1650/11375] loss=0.3350, lr=0.0000058, metrics:accuracy:0.7519,f1:0.6539
INFO:root:08:05:03 [Epoch 1 Batch 1660/11375] loss=0.4232, lr=0.0000058, metrics:accuracy:0.7522,f1:0.6544
INFO:root:08:05:04 [Epoch 1 Batch 1670/11375] loss=0.4255, lr=0.0000059, metrics:accuracy:0.7525,f1:0.6555
INFO:root:08:05:05 [Epoch 1 Batch 1680/11375] loss=0.4003, lr=0.0000059, metrics:accuracy:0.7529,f1:0.6569
INFO:root:08:05:06 [Epoch 1 Batch 1690/11375] loss=0.3589, lr=0.0000059, metrics:accuracy:0.7534,f1:0.6575
INFO:root:08:05:07 [Epoch 1 Batch 1700/11375] loss=0.3839, lr=0.0000060, metrics:accuracy:0.7536,f1:0.6580
INFO:root:08:05:09 [Epoch 1 Batch 1710/11375] loss=0.4321, lr=0.0000060, metrics:accuracy:0.7538,f1:0.6582
INFO:root:08:05:10 [Epoch 1 Batch 1720/11375] loss=0.4224, lr=0.0000060, metrics:accuracy:0.7541,f1:0.6589
INFO:root:08:05:11 [Epoch 1 Batch 1730/11375] loss=0.3955, lr=0.0000061, metrics:accuracy:0.7543,f1:0.6591
INFO:root:08:05:12 [Epoch 1 Batch 1740/11375] loss=0.4818, lr=0.0000061, metrics:accuracy:0.7543,f1:0.6596
INFO:root:08:05:13 [Epoch 1 Batch 1750/11375] loss=0.3620, lr=0.0000062, metrics:accuracy:0.7548,f1:0.6605
INFO:root:08:05:15 [Epoch 1 Batch 1760/11375] loss=0.3833, lr=0.0000062, metrics:accuracy:0.7552,f1:0.6608
INFO:root:08:05:16 [Epoch 1 Batch 1770/11375] loss=0.3988, lr=0.0000062, metrics:accuracy:0.7556,f1:0.6616
INFO:root:08:05:17 [Epoch 1 Batch 1780/11375] loss=0.4113, lr=0.0000063, metrics:accuracy:0.7559,f1:0.6625
INFO:root:08:05:18 [Epoch 1 Batch 1790/11375] loss=0.4167, lr=0.0000063, metrics:accuracy:0.7561,f1:0.6633
INFO:root:08:05:19 [Epoch 1 Batch 1800/11375] loss=0.4580, lr=0.0000063, metrics:accuracy:0.7561,f1:0.6639
INFO:root:08:05:20 [Epoch 1 Batch 1810/11375] loss=0.3974, lr=0.0000064, metrics:accuracy:0.7564,f1:0.6646
INFO:root:08:05:21 [Epoch 1 Batch 1820/11375] loss=0.4228, lr=0.0000064, metrics:accuracy:0.7566,f1:0.6650
INFO:root:08:05:22 [Epoch 1 Batch 1830/11375] loss=0.4066, lr=0.0000064, metrics:accuracy:0.7569,f1:0.6656
INFO:root:08:05:24 [Epoch 1 Batch 1840/11375] loss=0.4175, lr=0.0000065, metrics:accuracy:0.7571,f1:0.6662
INFO:root:08:05:25 [Epoch 1 Batch 1850/11375] loss=0.4013, lr=0.0000065, metrics:accuracy:0.7574,f1:0.6664
INFO:root:08:05:26 [Epoch 1 Batch 1860/11375] loss=0.3858, lr=0.0000065, metrics:accuracy:0.7576,f1:0.6668
INFO:root:08:05:27 [Epoch 1 Batch 1870/11375] loss=0.4733, lr=0.0000066, metrics:accuracy:0.7576,f1:0.6669
INFO:root:08:05:28 [Epoch 1 Batch 1880/11375] loss=0.3404, lr=0.0000066, metrics:accuracy:0.7580,f1:0.6674
INFO:root:08:05:30 [Epoch 1 Batch 1890/11375] loss=0.3337, lr=0.0000066, metrics:accuracy:0.7585,f1:0.6676
INFO:root:08:05:31 [Epoch 1 Batch 1900/11375] loss=0.3629, lr=0.0000067, metrics:accuracy:0.7589,f1:0.6683
INFO:root:08:05:32 [Epoch 1 Batch 1910/11375] loss=0.4094, lr=0.0000067, metrics:accuracy:0.7591,f1:0.6689
INFO:root:08:05:33 [Epoch 1 Batch 1920/11375] loss=0.4496, lr=0.0000068, metrics:accuracy:0.7594,f1:0.6695
INFO:root:08:05:34 [Epoch 1 Batch 1930/11375] loss=0.3922, lr=0.0000068, metrics:accuracy:0.7596,f1:0.6700
INFO:root:08:05:36 [Epoch 1 Batch 1940/11375] loss=0.3707, lr=0.0000068, metrics:accuracy:0.7599,f1:0.6703
INFO:root:08:05:37 [Epoch 1 Batch 1950/11375] loss=0.4278, lr=0.0000069, metrics:accuracy:0.7602,f1:0.6706
INFO:root:08:05:38 [Epoch 1 Batch 1960/11375] loss=0.3622, lr=0.0000069, metrics:accuracy:0.7605,f1:0.6709
INFO:root:08:05:40 [Epoch 1 Batch 1970/11375] loss=0.3330, lr=0.0000069, metrics:accuracy:0.7610,f1:0.6716
INFO:root:08:05:41 [Epoch 1 Batch 1980/11375] loss=0.2929, lr=0.0000070, metrics:accuracy:0.7615,f1:0.6722
INFO:root:08:05:42 [Epoch 1 Batch 1990/11375] loss=0.4192, lr=0.0000070, metrics:accuracy:0.7617,f1:0.6731
INFO:root:08:05:43 [Epoch 1 Batch 2000/11375] loss=0.4220, lr=0.0000070, metrics:accuracy:0.7619,f1:0.6736
INFO:root:08:05:44 [Epoch 1 Batch 2010/11375] loss=0.3748, lr=0.0000071, metrics:accuracy:0.7621,f1:0.6739
INFO:root:08:05:46 [Epoch 1 Batch 2020/11375] loss=0.3998, lr=0.0000071, metrics:accuracy:0.7624,f1:0.6743
INFO:root:08:05:47 [Epoch 1 Batch 2030/11375] loss=0.3585, lr=0.0000071, metrics:accuracy:0.7627,f1:0.6748
INFO:root:08:05:48 [Epoch 1 Batch 2040/11375] loss=0.4589, lr=0.0000072, metrics:accuracy:0.7627,f1:0.6749
INFO:root:08:05:49 [Epoch 1 Batch 2050/11375] loss=0.3715, lr=0.0000072, metrics:accuracy:0.7631,f1:0.6755
INFO:root:08:05:51 [Epoch 1 Batch 2060/11375] loss=0.2631, lr=0.0000072, metrics:accuracy:0.7637,f1:0.6757
INFO:root:08:05:52 [Epoch 1 Batch 2070/11375] loss=0.4285, lr=0.0000073, metrics:accuracy:0.7639,f1:0.6763
INFO:root:08:05:53 [Epoch 1 Batch 2080/11375] loss=0.3966, lr=0.0000073, metrics:accuracy:0.7642,f1:0.6769
INFO:root:08:05:54 [Epoch 1 Batch 2090/11375] loss=0.4706, lr=0.0000073, metrics:accuracy:0.7643,f1:0.6771
INFO:root:08:05:55 [Epoch 1 Batch 2100/11375] loss=0.3572, lr=0.0000074, metrics:accuracy:0.7646,f1:0.6777
INFO:root:08:05:57 [Epoch 1 Batch 2110/11375] loss=0.3639, lr=0.0000074, metrics:accuracy:0.7649,f1:0.6779
INFO:root:08:05:58 [Epoch 1 Batch 2120/11375] loss=0.3093, lr=0.0000075, metrics:accuracy:0.7654,f1:0.6780
INFO:root:08:05:59 [Epoch 1 Batch 2130/11375] loss=0.3894, lr=0.0000075, metrics:accuracy:0.7655,f1:0.6783
INFO:root:08:06:00 [Epoch 1 Batch 2140/11375] loss=0.4140, lr=0.0000075, metrics:accuracy:0.7657,f1:0.6787
INFO:root:08:06:02 [Epoch 1 Batch 2150/11375] loss=0.4326, lr=0.0000076, metrics:accuracy:0.7659,f1:0.6789
INFO:root:08:06:03 [Epoch 1 Batch 2160/11375] loss=0.3988, lr=0.0000076, metrics:accuracy:0.7660,f1:0.6792
INFO:root:08:06:04 [Epoch 1 Batch 2170/11375] loss=0.4169, lr=0.0000076, metrics:accuracy:0.7662,f1:0.6798
INFO:root:08:06:05 [Epoch 1 Batch 2180/11375] loss=0.3346, lr=0.0000077, metrics:accuracy:0.7665,f1:0.6802
INFO:root:08:06:06 [Epoch 1 Batch 2190/11375] loss=0.3581, lr=0.0000077, metrics:accuracy:0.7668,f1:0.6808
INFO:root:08:06:07 [Epoch 1 Batch 2200/11375] loss=0.4272, lr=0.0000077, metrics:accuracy:0.7671,f1:0.6814
INFO:root:08:06:09 [Epoch 1 Batch 2210/11375] loss=0.3975, lr=0.0000078, metrics:accuracy:0.7672,f1:0.6818
INFO:root:08:06:10 [Epoch 1 Batch 2220/11375] loss=0.4313, lr=0.0000078, metrics:accuracy:0.7673,f1:0.6824
INFO:root:08:06:11 [Epoch 1 Batch 2230/11375] loss=0.4124, lr=0.0000078, metrics:accuracy:0.7676,f1:0.6831
INFO:root:08:06:12 [Epoch 1 Batch 2240/11375] loss=0.3950, lr=0.0000079, metrics:accuracy:0.7678,f1:0.6832
INFO:root:08:06:13 [Epoch 1 Batch 2250/11375] loss=0.4004, lr=0.0000079, metrics:accuracy:0.7679,f1:0.6834
INFO:root:08:06:15 [Epoch 1 Batch 2260/11375] loss=0.3759, lr=0.0000079, metrics:accuracy:0.7681,f1:0.6838
INFO:root:08:06:16 [Epoch 1 Batch 2270/11375] loss=0.3239, lr=0.0000080, metrics:accuracy:0.7685,f1:0.6842
INFO:root:08:06:17 [Epoch 1 Batch 2280/11375] loss=0.4485, lr=0.0000080, metrics:accuracy:0.7686,f1:0.6844
INFO:root:08:06:18 [Epoch 1 Batch 2290/11375] loss=0.3931, lr=0.0000081, metrics:accuracy:0.7688,f1:0.6846
INFO:root:08:06:19 [Epoch 1 Batch 2300/11375] loss=0.3902, lr=0.0000081, metrics:accuracy:0.7691,f1:0.6847
INFO:root:08:06:21 [Epoch 1 Batch 2310/11375] loss=0.3636, lr=0.0000081, metrics:accuracy:0.7693,f1:0.6849
INFO:root:08:06:22 [Epoch 1 Batch 2320/11375] loss=0.3373, lr=0.0000082, metrics:accuracy:0.7697,f1:0.6852
INFO:root:08:06:23 [Epoch 1 Batch 2330/11375] loss=0.4248, lr=0.0000082, metrics:accuracy:0.7698,f1:0.6853
INFO:root:08:06:25 [Epoch 1 Batch 2340/11375] loss=0.4170, lr=0.0000082, metrics:accuracy:0.7699,f1:0.6858
INFO:root:08:06:26 [Epoch 1 Batch 2350/11375] loss=0.4005, lr=0.0000083, metrics:accuracy:0.7701,f1:0.6863
INFO:root:08:06:27 [Epoch 1 Batch 2360/11375] loss=0.3671, lr=0.0000083, metrics:accuracy:0.7703,f1:0.6867
INFO:root:08:06:28 [Epoch 1 Batch 2370/11375] loss=0.4404, lr=0.0000083, metrics:accuracy:0.7705,f1:0.6870
INFO:root:08:06:29 [Epoch 1 Batch 2380/11375] loss=0.4035, lr=0.0000084, metrics:accuracy:0.7706,f1:0.6876
INFO:root:08:06:30 [Epoch 1 Batch 2390/11375] loss=0.4138, lr=0.0000084, metrics:accuracy:0.7708,f1:0.6880
INFO:root:08:06:31 [Epoch 1 Batch 2400/11375] loss=0.3670, lr=0.0000084, metrics:accuracy:0.7710,f1:0.6882
INFO:root:08:06:33 [Epoch 1 Batch 2410/11375] loss=0.3653, lr=0.0000085, metrics:accuracy:0.7713,f1:0.6885
INFO:root:08:06:34 [Epoch 1 Batch 2420/11375] loss=0.3299, lr=0.0000085, metrics:accuracy:0.7716,f1:0.6890
INFO:root:08:06:35 [Epoch 1 Batch 2430/11375] loss=0.3721, lr=0.0000085, metrics:accuracy:0.7719,f1:0.6896
INFO:root:08:06:36 [Epoch 1 Batch 2440/11375] loss=0.3714, lr=0.0000086, metrics:accuracy:0.7722,f1:0.6902
INFO:root:08:06:37 [Epoch 1 Batch 2450/11375] loss=0.3482, lr=0.0000086, metrics:accuracy:0.7724,f1:0.6907
INFO:root:08:06:38 [Epoch 1 Batch 2460/11375] loss=0.3827, lr=0.0000087, metrics:accuracy:0.7727,f1:0.6912
INFO:root:08:06:40 [Epoch 1 Batch 2470/11375] loss=0.3852, lr=0.0000087, metrics:accuracy:0.7729,f1:0.6916
INFO:root:08:06:41 [Epoch 1 Batch 2480/11375] loss=0.4262, lr=0.0000087, metrics:accuracy:0.7730,f1:0.6917
INFO:root:08:06:42 [Epoch 1 Batch 2490/11375] loss=0.3818, lr=0.0000088, metrics:accuracy:0.7733,f1:0.6925
INFO:root:08:06:43 [Epoch 1 Batch 2500/11375] loss=0.3556, lr=0.0000088, metrics:accuracy:0.7735,f1:0.6928
INFO:root:08:06:44 [Epoch 1 Batch 2510/11375] loss=0.3658, lr=0.0000088, metrics:accuracy:0.7737,f1:0.6932
INFO:root:08:06:45 [Epoch 1 Batch 2520/11375] loss=0.3646, lr=0.0000089, metrics:accuracy:0.7740,f1:0.6935
INFO:root:08:06:47 [Epoch 1 Batch 2530/11375] loss=0.3184, lr=0.0000089, metrics:accuracy:0.7742,f1:0.6936
INFO:root:08:06:48 [Epoch 1 Batch 2540/11375] loss=0.2985, lr=0.0000089, metrics:accuracy:0.7745,f1:0.6940
INFO:root:08:06:49 [Epoch 1 Batch 2550/11375] loss=0.3822, lr=0.0000090, metrics:accuracy:0.7748,f1:0.6941
INFO:root:08:06:50 [Epoch 1 Batch 2560/11375] loss=0.3500, lr=0.0000090, metrics:accuracy:0.7750,f1:0.6946
INFO:root:08:06:51 [Epoch 1 Batch 2570/11375] loss=0.4591, lr=0.0000090, metrics:accuracy:0.7751,f1:0.6948
INFO:root:08:06:52 [Epoch 1 Batch 2580/11375] loss=0.3931, lr=0.0000091, metrics:accuracy:0.7753,f1:0.6953
INFO:root:08:06:53 [Epoch 1 Batch 2590/11375] loss=0.4467, lr=0.0000091, metrics:accuracy:0.7753,f1:0.6954
INFO:root:08:06:55 [Epoch 1 Batch 2600/11375] loss=0.4049, lr=0.0000091, metrics:accuracy:0.7754,f1:0.6958
INFO:root:08:06:56 [Epoch 1 Batch 2610/11375] loss=0.3356, lr=0.0000092, metrics:accuracy:0.7758,f1:0.6965
INFO:root:08:06:57 [Epoch 1 Batch 2620/11375] loss=0.3424, lr=0.0000092, metrics:accuracy:0.7760,f1:0.6966
INFO:root:08:06:58 [Epoch 1 Batch 2630/11375] loss=0.3310, lr=0.0000092, metrics:accuracy:0.7763,f1:0.6969
INFO:root:08:06:59 [Epoch 1 Batch 2640/11375] loss=0.3777, lr=0.0000093, metrics:accuracy:0.7765,f1:0.6975
INFO:root:08:07:00 [Epoch 1 Batch 2650/11375] loss=0.3840, lr=0.0000093, metrics:accuracy:0.7768,f1:0.6981
INFO:root:08:07:01 [Epoch 1 Batch 2660/11375] loss=0.4289, lr=0.0000094, metrics:accuracy:0.7769,f1:0.6984
INFO:root:08:07:03 [Epoch 1 Batch 2670/11375] loss=0.4030, lr=0.0000094, metrics:accuracy:0.7770,f1:0.6986
INFO:root:08:07:04 [Epoch 1 Batch 2680/11375] loss=0.3821, lr=0.0000094, metrics:accuracy:0.7771,f1:0.6988
INFO:root:08:07:05 [Epoch 1 Batch 2690/11375] loss=0.3679, lr=0.0000095, metrics:accuracy:0.7773,f1:0.6991
INFO:root:08:07:06 [Epoch 1 Batch 2700/11375] loss=0.3846, lr=0.0000095, metrics:accuracy:0.7774,f1:0.6992
INFO:root:08:07:07 [Epoch 1 Batch 2710/11375] loss=0.4728, lr=0.0000095, metrics:accuracy:0.7774,f1:0.6994
INFO:root:08:07:08 [Epoch 1 Batch 2720/11375] loss=0.3786, lr=0.0000096, metrics:accuracy:0.7776,f1:0.7000
INFO:root:08:07:10 [Epoch 1 Batch 2730/11375] loss=0.3538, lr=0.0000096, metrics:accuracy:0.7780,f1:0.7004
INFO:root:08:07:11 [Epoch 1 Batch 2740/11375] loss=0.3326, lr=0.0000096, metrics:accuracy:0.7782,f1:0.7005
INFO:root:08:07:12 [Epoch 1 Batch 2750/11375] loss=0.3764, lr=0.0000097, metrics:accuracy:0.7783,f1:0.7006
INFO:root:08:07:14 [Epoch 1 Batch 2760/11375] loss=0.3721, lr=0.0000097, metrics:accuracy:0.7785,f1:0.7010
INFO:root:08:07:15 [Epoch 1 Batch 2770/11375] loss=0.4190, lr=0.0000097, metrics:accuracy:0.7785,f1:0.7011
INFO:root:08:07:16 [Epoch 1 Batch 2780/11375] loss=0.3178, lr=0.0000098, metrics:accuracy:0.7788,f1:0.7015
INFO:root:08:07:17 [Epoch 1 Batch 2790/11375] loss=0.3386, lr=0.0000098, metrics:accuracy:0.7791,f1:0.7018
INFO:root:08:07:18 [Epoch 1 Batch 2800/11375] loss=0.3614, lr=0.0000098, metrics:accuracy:0.7793,f1:0.7019
INFO:root:08:07:19 [Epoch 1 Batch 2810/11375] loss=0.3434, lr=0.0000099, metrics:accuracy:0.7795,f1:0.7025
INFO:root:08:07:21 [Epoch 1 Batch 2820/11375] loss=0.3871, lr=0.0000099, metrics:accuracy:0.7796,f1:0.7026
INFO:root:08:07:22 [Epoch 1 Batch 2830/11375] loss=0.3980, lr=0.0000100, metrics:accuracy:0.7798,f1:0.7030
INFO:root:08:07:23 [Epoch 1 Batch 2840/11375] loss=0.3284, lr=0.0000100, metrics:accuracy:0.7801,f1:0.7034
INFO:root:08:07:24 [Epoch 1 Batch 2850/11375] loss=0.3491, lr=0.0000100, metrics:accuracy:0.7803,f1:0.7035
INFO:root:08:07:25 [Epoch 1 Batch 2860/11375] loss=0.3283, lr=0.0000101, metrics:accuracy:0.7805,f1:0.7038
INFO:root:08:07:27 [Epoch 1 Batch 2870/11375] loss=0.3477, lr=0.0000101, metrics:accuracy:0.7807,f1:0.7040
INFO:root:08:07:28 [Epoch 1 Batch 2880/11375] loss=0.3277, lr=0.0000101, metrics:accuracy:0.7810,f1:0.7041
INFO:root:08:07:29 [Epoch 1 Batch 2890/11375] loss=0.3763, lr=0.0000102, metrics:accuracy:0.7811,f1:0.7045
INFO:root:08:07:30 [Epoch 1 Batch 2900/11375] loss=0.3617, lr=0.0000102, metrics:accuracy:0.7812,f1:0.7046
INFO:root:08:07:32 [Epoch 1 Batch 2910/11375] loss=0.3070, lr=0.0000102, metrics:accuracy:0.7814,f1:0.7047
INFO:root:08:07:33 [Epoch 1 Batch 2920/11375] loss=0.3343, lr=0.0000103, metrics:accuracy:0.7816,f1:0.7052
INFO:root:08:07:34 [Epoch 1 Batch 2930/11375] loss=0.4008, lr=0.0000103, metrics:accuracy:0.7818,f1:0.7054
INFO:root:08:07:35 [Epoch 1 Batch 2940/11375] loss=0.3702, lr=0.0000103, metrics:accuracy:0.7820,f1:0.7059
INFO:root:08:07:36 [Epoch 1 Batch 2950/11375] loss=0.3699, lr=0.0000104, metrics:accuracy:0.7821,f1:0.7062
INFO:root:08:07:37 [Epoch 1 Batch 2960/11375] loss=0.3514, lr=0.0000104, metrics:accuracy:0.7823,f1:0.7065
INFO:root:08:07:39 [Epoch 1 Batch 2970/11375] loss=0.3606, lr=0.0000104, metrics:accuracy:0.7825,f1:0.7066
INFO:root:08:07:40 [Epoch 1 Batch 2980/11375] loss=0.3593, lr=0.0000105, metrics:accuracy:0.7826,f1:0.7071
INFO:root:08:07:41 [Epoch 1 Batch 2990/11375] loss=0.3898, lr=0.0000105, metrics:accuracy:0.7827,f1:0.7072
INFO:root:08:07:42 [Epoch 1 Batch 3000/11375] loss=0.3226, lr=0.0000106, metrics:accuracy:0.7829,f1:0.7074
INFO:root:08:07:43 [Epoch 1 Batch 3010/11375] loss=0.3506, lr=0.0000106, metrics:accuracy:0.7831,f1:0.7075
INFO:root:08:07:45 [Epoch 1 Batch 3020/11375] loss=0.3984, lr=0.0000106, metrics:accuracy:0.7832,f1:0.7076
INFO:root:08:07:46 [Epoch 1 Batch 3030/11375] loss=0.4599, lr=0.0000107, metrics:accuracy:0.7832,f1:0.7078
INFO:root:08:07:47 [Epoch 1 Batch 3040/11375] loss=0.4094, lr=0.0000107, metrics:accuracy:0.7834,f1:0.7082
INFO:root:08:07:48 [Epoch 1 Batch 3050/11375] loss=0.3459, lr=0.0000107, metrics:accuracy:0.7836,f1:0.7084
INFO:root:08:07:50 [Epoch 1 Batch 3060/11375] loss=0.2996, lr=0.0000108, metrics:accuracy:0.7839,f1:0.7087
INFO:root:08:07:51 [Epoch 1 Batch 3070/11375] loss=0.4253, lr=0.0000108, metrics:accuracy:0.7840,f1:0.7087
INFO:root:08:07:52 [Epoch 1 Batch 3080/11375] loss=0.4355, lr=0.0000108, metrics:accuracy:0.7840,f1:0.7089
INFO:root:08:07:53 [Epoch 1 Batch 3090/11375] loss=0.2716, lr=0.0000109, metrics:accuracy:0.7844,f1:0.7092
INFO:root:08:07:54 [Epoch 1 Batch 3100/11375] loss=0.4119, lr=0.0000109, metrics:accuracy:0.7845,f1:0.7093
INFO:root:08:07:56 [Epoch 1 Batch 3110/11375] loss=0.3163, lr=0.0000109, metrics:accuracy:0.7847,f1:0.7094
INFO:root:08:07:57 [Epoch 1 Batch 3120/11375] loss=0.3792, lr=0.0000110, metrics:accuracy:0.7849,f1:0.7098
INFO:root:08:07:58 [Epoch 1 Batch 3130/11375] loss=0.4782, lr=0.0000110, metrics:accuracy:0.7848,f1:0.7096
INFO:root:08:07:59 [Epoch 1 Batch 3140/11375] loss=0.2744, lr=0.0000110, metrics:accuracy:0.7851,f1:0.7098
INFO:root:08:08:00 [Epoch 1 Batch 3150/11375] loss=0.3786, lr=0.0000111, metrics:accuracy:0.7851,f1:0.7101
INFO:root:08:08:02 [Epoch 1 Batch 3160/11375] loss=0.3923, lr=0.0000111, metrics:accuracy:0.7853,f1:0.7103
INFO:root:08:08:03 [Epoch 1 Batch 3170/11375] loss=0.2971, lr=0.0000111, metrics:accuracy:0.7855,f1:0.7105
INFO:root:08:08:04 [Epoch 1 Batch 3180/11375] loss=0.3740, lr=0.0000112, metrics:accuracy:0.7857,f1:0.7107
INFO:root:08:08:05 [Epoch 1 Batch 3190/11375] loss=0.3508, lr=0.0000112, metrics:accuracy:0.7858,f1:0.7109
INFO:root:08:08:06 [Epoch 1 Batch 3200/11375] loss=0.3465, lr=0.0000113, metrics:accuracy:0.7860,f1:0.7112
INFO:root:08:08:08 [Epoch 1 Batch 3210/11375] loss=0.4057, lr=0.0000113, metrics:accuracy:0.7861,f1:0.7114
INFO:root:08:08:09 [Epoch 1 Batch 3220/11375] loss=0.3340, lr=0.0000113, metrics:accuracy:0.7863,f1:0.7116
INFO:root:08:08:10 [Epoch 1 Batch 3230/11375] loss=0.3651, lr=0.0000114, metrics:accuracy:0.7865,f1:0.7118
INFO:root:08:08:11 [Epoch 1 Batch 3240/11375] loss=0.3747, lr=0.0000114, metrics:accuracy:0.7866,f1:0.7121
INFO:root:08:08:12 [Epoch 1 Batch 3250/11375] loss=0.3381, lr=0.0000114, metrics:accuracy:0.7868,f1:0.7124
INFO:root:08:08:13 [Epoch 1 Batch 3260/11375] loss=0.3938, lr=0.0000115, metrics:accuracy:0.7869,f1:0.7128
INFO:root:08:08:14 [Epoch 1 Batch 3270/11375] loss=0.4157, lr=0.0000115, metrics:accuracy:0.7869,f1:0.7131
INFO:root:08:08:15 [Epoch 1 Batch 3280/11375] loss=0.4407, lr=0.0000115, metrics:accuracy:0.7869,f1:0.7132
INFO:root:08:08:17 [Epoch 1 Batch 3290/11375] loss=0.3030, lr=0.0000116, metrics:accuracy:0.7872,f1:0.7135
INFO:root:08:08:18 [Epoch 1 Batch 3300/11375] loss=0.3115, lr=0.0000116, metrics:accuracy:0.7874,f1:0.7138
INFO:root:08:08:19 [Epoch 1 Batch 3310/11375] loss=0.3566, lr=0.0000116, metrics:accuracy:0.7875,f1:0.7140
INFO:root:08:08:20 [Epoch 1 Batch 3320/11375] loss=0.3923, lr=0.0000117, metrics:accuracy:0.7876,f1:0.7142
INFO:root:08:08:22 [Epoch 1 Batch 3330/11375] loss=0.3752, lr=0.0000117, metrics:accuracy:0.7877,f1:0.7142
INFO:root:08:08:23 [Epoch 1 Batch 3340/11375] loss=0.3459, lr=0.0000117, metrics:accuracy:0.7878,f1:0.7143
INFO:root:08:08:24 [Epoch 1 Batch 3350/11375] loss=0.4001, lr=0.0000118, metrics:accuracy:0.7879,f1:0.7146
INFO:root:08:08:25 [Epoch 1 Batch 3360/11375] loss=0.3494, lr=0.0000118, metrics:accuracy:0.7881,f1:0.7147
INFO:root:08:08:26 [Epoch 1 Batch 3370/11375] loss=0.2775, lr=0.0000119, metrics:accuracy:0.7884,f1:0.7150
INFO:root:08:08:28 [Epoch 1 Batch 3380/11375] loss=0.3592, lr=0.0000119, metrics:accuracy:0.7885,f1:0.7152
INFO:root:08:08:29 [Epoch 1 Batch 3390/11375] loss=0.3981, lr=0.0000119, metrics:accuracy:0.7886,f1:0.7154
INFO:root:08:08:30 [Epoch 1 Batch 3400/11375] loss=0.3367, lr=0.0000120, metrics:accuracy:0.7887,f1:0.7157
INFO:root:08:08:31 [Epoch 1 Batch 3410/11375] loss=0.3805, lr=0.0000120, metrics:accuracy:0.7888,f1:0.7158
INFO:root:08:08:32 [Epoch 1 Batch 3420/11375] loss=0.3577, lr=0.0000120, metrics:accuracy:0.7889,f1:0.7160
INFO:root:08:08:34 [Epoch 1 Batch 3430/11375] loss=0.3562, lr=0.0000121, metrics:accuracy:0.7891,f1:0.7161
INFO:root:08:08:35 [Epoch 1 Batch 3440/11375] loss=0.3738, lr=0.0000121, metrics:accuracy:0.7892,f1:0.7165
INFO:root:08:08:36 [Epoch 1 Batch 3450/11375] loss=0.3038, lr=0.0000121, metrics:accuracy:0.7894,f1:0.7167
INFO:root:08:08:37 [Epoch 1 Batch 3460/11375] loss=0.4451, lr=0.0000122, metrics:accuracy:0.7894,f1:0.7169
INFO:root:08:08:38 [Epoch 1 Batch 3470/11375] loss=0.2943, lr=0.0000122, metrics:accuracy:0.7896,f1:0.7170
INFO:root:08:08:40 [Epoch 1 Batch 3480/11375] loss=0.3600, lr=0.0000122, metrics:accuracy:0.7898,f1:0.7172
INFO:root:08:08:41 [Epoch 1 Batch 3490/11375] loss=0.3248, lr=0.0000123, metrics:accuracy:0.7900,f1:0.7174
INFO:root:08:08:42 [Epoch 1 Batch 3500/11375] loss=0.3794, lr=0.0000123, metrics:accuracy:0.7901,f1:0.7175
INFO:root:08:08:43 [Epoch 1 Batch 3510/11375] loss=0.3647, lr=0.0000123, metrics:accuracy:0.7902,f1:0.7175
INFO:root:08:08:44 [Epoch 1 Batch 3520/11375] loss=0.3701, lr=0.0000124, metrics:accuracy:0.7903,f1:0.7178
INFO:root:08:08:46 [Epoch 1 Batch 3530/11375] loss=0.3682, lr=0.0000124, metrics:accuracy:0.7904,f1:0.7179
INFO:root:08:08:47 [Epoch 1 Batch 3540/11375] loss=0.2693, lr=0.0000125, metrics:accuracy:0.7906,f1:0.7181
INFO:root:08:08:48 [Epoch 1 Batch 3550/11375] loss=0.3536, lr=0.0000125, metrics:accuracy:0.7907,f1:0.7181
INFO:root:08:08:50 [Epoch 1 Batch 3560/11375] loss=0.3195, lr=0.0000125, metrics:accuracy:0.7909,f1:0.7182
INFO:root:08:08:51 [Epoch 1 Batch 3570/11375] loss=0.3041, lr=0.0000126, metrics:accuracy:0.7911,f1:0.7185
INFO:root:08:08:52 [Epoch 1 Batch 3580/11375] loss=0.2975, lr=0.0000126, metrics:accuracy:0.7913,f1:0.7189
INFO:root:08:08:53 [Epoch 1 Batch 3590/11375] loss=0.3813, lr=0.0000126, metrics:accuracy:0.7914,f1:0.7192
INFO:root:08:08:54 [Epoch 1 Batch 3600/11375] loss=0.4019, lr=0.0000127, metrics:accuracy:0.7914,f1:0.7192
INFO:root:08:08:55 [Epoch 1 Batch 3610/11375] loss=0.3189, lr=0.0000127, metrics:accuracy:0.7916,f1:0.7196
INFO:root:08:08:57 [Epoch 1 Batch 3620/11375] loss=0.3840, lr=0.0000127, metrics:accuracy:0.7917,f1:0.7201
INFO:root:08:08:58 [Epoch 1 Batch 3630/11375] loss=0.3527, lr=0.0000128, metrics:accuracy:0.7919,f1:0.7204
INFO:root:08:08:59 [Epoch 1 Batch 3640/11375] loss=0.4450, lr=0.0000128, metrics:accuracy:0.7919,f1:0.7206
INFO:root:08:09:00 [Epoch 1 Batch 3650/11375] loss=0.4531, lr=0.0000128, metrics:accuracy:0.7919,f1:0.7208
INFO:root:08:09:01 [Epoch 1 Batch 3660/11375] loss=0.3898, lr=0.0000129, metrics:accuracy:0.7919,f1:0.7209
INFO:root:08:09:02 [Epoch 1 Batch 3670/11375] loss=0.3072, lr=0.0000129, metrics:accuracy:0.7921,f1:0.7212
INFO:root:08:09:03 [Epoch 1 Batch 3680/11375] loss=0.4052, lr=0.0000129, metrics:accuracy:0.7921,f1:0.7214
INFO:root:08:09:05 [Epoch 1 Batch 3690/11375] loss=0.3427, lr=0.0000130, metrics:accuracy:0.7923,f1:0.7216
INFO:root:08:09:06 [Epoch 1 Batch 3700/11375] loss=0.3605, lr=0.0000130, metrics:accuracy:0.7924,f1:0.7218
INFO:root:08:09:07 [Epoch 1 Batch 3710/11375] loss=0.3076, lr=0.0000130, metrics:accuracy:0.7926,f1:0.7222
INFO:root:08:09:08 [Epoch 1 Batch 3720/11375] loss=0.4319, lr=0.0000131, metrics:accuracy:0.7926,f1:0.7225
INFO:root:08:09:09 [Epoch 1 Batch 3730/11375] loss=0.3120, lr=0.0000131, metrics:accuracy:0.7928,f1:0.7228
INFO:root:08:09:10 [Epoch 1 Batch 3740/11375] loss=0.2974, lr=0.0000132, metrics:accuracy:0.7931,f1:0.7230
INFO:root:08:09:12 [Epoch 1 Batch 3750/11375] loss=0.3234, lr=0.0000132, metrics:accuracy:0.7932,f1:0.7234
INFO:root:08:09:13 [Epoch 1 Batch 3760/11375] loss=0.3420, lr=0.0000132, metrics:accuracy:0.7934,f1:0.7236
INFO:root:08:09:14 [Epoch 1 Batch 3770/11375] loss=0.3051, lr=0.0000133, metrics:accuracy:0.7936,f1:0.7238
INFO:root:08:09:15 [Epoch 1 Batch 3780/11375] loss=0.4233, lr=0.0000133, metrics:accuracy:0.7937,f1:0.7239
INFO:root:08:09:16 [Epoch 1 Batch 3790/11375] loss=0.2872, lr=0.0000133, metrics:accuracy:0.7938,f1:0.7240
INFO:root:08:09:18 [Epoch 1 Batch 3800/11375] loss=0.3122, lr=0.0000134, metrics:accuracy:0.7940,f1:0.7241
INFO:root:08:09:19 [Epoch 1 Batch 3810/11375] loss=0.4258, lr=0.0000134, metrics:accuracy:0.7941,f1:0.7242
INFO:root:08:09:20 [Epoch 1 Batch 3820/11375] loss=0.3403, lr=0.0000134, metrics:accuracy:0.7942,f1:0.7243
INFO:root:08:09:21 [Epoch 1 Batch 3830/11375] loss=0.3437, lr=0.0000135, metrics:accuracy:0.7943,f1:0.7246
INFO:root:08:09:22 [Epoch 1 Batch 3840/11375] loss=0.4159, lr=0.0000135, metrics:accuracy:0.7943,f1:0.7248
INFO:root:08:09:24 [Epoch 1 Batch 3850/11375] loss=0.2935, lr=0.0000135, metrics:accuracy:0.7945,f1:0.7250
INFO:root:08:09:25 [Epoch 1 Batch 3860/11375] loss=0.3619, lr=0.0000136, metrics:accuracy:0.7946,f1:0.7251
INFO:root:08:09:26 [Epoch 1 Batch 3870/11375] loss=0.2778, lr=0.0000136, metrics:accuracy:0.7948,f1:0.7254
INFO:root:08:09:27 [Epoch 1 Batch 3880/11375] loss=0.3015, lr=0.0000136, metrics:accuracy:0.7950,f1:0.7255
INFO:root:08:09:28 [Epoch 1 Batch 3890/11375] loss=0.3683, lr=0.0000137, metrics:accuracy:0.7951,f1:0.7256
INFO:root:08:09:30 [Epoch 1 Batch 3900/11375] loss=0.3333, lr=0.0000137, metrics:accuracy:0.7952,f1:0.7258
INFO:root:08:09:31 [Epoch 1 Batch 3910/11375] loss=0.4104, lr=0.0000138, metrics:accuracy:0.7952,f1:0.7259
INFO:root:08:09:32 [Epoch 1 Batch 3920/11375] loss=0.3663, lr=0.0000138, metrics:accuracy:0.7953,f1:0.7260
INFO:root:08:09:33 [Epoch 1 Batch 3930/11375] loss=0.3505, lr=0.0000138, metrics:accuracy:0.7954,f1:0.7261
INFO:root:08:09:34 [Epoch 1 Batch 3940/11375] loss=0.2857, lr=0.0000139, metrics:accuracy:0.7956,f1:0.7262
INFO:root:08:09:36 [Epoch 1 Batch 3950/11375] loss=0.3524, lr=0.0000139, metrics:accuracy:0.7957,f1:0.7263
INFO:root:08:09:37 [Epoch 1 Batch 3960/11375] loss=0.2981, lr=0.0000139, metrics:accuracy:0.7958,f1:0.7265
INFO:root:08:09:38 [Epoch 1 Batch 3970/11375] loss=0.3461, lr=0.0000140, metrics:accuracy:0.7960,f1:0.7267
INFO:root:08:09:39 [Epoch 1 Batch 3980/11375] loss=0.3420, lr=0.0000140, metrics:accuracy:0.7961,f1:0.7267
INFO:root:08:09:40 [Epoch 1 Batch 3990/11375] loss=0.3321, lr=0.0000140, metrics:accuracy:0.7962,f1:0.7268
INFO:root:08:09:42 [Epoch 1 Batch 4000/11375] loss=0.3527, lr=0.0000141, metrics:accuracy:0.7963,f1:0.7270
INFO:root:08:09:43 [Epoch 1 Batch 4010/11375] loss=0.3314, lr=0.0000141, metrics:accuracy:0.7964,f1:0.7272
INFO:root:08:09:44 [Epoch 1 Batch 4020/11375] loss=0.3378, lr=0.0000141, metrics:accuracy:0.7966,f1:0.7273
INFO:root:08:09:45 [Epoch 1 Batch 4030/11375] loss=0.3479, lr=0.0000142, metrics:accuracy:0.7967,f1:0.7275
INFO:root:08:09:46 [Epoch 1 Batch 4040/11375] loss=0.3216, lr=0.0000142, metrics:accuracy:0.7968,f1:0.7278
INFO:root:08:09:48 [Epoch 1 Batch 4050/11375] loss=0.3842, lr=0.0000142, metrics:accuracy:0.7968,f1:0.7277
INFO:root:08:09:49 [Epoch 1 Batch 4060/11375] loss=0.2930, lr=0.0000143, metrics:accuracy:0.7970,f1:0.7279
INFO:root:08:09:50 [Epoch 1 Batch 4070/11375] loss=0.2303, lr=0.0000143, metrics:accuracy:0.7973,f1:0.7281
INFO:root:08:09:51 [Epoch 1 Batch 4080/11375] loss=0.3996, lr=0.0000144, metrics:accuracy:0.7974,f1:0.7283
INFO:root:08:09:53 [Epoch 1 Batch 4090/11375] loss=0.3878, lr=0.0000144, metrics:accuracy:0.7974,f1:0.7283
INFO:root:08:09:54 [Epoch 1 Batch 4100/11375] loss=0.2473, lr=0.0000144, metrics:accuracy:0.7976,f1:0.7284
INFO:root:08:09:55 [Epoch 1 Batch 4110/11375] loss=0.3138, lr=0.0000145, metrics:accuracy:0.7978,f1:0.7287
INFO:root:08:09:56 [Epoch 1 Batch 4120/11375] loss=0.3429, lr=0.0000145, metrics:accuracy:0.7979,f1:0.7289
INFO:root:08:09:57 [Epoch 1 Batch 4130/11375] loss=0.4068, lr=0.0000145, metrics:accuracy:0.7980,f1:0.7289
INFO:root:08:09:59 [Epoch 1 Batch 4140/11375] loss=0.2935, lr=0.0000146, metrics:accuracy:0.7981,f1:0.7289
INFO:root:08:10:00 [Epoch 1 Batch 4150/11375] loss=0.3389, lr=0.0000146, metrics:accuracy:0.7982,f1:0.7291
INFO:root:08:10:01 [Epoch 1 Batch 4160/11375] loss=0.3098, lr=0.0000146, metrics:accuracy:0.7984,f1:0.7292
INFO:root:08:10:02 [Epoch 1 Batch 4170/11375] loss=0.3496, lr=0.0000147, metrics:accuracy:0.7985,f1:0.7294
INFO:root:08:10:03 [Epoch 1 Batch 4180/11375] loss=0.2727, lr=0.0000147, metrics:accuracy:0.7987,f1:0.7296
INFO:root:08:10:05 [Epoch 1 Batch 4190/11375] loss=0.2778, lr=0.0000147, metrics:accuracy:0.7989,f1:0.7298
INFO:root:08:10:06 [Epoch 1 Batch 4200/11375] loss=0.3505, lr=0.0000148, metrics:accuracy:0.7990,f1:0.7300
INFO:root:08:10:07 [Epoch 1 Batch 4210/11375] loss=0.2937, lr=0.0000148, metrics:accuracy:0.7992,f1:0.7301
INFO:root:08:10:08 [Epoch 1 Batch 4220/11375] loss=0.3559, lr=0.0000148, metrics:accuracy:0.7993,f1:0.7303
INFO:root:08:10:10 [Epoch 1 Batch 4230/11375] loss=0.2791, lr=0.0000149, metrics:accuracy:0.7995,f1:0.7307
INFO:root:08:10:11 [Epoch 1 Batch 4240/11375] loss=0.3439, lr=0.0000149, metrics:accuracy:0.7996,f1:0.7308
INFO:root:08:10:12 [Epoch 1 Batch 4250/11375] loss=0.3694, lr=0.0000149, metrics:accuracy:0.7997,f1:0.7309
INFO:root:08:10:13 [Epoch 1 Batch 4260/11375] loss=0.3715, lr=0.0000150, metrics:accuracy:0.7997,f1:0.7311
INFO:root:08:10:14 [Epoch 1 Batch 4270/11375] loss=0.4169, lr=0.0000150, metrics:accuracy:0.7998,f1:0.7314
INFO:root:08:10:16 [Epoch 1 Batch 4280/11375] loss=0.3648, lr=0.0000151, metrics:accuracy:0.7999,f1:0.7315
INFO:root:08:10:17 [Epoch 1 Batch 4290/11375] loss=0.3324, lr=0.0000151, metrics:accuracy:0.8000,f1:0.7317
INFO:root:08:10:18 [Epoch 1 Batch 4300/11375] loss=0.3083, lr=0.0000151, metrics:accuracy:0.8002,f1:0.7319
INFO:root:08:10:19 [Epoch 1 Batch 4310/11375] loss=0.3617, lr=0.0000152, metrics:accuracy:0.8002,f1:0.7321
INFO:root:08:10:20 [Epoch 1 Batch 4320/11375] loss=0.2678, lr=0.0000152, metrics:accuracy:0.8004,f1:0.7322
INFO:root:08:10:22 [Epoch 1 Batch 4330/11375] loss=0.3181, lr=0.0000152, metrics:accuracy:0.8006,f1:0.7325
INFO:root:08:10:23 [Epoch 1 Batch 4340/11375] loss=0.3318, lr=0.0000153, metrics:accuracy:0.8007,f1:0.7327
INFO:root:08:10:24 [Epoch 1 Batch 4350/11375] loss=0.2514, lr=0.0000153, metrics:accuracy:0.8010,f1:0.7328
INFO:root:08:10:25 [Epoch 1 Batch 4360/11375] loss=0.3108, lr=0.0000153, metrics:accuracy:0.8011,f1:0.7331
INFO:root:08:10:27 [Epoch 1 Batch 4370/11375] loss=0.2895, lr=0.0000154, metrics:accuracy:0.8013,f1:0.7333
INFO:root:08:10:28 [Epoch 1 Batch 4380/11375] loss=0.2926, lr=0.0000154, metrics:accuracy:0.8015,f1:0.7335
INFO:root:08:10:29 [Epoch 1 Batch 4390/11375] loss=0.3138, lr=0.0000154, metrics:accuracy:0.8016,f1:0.7337
INFO:root:08:10:30 [Epoch 1 Batch 4400/11375] loss=0.2850, lr=0.0000155, metrics:accuracy:0.8018,f1:0.7339
INFO:root:08:10:31 [Epoch 1 Batch 4410/11375] loss=0.2990, lr=0.0000155, metrics:accuracy:0.8019,f1:0.7340
INFO:root:08:10:33 [Epoch 1 Batch 4420/11375] loss=0.3365, lr=0.0000155, metrics:accuracy:0.8020,f1:0.7343
INFO:root:08:10:34 [Epoch 1 Batch 4430/11375] loss=0.3296, lr=0.0000156, metrics:accuracy:0.8021,f1:0.7345
INFO:root:08:10:35 [Epoch 1 Batch 4440/11375] loss=0.3075, lr=0.0000156, metrics:accuracy:0.8022,f1:0.7347
INFO:root:08:10:36 [Epoch 1 Batch 4450/11375] loss=0.4137, lr=0.0000157, metrics:accuracy:0.8022,f1:0.7348
INFO:root:08:10:37 [Epoch 1 Batch 4460/11375] loss=0.3045, lr=0.0000157, metrics:accuracy:0.8024,f1:0.7350
INFO:root:08:10:39 [Epoch 1 Batch 4470/11375] loss=0.3371, lr=0.0000157, metrics:accuracy:0.8025,f1:0.7352
INFO:root:08:10:40 [Epoch 1 Batch 4480/11375] loss=0.3508, lr=0.0000158, metrics:accuracy:0.8026,f1:0.7353
INFO:root:08:10:41 [Epoch 1 Batch 4490/11375] loss=0.3234, lr=0.0000158, metrics:accuracy:0.8028,f1:0.7356
INFO:root:08:10:42 [Epoch 1 Batch 4500/11375] loss=0.4285, lr=0.0000158, metrics:accuracy:0.8028,f1:0.7357
INFO:root:08:10:43 [Epoch 1 Batch 4510/11375] loss=0.2687, lr=0.0000159, metrics:accuracy:0.8030,f1:0.7361
INFO:root:08:10:44 [Epoch 1 Batch 4520/11375] loss=0.3572, lr=0.0000159, metrics:accuracy:0.8030,f1:0.7360
INFO:root:08:10:45 [Epoch 1 Batch 4530/11375] loss=0.3070, lr=0.0000159, metrics:accuracy:0.8032,f1:0.7362
INFO:root:08:10:47 [Epoch 1 Batch 4540/11375] loss=0.3590, lr=0.0000160, metrics:accuracy:0.8032,f1:0.7364
INFO:root:08:10:48 [Epoch 1 Batch 4550/11375] loss=0.3364, lr=0.0000160, metrics:accuracy:0.8033,f1:0.7367
INFO:root:08:10:49 [Epoch 1 Batch 4560/11375] loss=0.3391, lr=0.0000160, metrics:accuracy:0.8035,f1:0.7368
INFO:root:08:10:50 [Epoch 1 Batch 4570/11375] loss=0.3568, lr=0.0000161, metrics:accuracy:0.8036,f1:0.7368
INFO:root:08:10:51 [Epoch 1 Batch 4580/11375] loss=0.3831, lr=0.0000161, metrics:accuracy:0.8036,f1:0.7369
INFO:root:08:10:52 [Epoch 1 Batch 4590/11375] loss=0.3544, lr=0.0000161, metrics:accuracy:0.8037,f1:0.7371
INFO:root:08:10:54 [Epoch 1 Batch 4600/11375] loss=0.3464, lr=0.0000162, metrics:accuracy:0.8038,f1:0.7372
INFO:root:08:10:55 [Epoch 1 Batch 4610/11375] loss=0.3858, lr=0.0000162, metrics:accuracy:0.8038,f1:0.7373
INFO:root:08:10:56 [Epoch 1 Batch 4620/11375] loss=0.3497, lr=0.0000162, metrics:accuracy:0.8039,f1:0.7374
INFO:root:08:10:57 [Epoch 1 Batch 4630/11375] loss=0.3416, lr=0.0000163, metrics:accuracy:0.8040,f1:0.7375
INFO:root:08:10:58 [Epoch 1 Batch 4640/11375] loss=0.3811, lr=0.0000163, metrics:accuracy:0.8041,f1:0.7376
INFO:root:08:10:59 [Epoch 1 Batch 4650/11375] loss=0.3688, lr=0.0000164, metrics:accuracy:0.8041,f1:0.7376
INFO:root:08:11:01 [Epoch 1 Batch 4660/11375] loss=0.4143, lr=0.0000164, metrics:accuracy:0.8041,f1:0.7378
INFO:root:08:11:02 [Epoch 1 Batch 4670/11375] loss=0.3112, lr=0.0000164, metrics:accuracy:0.8042,f1:0.7380
INFO:root:08:11:03 [Epoch 1 Batch 4680/11375] loss=0.2922, lr=0.0000165, metrics:accuracy:0.8044,f1:0.7382
INFO:root:08:11:04 [Epoch 1 Batch 4690/11375] loss=0.2962, lr=0.0000165, metrics:accuracy:0.8045,f1:0.7383
INFO:root:08:11:05 [Epoch 1 Batch 4700/11375] loss=0.2571, lr=0.0000165, metrics:accuracy:0.8047,f1:0.7385
INFO:root:08:11:07 [Epoch 1 Batch 4710/11375] loss=0.3202, lr=0.0000166, metrics:accuracy:0.8048,f1:0.7387
INFO:root:08:11:08 [Epoch 1 Batch 4720/11375] loss=0.3408, lr=0.0000166, metrics:accuracy:0.8049,f1:0.7388
INFO:root:08:11:09 [Epoch 1 Batch 4730/11375] loss=0.3052, lr=0.0000166, metrics:accuracy:0.8050,f1:0.7390
INFO:root:08:11:10 [Epoch 1 Batch 4740/11375] loss=0.3150, lr=0.0000167, metrics:accuracy:0.8052,f1:0.7394
INFO:root:08:11:11 [Epoch 1 Batch 4750/11375] loss=0.3537, lr=0.0000167, metrics:accuracy:0.8053,f1:0.7396
INFO:root:08:11:12 [Epoch 1 Batch 4760/11375] loss=0.3995, lr=0.0000167, metrics:accuracy:0.8053,f1:0.7395
INFO:root:08:11:13 [Epoch 1 Batch 4770/11375] loss=0.3149, lr=0.0000168, metrics:accuracy:0.8054,f1:0.7397
INFO:root:08:11:15 [Epoch 1 Batch 4780/11375] loss=0.3352, lr=0.0000168, metrics:accuracy:0.8055,f1:0.7397
INFO:root:08:11:16 [Epoch 1 Batch 4790/11375] loss=0.3086, lr=0.0000168, metrics:accuracy:0.8056,f1:0.7399
INFO:root:08:11:17 [Epoch 1 Batch 4800/11375] loss=0.3051, lr=0.0000169, metrics:accuracy:0.8057,f1:0.7400
INFO:root:08:11:18 [Epoch 1 Batch 4810/11375] loss=0.3447, lr=0.0000169, metrics:accuracy:0.8058,f1:0.7401
INFO:root:08:11:19 [Epoch 1 Batch 4820/11375] loss=0.2911, lr=0.0000170, metrics:accuracy:0.8059,f1:0.7402
INFO:root:08:11:21 [Epoch 1 Batch 4830/11375] loss=0.2862, lr=0.0000170, metrics:accuracy:0.8061,f1:0.7405
INFO:root:08:11:22 [Epoch 1 Batch 4840/11375] loss=0.2895, lr=0.0000170, metrics:accuracy:0.8062,f1:0.7406
INFO:root:08:11:23 [Epoch 1 Batch 4850/11375] loss=0.3284, lr=0.0000171, metrics:accuracy:0.8063,f1:0.7408
INFO:root:08:11:24 [Epoch 1 Batch 4860/11375] loss=0.4167, lr=0.0000171, metrics:accuracy:0.8063,f1:0.7408
INFO:root:08:11:25 [Epoch 1 Batch 4870/11375] loss=0.3775, lr=0.0000171, metrics:accuracy:0.8063,f1:0.7408
INFO:root:08:11:27 [Epoch 1 Batch 4880/11375] loss=0.3512, lr=0.0000172, metrics:accuracy:0.8064,f1:0.7409
INFO:root:08:11:28 [Epoch 1 Batch 4890/11375] loss=0.2385, lr=0.0000172, metrics:accuracy:0.8066,f1:0.7411
INFO:root:08:11:29 [Epoch 1 Batch 4900/11375] loss=0.2915, lr=0.0000172, metrics:accuracy:0.8067,f1:0.7412
INFO:root:08:11:30 [Epoch 1 Batch 4910/11375] loss=0.3833, lr=0.0000173, metrics:accuracy:0.8068,f1:0.7413
INFO:root:08:11:31 [Epoch 1 Batch 4920/11375] loss=0.3522, lr=0.0000173, metrics:accuracy:0.8068,f1:0.7414
INFO:root:08:11:33 [Epoch 1 Batch 4930/11375] loss=0.3512, lr=0.0000173, metrics:accuracy:0.8069,f1:0.7416
INFO:root:08:11:34 [Epoch 1 Batch 4940/11375] loss=0.3162, lr=0.0000174, metrics:accuracy:0.8070,f1:0.7418
INFO:root:08:11:35 [Epoch 1 Batch 4950/11375] loss=0.4208, lr=0.0000174, metrics:accuracy:0.8070,f1:0.7418
INFO:root:08:11:36 [Epoch 1 Batch 4960/11375] loss=0.3497, lr=0.0000174, metrics:accuracy:0.8070,f1:0.7419
INFO:root:08:11:37 [Epoch 1 Batch 4970/11375] loss=0.3043, lr=0.0000175, metrics:accuracy:0.8071,f1:0.7420
INFO:root:08:11:39 [Epoch 1 Batch 4980/11375] loss=0.3178, lr=0.0000175, metrics:accuracy:0.8072,f1:0.7420
INFO:root:08:11:40 [Epoch 1 Batch 4990/11375] loss=0.3542, lr=0.0000176, metrics:accuracy:0.8072,f1:0.7422
INFO:root:08:11:41 [Epoch 1 Batch 5000/11375] loss=0.3357, lr=0.0000176, metrics:accuracy:0.8073,f1:0.7423
INFO:root:08:11:42 [Epoch 1 Batch 5010/11375] loss=0.3392, lr=0.0000176, metrics:accuracy:0.8074,f1:0.7424
INFO:root:08:11:43 [Epoch 1 Batch 5020/11375] loss=0.3822, lr=0.0000177, metrics:accuracy:0.8074,f1:0.7426
INFO:root:08:11:44 [Epoch 1 Batch 5030/11375] loss=0.3324, lr=0.0000177, metrics:accuracy:0.8075,f1:0.7426
INFO:root:08:11:46 [Epoch 1 Batch 5040/11375] loss=0.2815, lr=0.0000177, metrics:accuracy:0.8076,f1:0.7430
INFO:root:08:11:47 [Epoch 1 Batch 5050/11375] loss=0.3157, lr=0.0000178, metrics:accuracy:0.8077,f1:0.7430
INFO:root:08:11:48 [Epoch 1 Batch 5060/11375] loss=0.4103, lr=0.0000178, metrics:accuracy:0.8077,f1:0.7431
INFO:root:08:11:49 [Epoch 1 Batch 5070/11375] loss=0.3492, lr=0.0000178, metrics:accuracy:0.8078,f1:0.7433
INFO:root:08:11:50 [Epoch 1 Batch 5080/11375] loss=0.2888, lr=0.0000179, metrics:accuracy:0.8080,f1:0.7435
INFO:root:08:11:51 [Epoch 1 Batch 5090/11375] loss=0.3455, lr=0.0000179, metrics:accuracy:0.8081,f1:0.7436
INFO:root:08:11:53 [Epoch 1 Batch 5100/11375] loss=0.2754, lr=0.0000179, metrics:accuracy:0.8082,f1:0.7438
INFO:root:08:11:54 [Epoch 1 Batch 5110/11375] loss=0.3495, lr=0.0000180, metrics:accuracy:0.8083,f1:0.7439
INFO:root:08:11:55 [Epoch 1 Batch 5120/11375] loss=0.3797, lr=0.0000180, metrics:accuracy:0.8083,f1:0.7440
INFO:root:08:11:56 [Epoch 1 Batch 5130/11375] loss=0.2697, lr=0.0000180, metrics:accuracy:0.8085,f1:0.7441
INFO:root:08:11:57 [Epoch 1 Batch 5140/11375] loss=0.3639, lr=0.0000181, metrics:accuracy:0.8085,f1:0.7443
INFO:root:08:11:59 [Epoch 1 Batch 5150/11375] loss=0.3997, lr=0.0000181, metrics:accuracy:0.8086,f1:0.7444
INFO:root:08:12:00 [Epoch 1 Batch 5160/11375] loss=0.2642, lr=0.0000181, metrics:accuracy:0.8087,f1:0.7446
INFO:root:08:12:01 [Epoch 1 Batch 5170/11375] loss=0.2640, lr=0.0000182, metrics:accuracy:0.8089,f1:0.7448
INFO:root:08:12:02 [Epoch 1 Batch 5180/11375] loss=0.3729, lr=0.0000182, metrics:accuracy:0.8089,f1:0.7448
INFO:root:08:12:04 [Epoch 1 Batch 5190/11375] loss=0.2488, lr=0.0000183, metrics:accuracy:0.8091,f1:0.7450
INFO:root:08:12:05 [Epoch 1 Batch 5200/11375] loss=0.2949, lr=0.0000183, metrics:accuracy:0.8092,f1:0.7450
INFO:root:08:12:06 [Epoch 1 Batch 5210/11375] loss=0.3319, lr=0.0000183, metrics:accuracy:0.8093,f1:0.7452
INFO:root:08:12:07 [Epoch 1 Batch 5220/11375] loss=0.2832, lr=0.0000184, metrics:accuracy:0.8094,f1:0.7453
INFO:root:08:12:08 [Epoch 1 Batch 5230/11375] loss=0.3495, lr=0.0000184, metrics:accuracy:0.8095,f1:0.7456
INFO:root:08:12:09 [Epoch 1 Batch 5240/11375] loss=0.3222, lr=0.0000184, metrics:accuracy:0.8095,f1:0.7457
INFO:root:08:12:11 [Epoch 1 Batch 5250/11375] loss=0.2261, lr=0.0000185, metrics:accuracy:0.8097,f1:0.7458
INFO:root:08:12:12 [Epoch 1 Batch 5260/11375] loss=0.3304, lr=0.0000185, metrics:accuracy:0.8098,f1:0.7459
INFO:root:08:12:13 [Epoch 1 Batch 5270/11375] loss=0.3060, lr=0.0000185, metrics:accuracy:0.8099,f1:0.7461
INFO:root:08:12:14 [Epoch 1 Batch 5280/11375] loss=0.3656, lr=0.0000186, metrics:accuracy:0.8099,f1:0.7462
INFO:root:08:12:15 [Epoch 1 Batch 5290/11375] loss=0.3117, lr=0.0000186, metrics:accuracy:0.8100,f1:0.7463
INFO:root:08:12:17 [Epoch 1 Batch 5300/11375] loss=0.3210, lr=0.0000186, metrics:accuracy:0.8101,f1:0.7465
INFO:root:08:12:18 [Epoch 1 Batch 5310/11375] loss=0.3107, lr=0.0000187, metrics:accuracy:0.8102,f1:0.7467
INFO:root:08:12:19 [Epoch 1 Batch 5320/11375] loss=0.2702, lr=0.0000187, metrics:accuracy:0.8104,f1:0.7468
INFO:root:08:12:20 [Epoch 1 Batch 5330/11375] loss=0.3136, lr=0.0000187, metrics:accuracy:0.8104,f1:0.7469
INFO:root:08:12:22 [Epoch 1 Batch 5340/11375] loss=0.2851, lr=0.0000188, metrics:accuracy:0.8106,f1:0.7470
INFO:root:08:12:23 [Epoch 1 Batch 5350/11375] loss=0.3378, lr=0.0000188, metrics:accuracy:0.8106,f1:0.7471
INFO:root:08:12:24 [Epoch 1 Batch 5360/11375] loss=0.3446, lr=0.0000189, metrics:accuracy:0.8107,f1:0.7472
INFO:root:08:12:25 [Epoch 1 Batch 5370/11375] loss=0.2653, lr=0.0000189, metrics:accuracy:0.8108,f1:0.7473
INFO:root:08:12:27 [Epoch 1 Batch 5380/11375] loss=0.3083, lr=0.0000189, metrics:accuracy:0.8109,f1:0.7474
INFO:root:08:12:28 [Epoch 1 Batch 5390/11375] loss=0.1988, lr=0.0000190, metrics:accuracy:0.8111,f1:0.7476
INFO:root:08:12:29 [Epoch 1 Batch 5400/11375] loss=0.4037, lr=0.0000190, metrics:accuracy:0.8112,f1:0.7476
INFO:root:08:12:30 [Epoch 1 Batch 5410/11375] loss=0.4000, lr=0.0000190, metrics:accuracy:0.8112,f1:0.7476
INFO:root:08:12:31 [Epoch 1 Batch 5420/11375] loss=0.3628, lr=0.0000191, metrics:accuracy:0.8111,f1:0.7475
INFO:root:08:12:33 [Epoch 1 Batch 5430/11375] loss=0.3059, lr=0.0000191, metrics:accuracy:0.8113,f1:0.7478
INFO:root:08:12:34 [Epoch 1 Batch 5440/11375] loss=0.3940, lr=0.0000191, metrics:accuracy:0.8113,f1:0.7478
INFO:root:08:12:35 [Epoch 1 Batch 5450/11375] loss=0.2880, lr=0.0000192, metrics:accuracy:0.8114,f1:0.7479
INFO:root:08:12:36 [Epoch 1 Batch 5460/11375] loss=0.3058, lr=0.0000192, metrics:accuracy:0.8115,f1:0.7481
INFO:root:08:12:38 [Epoch 1 Batch 5470/11375] loss=0.2368, lr=0.0000192, metrics:accuracy:0.8116,f1:0.7483
INFO:root:08:12:39 [Epoch 1 Batch 5480/11375] loss=0.4071, lr=0.0000193, metrics:accuracy:0.8117,f1:0.7483
INFO:root:08:12:40 [Epoch 1 Batch 5490/11375] loss=0.2763, lr=0.0000193, metrics:accuracy:0.8118,f1:0.7484
INFO:root:08:12:41 [Epoch 1 Batch 5500/11375] loss=0.3417, lr=0.0000193, metrics:accuracy:0.8118,f1:0.7485
INFO:root:08:12:42 [Epoch 1 Batch 5510/11375] loss=0.3783, lr=0.0000194, metrics:accuracy:0.8119,f1:0.7486
INFO:root:08:12:43 [Epoch 1 Batch 5520/11375] loss=0.4051, lr=0.0000194, metrics:accuracy:0.8119,f1:0.7485
INFO:root:08:12:44 [Epoch 1 Batch 5530/11375] loss=0.3583, lr=0.0000195, metrics:accuracy:0.8120,f1:0.7487
INFO:root:08:12:46 [Epoch 1 Batch 5540/11375] loss=0.3525, lr=0.0000195, metrics:accuracy:0.8120,f1:0.7487
INFO:root:08:12:47 [Epoch 1 Batch 5550/11375] loss=0.2620, lr=0.0000195, metrics:accuracy:0.8121,f1:0.7489
INFO:root:08:12:48 [Epoch 1 Batch 5560/11375] loss=0.3264, lr=0.0000196, metrics:accuracy:0.8122,f1:0.7490
INFO:root:08:12:49 [Epoch 1 Batch 5570/11375] loss=0.3011, lr=0.0000196, metrics:accuracy:0.8123,f1:0.7492
INFO:root:08:12:51 [Epoch 1 Batch 5580/11375] loss=0.2001, lr=0.0000196, metrics:accuracy:0.8125,f1:0.7494
INFO:root:08:12:52 [Epoch 1 Batch 5590/11375] loss=0.3367, lr=0.0000197, metrics:accuracy:0.8126,f1:0.7496
INFO:root:08:12:53 [Epoch 1 Batch 5600/11375] loss=0.2842, lr=0.0000197, metrics:accuracy:0.8127,f1:0.7497
INFO:root:08:12:54 [Epoch 1 Batch 5610/11375] loss=0.3209, lr=0.0000197, metrics:accuracy:0.8128,f1:0.7498
INFO:root:08:12:55 [Epoch 1 Batch 5620/11375] loss=0.2936, lr=0.0000198, metrics:accuracy:0.8129,f1:0.7500
INFO:root:08:12:56 [Epoch 1 Batch 5630/11375] loss=0.3701, lr=0.0000198, metrics:accuracy:0.8130,f1:0.7502
INFO:root:08:12:57 [Epoch 1 Batch 5640/11375] loss=0.2611, lr=0.0000198, metrics:accuracy:0.8131,f1:0.7503
INFO:root:08:12:59 [Epoch 1 Batch 5650/11375] loss=0.3121, lr=0.0000199, metrics:accuracy:0.8132,f1:0.7504
INFO:root:08:13:00 [Epoch 1 Batch 5660/11375] loss=0.2943, lr=0.0000199, metrics:accuracy:0.8133,f1:0.7505
INFO:root:08:13:01 [Epoch 1 Batch 5670/11375] loss=0.3030, lr=0.0000199, metrics:accuracy:0.8134,f1:0.7506
INFO:root:08:13:02 [Epoch 1 Batch 5680/11375] loss=0.3171, lr=0.0000200, metrics:accuracy:0.8135,f1:0.7507
INFO:root:08:13:03 [Epoch 1 Batch 5690/11375] loss=0.3348, lr=0.0000200, metrics:accuracy:0.8135,f1:0.7508
INFO:root:08:13:05 [Epoch 1 Batch 5700/11375] loss=0.3251, lr=0.0000200, metrics:accuracy:0.8136,f1:0.7509
INFO:root:08:13:06 [Epoch 1 Batch 5710/11375] loss=0.3197, lr=0.0000200, metrics:accuracy:0.8136,f1:0.7510
INFO:root:08:13:07 [Epoch 1 Batch 5720/11375] loss=0.3414, lr=0.0000200, metrics:accuracy:0.8137,f1:0.7511
INFO:root:08:13:09 [Epoch 1 Batch 5730/11375] loss=0.3264, lr=0.0000200, metrics:accuracy:0.8138,f1:0.7512
INFO:root:08:13:10 [Epoch 1 Batch 5740/11375] loss=0.2999, lr=0.0000200, metrics:accuracy:0.8139,f1:0.7513
INFO:root:08:13:11 [Epoch 1 Batch 5750/11375] loss=0.3549, lr=0.0000200, metrics:accuracy:0.8140,f1:0.7514
INFO:root:08:13:12 [Epoch 1 Batch 5760/11375] loss=0.3339, lr=0.0000200, metrics:accuracy:0.8140,f1:0.7514
INFO:root:08:13:13 [Epoch 1 Batch 5770/11375] loss=0.3948, lr=0.0000200, metrics:accuracy:0.8140,f1:0.7515
INFO:root:08:13:14 [Epoch 1 Batch 5780/11375] loss=0.2786, lr=0.0000200, metrics:accuracy:0.8141,f1:0.7516
INFO:root:08:13:16 [Epoch 1 Batch 5790/11375] loss=0.3950, lr=0.0000200, metrics:accuracy:0.8141,f1:0.7517
INFO:root:08:13:17 [Epoch 1 Batch 5800/11375] loss=0.3315, lr=0.0000200, metrics:accuracy:0.8141,f1:0.7517
INFO:root:08:13:18 [Epoch 1 Batch 5810/11375] loss=0.2669, lr=0.0000200, metrics:accuracy:0.8143,f1:0.7518
INFO:root:08:13:19 [Epoch 1 Batch 5820/11375] loss=0.2745, lr=0.0000199, metrics:accuracy:0.8144,f1:0.7520
INFO:root:08:13:21 [Epoch 1 Batch 5830/11375] loss=0.3573, lr=0.0000199, metrics:accuracy:0.8145,f1:0.7521
INFO:root:08:13:22 [Epoch 1 Batch 5840/11375] loss=0.2881, lr=0.0000199, metrics:accuracy:0.8146,f1:0.7522
INFO:root:08:13:23 [Epoch 1 Batch 5850/11375] loss=0.2935, lr=0.0000199, metrics:accuracy:0.8147,f1:0.7523
INFO:root:08:13:24 [Epoch 1 Batch 5860/11375] loss=0.3325, lr=0.0000199, metrics:accuracy:0.8148,f1:0.7524
INFO:root:08:13:25 [Epoch 1 Batch 5870/11375] loss=0.3005, lr=0.0000199, metrics:accuracy:0.8148,f1:0.7524
INFO:root:08:13:27 [Epoch 1 Batch 5880/11375] loss=0.4029, lr=0.0000199, metrics:accuracy:0.8148,f1:0.7524
INFO:root:08:13:28 [Epoch 1 Batch 5890/11375] loss=0.3132, lr=0.0000199, metrics:accuracy:0.8149,f1:0.7525
INFO:root:08:13:29 [Epoch 1 Batch 5900/11375] loss=0.3495, lr=0.0000199, metrics:accuracy:0.8150,f1:0.7526
INFO:root:08:13:30 [Epoch 1 Batch 5910/11375] loss=0.2571, lr=0.0000199, metrics:accuracy:0.8151,f1:0.7527
INFO:root:08:13:32 [Epoch 1 Batch 5920/11375] loss=0.3019, lr=0.0000199, metrics:accuracy:0.8151,f1:0.7528
INFO:root:08:13:33 [Epoch 1 Batch 5930/11375] loss=0.3204, lr=0.0000199, metrics:accuracy:0.8152,f1:0.7529
INFO:root:08:13:34 [Epoch 1 Batch 5940/11375] loss=0.4186, lr=0.0000199, metrics:accuracy:0.8152,f1:0.7530
INFO:root:08:13:35 [Epoch 1 Batch 5950/11375] loss=0.3476, lr=0.0000199, metrics:accuracy:0.8153,f1:0.7531
INFO:root:08:13:36 [Epoch 1 Batch 5960/11375] loss=0.2719, lr=0.0000199, metrics:accuracy:0.8154,f1:0.7532
INFO:root:08:13:37 [Epoch 1 Batch 5970/11375] loss=0.3912, lr=0.0000199, metrics:accuracy:0.8154,f1:0.7533
INFO:root:08:13:39 [Epoch 1 Batch 5980/11375] loss=0.3405, lr=0.0000199, metrics:accuracy:0.8155,f1:0.7535
INFO:root:08:13:40 [Epoch 1 Batch 5990/11375] loss=0.3570, lr=0.0000199, metrics:accuracy:0.8155,f1:0.7536
INFO:root:08:13:41 [Epoch 1 Batch 6000/11375] loss=0.2969, lr=0.0000199, metrics:accuracy:0.8156,f1:0.7537
INFO:root:08:13:42 [Epoch 1 Batch 6010/11375] loss=0.2492, lr=0.0000199, metrics:accuracy:0.8158,f1:0.7538
INFO:root:08:13:43 [Epoch 1 Batch 6020/11375] loss=0.3058, lr=0.0000199, metrics:accuracy:0.8158,f1:0.7539
INFO:root:08:13:45 [Epoch 1 Batch 6030/11375] loss=0.3053, lr=0.0000199, metrics:accuracy:0.8159,f1:0.7541
INFO:root:08:13:46 [Epoch 1 Batch 6040/11375] loss=0.2803, lr=0.0000199, metrics:accuracy:0.8160,f1:0.7541
INFO:root:08:13:47 [Epoch 1 Batch 6050/11375] loss=0.3074, lr=0.0000199, metrics:accuracy:0.8161,f1:0.7542
INFO:root:08:13:48 [Epoch 1 Batch 6060/11375] loss=0.2297, lr=0.0000199, metrics:accuracy:0.8163,f1:0.7543
INFO:root:08:13:50 [Epoch 1 Batch 6070/11375] loss=0.3013, lr=0.0000198, metrics:accuracy:0.8163,f1:0.7545
INFO:root:08:13:51 [Epoch 1 Batch 6080/11375] loss=0.2890, lr=0.0000198, metrics:accuracy:0.8164,f1:0.7545
INFO:root:08:13:52 [Epoch 1 Batch 6090/11375] loss=0.3778, lr=0.0000198, metrics:accuracy:0.8164,f1:0.7547
INFO:root:08:13:53 [Epoch 1 Batch 6100/11375] loss=0.2632, lr=0.0000198, metrics:accuracy:0.8166,f1:0.7549
INFO:root:08:13:55 [Epoch 1 Batch 6110/11375] loss=0.2912, lr=0.0000198, metrics:accuracy:0.8167,f1:0.7549
INFO:root:08:13:56 [Epoch 1 Batch 6120/11375] loss=0.2637, lr=0.0000198, metrics:accuracy:0.8168,f1:0.7550
INFO:root:08:13:57 [Epoch 1 Batch 6130/11375] loss=0.3537, lr=0.0000198, metrics:accuracy:0.8168,f1:0.7551
INFO:root:08:13:58 [Epoch 1 Batch 6140/11375] loss=0.3717, lr=0.0000198, metrics:accuracy:0.8168,f1:0.7552
INFO:root:08:13:59 [Epoch 1 Batch 6150/11375] loss=0.3427, lr=0.0000198, metrics:accuracy:0.8169,f1:0.7553
INFO:root:08:14:00 [Epoch 1 Batch 6160/11375] loss=0.3101, lr=0.0000198, metrics:accuracy:0.8170,f1:0.7554
INFO:root:08:14:02 [Epoch 1 Batch 6170/11375] loss=0.2822, lr=0.0000198, metrics:accuracy:0.8171,f1:0.7555
INFO:root:08:14:03 [Epoch 1 Batch 6180/11375] loss=0.2913, lr=0.0000198, metrics:accuracy:0.8172,f1:0.7556
INFO:root:08:14:04 [Epoch 1 Batch 6190/11375] loss=0.3428, lr=0.0000198, metrics:accuracy:0.8172,f1:0.7556
INFO:root:08:14:05 [Epoch 1 Batch 6200/11375] loss=0.3209, lr=0.0000198, metrics:accuracy:0.8173,f1:0.7558
INFO:root:08:14:06 [Epoch 1 Batch 6210/11375] loss=0.2603, lr=0.0000198, metrics:accuracy:0.8174,f1:0.7558
INFO:root:08:14:08 [Epoch 1 Batch 6220/11375] loss=0.3458, lr=0.0000198, metrics:accuracy:0.8175,f1:0.7560
INFO:root:08:14:09 [Epoch 1 Batch 6230/11375] loss=0.3829, lr=0.0000198, metrics:accuracy:0.8175,f1:0.7561
INFO:root:08:14:10 [Epoch 1 Batch 6240/11375] loss=0.3776, lr=0.0000198, metrics:accuracy:0.8176,f1:0.7563
INFO:root:08:14:11 [Epoch 1 Batch 6250/11375] loss=0.3446, lr=0.0000198, metrics:accuracy:0.8177,f1:0.7564
INFO:root:08:14:12 [Epoch 1 Batch 6260/11375] loss=0.2692, lr=0.0000198, metrics:accuracy:0.8178,f1:0.7565
INFO:root:08:14:13 [Epoch 1 Batch 6270/11375] loss=0.3069, lr=0.0000198, metrics:accuracy:0.8179,f1:0.7566
INFO:root:08:14:15 [Epoch 1 Batch 6280/11375] loss=0.3232, lr=0.0000198, metrics:accuracy:0.8179,f1:0.7567
INFO:root:08:14:16 [Epoch 1 Batch 6290/11375] loss=0.3749, lr=0.0000198, metrics:accuracy:0.8179,f1:0.7568
INFO:root:08:14:17 [Epoch 1 Batch 6300/11375] loss=0.3585, lr=0.0000198, metrics:accuracy:0.8180,f1:0.7568
INFO:root:08:14:18 [Epoch 1 Batch 6310/11375] loss=0.3605, lr=0.0000198, metrics:accuracy:0.8180,f1:0.7569
INFO:root:08:14:19 [Epoch 1 Batch 6320/11375] loss=0.3511, lr=0.0000198, metrics:accuracy:0.8180,f1:0.7570
INFO:root:08:14:20 [Epoch 1 Batch 6330/11375] loss=0.3397, lr=0.0000197, metrics:accuracy:0.8181,f1:0.7572
INFO:root:08:14:21 [Epoch 1 Batch 6340/11375] loss=0.3459, lr=0.0000197, metrics:accuracy:0.8181,f1:0.7572
INFO:root:08:14:23 [Epoch 1 Batch 6350/11375] loss=0.3401, lr=0.0000197, metrics:accuracy:0.8181,f1:0.7573
INFO:root:08:14:24 [Epoch 1 Batch 6360/11375] loss=0.3109, lr=0.0000197, metrics:accuracy:0.8182,f1:0.7574
INFO:root:08:14:25 [Epoch 1 Batch 6370/11375] loss=0.3194, lr=0.0000197, metrics:accuracy:0.8182,f1:0.7575
INFO:root:08:14:26 [Epoch 1 Batch 6380/11375] loss=0.3293, lr=0.0000197, metrics:accuracy:0.8183,f1:0.7576
INFO:root:08:14:27 [Epoch 1 Batch 6390/11375] loss=0.2964, lr=0.0000197, metrics:accuracy:0.8184,f1:0.7578
INFO:root:08:14:29 [Epoch 1 Batch 6400/11375] loss=0.2801, lr=0.0000197, metrics:accuracy:0.8185,f1:0.7579
INFO:root:08:14:30 [Epoch 1 Batch 6410/11375] loss=0.3686, lr=0.0000197, metrics:accuracy:0.8185,f1:0.7580
INFO:root:08:14:31 [Epoch 1 Batch 6420/11375] loss=0.3194, lr=0.0000197, metrics:accuracy:0.8186,f1:0.7581
INFO:root:08:14:32 [Epoch 1 Batch 6430/11375] loss=0.3198, lr=0.0000197, metrics:accuracy:0.8186,f1:0.7581
INFO:root:08:14:33 [Epoch 1 Batch 6440/11375] loss=0.2790, lr=0.0000197, metrics:accuracy:0.8187,f1:0.7583
INFO:root:08:14:34 [Epoch 1 Batch 6450/11375] loss=0.3293, lr=0.0000197, metrics:accuracy:0.8187,f1:0.7584
INFO:root:08:14:35 [Epoch 1 Batch 6460/11375] loss=0.2661, lr=0.0000197, metrics:accuracy:0.8189,f1:0.7586
INFO:root:08:14:37 [Epoch 1 Batch 6470/11375] loss=0.2580, lr=0.0000197, metrics:accuracy:0.8190,f1:0.7588
INFO:root:08:14:38 [Epoch 1 Batch 6480/11375] loss=0.3276, lr=0.0000197, metrics:accuracy:0.8191,f1:0.7589
INFO:root:08:14:39 [Epoch 1 Batch 6490/11375] loss=0.2345, lr=0.0000197, metrics:accuracy:0.8192,f1:0.7590
INFO:root:08:14:40 [Epoch 1 Batch 6500/11375] loss=0.3396, lr=0.0000197, metrics:accuracy:0.8192,f1:0.7591
INFO:root:08:14:41 [Epoch 1 Batch 6510/11375] loss=0.3768, lr=0.0000197, metrics:accuracy:0.8192,f1:0.7592
INFO:root:08:14:42 [Epoch 1 Batch 6520/11375] loss=0.3822, lr=0.0000197, metrics:accuracy:0.8192,f1:0.7592
INFO:root:08:14:44 [Epoch 1 Batch 6530/11375] loss=0.3696, lr=0.0000197, metrics:accuracy:0.8193,f1:0.7593
INFO:root:08:14:45 [Epoch 1 Batch 6540/11375] loss=0.2531, lr=0.0000197, metrics:accuracy:0.8194,f1:0.7594
INFO:root:08:14:46 [Epoch 1 Batch 6550/11375] loss=0.3159, lr=0.0000197, metrics:accuracy:0.8194,f1:0.7594
INFO:root:08:14:47 [Epoch 1 Batch 6560/11375] loss=0.4439, lr=0.0000197, metrics:accuracy:0.8194,f1:0.7593
INFO:root:08:14:48 [Epoch 1 Batch 6570/11375] loss=0.3242, lr=0.0000197, metrics:accuracy:0.8194,f1:0.7595
INFO:root:08:14:49 [Epoch 1 Batch 6580/11375] loss=0.3171, lr=0.0000197, metrics:accuracy:0.8195,f1:0.7596
INFO:root:08:14:51 [Epoch 1 Batch 6590/11375] loss=0.2776, lr=0.0000196, metrics:accuracy:0.8196,f1:0.7597
INFO:root:08:14:52 [Epoch 1 Batch 6600/11375] loss=0.3221, lr=0.0000196, metrics:accuracy:0.8196,f1:0.7598
INFO:root:08:14:53 [Epoch 1 Batch 6610/11375] loss=0.3357, lr=0.0000196, metrics:accuracy:0.8197,f1:0.7599
INFO:root:08:14:54 [Epoch 1 Batch 6620/11375] loss=0.3255, lr=0.0000196, metrics:accuracy:0.8197,f1:0.7599
INFO:root:08:14:55 [Epoch 1 Batch 6630/11375] loss=0.2807, lr=0.0000196, metrics:accuracy:0.8197,f1:0.7600
INFO:root:08:14:56 [Epoch 1 Batch 6640/11375] loss=0.3479, lr=0.0000196, metrics:accuracy:0.8197,f1:0.7599
INFO:root:08:14:58 [Epoch 1 Batch 6650/11375] loss=0.3131, lr=0.0000196, metrics:accuracy:0.8198,f1:0.7600
INFO:root:08:14:59 [Epoch 1 Batch 6660/11375] loss=0.3155, lr=0.0000196, metrics:accuracy:0.8198,f1:0.7601
INFO:root:08:15:00 [Epoch 1 Batch 6670/11375] loss=0.3408, lr=0.0000196, metrics:accuracy:0.8199,f1:0.7603
INFO:root:08:15:01 [Epoch 1 Batch 6680/11375] loss=0.3198, lr=0.0000196, metrics:accuracy:0.8200,f1:0.7604
INFO:root:08:15:02 [Epoch 1 Batch 6690/11375] loss=0.2594, lr=0.0000196, metrics:accuracy:0.8201,f1:0.7605
INFO:root:08:15:03 [Epoch 1 Batch 6700/11375] loss=0.2499, lr=0.0000196, metrics:accuracy:0.8202,f1:0.7607
INFO:root:08:15:05 [Epoch 1 Batch 6710/11375] loss=0.3027, lr=0.0000196, metrics:accuracy:0.8203,f1:0.7607
INFO:root:08:15:06 [Epoch 1 Batch 6720/11375] loss=0.3353, lr=0.0000196, metrics:accuracy:0.8203,f1:0.7608
INFO:root:08:15:07 [Epoch 1 Batch 6730/11375] loss=0.3061, lr=0.0000196, metrics:accuracy:0.8204,f1:0.7609
INFO:root:08:15:08 [Epoch 1 Batch 6740/11375] loss=0.3860, lr=0.0000196, metrics:accuracy:0.8204,f1:0.7610
INFO:root:08:15:09 [Epoch 1 Batch 6750/11375] loss=0.3809, lr=0.0000196, metrics:accuracy:0.8204,f1:0.7610
INFO:root:08:15:10 [Epoch 1 Batch 6760/11375] loss=0.2587, lr=0.0000196, metrics:accuracy:0.8205,f1:0.7611
INFO:root:08:15:11 [Epoch 1 Batch 6770/11375] loss=0.3688, lr=0.0000196, metrics:accuracy:0.8205,f1:0.7613
INFO:root:08:15:13 [Epoch 1 Batch 6780/11375] loss=0.4007, lr=0.0000196, metrics:accuracy:0.8205,f1:0.7613
INFO:root:08:15:14 [Epoch 1 Batch 6790/11375] loss=0.2700, lr=0.0000196, metrics:accuracy:0.8206,f1:0.7614
INFO:root:08:15:15 [Epoch 1 Batch 6800/11375] loss=0.3981, lr=0.0000196, metrics:accuracy:0.8206,f1:0.7614
INFO:root:08:15:16 [Epoch 1 Batch 6810/11375] loss=0.1943, lr=0.0000196, metrics:accuracy:0.8207,f1:0.7615
INFO:root:08:15:17 [Epoch 1 Batch 6820/11375] loss=0.3370, lr=0.0000196, metrics:accuracy:0.8208,f1:0.7616
INFO:root:08:15:18 [Epoch 1 Batch 6830/11375] loss=0.2835, lr=0.0000196, metrics:accuracy:0.8209,f1:0.7618
INFO:root:08:15:20 [Epoch 1 Batch 6840/11375] loss=0.3890, lr=0.0000195, metrics:accuracy:0.8209,f1:0.7618
INFO:root:08:15:21 [Epoch 1 Batch 6850/11375] loss=0.3588, lr=0.0000195, metrics:accuracy:0.8209,f1:0.7618
INFO:root:08:15:22 [Epoch 1 Batch 6860/11375] loss=0.3117, lr=0.0000195, metrics:accuracy:0.8210,f1:0.7619
INFO:root:08:15:23 [Epoch 1 Batch 6870/11375] loss=0.3076, lr=0.0000195, metrics:accuracy:0.8210,f1:0.7620
INFO:root:08:15:24 [Epoch 1 Batch 6880/11375] loss=0.3205, lr=0.0000195, metrics:accuracy:0.8211,f1:0.7621
INFO:root:08:15:26 [Epoch 1 Batch 6890/11375] loss=0.3096, lr=0.0000195, metrics:accuracy:0.8212,f1:0.7622
INFO:root:08:15:27 [Epoch 1 Batch 6900/11375] loss=0.3195, lr=0.0000195, metrics:accuracy:0.8212,f1:0.7622
INFO:root:08:15:28 [Epoch 1 Batch 6910/11375] loss=0.3216, lr=0.0000195, metrics:accuracy:0.8213,f1:0.7623
INFO:root:08:15:29 [Epoch 1 Batch 6920/11375] loss=0.3613, lr=0.0000195, metrics:accuracy:0.8213,f1:0.7622
INFO:root:08:15:30 [Epoch 1 Batch 6930/11375] loss=0.3256, lr=0.0000195, metrics:accuracy:0.8213,f1:0.7622
INFO:root:08:15:32 [Epoch 1 Batch 6940/11375] loss=0.2963, lr=0.0000195, metrics:accuracy:0.8214,f1:0.7622
INFO:root:08:15:33 [Epoch 1 Batch 6950/11375] loss=0.3717, lr=0.0000195, metrics:accuracy:0.8214,f1:0.7623
INFO:root:08:15:34 [Epoch 1 Batch 6960/11375] loss=0.2586, lr=0.0000195, metrics:accuracy:0.8215,f1:0.7625
INFO:root:08:15:35 [Epoch 1 Batch 6970/11375] loss=0.2817, lr=0.0000195, metrics:accuracy:0.8216,f1:0.7625
INFO:root:08:15:37 [Epoch 1 Batch 6980/11375] loss=0.2871, lr=0.0000195, metrics:accuracy:0.8216,f1:0.7627
INFO:root:08:15:38 [Epoch 1 Batch 6990/11375] loss=0.2804, lr=0.0000195, metrics:accuracy:0.8217,f1:0.7628
INFO:root:08:15:39 [Epoch 1 Batch 7000/11375] loss=0.2984, lr=0.0000195, metrics:accuracy:0.8218,f1:0.7629
INFO:root:08:15:40 [Epoch 1 Batch 7010/11375] loss=0.2213, lr=0.0000195, metrics:accuracy:0.8219,f1:0.7631
INFO:root:08:15:41 [Epoch 1 Batch 7020/11375] loss=0.2744, lr=0.0000195, metrics:accuracy:0.8220,f1:0.7632
INFO:root:08:15:42 [Epoch 1 Batch 7030/11375] loss=0.2935, lr=0.0000195, metrics:accuracy:0.8221,f1:0.7634
INFO:root:08:15:44 [Epoch 1 Batch 7040/11375] loss=0.2775, lr=0.0000195, metrics:accuracy:0.8222,f1:0.7635
INFO:root:08:15:45 [Epoch 1 Batch 7050/11375] loss=0.3355, lr=0.0000195, metrics:accuracy:0.8222,f1:0.7635
INFO:root:08:15:46 [Epoch 1 Batch 7060/11375] loss=0.3171, lr=0.0000195, metrics:accuracy:0.8223,f1:0.7636
INFO:root:08:15:47 [Epoch 1 Batch 7070/11375] loss=0.3162, lr=0.0000195, metrics:accuracy:0.8224,f1:0.7637
INFO:root:08:15:48 [Epoch 1 Batch 7080/11375] loss=0.3342, lr=0.0000195, metrics:accuracy:0.8224,f1:0.7637
INFO:root:08:15:49 [Epoch 1 Batch 7090/11375] loss=0.3136, lr=0.0000195, metrics:accuracy:0.8224,f1:0.7639
INFO:root:08:15:51 [Epoch 1 Batch 7100/11375] loss=0.2854, lr=0.0000194, metrics:accuracy:0.8225,f1:0.7639
INFO:root:08:15:52 [Epoch 1 Batch 7110/11375] loss=0.2596, lr=0.0000194, metrics:accuracy:0.8226,f1:0.7640
INFO:root:08:15:53 [Epoch 1 Batch 7120/11375] loss=0.3854, lr=0.0000194, metrics:accuracy:0.8226,f1:0.7641
INFO:root:08:15:54 [Epoch 1 Batch 7130/11375] loss=0.2532, lr=0.0000194, metrics:accuracy:0.8227,f1:0.7641
INFO:root:08:15:56 [Epoch 1 Batch 7140/11375] loss=0.2749, lr=0.0000194, metrics:accuracy:0.8228,f1:0.7641
INFO:root:08:15:57 [Epoch 1 Batch 7150/11375] loss=0.3184, lr=0.0000194, metrics:accuracy:0.8228,f1:0.7642
INFO:root:08:15:58 [Epoch 1 Batch 7160/11375] loss=0.2270, lr=0.0000194, metrics:accuracy:0.8229,f1:0.7643
INFO:root:08:15:59 [Epoch 1 Batch 7170/11375] loss=0.2712, lr=0.0000194, metrics:accuracy:0.8230,f1:0.7644
INFO:root:08:16:02 [Epoch 1 Batch 7180/11375] loss=0.3902, lr=0.0000194, metrics:accuracy:0.8230,f1:0.7644
INFO:root:08:16:03 [Epoch 1 Batch 7190/11375] loss=0.3501, lr=0.0000194, metrics:accuracy:0.8231,f1:0.7644
INFO:root:08:16:04 [Epoch 1 Batch 7200/11375] loss=0.3390, lr=0.0000194, metrics:accuracy:0.8231,f1:0.7646
INFO:root:08:16:05 [Epoch 1 Batch 7210/11375] loss=0.2660, lr=0.0000194, metrics:accuracy:0.8232,f1:0.7646
INFO:root:08:16:06 [Epoch 1 Batch 7220/11375] loss=0.2759, lr=0.0000194, metrics:accuracy:0.8232,f1:0.7647
INFO:root:08:16:07 [Epoch 1 Batch 7230/11375] loss=0.3502, lr=0.0000194, metrics:accuracy:0.8233,f1:0.7647
INFO:root:08:16:09 [Epoch 1 Batch 7240/11375] loss=0.2926, lr=0.0000194, metrics:accuracy:0.8233,f1:0.7648
INFO:root:08:16:10 [Epoch 1 Batch 7250/11375] loss=0.3480, lr=0.0000194, metrics:accuracy:0.8234,f1:0.7649
INFO:root:08:16:11 [Epoch 1 Batch 7260/11375] loss=0.3296, lr=0.0000194, metrics:accuracy:0.8234,f1:0.7649
INFO:root:08:16:12 [Epoch 1 Batch 7270/11375] loss=0.2495, lr=0.0000194, metrics:accuracy:0.8235,f1:0.7651
INFO:root:08:16:13 [Epoch 1 Batch 7280/11375] loss=0.3477, lr=0.0000194, metrics:accuracy:0.8235,f1:0.7651
INFO:root:08:16:14 [Epoch 1 Batch 7290/11375] loss=0.3566, lr=0.0000194, metrics:accuracy:0.8236,f1:0.7652
INFO:root:08:16:16 [Epoch 1 Batch 7300/11375] loss=0.2405, lr=0.0000194, metrics:accuracy:0.8237,f1:0.7653
INFO:root:08:16:17 [Epoch 1 Batch 7310/11375] loss=0.3305, lr=0.0000194, metrics:accuracy:0.8237,f1:0.7653
INFO:root:08:16:18 [Epoch 1 Batch 7320/11375] loss=0.2995, lr=0.0000194, metrics:accuracy:0.8237,f1:0.7654
INFO:root:08:16:19 [Epoch 1 Batch 7330/11375] loss=0.2801, lr=0.0000194, metrics:accuracy:0.8238,f1:0.7655
INFO:root:08:16:20 [Epoch 1 Batch 7340/11375] loss=0.3272, lr=0.0000194, metrics:accuracy:0.8239,f1:0.7655
INFO:root:08:16:21 [Epoch 1 Batch 7350/11375] loss=0.3061, lr=0.0000193, metrics:accuracy:0.8239,f1:0.7656
INFO:root:08:16:23 [Epoch 1 Batch 7360/11375] loss=0.2458, lr=0.0000193, metrics:accuracy:0.8240,f1:0.7657
INFO:root:08:16:24 [Epoch 1 Batch 7370/11375] loss=0.2846, lr=0.0000193, metrics:accuracy:0.8241,f1:0.7658
INFO:root:08:16:25 [Epoch 1 Batch 7380/11375] loss=0.2726, lr=0.0000193, metrics:accuracy:0.8242,f1:0.7659
INFO:root:08:16:26 [Epoch 1 Batch 7390/11375] loss=0.2366, lr=0.0000193, metrics:accuracy:0.8243,f1:0.7659
INFO:root:08:16:28 [Epoch 1 Batch 7400/11375] loss=0.3133, lr=0.0000193, metrics:accuracy:0.8243,f1:0.7660
INFO:root:08:16:29 [Epoch 1 Batch 7410/11375] loss=0.3257, lr=0.0000193, metrics:accuracy:0.8244,f1:0.7661
INFO:root:08:16:30 [Epoch 1 Batch 7420/11375] loss=0.3212, lr=0.0000193, metrics:accuracy:0.8244,f1:0.7662
INFO:root:08:16:31 [Epoch 1 Batch 7430/11375] loss=0.2375, lr=0.0000193, metrics:accuracy:0.8245,f1:0.7663
INFO:root:08:16:32 [Epoch 1 Batch 7440/11375] loss=0.3628, lr=0.0000193, metrics:accuracy:0.8245,f1:0.7664
INFO:root:08:16:33 [Epoch 1 Batch 7450/11375] loss=0.3163, lr=0.0000193, metrics:accuracy:0.8246,f1:0.7665
INFO:root:08:16:34 [Epoch 1 Batch 7460/11375] loss=0.2811, lr=0.0000193, metrics:accuracy:0.8247,f1:0.7665
INFO:root:08:16:36 [Epoch 1 Batch 7470/11375] loss=0.2964, lr=0.0000193, metrics:accuracy:0.8247,f1:0.7666
INFO:root:08:16:37 [Epoch 1 Batch 7480/11375] loss=0.2845, lr=0.0000193, metrics:accuracy:0.8248,f1:0.7667
INFO:root:08:16:38 [Epoch 1 Batch 7490/11375] loss=0.3118, lr=0.0000193, metrics:accuracy:0.8248,f1:0.7667
INFO:root:08:16:39 [Epoch 1 Batch 7500/11375] loss=0.3305, lr=0.0000193, metrics:accuracy:0.8249,f1:0.7669
INFO:root:08:16:40 [Epoch 1 Batch 7510/11375] loss=0.2820, lr=0.0000193, metrics:accuracy:0.8250,f1:0.7669
INFO:root:08:16:42 [Epoch 1 Batch 7520/11375] loss=0.2806, lr=0.0000193, metrics:accuracy:0.8250,f1:0.7669
INFO:root:08:16:43 [Epoch 1 Batch 7530/11375] loss=0.3623, lr=0.0000193, metrics:accuracy:0.8250,f1:0.7669
INFO:root:08:16:44 [Epoch 1 Batch 7540/11375] loss=0.3288, lr=0.0000193, metrics:accuracy:0.8250,f1:0.7669
INFO:root:08:16:45 [Epoch 1 Batch 7550/11375] loss=0.3654, lr=0.0000193, metrics:accuracy:0.8250,f1:0.7669
INFO:root:08:16:46 [Epoch 1 Batch 7560/11375] loss=0.3492, lr=0.0000193, metrics:accuracy:0.8250,f1:0.7670
INFO:root:08:16:47 [Epoch 1 Batch 7570/11375] loss=0.3837, lr=0.0000193, metrics:accuracy:0.8250,f1:0.7670
INFO:root:08:16:49 [Epoch 1 Batch 7580/11375] loss=0.2957, lr=0.0000193, metrics:accuracy:0.8250,f1:0.7670
INFO:root:08:16:50 [Epoch 1 Batch 7590/11375] loss=0.2662, lr=0.0000193, metrics:accuracy:0.8251,f1:0.7671
INFO:root:08:16:51 [Epoch 1 Batch 7600/11375] loss=0.3303, lr=0.0000193, metrics:accuracy:0.8252,f1:0.7672
INFO:root:08:16:52 [Epoch 1 Batch 7610/11375] loss=0.3274, lr=0.0000192, metrics:accuracy:0.8252,f1:0.7673
INFO:root:08:16:53 [Epoch 1 Batch 7620/11375] loss=0.2967, lr=0.0000192, metrics:accuracy:0.8253,f1:0.7673
INFO:root:08:16:54 [Epoch 1 Batch 7630/11375] loss=0.2729, lr=0.0000192, metrics:accuracy:0.8253,f1:0.7674
INFO:root:08:16:56 [Epoch 1 Batch 7640/11375] loss=0.3066, lr=0.0000192, metrics:accuracy:0.8254,f1:0.7675
INFO:root:08:16:57 [Epoch 1 Batch 7650/11375] loss=0.2554, lr=0.0000192, metrics:accuracy:0.8255,f1:0.7676
INFO:root:08:16:58 [Epoch 1 Batch 7660/11375] loss=0.2563, lr=0.0000192, metrics:accuracy:0.8256,f1:0.7677
INFO:root:08:16:59 [Epoch 1 Batch 7670/11375] loss=0.2751, lr=0.0000192, metrics:accuracy:0.8257,f1:0.7678
INFO:root:08:17:00 [Epoch 1 Batch 7680/11375] loss=0.3432, lr=0.0000192, metrics:accuracy:0.8257,f1:0.7678
INFO:root:08:17:01 [Epoch 1 Batch 7690/11375] loss=0.3306, lr=0.0000192, metrics:accuracy:0.8257,f1:0.7679
INFO:root:08:17:03 [Epoch 1 Batch 7700/11375] loss=0.2090, lr=0.0000192, metrics:accuracy:0.8258,f1:0.7679
INFO:root:08:17:04 [Epoch 1 Batch 7710/11375] loss=0.3333, lr=0.0000192, metrics:accuracy:0.8259,f1:0.7680
INFO:root:08:17:05 [Epoch 1 Batch 7720/11375] loss=0.2966, lr=0.0000192, metrics:accuracy:0.8260,f1:0.7682
INFO:root:08:17:06 [Epoch 1 Batch 7730/11375] loss=0.2620, lr=0.0000192, metrics:accuracy:0.8260,f1:0.7682
INFO:root:08:17:07 [Epoch 1 Batch 7740/11375] loss=0.2656, lr=0.0000192, metrics:accuracy:0.8261,f1:0.7683
INFO:root:08:17:09 [Epoch 1 Batch 7750/11375] loss=0.3258, lr=0.0000192, metrics:accuracy:0.8261,f1:0.7684
INFO:root:08:17:10 [Epoch 1 Batch 7760/11375] loss=0.2576, lr=0.0000192, metrics:accuracy:0.8262,f1:0.7685
INFO:root:08:17:11 [Epoch 1 Batch 7770/11375] loss=0.2045, lr=0.0000192, metrics:accuracy:0.8263,f1:0.7686
INFO:root:08:17:12 [Epoch 1 Batch 7780/11375] loss=0.3063, lr=0.0000192, metrics:accuracy:0.8264,f1:0.7686
INFO:root:08:17:13 [Epoch 1 Batch 7790/11375] loss=0.3075, lr=0.0000192, metrics:accuracy:0.8264,f1:0.7687
INFO:root:08:17:14 [Epoch 1 Batch 7800/11375] loss=0.2964, lr=0.0000192, metrics:accuracy:0.8265,f1:0.7688
INFO:root:08:17:16 [Epoch 1 Batch 7810/11375] loss=0.4110, lr=0.0000192, metrics:accuracy:0.8265,f1:0.7688
INFO:root:08:17:17 [Epoch 1 Batch 7820/11375] loss=0.2890, lr=0.0000192, metrics:accuracy:0.8266,f1:0.7689
INFO:root:08:17:18 [Epoch 1 Batch 7830/11375] loss=0.3472, lr=0.0000192, metrics:accuracy:0.8266,f1:0.7689
INFO:root:08:17:19 [Epoch 1 Batch 7840/11375] loss=0.3130, lr=0.0000192, metrics:accuracy:0.8266,f1:0.7690
INFO:root:08:17:20 [Epoch 1 Batch 7850/11375] loss=0.2921, lr=0.0000192, metrics:accuracy:0.8266,f1:0.7691
INFO:root:08:17:21 [Epoch 1 Batch 7860/11375] loss=0.3512, lr=0.0000192, metrics:accuracy:0.8266,f1:0.7691
INFO:root:08:17:23 [Epoch 1 Batch 7870/11375] loss=0.3058, lr=0.0000191, metrics:accuracy:0.8267,f1:0.7692
INFO:root:08:17:24 [Epoch 1 Batch 7880/11375] loss=0.3255, lr=0.0000191, metrics:accuracy:0.8267,f1:0.7692
INFO:root:08:17:25 [Epoch 1 Batch 7890/11375] loss=0.2799, lr=0.0000191, metrics:accuracy:0.8268,f1:0.7693
INFO:root:08:17:26 [Epoch 1 Batch 7900/11375] loss=0.3695, lr=0.0000191, metrics:accuracy:0.8268,f1:0.7693
INFO:root:08:17:27 [Epoch 1 Batch 7910/11375] loss=0.2743, lr=0.0000191, metrics:accuracy:0.8269,f1:0.7694
INFO:root:08:17:28 [Epoch 1 Batch 7920/11375] loss=0.3204, lr=0.0000191, metrics:accuracy:0.8269,f1:0.7695
INFO:root:08:17:30 [Epoch 1 Batch 7930/11375] loss=0.2544, lr=0.0000191, metrics:accuracy:0.8270,f1:0.7695
INFO:root:08:17:31 [Epoch 1 Batch 7940/11375] loss=0.2512, lr=0.0000191, metrics:accuracy:0.8271,f1:0.7696
INFO:root:08:17:32 [Epoch 1 Batch 7950/11375] loss=0.2949, lr=0.0000191, metrics:accuracy:0.8271,f1:0.7696
INFO:root:08:17:33 [Epoch 1 Batch 7960/11375] loss=0.2720, lr=0.0000191, metrics:accuracy:0.8272,f1:0.7698
INFO:root:08:17:35 [Epoch 1 Batch 7970/11375] loss=0.2164, lr=0.0000191, metrics:accuracy:0.8273,f1:0.7699
INFO:root:08:17:36 [Epoch 1 Batch 7980/11375] loss=0.3194, lr=0.0000191, metrics:accuracy:0.8273,f1:0.7699
INFO:root:08:17:37 [Epoch 1 Batch 7990/11375] loss=0.3843, lr=0.0000191, metrics:accuracy:0.8273,f1:0.7699
INFO:root:08:17:38 [Epoch 1 Batch 8000/11375] loss=0.2870, lr=0.0000191, metrics:accuracy:0.8274,f1:0.7700
INFO:root:08:17:39 [Epoch 1 Batch 8010/11375] loss=0.2756, lr=0.0000191, metrics:accuracy:0.8275,f1:0.7700
INFO:root:08:17:41 [Epoch 1 Batch 8020/11375] loss=0.2171, lr=0.0000191, metrics:accuracy:0.8275,f1:0.7701
INFO:root:08:17:42 [Epoch 1 Batch 8030/11375] loss=0.2234, lr=0.0000191, metrics:accuracy:0.8277,f1:0.7703
INFO:root:08:17:43 [Epoch 1 Batch 8040/11375] loss=0.3161, lr=0.0000191, metrics:accuracy:0.8277,f1:0.7704
INFO:root:08:17:44 [Epoch 1 Batch 8050/11375] loss=0.3347, lr=0.0000191, metrics:accuracy:0.8277,f1:0.7704
INFO:root:08:17:45 [Epoch 1 Batch 8060/11375] loss=0.2830, lr=0.0000191, metrics:accuracy:0.8278,f1:0.7705
INFO:root:08:17:47 [Epoch 1 Batch 8070/11375] loss=0.2649, lr=0.0000191, metrics:accuracy:0.8279,f1:0.7705
INFO:root:08:17:48 [Epoch 1 Batch 8080/11375] loss=0.2747, lr=0.0000191, metrics:accuracy:0.8279,f1:0.7706
INFO:root:08:17:49 [Epoch 1 Batch 8090/11375] loss=0.2936, lr=0.0000191, metrics:accuracy:0.8280,f1:0.7707
INFO:root:08:17:50 [Epoch 1 Batch 8100/11375] loss=0.3285, lr=0.0000191, metrics:accuracy:0.8280,f1:0.7708
INFO:root:08:17:51 [Epoch 1 Batch 8110/11375] loss=0.2707, lr=0.0000191, metrics:accuracy:0.8281,f1:0.7709
INFO:root:08:17:52 [Epoch 1 Batch 8120/11375] loss=0.3107, lr=0.0000190, metrics:accuracy:0.8281,f1:0.7709
INFO:root:08:17:54 [Epoch 1 Batch 8130/11375] loss=0.2842, lr=0.0000190, metrics:accuracy:0.8282,f1:0.7710
INFO:root:08:17:55 [Epoch 1 Batch 8140/11375] loss=0.3537, lr=0.0000190, metrics:accuracy:0.8282,f1:0.7711
INFO:root:08:17:56 [Epoch 1 Batch 8150/11375] loss=0.3078, lr=0.0000190, metrics:accuracy:0.8283,f1:0.7711
INFO:root:08:17:57 [Epoch 1 Batch 8160/11375] loss=0.3197, lr=0.0000190, metrics:accuracy:0.8283,f1:0.7712
INFO:root:08:17:58 [Epoch 1 Batch 8170/11375] loss=0.2994, lr=0.0000190, metrics:accuracy:0.8284,f1:0.7713
INFO:root:08:17:59 [Epoch 1 Batch 8180/11375] loss=0.3738, lr=0.0000190, metrics:accuracy:0.8284,f1:0.7714
INFO:root:08:18:00 [Epoch 1 Batch 8190/11375] loss=0.2783, lr=0.0000190, metrics:accuracy:0.8284,f1:0.7715
INFO:root:08:18:02 [Epoch 1 Batch 8200/11375] loss=0.3133, lr=0.0000190, metrics:accuracy:0.8285,f1:0.7715
INFO:root:08:18:03 [Epoch 1 Batch 8210/11375] loss=0.2747, lr=0.0000190, metrics:accuracy:0.8285,f1:0.7716
INFO:root:08:18:04 [Epoch 1 Batch 8220/11375] loss=0.2574, lr=0.0000190, metrics:accuracy:0.8286,f1:0.7716
INFO:root:08:18:05 [Epoch 1 Batch 8230/11375] loss=0.2805, lr=0.0000190, metrics:accuracy:0.8287,f1:0.7716
INFO:root:08:18:06 [Epoch 1 Batch 8240/11375] loss=0.3423, lr=0.0000190, metrics:accuracy:0.8287,f1:0.7717
INFO:root:08:18:08 [Epoch 1 Batch 8250/11375] loss=0.3312, lr=0.0000190, metrics:accuracy:0.8287,f1:0.7718
INFO:root:08:18:09 [Epoch 1 Batch 8260/11375] loss=0.2591, lr=0.0000190, metrics:accuracy:0.8288,f1:0.7719
INFO:root:08:18:10 [Epoch 1 Batch 8270/11375] loss=0.2839, lr=0.0000190, metrics:accuracy:0.8289,f1:0.7720
INFO:root:08:18:11 [Epoch 1 Batch 8280/11375] loss=0.2746, lr=0.0000190, metrics:accuracy:0.8290,f1:0.7721
INFO:root:08:18:12 [Epoch 1 Batch 8290/11375] loss=0.2818, lr=0.0000190, metrics:accuracy:0.8290,f1:0.7721
INFO:root:08:18:14 [Epoch 1 Batch 8300/11375] loss=0.3421, lr=0.0000190, metrics:accuracy:0.8290,f1:0.7721
INFO:root:08:18:15 [Epoch 1 Batch 8310/11375] loss=0.3223, lr=0.0000190, metrics:accuracy:0.8291,f1:0.7722
INFO:root:08:18:16 [Epoch 1 Batch 8320/11375] loss=0.3159, lr=0.0000190, metrics:accuracy:0.8291,f1:0.7723
INFO:root:08:18:17 [Epoch 1 Batch 8330/11375] loss=0.2434, lr=0.0000190, metrics:accuracy:0.8292,f1:0.7725
INFO:root:08:18:18 [Epoch 1 Batch 8340/11375] loss=0.3167, lr=0.0000190, metrics:accuracy:0.8292,f1:0.7725
INFO:root:08:18:20 [Epoch 1 Batch 8350/11375] loss=0.3151, lr=0.0000190, metrics:accuracy:0.8293,f1:0.7725
INFO:root:08:18:21 [Epoch 1 Batch 8360/11375] loss=0.3585, lr=0.0000190, metrics:accuracy:0.8293,f1:0.7726
INFO:root:08:18:22 [Epoch 1 Batch 8370/11375] loss=0.3050, lr=0.0000190, metrics:accuracy:0.8293,f1:0.7727
INFO:root:08:18:23 [Epoch 1 Batch 8380/11375] loss=0.3574, lr=0.0000189, metrics:accuracy:0.8293,f1:0.7727
INFO:root:08:18:24 [Epoch 1 Batch 8390/11375] loss=0.3565, lr=0.0000189, metrics:accuracy:0.8293,f1:0.7727
INFO:root:08:18:26 [Epoch 1 Batch 8400/11375] loss=0.3067, lr=0.0000189, metrics:accuracy:0.8294,f1:0.7728
INFO:root:08:18:27 [Epoch 1 Batch 8410/11375] loss=0.2266, lr=0.0000189, metrics:accuracy:0.8295,f1:0.7729
INFO:root:08:18:28 [Epoch 1 Batch 8420/11375] loss=0.3403, lr=0.0000189, metrics:accuracy:0.8295,f1:0.7730
INFO:root:08:18:29 [Epoch 1 Batch 8430/11375] loss=0.2582, lr=0.0000189, metrics:accuracy:0.8296,f1:0.7731
INFO:root:08:18:30 [Epoch 1 Batch 8440/11375] loss=0.3219, lr=0.0000189, metrics:accuracy:0.8296,f1:0.7731
INFO:root:08:18:31 [Epoch 1 Batch 8450/11375] loss=0.2510, lr=0.0000189, metrics:accuracy:0.8297,f1:0.7732
INFO:root:08:18:33 [Epoch 1 Batch 8460/11375] loss=0.3168, lr=0.0000189, metrics:accuracy:0.8297,f1:0.7733
INFO:root:08:18:34 [Epoch 1 Batch 8470/11375] loss=0.2943, lr=0.0000189, metrics:accuracy:0.8298,f1:0.7734
INFO:root:08:18:35 [Epoch 1 Batch 8480/11375] loss=0.3439, lr=0.0000189, metrics:accuracy:0.8299,f1:0.7735
INFO:root:08:18:36 [Epoch 1 Batch 8490/11375] loss=0.3724, lr=0.0000189, metrics:accuracy:0.8299,f1:0.7736
INFO:root:08:18:38 [Epoch 1 Batch 8500/11375] loss=0.3204, lr=0.0000189, metrics:accuracy:0.8299,f1:0.7735
INFO:root:08:18:39 [Epoch 1 Batch 8510/11375] loss=0.3433, lr=0.0000189, metrics:accuracy:0.8299,f1:0.7736
INFO:root:08:18:40 [Epoch 1 Batch 8520/11375] loss=0.3325, lr=0.0000189, metrics:accuracy:0.8299,f1:0.7737
INFO:root:08:18:41 [Epoch 1 Batch 8530/11375] loss=0.2877, lr=0.0000189, metrics:accuracy:0.8300,f1:0.7737
INFO:root:08:18:42 [Epoch 1 Batch 8540/11375] loss=0.2297, lr=0.0000189, metrics:accuracy:0.8301,f1:0.7738
INFO:root:08:18:44 [Epoch 1 Batch 8550/11375] loss=0.1691, lr=0.0000189, metrics:accuracy:0.8301,f1:0.7739
INFO:root:08:18:45 [Epoch 1 Batch 8560/11375] loss=0.3444, lr=0.0000189, metrics:accuracy:0.8302,f1:0.7739
INFO:root:08:18:46 [Epoch 1 Batch 8570/11375] loss=0.3298, lr=0.0000189, metrics:accuracy:0.8302,f1:0.7740
INFO:root:08:18:47 [Epoch 1 Batch 8580/11375] loss=0.2650, lr=0.0000189, metrics:accuracy:0.8303,f1:0.7741
INFO:root:08:18:48 [Epoch 1 Batch 8590/11375] loss=0.3129, lr=0.0000189, metrics:accuracy:0.8304,f1:0.7741
INFO:root:08:18:50 [Epoch 1 Batch 8600/11375] loss=0.2942, lr=0.0000189, metrics:accuracy:0.8304,f1:0.7742
INFO:root:08:18:51 [Epoch 1 Batch 8610/11375] loss=0.2294, lr=0.0000189, metrics:accuracy:0.8305,f1:0.7743
INFO:root:08:18:52 [Epoch 1 Batch 8620/11375] loss=0.2982, lr=0.0000189, metrics:accuracy:0.8306,f1:0.7744
INFO:root:08:18:53 [Epoch 1 Batch 8630/11375] loss=0.3013, lr=0.0000188, metrics:accuracy:0.8306,f1:0.7744
INFO:root:08:18:55 [Epoch 1 Batch 8640/11375] loss=0.2509, lr=0.0000188, metrics:accuracy:0.8307,f1:0.7745
INFO:root:08:18:56 [Epoch 1 Batch 8650/11375] loss=0.3196, lr=0.0000188, metrics:accuracy:0.8307,f1:0.7745
INFO:root:08:18:57 [Epoch 1 Batch 8660/11375] loss=0.3373, lr=0.0000188, metrics:accuracy:0.8307,f1:0.7746
INFO:root:08:18:58 [Epoch 1 Batch 8670/11375] loss=0.2608, lr=0.0000188, metrics:accuracy:0.8308,f1:0.7747
INFO:root:08:18:59 [Epoch 1 Batch 8680/11375] loss=0.2011, lr=0.0000188, metrics:accuracy:0.8309,f1:0.7748
INFO:root:08:19:00 [Epoch 1 Batch 8690/11375] loss=0.3323, lr=0.0000188, metrics:accuracy:0.8309,f1:0.7748
INFO:root:08:19:02 [Epoch 1 Batch 8700/11375] loss=0.2836, lr=0.0000188, metrics:accuracy:0.8310,f1:0.7749
INFO:root:08:19:03 [Epoch 1 Batch 8710/11375] loss=0.2903, lr=0.0000188, metrics:accuracy:0.8310,f1:0.7750
INFO:root:08:19:04 [Epoch 1 Batch 8720/11375] loss=0.2832, lr=0.0000188, metrics:accuracy:0.8311,f1:0.7751
INFO:root:08:19:05 [Epoch 1 Batch 8730/11375] loss=0.2723, lr=0.0000188, metrics:accuracy:0.8311,f1:0.7751
INFO:root:08:19:06 [Epoch 1 Batch 8740/11375] loss=0.2725, lr=0.0000188, metrics:accuracy:0.8311,f1:0.7752
INFO:root:08:19:08 [Epoch 1 Batch 8750/11375] loss=0.2683, lr=0.0000188, metrics:accuracy:0.8312,f1:0.7752
INFO:root:08:19:09 [Epoch 1 Batch 8760/11375] loss=0.2574, lr=0.0000188, metrics:accuracy:0.8313,f1:0.7753
INFO:root:08:19:10 [Epoch 1 Batch 8770/11375] loss=0.2238, lr=0.0000188, metrics:accuracy:0.8314,f1:0.7754
INFO:root:08:19:12 [Epoch 1 Batch 8780/11375] loss=0.2996, lr=0.0000188, metrics:accuracy:0.8314,f1:0.7755
INFO:root:08:19:13 [Epoch 1 Batch 8790/11375] loss=0.2600, lr=0.0000188, metrics:accuracy:0.8315,f1:0.7755
INFO:root:08:19:14 [Epoch 1 Batch 8800/11375] loss=0.3129, lr=0.0000188, metrics:accuracy:0.8315,f1:0.7755
INFO:root:08:19:15 [Epoch 1 Batch 8810/11375] loss=0.3314, lr=0.0000188, metrics:accuracy:0.8315,f1:0.7756
INFO:root:08:19:16 [Epoch 1 Batch 8820/11375] loss=0.3086, lr=0.0000188, metrics:accuracy:0.8316,f1:0.7757
INFO:root:08:19:18 [Epoch 1 Batch 8830/11375] loss=0.2657, lr=0.0000188, metrics:accuracy:0.8317,f1:0.7758
INFO:root:08:19:19 [Epoch 1 Batch 8840/11375] loss=0.3448, lr=0.0000188, metrics:accuracy:0.8317,f1:0.7758
INFO:root:08:19:20 [Epoch 1 Batch 8850/11375] loss=0.2483, lr=0.0000188, metrics:accuracy:0.8318,f1:0.7759
INFO:root:08:19:21 [Epoch 1 Batch 8860/11375] loss=0.2700, lr=0.0000188, metrics:accuracy:0.8318,f1:0.7760
INFO:root:08:19:23 [Epoch 1 Batch 8870/11375] loss=0.3154, lr=0.0000188, metrics:accuracy:0.8318,f1:0.7760
INFO:root:08:19:24 [Epoch 1 Batch 8880/11375] loss=0.3100, lr=0.0000188, metrics:accuracy:0.8319,f1:0.7761
INFO:root:08:19:25 [Epoch 1 Batch 8890/11375] loss=0.3180, lr=0.0000187, metrics:accuracy:0.8319,f1:0.7762
INFO:root:08:19:26 [Epoch 1 Batch 8900/11375] loss=0.2653, lr=0.0000187, metrics:accuracy:0.8320,f1:0.7762
INFO:root:08:19:27 [Epoch 1 Batch 8910/11375] loss=0.2744, lr=0.0000187, metrics:accuracy:0.8320,f1:0.7763
INFO:root:08:19:29 [Epoch 1 Batch 8920/11375] loss=0.2204, lr=0.0000187, metrics:accuracy:0.8321,f1:0.7764
INFO:root:08:19:30 [Epoch 1 Batch 8930/11375] loss=0.2572, lr=0.0000187, metrics:accuracy:0.8322,f1:0.7765
INFO:root:08:19:31 [Epoch 1 Batch 8940/11375] loss=0.2930, lr=0.0000187, metrics:accuracy:0.8322,f1:0.7766
INFO:root:08:19:32 [Epoch 1 Batch 8950/11375] loss=0.3243, lr=0.0000187, metrics:accuracy:0.8323,f1:0.7767
INFO:root:08:19:33 [Epoch 1 Batch 8960/11375] loss=0.2901, lr=0.0000187, metrics:accuracy:0.8323,f1:0.7768
INFO:root:08:19:34 [Epoch 1 Batch 8970/11375] loss=0.2576, lr=0.0000187, metrics:accuracy:0.8324,f1:0.7768
INFO:root:08:19:36 [Epoch 1 Batch 8980/11375] loss=0.2626, lr=0.0000187, metrics:accuracy:0.8324,f1:0.7769
INFO:root:08:19:37 [Epoch 1 Batch 8990/11375] loss=0.3223, lr=0.0000187, metrics:accuracy:0.8325,f1:0.7769
INFO:root:08:19:38 [Epoch 1 Batch 9000/11375] loss=0.2770, lr=0.0000187, metrics:accuracy:0.8325,f1:0.7770
INFO:root:08:19:39 [Epoch 1 Batch 9010/11375] loss=0.2724, lr=0.0000187, metrics:accuracy:0.8326,f1:0.7771
INFO:root:08:19:40 [Epoch 1 Batch 9020/11375] loss=0.2841, lr=0.0000187, metrics:accuracy:0.8326,f1:0.7772
INFO:root:08:19:42 [Epoch 1 Batch 9030/11375] loss=0.3098, lr=0.0000187, metrics:accuracy:0.8327,f1:0.7773
INFO:root:08:19:43 [Epoch 1 Batch 9040/11375] loss=0.3065, lr=0.0000187, metrics:accuracy:0.8327,f1:0.7773
INFO:root:08:19:44 [Epoch 1 Batch 9050/11375] loss=0.2985, lr=0.0000187, metrics:accuracy:0.8328,f1:0.7774
INFO:root:08:19:45 [Epoch 1 Batch 9060/11375] loss=0.2426, lr=0.0000187, metrics:accuracy:0.8328,f1:0.7775
INFO:root:08:19:46 [Epoch 1 Batch 9070/11375] loss=0.3176, lr=0.0000187, metrics:accuracy:0.8328,f1:0.7775
INFO:root:08:19:47 [Epoch 1 Batch 9080/11375] loss=0.2974, lr=0.0000187, metrics:accuracy:0.8329,f1:0.7776
INFO:root:08:19:48 [Epoch 1 Batch 9090/11375] loss=0.3730, lr=0.0000187, metrics:accuracy:0.8329,f1:0.7776
INFO:root:08:19:50 [Epoch 1 Batch 9100/11375] loss=0.2603, lr=0.0000187, metrics:accuracy:0.8329,f1:0.7777
INFO:root:08:19:51 [Epoch 1 Batch 9110/11375] loss=0.2378, lr=0.0000187, metrics:accuracy:0.8330,f1:0.7777
INFO:root:08:19:52 [Epoch 1 Batch 9120/11375] loss=0.2487, lr=0.0000187, metrics:accuracy:0.8331,f1:0.7778
INFO:root:08:19:53 [Epoch 1 Batch 9130/11375] loss=0.2289, lr=0.0000187, metrics:accuracy:0.8332,f1:0.7779
INFO:root:08:19:55 [Epoch 1 Batch 9140/11375] loss=0.3032, lr=0.0000186, metrics:accuracy:0.8332,f1:0.7779
INFO:root:08:19:56 [Epoch 1 Batch 9150/11375] loss=0.2699, lr=0.0000186, metrics:accuracy:0.8332,f1:0.7779
INFO:root:08:19:57 [Epoch 1 Batch 9160/11375] loss=0.3112, lr=0.0000186, metrics:accuracy:0.8333,f1:0.7780
INFO:root:08:19:58 [Epoch 1 Batch 9170/11375] loss=0.2822, lr=0.0000186, metrics:accuracy:0.8333,f1:0.7780
INFO:root:08:19:59 [Epoch 1 Batch 9180/11375] loss=0.3533, lr=0.0000186, metrics:accuracy:0.8333,f1:0.7780
INFO:root:08:20:00 [Epoch 1 Batch 9190/11375] loss=0.3435, lr=0.0000186, metrics:accuracy:0.8333,f1:0.7781
INFO:root:08:20:02 [Epoch 1 Batch 9200/11375] loss=0.2373, lr=0.0000186, metrics:accuracy:0.8334,f1:0.7781
INFO:root:08:20:03 [Epoch 1 Batch 9210/11375] loss=0.2318, lr=0.0000186, metrics:accuracy:0.8335,f1:0.7782
INFO:root:08:20:04 [Epoch 1 Batch 9220/11375] loss=0.3180, lr=0.0000186, metrics:accuracy:0.8335,f1:0.7782
INFO:root:08:20:05 [Epoch 1 Batch 9230/11375] loss=0.2660, lr=0.0000186, metrics:accuracy:0.8335,f1:0.7783
INFO:root:08:20:07 [Epoch 1 Batch 9240/11375] loss=0.3344, lr=0.0000186, metrics:accuracy:0.8335,f1:0.7783
INFO:root:08:20:08 [Epoch 1 Batch 9250/11375] loss=0.2690, lr=0.0000186, metrics:accuracy:0.8336,f1:0.7784
INFO:root:08:20:09 [Epoch 1 Batch 9260/11375] loss=0.2365, lr=0.0000186, metrics:accuracy:0.8337,f1:0.7784
INFO:root:08:20:10 [Epoch 1 Batch 9270/11375] loss=0.2223, lr=0.0000186, metrics:accuracy:0.8337,f1:0.7785
INFO:root:08:20:12 [Epoch 1 Batch 9280/11375] loss=0.2440, lr=0.0000186, metrics:accuracy:0.8338,f1:0.7785
INFO:root:08:20:13 [Epoch 1 Batch 9290/11375] loss=0.3247, lr=0.0000186, metrics:accuracy:0.8338,f1:0.7785
INFO:root:08:20:14 [Epoch 1 Batch 9300/11375] loss=0.3354, lr=0.0000186, metrics:accuracy:0.8339,f1:0.7786
INFO:root:08:20:15 [Epoch 1 Batch 9310/11375] loss=0.2798, lr=0.0000186, metrics:accuracy:0.8339,f1:0.7786
INFO:root:08:20:16 [Epoch 1 Batch 9320/11375] loss=0.2636, lr=0.0000186, metrics:accuracy:0.8340,f1:0.7787
INFO:root:08:20:17 [Epoch 1 Batch 9330/11375] loss=0.2624, lr=0.0000186, metrics:accuracy:0.8340,f1:0.7788
INFO:root:08:20:19 [Epoch 1 Batch 9340/11375] loss=0.2851, lr=0.0000186, metrics:accuracy:0.8341,f1:0.7789
INFO:root:08:20:20 [Epoch 1 Batch 9350/11375] loss=0.2810, lr=0.0000186, metrics:accuracy:0.8341,f1:0.7789
INFO:root:08:20:21 [Epoch 1 Batch 9360/11375] loss=0.2772, lr=0.0000186, metrics:accuracy:0.8342,f1:0.7790
INFO:root:08:20:23 [Epoch 1 Batch 9370/11375] loss=0.2716, lr=0.0000186, metrics:accuracy:0.8342,f1:0.7790
INFO:root:08:20:24 [Epoch 1 Batch 9380/11375] loss=0.3313, lr=0.0000186, metrics:accuracy:0.8342,f1:0.7790
INFO:root:08:20:25 [Epoch 1 Batch 9390/11375] loss=0.3068, lr=0.0000186, metrics:accuracy:0.8343,f1:0.7791
INFO:root:08:20:26 [Epoch 1 Batch 9400/11375] loss=0.3191, lr=0.0000185, metrics:accuracy:0.8343,f1:0.7792
INFO:root:08:20:27 [Epoch 1 Batch 9410/11375] loss=0.1467, lr=0.0000185, metrics:accuracy:0.8344,f1:0.7793
INFO:root:08:20:29 [Epoch 1 Batch 9420/11375] loss=0.2644, lr=0.0000185, metrics:accuracy:0.8345,f1:0.7794
INFO:root:08:20:30 [Epoch 1 Batch 9430/11375] loss=0.2524, lr=0.0000185, metrics:accuracy:0.8345,f1:0.7794
INFO:root:08:20:31 [Epoch 1 Batch 9440/11375] loss=0.2728, lr=0.0000185, metrics:accuracy:0.8346,f1:0.7795
INFO:root:08:20:32 [Epoch 1 Batch 9450/11375] loss=0.2404, lr=0.0000185, metrics:accuracy:0.8346,f1:0.7795
INFO:root:08:20:33 [Epoch 1 Batch 9460/11375] loss=0.3207, lr=0.0000185, metrics:accuracy:0.8346,f1:0.7795
INFO:root:08:20:35 [Epoch 1 Batch 9470/11375] loss=0.2542, lr=0.0000185, metrics:accuracy:0.8347,f1:0.7796
INFO:root:08:20:36 [Epoch 1 Batch 9480/11375] loss=0.3472, lr=0.0000185, metrics:accuracy:0.8347,f1:0.7796
INFO:root:08:20:37 [Epoch 1 Batch 9490/11375] loss=0.2494, lr=0.0000185, metrics:accuracy:0.8347,f1:0.7797
INFO:root:08:20:38 [Epoch 1 Batch 9500/11375] loss=0.3537, lr=0.0000185, metrics:accuracy:0.8347,f1:0.7797
INFO:root:08:20:39 [Epoch 1 Batch 9510/11375] loss=0.3468, lr=0.0000185, metrics:accuracy:0.8347,f1:0.7797
INFO:root:08:20:40 [Epoch 1 Batch 9520/11375] loss=0.3212, lr=0.0000185, metrics:accuracy:0.8348,f1:0.7797
INFO:root:08:20:41 [Epoch 1 Batch 9530/11375] loss=0.2528, lr=0.0000185, metrics:accuracy:0.8348,f1:0.7798
INFO:root:08:20:43 [Epoch 1 Batch 9540/11375] loss=0.2601, lr=0.0000185, metrics:accuracy:0.8349,f1:0.7798
INFO:root:08:20:44 [Epoch 1 Batch 9550/11375] loss=0.2381, lr=0.0000185, metrics:accuracy:0.8349,f1:0.7798
INFO:root:08:20:45 [Epoch 1 Batch 9560/11375] loss=0.2542, lr=0.0000185, metrics:accuracy:0.8350,f1:0.7799
INFO:root:08:20:46 [Epoch 1 Batch 9570/11375] loss=0.3024, lr=0.0000185, metrics:accuracy:0.8350,f1:0.7799
INFO:root:08:20:47 [Epoch 1 Batch 9580/11375] loss=0.3359, lr=0.0000185, metrics:accuracy:0.8350,f1:0.7800
INFO:root:08:20:49 [Epoch 1 Batch 9590/11375] loss=0.3184, lr=0.0000185, metrics:accuracy:0.8351,f1:0.7800
INFO:root:08:20:50 [Epoch 1 Batch 9600/11375] loss=0.2148, lr=0.0000185, metrics:accuracy:0.8351,f1:0.7800
INFO:root:08:20:51 [Epoch 1 Batch 9610/11375] loss=0.2402, lr=0.0000185, metrics:accuracy:0.8352,f1:0.7802
INFO:root:08:20:52 [Epoch 1 Batch 9620/11375] loss=0.2562, lr=0.0000185, metrics:accuracy:0.8353,f1:0.7802
INFO:root:08:20:54 [Epoch 1 Batch 9630/11375] loss=0.2445, lr=0.0000185, metrics:accuracy:0.8354,f1:0.7803
INFO:root:08:20:55 [Epoch 1 Batch 9640/11375] loss=0.3347, lr=0.0000185, metrics:accuracy:0.8354,f1:0.7804
INFO:root:08:20:56 [Epoch 1 Batch 9650/11375] loss=0.3258, lr=0.0000185, metrics:accuracy:0.8354,f1:0.7804
INFO:root:08:20:57 [Epoch 1 Batch 9660/11375] loss=0.2890, lr=0.0000184, metrics:accuracy:0.8354,f1:0.7804
INFO:root:08:20:59 [Epoch 1 Batch 9670/11375] loss=0.2578, lr=0.0000184, metrics:accuracy:0.8355,f1:0.7805
INFO:root:08:21:00 [Epoch 1 Batch 9680/11375] loss=0.3583, lr=0.0000184, metrics:accuracy:0.8355,f1:0.7805
INFO:root:08:21:01 [Epoch 1 Batch 9690/11375] loss=0.2632, lr=0.0000184, metrics:accuracy:0.8356,f1:0.7806
INFO:root:08:21:02 [Epoch 1 Batch 9700/11375] loss=0.2527, lr=0.0000184, metrics:accuracy:0.8356,f1:0.7807
INFO:root:08:21:03 [Epoch 1 Batch 9710/11375] loss=0.2809, lr=0.0000184, metrics:accuracy:0.8357,f1:0.7808
INFO:root:08:21:04 [Epoch 1 Batch 9720/11375] loss=0.3474, lr=0.0000184, metrics:accuracy:0.8357,f1:0.7808
INFO:root:08:21:06 [Epoch 1 Batch 9730/11375] loss=0.3242, lr=0.0000184, metrics:accuracy:0.8357,f1:0.7808
INFO:root:08:21:07 [Epoch 1 Batch 9740/11375] loss=0.2405, lr=0.0000184, metrics:accuracy:0.8358,f1:0.7809
INFO:root:08:21:08 [Epoch 1 Batch 9750/11375] loss=0.3022, lr=0.0000184, metrics:accuracy:0.8358,f1:0.7809
INFO:root:08:21:09 [Epoch 1 Batch 9760/11375] loss=0.3270, lr=0.0000184, metrics:accuracy:0.8358,f1:0.7810
INFO:root:08:21:10 [Epoch 1 Batch 9770/11375] loss=0.2712, lr=0.0000184, metrics:accuracy:0.8359,f1:0.7811
INFO:root:08:21:11 [Epoch 1 Batch 9780/11375] loss=0.3270, lr=0.0000184, metrics:accuracy:0.8359,f1:0.7811
INFO:root:08:21:12 [Epoch 1 Batch 9790/11375] loss=0.2246, lr=0.0000184, metrics:accuracy:0.8360,f1:0.7812
INFO:root:08:21:14 [Epoch 1 Batch 9800/11375] loss=0.2472, lr=0.0000184, metrics:accuracy:0.8360,f1:0.7813
INFO:root:08:21:15 [Epoch 1 Batch 9810/11375] loss=0.2913, lr=0.0000184, metrics:accuracy:0.8361,f1:0.7813
INFO:root:08:21:16 [Epoch 1 Batch 9820/11375] loss=0.2717, lr=0.0000184, metrics:accuracy:0.8361,f1:0.7814
INFO:root:08:21:17 [Epoch 1 Batch 9830/11375] loss=0.2681, lr=0.0000184, metrics:accuracy:0.8362,f1:0.7815
INFO:root:08:21:18 [Epoch 1 Batch 9840/11375] loss=0.3051, lr=0.0000184, metrics:accuracy:0.8362,f1:0.7815
INFO:root:08:21:19 [Epoch 1 Batch 9850/11375] loss=0.3150, lr=0.0000184, metrics:accuracy:0.8362,f1:0.7816
INFO:root:08:21:21 [Epoch 1 Batch 9860/11375] loss=0.3754, lr=0.0000184, metrics:accuracy:0.8362,f1:0.7816
INFO:root:08:21:22 [Epoch 1 Batch 9870/11375] loss=0.2952, lr=0.0000184, metrics:accuracy:0.8363,f1:0.7817
INFO:root:08:21:23 [Epoch 1 Batch 9880/11375] loss=0.2879, lr=0.0000184, metrics:accuracy:0.8363,f1:0.7817
INFO:root:08:21:24 [Epoch 1 Batch 9890/11375] loss=0.2531, lr=0.0000184, metrics:accuracy:0.8364,f1:0.7818
INFO:root:08:21:26 [Epoch 1 Batch 9900/11375] loss=0.2306, lr=0.0000184, metrics:accuracy:0.8364,f1:0.7818
INFO:root:08:21:27 [Epoch 1 Batch 9910/11375] loss=0.2980, lr=0.0000183, metrics:accuracy:0.8365,f1:0.7818
INFO:root:08:21:28 [Epoch 1 Batch 9920/11375] loss=0.2379, lr=0.0000183, metrics:accuracy:0.8365,f1:0.7819
INFO:root:08:21:29 [Epoch 1 Batch 9930/11375] loss=0.2297, lr=0.0000183, metrics:accuracy:0.8366,f1:0.7819
INFO:root:08:21:30 [Epoch 1 Batch 9940/11375] loss=0.2885, lr=0.0000183, metrics:accuracy:0.8366,f1:0.7820
INFO:root:08:21:32 [Epoch 1 Batch 9950/11375] loss=0.2655, lr=0.0000183, metrics:accuracy:0.8367,f1:0.7821
INFO:root:08:21:33 [Epoch 1 Batch 9960/11375] loss=0.1889, lr=0.0000183, metrics:accuracy:0.8367,f1:0.7822
INFO:root:08:21:34 [Epoch 1 Batch 9970/11375] loss=0.2764, lr=0.0000183, metrics:accuracy:0.8368,f1:0.7823
INFO:root:08:21:35 [Epoch 1 Batch 9980/11375] loss=0.3161, lr=0.0000183, metrics:accuracy:0.8368,f1:0.7823
INFO:root:08:21:36 [Epoch 1 Batch 9990/11375] loss=0.3152, lr=0.0000183, metrics:accuracy:0.8368,f1:0.7823
INFO:root:08:21:37 [Epoch 1 Batch 10000/11375] loss=0.2879, lr=0.0000183, metrics:accuracy:0.8369,f1:0.7824
INFO:root:08:21:38 [Epoch 1 Batch 10010/11375] loss=0.2740, lr=0.0000183, metrics:accuracy:0.8369,f1:0.7825
INFO:root:08:21:40 [Epoch 1 Batch 10020/11375] loss=0.2964, lr=0.0000183, metrics:accuracy:0.8369,f1:0.7825
INFO:root:08:21:41 [Epoch 1 Batch 10030/11375] loss=0.2121, lr=0.0000183, metrics:accuracy:0.8370,f1:0.7826
INFO:root:08:21:42 [Epoch 1 Batch 10040/11375] loss=0.3593, lr=0.0000183, metrics:accuracy:0.8370,f1:0.7826
INFO:root:08:21:43 [Epoch 1 Batch 10050/11375] loss=0.3222, lr=0.0000183, metrics:accuracy:0.8370,f1:0.7827
INFO:root:08:21:44 [Epoch 1 Batch 10060/11375] loss=0.2451, lr=0.0000183, metrics:accuracy:0.8371,f1:0.7827
INFO:root:08:21:46 [Epoch 1 Batch 10070/11375] loss=0.2788, lr=0.0000183, metrics:accuracy:0.8371,f1:0.7828
INFO:root:08:21:47 [Epoch 1 Batch 10080/11375] loss=0.2560, lr=0.0000183, metrics:accuracy:0.8372,f1:0.7829
INFO:root:08:21:48 [Epoch 1 Batch 10090/11375] loss=0.2692, lr=0.0000183, metrics:accuracy:0.8372,f1:0.7829
INFO:root:08:21:49 [Epoch 1 Batch 10100/11375] loss=0.2630, lr=0.0000183, metrics:accuracy:0.8373,f1:0.7830
INFO:root:08:21:50 [Epoch 1 Batch 10110/11375] loss=0.2151, lr=0.0000183, metrics:accuracy:0.8373,f1:0.7830
INFO:root:08:21:51 [Epoch 1 Batch 10120/11375] loss=0.2952, lr=0.0000183, metrics:accuracy:0.8374,f1:0.7831
INFO:root:08:21:53 [Epoch 1 Batch 10130/11375] loss=0.2526, lr=0.0000183, metrics:accuracy:0.8374,f1:0.7832
INFO:root:08:21:54 [Epoch 1 Batch 10140/11375] loss=0.3049, lr=0.0000183, metrics:accuracy:0.8375,f1:0.7833
INFO:root:08:21:55 [Epoch 1 Batch 10150/11375] loss=0.2621, lr=0.0000183, metrics:accuracy:0.8375,f1:0.7833
INFO:root:08:21:56 [Epoch 1 Batch 10160/11375] loss=0.3249, lr=0.0000183, metrics:accuracy:0.8375,f1:0.7834
INFO:root:08:21:58 [Epoch 1 Batch 10170/11375] loss=0.2607, lr=0.0000182, metrics:accuracy:0.8376,f1:0.7834
INFO:root:08:21:59 [Epoch 1 Batch 10180/11375] loss=0.2853, lr=0.0000182, metrics:accuracy:0.8376,f1:0.7835
INFO:root:08:22:00 [Epoch 1 Batch 10190/11375] loss=0.2591, lr=0.0000182, metrics:accuracy:0.8377,f1:0.7835
INFO:root:08:22:01 [Epoch 1 Batch 10200/11375] loss=0.2681, lr=0.0000182, metrics:accuracy:0.8377,f1:0.7836
INFO:root:08:22:02 [Epoch 1 Batch 10210/11375] loss=0.1839, lr=0.0000182, metrics:accuracy:0.8378,f1:0.7836
INFO:root:08:22:03 [Epoch 1 Batch 10220/11375] loss=0.2699, lr=0.0000182, metrics:accuracy:0.8378,f1:0.7837
INFO:root:08:22:05 [Epoch 1 Batch 10230/11375] loss=0.2622, lr=0.0000182, metrics:accuracy:0.8379,f1:0.7838
INFO:root:08:22:06 [Epoch 1 Batch 10240/11375] loss=0.2516, lr=0.0000182, metrics:accuracy:0.8379,f1:0.7838
INFO:root:08:22:07 [Epoch 1 Batch 10250/11375] loss=0.3624, lr=0.0000182, metrics:accuracy:0.8380,f1:0.7839
INFO:root:08:22:08 [Epoch 1 Batch 10260/11375] loss=0.2313, lr=0.0000182, metrics:accuracy:0.8380,f1:0.7840
INFO:root:08:22:10 [Epoch 1 Batch 10270/11375] loss=0.3007, lr=0.0000182, metrics:accuracy:0.8381,f1:0.7840
INFO:root:08:22:11 [Epoch 1 Batch 10280/11375] loss=0.3275, lr=0.0000182, metrics:accuracy:0.8381,f1:0.7841
INFO:root:08:22:12 [Epoch 1 Batch 10290/11375] loss=0.2256, lr=0.0000182, metrics:accuracy:0.8382,f1:0.7842
INFO:root:08:22:13 [Epoch 1 Batch 10300/11375] loss=0.2547, lr=0.0000182, metrics:accuracy:0.8382,f1:0.7842
INFO:root:08:22:14 [Epoch 1 Batch 10310/11375] loss=0.2981, lr=0.0000182, metrics:accuracy:0.8382,f1:0.7843
INFO:root:08:22:15 [Epoch 1 Batch 10320/11375] loss=0.3306, lr=0.0000182, metrics:accuracy:0.8382,f1:0.7843
INFO:root:08:22:17 [Epoch 1 Batch 10330/11375] loss=0.2506, lr=0.0000182, metrics:accuracy:0.8383,f1:0.7843
INFO:root:08:22:18 [Epoch 1 Batch 10340/11375] loss=0.2815, lr=0.0000182, metrics:accuracy:0.8383,f1:0.7843
INFO:root:08:22:19 [Epoch 1 Batch 10350/11375] loss=0.3304, lr=0.0000182, metrics:accuracy:0.8383,f1:0.7844
INFO:root:08:22:20 [Epoch 1 Batch 10360/11375] loss=0.2334, lr=0.0000182, metrics:accuracy:0.8383,f1:0.7845
INFO:root:08:22:21 [Epoch 1 Batch 10370/11375] loss=0.2885, lr=0.0000182, metrics:accuracy:0.8384,f1:0.7845
INFO:root:08:22:23 [Epoch 1 Batch 10380/11375] loss=0.3306, lr=0.0000182, metrics:accuracy:0.8384,f1:0.7845
INFO:root:08:22:24 [Epoch 1 Batch 10390/11375] loss=0.2889, lr=0.0000182, metrics:accuracy:0.8384,f1:0.7846
INFO:root:08:22:25 [Epoch 1 Batch 10400/11375] loss=0.2206, lr=0.0000182, metrics:accuracy:0.8385,f1:0.7846
INFO:root:08:22:26 [Epoch 1 Batch 10410/11375] loss=0.2747, lr=0.0000182, metrics:accuracy:0.8385,f1:0.7847
INFO:root:08:22:28 [Epoch 1 Batch 10420/11375] loss=0.3026, lr=0.0000181, metrics:accuracy:0.8386,f1:0.7846
INFO:root:08:22:29 [Epoch 1 Batch 10430/11375] loss=0.2501, lr=0.0000181, metrics:accuracy:0.8386,f1:0.7847
INFO:root:08:22:30 [Epoch 1 Batch 10440/11375] loss=0.2490, lr=0.0000181, metrics:accuracy:0.8387,f1:0.7847
INFO:root:08:22:31 [Epoch 1 Batch 10450/11375] loss=0.3679, lr=0.0000181, metrics:accuracy:0.8386,f1:0.7848
INFO:root:08:22:32 [Epoch 1 Batch 10460/11375] loss=0.3275, lr=0.0000181, metrics:accuracy:0.8386,f1:0.7848
INFO:root:08:22:34 [Epoch 1 Batch 10470/11375] loss=0.2571, lr=0.0000181, metrics:accuracy:0.8387,f1:0.7848
INFO:root:08:22:35 [Epoch 1 Batch 10480/11375] loss=0.2156, lr=0.0000181, metrics:accuracy:0.8388,f1:0.7849
INFO:root:08:22:36 [Epoch 1 Batch 10490/11375] loss=0.2479, lr=0.0000181, metrics:accuracy:0.8388,f1:0.7850
INFO:root:08:22:37 [Epoch 1 Batch 10500/11375] loss=0.2723, lr=0.0000181, metrics:accuracy:0.8389,f1:0.7851
INFO:root:08:22:38 [Epoch 1 Batch 10510/11375] loss=0.2607, lr=0.0000181, metrics:accuracy:0.8389,f1:0.7852
INFO:root:08:22:39 [Epoch 1 Batch 10520/11375] loss=0.3862, lr=0.0000181, metrics:accuracy:0.8389,f1:0.7852
INFO:root:08:22:40 [Epoch 1 Batch 10530/11375] loss=0.2710, lr=0.0000181, metrics:accuracy:0.8390,f1:0.7853
INFO:root:08:22:42 [Epoch 1 Batch 10540/11375] loss=0.2880, lr=0.0000181, metrics:accuracy:0.8390,f1:0.7853
INFO:root:08:22:43 [Epoch 1 Batch 10550/11375] loss=0.2351, lr=0.0000181, metrics:accuracy:0.8391,f1:0.7854
INFO:root:08:22:44 [Epoch 1 Batch 10560/11375] loss=0.2551, lr=0.0000181, metrics:accuracy:0.8391,f1:0.7854
INFO:root:08:22:45 [Epoch 1 Batch 10570/11375] loss=0.3234, lr=0.0000181, metrics:accuracy:0.8391,f1:0.7855
INFO:root:08:22:46 [Epoch 1 Batch 10580/11375] loss=0.2780, lr=0.0000181, metrics:accuracy:0.8392,f1:0.7855
INFO:root:08:22:47 [Epoch 1 Batch 10590/11375] loss=0.3098, lr=0.0000181, metrics:accuracy:0.8392,f1:0.7856
INFO:root:08:22:48 [Epoch 1 Batch 10600/11375] loss=0.3163, lr=0.0000181, metrics:accuracy:0.8392,f1:0.7856
INFO:root:08:22:50 [Epoch 1 Batch 10610/11375] loss=0.3323, lr=0.0000181, metrics:accuracy:0.8392,f1:0.7856
INFO:root:08:22:51 [Epoch 1 Batch 10620/11375] loss=0.2635, lr=0.0000181, metrics:accuracy:0.8393,f1:0.7857
INFO:root:08:22:52 [Epoch 1 Batch 10630/11375] loss=0.2382, lr=0.0000181, metrics:accuracy:0.8393,f1:0.7857
INFO:root:08:22:53 [Epoch 1 Batch 10640/11375] loss=0.2625, lr=0.0000181, metrics:accuracy:0.8394,f1:0.7858
INFO:root:08:22:55 [Epoch 1 Batch 10650/11375] loss=0.2522, lr=0.0000181, metrics:accuracy:0.8394,f1:0.7859
INFO:root:08:22:56 [Epoch 1 Batch 10660/11375] loss=0.2983, lr=0.0000181, metrics:accuracy:0.8395,f1:0.7860
INFO:root:08:22:57 [Epoch 1 Batch 10670/11375] loss=0.2995, lr=0.0000181, metrics:accuracy:0.8395,f1:0.7860
INFO:root:08:22:58 [Epoch 1 Batch 10680/11375] loss=0.3141, lr=0.0000180, metrics:accuracy:0.8395,f1:0.7861
INFO:root:08:22:59 [Epoch 1 Batch 10690/11375] loss=0.2403, lr=0.0000180, metrics:accuracy:0.8396,f1:0.7861
INFO:root:08:23:01 [Epoch 1 Batch 10700/11375] loss=0.2901, lr=0.0000180, metrics:accuracy:0.8396,f1:0.7862
INFO:root:08:23:02 [Epoch 1 Batch 10710/11375] loss=0.3279, lr=0.0000180, metrics:accuracy:0.8396,f1:0.7862
INFO:root:08:23:03 [Epoch 1 Batch 10720/11375] loss=0.3136, lr=0.0000180, metrics:accuracy:0.8396,f1:0.7862
INFO:root:08:23:04 [Epoch 1 Batch 10730/11375] loss=0.3094, lr=0.0000180, metrics:accuracy:0.8397,f1:0.7863
INFO:root:08:23:05 [Epoch 1 Batch 10740/11375] loss=0.2882, lr=0.0000180, metrics:accuracy:0.8397,f1:0.7864
INFO:root:08:23:06 [Epoch 1 Batch 10750/11375] loss=0.3447, lr=0.0000180, metrics:accuracy:0.8397,f1:0.7864
INFO:root:08:23:08 [Epoch 1 Batch 10760/11375] loss=0.2686, lr=0.0000180, metrics:accuracy:0.8397,f1:0.7864
INFO:root:08:23:09 [Epoch 1 Batch 10770/11375] loss=0.2114, lr=0.0000180, metrics:accuracy:0.8398,f1:0.7865
INFO:root:08:23:10 [Epoch 1 Batch 10780/11375] loss=0.2211, lr=0.0000180, metrics:accuracy:0.8399,f1:0.7866
INFO:root:08:23:11 [Epoch 1 Batch 10790/11375] loss=0.3783, lr=0.0000180, metrics:accuracy:0.8399,f1:0.7866
INFO:root:08:23:12 [Epoch 1 Batch 10800/11375] loss=0.2692, lr=0.0000180, metrics:accuracy:0.8399,f1:0.7866
INFO:root:08:23:14 [Epoch 1 Batch 10810/11375] loss=0.3039, lr=0.0000180, metrics:accuracy:0.8399,f1:0.7866
INFO:root:08:23:15 [Epoch 1 Batch 10820/11375] loss=0.2475, lr=0.0000180, metrics:accuracy:0.8399,f1:0.7867
INFO:root:08:23:16 [Epoch 1 Batch 10830/11375] loss=0.2784, lr=0.0000180, metrics:accuracy:0.8400,f1:0.7867
INFO:root:08:23:17 [Epoch 1 Batch 10840/11375] loss=0.3195, lr=0.0000180, metrics:accuracy:0.8400,f1:0.7868
INFO:root:08:23:18 [Epoch 1 Batch 10850/11375] loss=0.2720, lr=0.0000180, metrics:accuracy:0.8400,f1:0.7868
INFO:root:08:23:19 [Epoch 1 Batch 10860/11375] loss=0.3247, lr=0.0000180, metrics:accuracy:0.8401,f1:0.7868
INFO:root:08:23:20 [Epoch 1 Batch 10870/11375] loss=0.3117, lr=0.0000180, metrics:accuracy:0.8401,f1:0.7869
INFO:root:08:23:22 [Epoch 1 Batch 10880/11375] loss=0.2515, lr=0.0000180, metrics:accuracy:0.8401,f1:0.7870
INFO:root:08:23:23 [Epoch 1 Batch 10890/11375] loss=0.2225, lr=0.0000180, metrics:accuracy:0.8402,f1:0.7870
INFO:root:08:23:24 [Epoch 1 Batch 10900/11375] loss=0.3108, lr=0.0000180, metrics:accuracy:0.8402,f1:0.7870
INFO:root:08:23:25 [Epoch 1 Batch 10910/11375] loss=0.2823, lr=0.0000180, metrics:accuracy:0.8402,f1:0.7871
INFO:root:08:23:26 [Epoch 1 Batch 10920/11375] loss=0.2614, lr=0.0000180, metrics:accuracy:0.8403,f1:0.7872
INFO:root:08:23:28 [Epoch 1 Batch 10930/11375] loss=0.3150, lr=0.0000180, metrics:accuracy:0.8403,f1:0.7872
INFO:root:08:23:29 [Epoch 1 Batch 10940/11375] loss=0.2512, lr=0.0000179, metrics:accuracy:0.8404,f1:0.7873
INFO:root:08:23:30 [Epoch 1 Batch 10950/11375] loss=0.3062, lr=0.0000179, metrics:accuracy:0.8404,f1:0.7873
INFO:root:08:23:31 [Epoch 1 Batch 10960/11375] loss=0.3248, lr=0.0000179, metrics:accuracy:0.8404,f1:0.7873
INFO:root:08:23:33 [Epoch 1 Batch 10970/11375] loss=0.1911, lr=0.0000179, metrics:accuracy:0.8405,f1:0.7874
INFO:root:08:23:34 [Epoch 1 Batch 10980/11375] loss=0.2819, lr=0.0000179, metrics:accuracy:0.8405,f1:0.7875
INFO:root:08:23:35 [Epoch 1 Batch 10990/11375] loss=0.3215, lr=0.0000179, metrics:accuracy:0.8405,f1:0.7874
INFO:root:08:23:36 [Epoch 1 Batch 11000/11375] loss=0.2654, lr=0.0000179, metrics:accuracy:0.8406,f1:0.7875
INFO:root:08:23:37 [Epoch 1 Batch 11010/11375] loss=0.2183, lr=0.0000179, metrics:accuracy:0.8406,f1:0.7876
INFO:root:08:23:38 [Epoch 1 Batch 11020/11375] loss=0.2534, lr=0.0000179, metrics:accuracy:0.8406,f1:0.7876
INFO:root:08:23:39 [Epoch 1 Batch 11030/11375] loss=0.3134, lr=0.0000179, metrics:accuracy:0.8407,f1:0.7877
INFO:root:08:23:41 [Epoch 1 Batch 11040/11375] loss=0.2484, lr=0.0000179, metrics:accuracy:0.8407,f1:0.7877
INFO:root:08:23:42 [Epoch 1 Batch 11050/11375] loss=0.2904, lr=0.0000179, metrics:accuracy:0.8407,f1:0.7877
INFO:root:08:23:43 [Epoch 1 Batch 11060/11375] loss=0.2489, lr=0.0000179, metrics:accuracy:0.8408,f1:0.7878
INFO:root:08:23:44 [Epoch 1 Batch 11070/11375] loss=0.3736, lr=0.0000179, metrics:accuracy:0.8408,f1:0.7878
INFO:root:08:23:45 [Epoch 1 Batch 11080/11375] loss=0.2494, lr=0.0000179, metrics:accuracy:0.8408,f1:0.7878
INFO:root:08:23:47 [Epoch 1 Batch 11090/11375] loss=0.3636, lr=0.0000179, metrics:accuracy:0.8408,f1:0.7878
INFO:root:08:23:48 [Epoch 1 Batch 11100/11375] loss=0.2072, lr=0.0000179, metrics:accuracy:0.8409,f1:0.7879
INFO:root:08:23:49 [Epoch 1 Batch 11110/11375] loss=0.2811, lr=0.0000179, metrics:accuracy:0.8410,f1:0.7880
INFO:root:08:23:50 [Epoch 1 Batch 11120/11375] loss=0.2800, lr=0.0000179, metrics:accuracy:0.8410,f1:0.7880
INFO:root:08:23:51 [Epoch 1 Batch 11130/11375] loss=0.2965, lr=0.0000179, metrics:accuracy:0.8410,f1:0.7881
INFO:root:08:23:53 [Epoch 1 Batch 11140/11375] loss=0.2087, lr=0.0000179, metrics:accuracy:0.8411,f1:0.7881
INFO:root:08:23:54 [Epoch 1 Batch 11150/11375] loss=0.2754, lr=0.0000179, metrics:accuracy:0.8411,f1:0.7882
INFO:root:08:23:55 [Epoch 1 Batch 11160/11375] loss=0.2884, lr=0.0000179, metrics:accuracy:0.8411,f1:0.7882
INFO:root:08:23:56 [Epoch 1 Batch 11170/11375] loss=0.2386, lr=0.0000179, metrics:accuracy:0.8411,f1:0.7882
INFO:root:08:23:57 [Epoch 1 Batch 11180/11375] loss=0.3026, lr=0.0000179, metrics:accuracy:0.8412,f1:0.7882
INFO:root:08:23:59 [Epoch 1 Batch 11190/11375] loss=0.2532, lr=0.0000178, metrics:accuracy:0.8412,f1:0.7883
INFO:root:08:24:00 [Epoch 1 Batch 11200/11375] loss=0.2689, lr=0.0000178, metrics:accuracy:0.8413,f1:0.7883
INFO:root:08:24:01 [Epoch 1 Batch 11210/11375] loss=0.2332, lr=0.0000178, metrics:accuracy:0.8413,f1:0.7883
INFO:root:08:24:02 [Epoch 1 Batch 11220/11375] loss=0.3281, lr=0.0000178, metrics:accuracy:0.8413,f1:0.7883
INFO:root:08:24:03 [Epoch 1 Batch 11230/11375] loss=0.3332, lr=0.0000178, metrics:accuracy:0.8413,f1:0.7884
INFO:root:08:24:05 [Epoch 1 Batch 11240/11375] loss=0.2875, lr=0.0000178, metrics:accuracy:0.8413,f1:0.7884
INFO:root:08:24:06 [Epoch 1 Batch 11250/11375] loss=0.2300, lr=0.0000178, metrics:accuracy:0.8414,f1:0.7884
INFO:root:08:24:07 [Epoch 1 Batch 11260/11375] loss=0.2837, lr=0.0000178, metrics:accuracy:0.8414,f1:0.7885
INFO:root:08:24:08 [Epoch 1 Batch 11270/11375] loss=0.2912, lr=0.0000178, metrics:accuracy:0.8415,f1:0.7885
INFO:root:08:24:09 [Epoch 1 Batch 11280/11375] loss=0.3147, lr=0.0000178, metrics:accuracy:0.8415,f1:0.7885
INFO:root:08:24:10 [Epoch 1 Batch 11290/11375] loss=0.3380, lr=0.0000178, metrics:accuracy:0.8415,f1:0.7886
INFO:root:08:24:12 [Epoch 1 Batch 11300/11375] loss=0.2938, lr=0.0000178, metrics:accuracy:0.8415,f1:0.7886
INFO:root:08:24:13 [Epoch 1 Batch 11310/11375] loss=0.3051, lr=0.0000178, metrics:accuracy:0.8415,f1:0.7887
INFO:root:08:24:14 [Epoch 1 Batch 11320/11375] loss=0.3084, lr=0.0000178, metrics:accuracy:0.8416,f1:0.7887
INFO:root:08:24:15 [Epoch 1 Batch 11330/11375] loss=0.2695, lr=0.0000178, metrics:accuracy:0.8416,f1:0.7888
INFO:root:08:24:16 [Epoch 1 Batch 11340/11375] loss=0.2478, lr=0.0000178, metrics:accuracy:0.8417,f1:0.7888
INFO:root:08:24:17 [Epoch 1 Batch 11350/11375] loss=0.2833, lr=0.0000178, metrics:accuracy:0.8417,f1:0.7888
INFO:root:08:24:19 [Epoch 1 Batch 11360/11375] loss=0.2875, lr=0.0000178, metrics:accuracy:0.8417,f1:0.7888
INFO:root:08:24:20 [Epoch 1 Batch 11370/11375] loss=0.2647, lr=0.0000178, metrics:accuracy:0.8417,f1:0.7889
INFO:root:08:24:20 Now we are doing evaluation on dev with gpu(0).
INFO:root:08:24:21 [Batch 10/5054] loss=0.2250, metrics:accuracy:0.8875,f1:0.8085
INFO:root:08:24:21 [Batch 20/5054] loss=0.3398, metrics:accuracy:0.8562,f1:0.7677
INFO:root:08:24:21 [Batch 30/5054] loss=0.2886, metrics:accuracy:0.8625,f1:0.7843
INFO:root:08:24:21 [Batch 40/5054] loss=0.1720, metrics:accuracy:0.8750,f1:0.8165
INFO:root:08:24:21 [Batch 50/5054] loss=0.2341, metrics:accuracy:0.8850,f1:0.8296
INFO:root:08:24:22 [Batch 60/5054] loss=0.4213, metrics:accuracy:0.8750,f1:0.8137
INFO:root:08:24:22 [Batch 70/5054] loss=0.1739, metrics:accuracy:0.8821,f1:0.8263
INFO:root:08:24:22 [Batch 80/5054] loss=0.2406, metrics:accuracy:0.8844,f1:0.8255
INFO:root:08:24:22 [Batch 90/5054] loss=0.2466, metrics:accuracy:0.8833,f1:0.8286
INFO:root:08:24:22 [Batch 100/5054] loss=0.2639, metrics:accuracy:0.8838,f1:0.8255
INFO:root:08:24:22 [Batch 110/5054] loss=0.1646, metrics:accuracy:0.8875,f1:0.8284
INFO:root:08:24:23 [Batch 120/5054] loss=0.2784, metrics:accuracy:0.8885,f1:0.8266
INFO:root:08:24:23 [Batch 130/5054] loss=0.1826, metrics:accuracy:0.8913,f1:0.8285
INFO:root:08:24:23 [Batch 140/5054] loss=0.2666, metrics:accuracy:0.8920,f1:0.8269
INFO:root:08:24:23 [Batch 150/5054] loss=0.3898, metrics:accuracy:0.8908,f1:0.8246
INFO:root:08:24:23 [Batch 160/5054] loss=0.2707, metrics:accuracy:0.8891,f1:0.8256
INFO:root:08:24:23 [Batch 170/5054] loss=0.2943, metrics:accuracy:0.8875,f1:0.8239
INFO:root:08:24:24 [Batch 180/5054] loss=0.3327, metrics:accuracy:0.8861,f1:0.8237
INFO:root:08:24:24 [Batch 190/5054] loss=0.1845, metrics:accuracy:0.8868,f1:0.8230
INFO:root:08:24:24 [Batch 200/5054] loss=0.3752, metrics:accuracy:0.8838,f1:0.8201
INFO:root:08:24:24 [Batch 210/5054] loss=0.3538, metrics:accuracy:0.8815,f1:0.8189
INFO:root:08:24:24 [Batch 220/5054] loss=0.1811, metrics:accuracy:0.8847,f1:0.8242
INFO:root:08:24:24 [Batch 230/5054] loss=0.2946, metrics:accuracy:0.8848,f1:0.8259
INFO:root:08:24:25 [Batch 240/5054] loss=0.2672, metrics:accuracy:0.8844,f1:0.8257
INFO:root:08:24:25 [Batch 250/5054] loss=0.2464, metrics:accuracy:0.8845,f1:0.8259
INFO:root:08:24:25 [Batch 260/5054] loss=0.2793, metrics:accuracy:0.8841,f1:0.8270
INFO:root:08:24:25 [Batch 270/5054] loss=0.4253, metrics:accuracy:0.8819,f1:0.8243
INFO:root:08:24:25 [Batch 280/5054] loss=0.2135, metrics:accuracy:0.8817,f1:0.8244
INFO:root:08:24:26 [Batch 290/5054] loss=0.3531, metrics:accuracy:0.8802,f1:0.8216
INFO:root:08:24:26 [Batch 300/5054] loss=0.2286, metrics:accuracy:0.8808,f1:0.8226
INFO:root:08:24:26 [Batch 310/5054] loss=0.2379, metrics:accuracy:0.8810,f1:0.8226
INFO:root:08:24:26 [Batch 320/5054] loss=0.4110, metrics:accuracy:0.8793,f1:0.8217
INFO:root:08:24:26 [Batch 330/5054] loss=0.1911, metrics:accuracy:0.8807,f1:0.8233
INFO:root:08:24:26 [Batch 340/5054] loss=0.1315, metrics:accuracy:0.8827,f1:0.8258
INFO:root:08:24:27 [Batch 350/5054] loss=0.2634, metrics:accuracy:0.8825,f1:0.8247
INFO:root:08:24:27 [Batch 360/5054] loss=0.1691, metrics:accuracy:0.8840,f1:0.8273
INFO:root:08:24:27 [Batch 370/5054] loss=0.3109, metrics:accuracy:0.8841,f1:0.8274
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INFO:root:08:25:33 [Batch 4160/5054] loss=0.3579, metrics:accuracy:0.8821,f1:0.8344
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INFO:root:08:25:33 [Batch 4190/5054] loss=0.2215, metrics:accuracy:0.8823,f1:0.8346
INFO:root:08:25:34 [Batch 4200/5054] loss=0.2894, metrics:accuracy:0.8823,f1:0.8346
INFO:root:08:25:34 [Batch 4210/5054] loss=0.3144, metrics:accuracy:0.8822,f1:0.8345
INFO:root:08:25:34 [Batch 4220/5054] loss=0.3498, metrics:accuracy:0.8822,f1:0.8344
INFO:root:08:25:34 [Batch 4230/5054] loss=0.2357, metrics:accuracy:0.8822,f1:0.8345
INFO:root:08:25:34 [Batch 4240/5054] loss=0.3096, metrics:accuracy:0.8822,f1:0.8344
INFO:root:08:25:35 [Batch 4250/5054] loss=0.2190, metrics:accuracy:0.8822,f1:0.8346
INFO:root:08:25:35 [Batch 4260/5054] loss=0.2643, metrics:accuracy:0.8822,f1:0.8346
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INFO:root:08:25:35 [Batch 4280/5054] loss=0.3179, metrics:accuracy:0.8821,f1:0.8343
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INFO:root:08:25:35 [Batch 4300/5054] loss=0.2545, metrics:accuracy:0.8823,f1:0.8346
INFO:root:08:25:36 [Batch 4310/5054] loss=0.2777, metrics:accuracy:0.8822,f1:0.8344
INFO:root:08:25:36 [Batch 4320/5054] loss=0.3230, metrics:accuracy:0.8821,f1:0.8343
INFO:root:08:25:36 [Batch 4330/5054] loss=0.1993, metrics:accuracy:0.8822,f1:0.8345
INFO:root:08:25:36 [Batch 4340/5054] loss=0.2805, metrics:accuracy:0.8823,f1:0.8345
INFO:root:08:25:36 [Batch 4350/5054] loss=0.3048, metrics:accuracy:0.8822,f1:0.8344
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INFO:root:08:25:37 [Batch 4370/5054] loss=0.3315, metrics:accuracy:0.8822,f1:0.8343
INFO:root:08:25:37 [Batch 4380/5054] loss=0.3493, metrics:accuracy:0.8821,f1:0.8343
INFO:root:08:25:37 [Batch 4390/5054] loss=0.4080, metrics:accuracy:0.8819,f1:0.8340
INFO:root:08:25:37 [Batch 4400/5054] loss=0.2369, metrics:accuracy:0.8820,f1:0.8340
INFO:root:08:25:37 [Batch 4410/5054] loss=0.2174, metrics:accuracy:0.8820,f1:0.8339
INFO:root:08:25:37 [Batch 4420/5054] loss=0.2187, metrics:accuracy:0.8821,f1:0.8340
INFO:root:08:25:38 [Batch 4430/5054] loss=0.3119, metrics:accuracy:0.8820,f1:0.8340
INFO:root:08:25:38 [Batch 4440/5054] loss=0.2298, metrics:accuracy:0.8821,f1:0.8342
INFO:root:08:25:38 [Batch 4450/5054] loss=0.2093, metrics:accuracy:0.8822,f1:0.8343
INFO:root:08:25:38 [Batch 4460/5054] loss=0.2606, metrics:accuracy:0.8822,f1:0.8343
INFO:root:08:25:38 [Batch 4470/5054] loss=0.2179, metrics:accuracy:0.8824,f1:0.8345
INFO:root:08:25:39 [Batch 4480/5054] loss=0.2580, metrics:accuracy:0.8824,f1:0.8346
INFO:root:08:25:39 [Batch 4490/5054] loss=0.2111, metrics:accuracy:0.8825,f1:0.8347
INFO:root:08:25:39 [Batch 4500/5054] loss=0.1612, metrics:accuracy:0.8826,f1:0.8348
INFO:root:08:25:39 [Batch 4510/5054] loss=0.2659, metrics:accuracy:0.8826,f1:0.8348
INFO:root:08:25:39 [Batch 4520/5054] loss=0.2789, metrics:accuracy:0.8827,f1:0.8348
INFO:root:08:25:39 [Batch 4530/5054] loss=0.2233, metrics:accuracy:0.8828,f1:0.8350
INFO:root:08:25:40 [Batch 4540/5054] loss=0.1558, metrics:accuracy:0.8829,f1:0.8351
INFO:root:08:25:40 [Batch 4550/5054] loss=0.3963, metrics:accuracy:0.8828,f1:0.8350
INFO:root:08:25:40 [Batch 4560/5054] loss=0.2673, metrics:accuracy:0.8828,f1:0.8351
INFO:root:08:25:40 [Batch 4570/5054] loss=0.3403, metrics:accuracy:0.8828,f1:0.8350
INFO:root:08:25:40 [Batch 4580/5054] loss=0.3143, metrics:accuracy:0.8828,f1:0.8350
INFO:root:08:25:40 [Batch 4590/5054] loss=0.2808, metrics:accuracy:0.8828,f1:0.8350
INFO:root:08:25:41 [Batch 4600/5054] loss=0.3319, metrics:accuracy:0.8827,f1:0.8350
INFO:root:08:25:41 [Batch 4610/5054] loss=0.1571, metrics:accuracy:0.8829,f1:0.8352
INFO:root:08:25:41 [Batch 4620/5054] loss=0.2186, metrics:accuracy:0.8829,f1:0.8353
INFO:root:08:25:41 [Batch 4630/5054] loss=0.1755, metrics:accuracy:0.8830,f1:0.8354
INFO:root:08:25:41 [Batch 4640/5054] loss=0.2871, metrics:accuracy:0.8830,f1:0.8354
INFO:root:08:25:41 [Batch 4650/5054] loss=0.1428, metrics:accuracy:0.8832,f1:0.8356
INFO:root:08:25:42 [Batch 4660/5054] loss=0.2149, metrics:accuracy:0.8832,f1:0.8357
INFO:root:08:25:42 [Batch 4670/5054] loss=0.1746, metrics:accuracy:0.8833,f1:0.8359
INFO:root:08:25:42 [Batch 4680/5054] loss=0.2833, metrics:accuracy:0.8833,f1:0.8359
INFO:root:08:25:42 [Batch 4690/5054] loss=0.2770, metrics:accuracy:0.8833,f1:0.8358
INFO:root:08:25:42 [Batch 4700/5054] loss=0.3334, metrics:accuracy:0.8831,f1:0.8356
INFO:root:08:25:43 [Batch 4710/5054] loss=0.3347, metrics:accuracy:0.8831,f1:0.8354
INFO:root:08:25:43 [Batch 4720/5054] loss=0.3425, metrics:accuracy:0.8830,f1:0.8354
INFO:root:08:25:43 [Batch 4730/5054] loss=0.4055, metrics:accuracy:0.8829,f1:0.8353
INFO:root:08:25:43 [Batch 4740/5054] loss=0.3025, metrics:accuracy:0.8828,f1:0.8351
INFO:root:08:25:43 [Batch 4750/5054] loss=0.2916, metrics:accuracy:0.8828,f1:0.8351
INFO:root:08:25:43 [Batch 4760/5054] loss=0.2409, metrics:accuracy:0.8828,f1:0.8351
INFO:root:08:25:44 [Batch 4770/5054] loss=0.2230, metrics:accuracy:0.8829,f1:0.8352
INFO:root:08:25:44 [Batch 4780/5054] loss=0.2154, metrics:accuracy:0.8830,f1:0.8353
INFO:root:08:25:44 [Batch 4790/5054] loss=0.3336, metrics:accuracy:0.8830,f1:0.8354
INFO:root:08:25:44 [Batch 4800/5054] loss=0.2639, metrics:accuracy:0.8831,f1:0.8355
INFO:root:08:25:44 [Batch 4810/5054] loss=0.4223, metrics:accuracy:0.8830,f1:0.8354
INFO:root:08:25:44 [Batch 4820/5054] loss=0.2678, metrics:accuracy:0.8829,f1:0.8354
INFO:root:08:25:45 [Batch 4830/5054] loss=0.2176, metrics:accuracy:0.8830,f1:0.8355
INFO:root:08:25:45 [Batch 4840/5054] loss=0.3434, metrics:accuracy:0.8830,f1:0.8355
INFO:root:08:25:45 [Batch 4850/5054] loss=0.2551, metrics:accuracy:0.8830,f1:0.8357
INFO:root:08:25:45 [Batch 4860/5054] loss=0.3070, metrics:accuracy:0.8830,f1:0.8357
INFO:root:08:25:45 [Batch 4870/5054] loss=0.1817, metrics:accuracy:0.8830,f1:0.8355
INFO:root:08:25:46 [Batch 4880/5054] loss=0.2240, metrics:accuracy:0.8830,f1:0.8356
INFO:root:08:25:46 [Batch 4890/5054] loss=0.3116, metrics:accuracy:0.8830,f1:0.8355
INFO:root:08:25:46 [Batch 4900/5054] loss=0.1824, metrics:accuracy:0.8830,f1:0.8356
INFO:root:08:25:46 [Batch 4910/5054] loss=0.2803, metrics:accuracy:0.8830,f1:0.8355
INFO:root:08:25:46 [Batch 4920/5054] loss=0.2930, metrics:accuracy:0.8829,f1:0.8353
INFO:root:08:25:46 [Batch 4930/5054] loss=0.2745, metrics:accuracy:0.8828,f1:0.8352
INFO:root:08:25:47 [Batch 4940/5054] loss=0.2079, metrics:accuracy:0.8829,f1:0.8353
INFO:root:08:25:47 [Batch 4950/5054] loss=0.3615, metrics:accuracy:0.8827,f1:0.8351
INFO:root:08:25:47 [Batch 4960/5054] loss=0.2133, metrics:accuracy:0.8828,f1:0.8351
INFO:root:08:25:47 [Batch 4970/5054] loss=0.3300, metrics:accuracy:0.8827,f1:0.8350
INFO:root:08:25:47 [Batch 4980/5054] loss=0.2827, metrics:accuracy:0.8827,f1:0.8350
INFO:root:08:25:47 [Batch 4990/5054] loss=0.2824, metrics:accuracy:0.8827,f1:0.8350
INFO:root:08:25:48 [Batch 5000/5054] loss=0.3444, metrics:accuracy:0.8826,f1:0.8349
INFO:root:08:25:48 [Batch 5010/5054] loss=0.3146, metrics:accuracy:0.8825,f1:0.8348
INFO:root:08:25:48 [Batch 5020/5054] loss=0.3948, metrics:accuracy:0.8824,f1:0.8346
INFO:root:08:25:48 [Batch 5030/5054] loss=0.1992, metrics:accuracy:0.8825,f1:0.8347
INFO:root:08:25:48 [Batch 5040/5054] loss=0.3088, metrics:accuracy:0.8825,f1:0.8347
INFO:root:08:25:48 [Batch 5050/5054] loss=0.2557, metrics:accuracy:0.8825,f1:0.8348
INFO:root:08:25:49 validation metrics:accuracy:0.8825,f1:0.8348
INFO:root:08:25:49 Time cost=88.23s, throughput=458.25 samples/s
INFO:root:08:25:49 params saved in: ./output_dir/model_bert_QQP_0.params
INFO:root:08:25:49 Time cost=1443.52s
INFO:root:08:25:51 [Epoch 2 Batch 10/11375] loss=0.2323, lr=0.0000178, metrics:accuracy:0.9125,f1:0.8923
INFO:root:08:25:52 [Epoch 2 Batch 20/11375] loss=0.1884, lr=0.0000178, metrics:accuracy:0.9187,f1:0.8968
INFO:root:08:25:53 [Epoch 2 Batch 30/11375] loss=0.2824, lr=0.0000178, metrics:accuracy:0.9094,f1:0.8803
INFO:root:08:25:54 [Epoch 2 Batch 40/11375] loss=0.2984, lr=0.0000178, metrics:accuracy:0.9062,f1:0.8763
INFO:root:08:25:55 [Epoch 2 Batch 50/11375] loss=0.2303, lr=0.0000178, metrics:accuracy:0.9069,f1:0.8815
INFO:root:08:25:56 [Epoch 2 Batch 60/11375] loss=0.2518, lr=0.0000178, metrics:accuracy:0.9057,f1:0.8784
INFO:root:08:25:58 [Epoch 2 Batch 70/11375] loss=0.2286, lr=0.0000177, metrics:accuracy:0.9045,f1:0.8747
INFO:root:08:25:59 [Epoch 2 Batch 80/11375] loss=0.2314, lr=0.0000177, metrics:accuracy:0.9051,f1:0.8757
INFO:root:08:26:00 [Epoch 2 Batch 90/11375] loss=0.2047, lr=0.0000177, metrics:accuracy:0.9059,f1:0.8754
INFO:root:08:26:01 [Epoch 2 Batch 100/11375] loss=0.2175, lr=0.0000177, metrics:accuracy:0.9069,f1:0.8779
INFO:root:08:26:03 [Epoch 2 Batch 110/11375] loss=0.2679, lr=0.0000177, metrics:accuracy:0.9057,f1:0.8761
INFO:root:08:26:04 [Epoch 2 Batch 120/11375] loss=0.2542, lr=0.0000177, metrics:accuracy:0.9042,f1:0.8724
INFO:root:08:26:05 [Epoch 2 Batch 130/11375] loss=0.1791, lr=0.0000177, metrics:accuracy:0.9053,f1:0.8718
INFO:root:08:26:07 [Epoch 2 Batch 140/11375] loss=0.2604, lr=0.0000177, metrics:accuracy:0.9049,f1:0.8720
INFO:root:08:26:08 [Epoch 2 Batch 150/11375] loss=0.2243, lr=0.0000177, metrics:accuracy:0.9052,f1:0.8736
INFO:root:08:26:09 [Epoch 2 Batch 160/11375] loss=0.2924, lr=0.0000177, metrics:accuracy:0.9035,f1:0.8719
INFO:root:08:26:10 [Epoch 2 Batch 170/11375] loss=0.1928, lr=0.0000177, metrics:accuracy:0.9050,f1:0.8744
INFO:root:08:26:11 [Epoch 2 Batch 180/11375] loss=0.2317, lr=0.0000177, metrics:accuracy:0.9047,f1:0.8727
INFO:root:08:26:13 [Epoch 2 Batch 190/11375] loss=0.2210, lr=0.0000177, metrics:accuracy:0.9044,f1:0.8720
INFO:root:08:26:14 [Epoch 2 Batch 200/11375] loss=0.2630, lr=0.0000177, metrics:accuracy:0.9036,f1:0.8703
INFO:root:08:26:15 [Epoch 2 Batch 210/11375] loss=0.2232, lr=0.0000177, metrics:accuracy:0.9034,f1:0.8706
INFO:root:08:26:16 [Epoch 2 Batch 220/11375] loss=0.1821, lr=0.0000177, metrics:accuracy:0.9050,f1:0.8721
INFO:root:08:26:17 [Epoch 2 Batch 230/11375] loss=0.2256, lr=0.0000177, metrics:accuracy:0.9052,f1:0.8732
INFO:root:08:26:19 [Epoch 2 Batch 240/11375] loss=0.2239, lr=0.0000177, metrics:accuracy:0.9048,f1:0.8724
INFO:root:08:26:20 [Epoch 2 Batch 250/11375] loss=0.1951, lr=0.0000177, metrics:accuracy:0.9055,f1:0.8736
INFO:root:08:26:21 [Epoch 2 Batch 260/11375] loss=0.1945, lr=0.0000177, metrics:accuracy:0.9061,f1:0.8736
INFO:root:08:26:22 [Epoch 2 Batch 270/11375] loss=0.2397, lr=0.0000177, metrics:accuracy:0.9064,f1:0.8736
INFO:root:08:26:24 [Epoch 2 Batch 280/11375] loss=0.1626, lr=0.0000177, metrics:accuracy:0.9078,f1:0.8747
INFO:root:08:26:25 [Epoch 2 Batch 290/11375] loss=0.1921, lr=0.0000177, metrics:accuracy:0.9082,f1:0.8754
INFO:root:08:26:26 [Epoch 2 Batch 300/11375] loss=0.2929, lr=0.0000177, metrics:accuracy:0.9067,f1:0.8736
INFO:root:08:26:27 [Epoch 2 Batch 310/11375] loss=0.2899, lr=0.0000177, metrics:accuracy:0.9057,f1:0.8730
INFO:root:08:26:29 [Epoch 2 Batch 320/11375] loss=0.2140, lr=0.0000177, metrics:accuracy:0.9055,f1:0.8719
INFO:root:08:26:30 [Epoch 2 Batch 330/11375] loss=0.2457, lr=0.0000176, metrics:accuracy:0.9047,f1:0.8710
INFO:root:08:26:31 [Epoch 2 Batch 340/11375] loss=0.2763, lr=0.0000176, metrics:accuracy:0.9045,f1:0.8716
INFO:root:08:26:32 [Epoch 2 Batch 350/11375] loss=0.2682, lr=0.0000176, metrics:accuracy:0.9036,f1:0.8703
INFO:root:08:26:33 [Epoch 2 Batch 360/11375] loss=0.2689, lr=0.0000176, metrics:accuracy:0.9034,f1:0.8701
INFO:root:08:26:35 [Epoch 2 Batch 370/11375] loss=0.2125, lr=0.0000176, metrics:accuracy:0.9034,f1:0.8700
INFO:root:08:26:36 [Epoch 2 Batch 380/11375] loss=0.2562, lr=0.0000176, metrics:accuracy:0.9027,f1:0.8690
INFO:root:08:26:37 [Epoch 2 Batch 390/11375] loss=0.2083, lr=0.0000176, metrics:accuracy:0.9029,f1:0.8696
INFO:root:08:26:38 [Epoch 2 Batch 400/11375] loss=0.2195, lr=0.0000176, metrics:accuracy:0.9031,f1:0.8700
INFO:root:08:26:39 [Epoch 2 Batch 410/11375] loss=0.2684, lr=0.0000176, metrics:accuracy:0.9030,f1:0.8698
INFO:root:08:26:40 [Epoch 2 Batch 420/11375] loss=0.2589, lr=0.0000176, metrics:accuracy:0.9027,f1:0.8697
INFO:root:08:26:41 [Epoch 2 Batch 430/11375] loss=0.2646, lr=0.0000176, metrics:accuracy:0.9027,f1:0.8701
INFO:root:08:26:43 [Epoch 2 Batch 440/11375] loss=0.2474, lr=0.0000176, metrics:accuracy:0.9021,f1:0.8688
INFO:root:08:26:44 [Epoch 2 Batch 450/11375] loss=0.2313, lr=0.0000176, metrics:accuracy:0.9022,f1:0.8690
INFO:root:08:26:45 [Epoch 2 Batch 460/11375] loss=0.2288, lr=0.0000176, metrics:accuracy:0.9023,f1:0.8688
INFO:root:08:26:46 [Epoch 2 Batch 470/11375] loss=0.3324, lr=0.0000176, metrics:accuracy:0.9017,f1:0.8683
INFO:root:08:26:48 [Epoch 2 Batch 480/11375] loss=0.1822, lr=0.0000176, metrics:accuracy:0.9019,f1:0.8685
INFO:root:08:26:49 [Epoch 2 Batch 490/11375] loss=0.2356, lr=0.0000176, metrics:accuracy:0.9019,f1:0.8690
INFO:root:08:26:50 [Epoch 2 Batch 500/11375] loss=0.2968, lr=0.0000176, metrics:accuracy:0.9015,f1:0.8683
INFO:root:08:26:51 [Epoch 2 Batch 510/11375] loss=0.2504, lr=0.0000176, metrics:accuracy:0.9013,f1:0.8679
INFO:root:08:26:52 [Epoch 2 Batch 520/11375] loss=0.2584, lr=0.0000176, metrics:accuracy:0.9012,f1:0.8675
INFO:root:08:26:53 [Epoch 2 Batch 530/11375] loss=0.2673, lr=0.0000176, metrics:accuracy:0.9013,f1:0.8681
INFO:root:08:26:55 [Epoch 2 Batch 540/11375] loss=0.1751, lr=0.0000176, metrics:accuracy:0.9021,f1:0.8692
INFO:root:08:26:56 [Epoch 2 Batch 550/11375] loss=0.3015, lr=0.0000176, metrics:accuracy:0.9018,f1:0.8690
INFO:root:08:26:57 [Epoch 2 Batch 560/11375] loss=0.2964, lr=0.0000176, metrics:accuracy:0.9010,f1:0.8678
INFO:root:08:26:58 [Epoch 2 Batch 570/11375] loss=0.2144, lr=0.0000176, metrics:accuracy:0.9013,f1:0.8677
INFO:root:08:26:59 [Epoch 2 Batch 580/11375] loss=0.1858, lr=0.0000175, metrics:accuracy:0.9018,f1:0.8684
INFO:root:08:27:01 [Epoch 2 Batch 590/11375] loss=0.1994, lr=0.0000175, metrics:accuracy:0.9019,f1:0.8682
INFO:root:08:27:02 [Epoch 2 Batch 600/11375] loss=0.2903, lr=0.0000175, metrics:accuracy:0.9018,f1:0.8679
INFO:root:08:27:03 [Epoch 2 Batch 610/11375] loss=0.2727, lr=0.0000175, metrics:accuracy:0.9016,f1:0.8676
INFO:root:08:27:05 [Epoch 2 Batch 620/11375] loss=0.1778, lr=0.0000175, metrics:accuracy:0.9021,f1:0.8680
INFO:root:08:27:06 [Epoch 2 Batch 630/11375] loss=0.2203, lr=0.0000175, metrics:accuracy:0.9022,f1:0.8682
INFO:root:08:27:07 [Epoch 2 Batch 640/11375] loss=0.2258, lr=0.0000175, metrics:accuracy:0.9023,f1:0.8684
INFO:root:08:27:08 [Epoch 2 Batch 650/11375] loss=0.2265, lr=0.0000175, metrics:accuracy:0.9020,f1:0.8678
INFO:root:08:27:09 [Epoch 2 Batch 660/11375] loss=0.1987, lr=0.0000175, metrics:accuracy:0.9024,f1:0.8685
INFO:root:08:27:11 [Epoch 2 Batch 670/11375] loss=0.2332, lr=0.0000175, metrics:accuracy:0.9022,f1:0.8680
INFO:root:08:27:12 [Epoch 2 Batch 680/11375] loss=0.2093, lr=0.0000175, metrics:accuracy:0.9023,f1:0.8683
INFO:root:08:27:13 [Epoch 2 Batch 690/11375] loss=0.2728, lr=0.0000175, metrics:accuracy:0.9023,f1:0.8684
INFO:root:08:27:14 [Epoch 2 Batch 700/11375] loss=0.2184, lr=0.0000175, metrics:accuracy:0.9024,f1:0.8686
INFO:root:08:27:15 [Epoch 2 Batch 710/11375] loss=0.2222, lr=0.0000175, metrics:accuracy:0.9025,f1:0.8688
INFO:root:08:27:17 [Epoch 2 Batch 720/11375] loss=0.2065, lr=0.0000175, metrics:accuracy:0.9027,f1:0.8686
INFO:root:08:27:18 [Epoch 2 Batch 730/11375] loss=0.2449, lr=0.0000175, metrics:accuracy:0.9027,f1:0.8687
INFO:root:08:27:19 [Epoch 2 Batch 740/11375] loss=0.1654, lr=0.0000175, metrics:accuracy:0.9032,f1:0.8694
INFO:root:08:27:20 [Epoch 2 Batch 750/11375] loss=0.1511, lr=0.0000175, metrics:accuracy:0.9036,f1:0.8700
INFO:root:08:27:21 [Epoch 2 Batch 760/11375] loss=0.2359, lr=0.0000175, metrics:accuracy:0.9033,f1:0.8695
INFO:root:08:27:23 [Epoch 2 Batch 770/11375] loss=0.3095, lr=0.0000175, metrics:accuracy:0.9028,f1:0.8690
INFO:root:08:27:24 [Epoch 2 Batch 780/11375] loss=0.2417, lr=0.0000175, metrics:accuracy:0.9029,f1:0.8690
INFO:root:08:27:25 [Epoch 2 Batch 790/11375] loss=0.1889, lr=0.0000175, metrics:accuracy:0.9031,f1:0.8692
INFO:root:08:27:26 [Epoch 2 Batch 800/11375] loss=0.2241, lr=0.0000175, metrics:accuracy:0.9030,f1:0.8690
INFO:root:08:27:28 [Epoch 2 Batch 810/11375] loss=0.2795, lr=0.0000175, metrics:accuracy:0.9029,f1:0.8691
INFO:root:08:27:29 [Epoch 2 Batch 820/11375] loss=0.2142, lr=0.0000175, metrics:accuracy:0.9031,f1:0.8695
INFO:root:08:27:30 [Epoch 2 Batch 830/11375] loss=0.1986, lr=0.0000175, metrics:accuracy:0.9034,f1:0.8698
INFO:root:08:27:31 [Epoch 2 Batch 840/11375] loss=0.2473, lr=0.0000174, metrics:accuracy:0.9033,f1:0.8695
INFO:root:08:27:32 [Epoch 2 Batch 850/11375] loss=0.2307, lr=0.0000174, metrics:accuracy:0.9036,f1:0.8699
INFO:root:08:27:34 [Epoch 2 Batch 860/11375] loss=0.2162, lr=0.0000174, metrics:accuracy:0.9037,f1:0.8697
INFO:root:08:27:35 [Epoch 2 Batch 870/11375] loss=0.2952, lr=0.0000174, metrics:accuracy:0.9035,f1:0.8696
INFO:root:08:27:36 [Epoch 2 Batch 880/11375] loss=0.2410, lr=0.0000174, metrics:accuracy:0.9036,f1:0.8695
INFO:root:08:27:37 [Epoch 2 Batch 890/11375] loss=0.2515, lr=0.0000174, metrics:accuracy:0.9033,f1:0.8692
INFO:root:08:27:38 [Epoch 2 Batch 900/11375] loss=0.2205, lr=0.0000174, metrics:accuracy:0.9034,f1:0.8693
INFO:root:08:27:40 [Epoch 2 Batch 910/11375] loss=0.2706, lr=0.0000174, metrics:accuracy:0.9030,f1:0.8692
INFO:root:08:27:41 [Epoch 2 Batch 920/11375] loss=0.3049, lr=0.0000174, metrics:accuracy:0.9025,f1:0.8687
INFO:root:08:27:42 [Epoch 2 Batch 930/11375] loss=0.2374, lr=0.0000174, metrics:accuracy:0.9027,f1:0.8688
INFO:root:08:27:43 [Epoch 2 Batch 940/11375] loss=0.2111, lr=0.0000174, metrics:accuracy:0.9028,f1:0.8689
INFO:root:08:27:44 [Epoch 2 Batch 950/11375] loss=0.2173, lr=0.0000174, metrics:accuracy:0.9030,f1:0.8691
INFO:root:08:27:46 [Epoch 2 Batch 960/11375] loss=0.2043, lr=0.0000174, metrics:accuracy:0.9029,f1:0.8690
INFO:root:08:27:47 [Epoch 2 Batch 970/11375] loss=0.1823, lr=0.0000174, metrics:accuracy:0.9032,f1:0.8693
INFO:root:08:27:48 [Epoch 2 Batch 980/11375] loss=0.2039, lr=0.0000174, metrics:accuracy:0.9033,f1:0.8694
INFO:root:08:27:49 [Epoch 2 Batch 990/11375] loss=0.2144, lr=0.0000174, metrics:accuracy:0.9035,f1:0.8698
INFO:root:08:27:51 [Epoch 2 Batch 1000/11375] loss=0.1880, lr=0.0000174, metrics:accuracy:0.9037,f1:0.8698
INFO:root:08:27:52 [Epoch 2 Batch 1010/11375] loss=0.2516, lr=0.0000174, metrics:accuracy:0.9035,f1:0.8697
INFO:root:08:27:53 [Epoch 2 Batch 1020/11375] loss=0.2549, lr=0.0000174, metrics:accuracy:0.9034,f1:0.8696
INFO:root:08:27:54 [Epoch 2 Batch 1030/11375] loss=0.2327, lr=0.0000174, metrics:accuracy:0.9035,f1:0.8699
INFO:root:08:27:55 [Epoch 2 Batch 1040/11375] loss=0.2736, lr=0.0000174, metrics:accuracy:0.9032,f1:0.8693
INFO:root:08:27:56 [Epoch 2 Batch 1050/11375] loss=0.2399, lr=0.0000174, metrics:accuracy:0.9030,f1:0.8691
INFO:root:08:27:57 [Epoch 2 Batch 1060/11375] loss=0.2350, lr=0.0000174, metrics:accuracy:0.9029,f1:0.8691
INFO:root:08:27:59 [Epoch 2 Batch 1070/11375] loss=0.2417, lr=0.0000174, metrics:accuracy:0.9029,f1:0.8689
INFO:root:08:28:00 [Epoch 2 Batch 1080/11375] loss=0.2963, lr=0.0000174, metrics:accuracy:0.9026,f1:0.8686
INFO:root:08:28:01 [Epoch 2 Batch 1090/11375] loss=0.2622, lr=0.0000174, metrics:accuracy:0.9025,f1:0.8683
INFO:root:08:28:02 [Epoch 2 Batch 1100/11375] loss=0.2774, lr=0.0000173, metrics:accuracy:0.9023,f1:0.8681
INFO:root:08:28:03 [Epoch 2 Batch 1110/11375] loss=0.2265, lr=0.0000173, metrics:accuracy:0.9023,f1:0.8683
INFO:root:08:28:05 [Epoch 2 Batch 1120/11375] loss=0.2034, lr=0.0000173, metrics:accuracy:0.9024,f1:0.8684
INFO:root:08:28:06 [Epoch 2 Batch 1130/11375] loss=0.2380, lr=0.0000173, metrics:accuracy:0.9025,f1:0.8685
INFO:root:08:28:07 [Epoch 2 Batch 1140/11375] loss=0.2098, lr=0.0000173, metrics:accuracy:0.9025,f1:0.8687
INFO:root:08:28:08 [Epoch 2 Batch 1150/11375] loss=0.2052, lr=0.0000173, metrics:accuracy:0.9025,f1:0.8687
INFO:root:08:28:09 [Epoch 2 Batch 1160/11375] loss=0.1982, lr=0.0000173, metrics:accuracy:0.9026,f1:0.8689
INFO:root:08:28:11 [Epoch 2 Batch 1170/11375] loss=0.2010, lr=0.0000173, metrics:accuracy:0.9027,f1:0.8689
INFO:root:08:28:12 [Epoch 2 Batch 1180/11375] loss=0.1816, lr=0.0000173, metrics:accuracy:0.9029,f1:0.8692
INFO:root:08:28:13 [Epoch 2 Batch 1190/11375] loss=0.2273, lr=0.0000173, metrics:accuracy:0.9029,f1:0.8692
INFO:root:08:28:14 [Epoch 2 Batch 1200/11375] loss=0.2671, lr=0.0000173, metrics:accuracy:0.9030,f1:0.8693
INFO:root:08:28:16 [Epoch 2 Batch 1210/11375] loss=0.2214, lr=0.0000173, metrics:accuracy:0.9030,f1:0.8694
INFO:root:08:28:17 [Epoch 2 Batch 1220/11375] loss=0.1799, lr=0.0000173, metrics:accuracy:0.9032,f1:0.8697
INFO:root:08:28:18 [Epoch 2 Batch 1230/11375] loss=0.2536, lr=0.0000173, metrics:accuracy:0.9031,f1:0.8695
INFO:root:08:28:19 [Epoch 2 Batch 1240/11375] loss=0.2448, lr=0.0000173, metrics:accuracy:0.9031,f1:0.8695
INFO:root:08:28:20 [Epoch 2 Batch 1250/11375] loss=0.1822, lr=0.0000173, metrics:accuracy:0.9032,f1:0.8696
INFO:root:08:28:21 [Epoch 2 Batch 1260/11375] loss=0.2470, lr=0.0000173, metrics:accuracy:0.9031,f1:0.8698
INFO:root:08:28:23 [Epoch 2 Batch 1270/11375] loss=0.2114, lr=0.0000173, metrics:accuracy:0.9033,f1:0.8699
INFO:root:08:28:24 [Epoch 2 Batch 1280/11375] loss=0.2209, lr=0.0000173, metrics:accuracy:0.9033,f1:0.8698
INFO:root:08:28:25 [Epoch 2 Batch 1290/11375] loss=0.2801, lr=0.0000173, metrics:accuracy:0.9030,f1:0.8694
INFO:root:08:28:26 [Epoch 2 Batch 1300/11375] loss=0.1968, lr=0.0000173, metrics:accuracy:0.9031,f1:0.8695
INFO:root:08:28:27 [Epoch 2 Batch 1310/11375] loss=0.2304, lr=0.0000173, metrics:accuracy:0.9032,f1:0.8698
INFO:root:08:28:29 [Epoch 2 Batch 1320/11375] loss=0.2329, lr=0.0000173, metrics:accuracy:0.9031,f1:0.8699
INFO:root:08:28:30 [Epoch 2 Batch 1330/11375] loss=0.2831, lr=0.0000173, metrics:accuracy:0.9030,f1:0.8699
INFO:root:08:28:31 [Epoch 2 Batch 1340/11375] loss=0.2588, lr=0.0000173, metrics:accuracy:0.9030,f1:0.8700
INFO:root:08:28:32 [Epoch 2 Batch 1350/11375] loss=0.1901, lr=0.0000172, metrics:accuracy:0.9032,f1:0.8702
INFO:root:08:28:33 [Epoch 2 Batch 1360/11375] loss=0.1983, lr=0.0000172, metrics:accuracy:0.9033,f1:0.8705
INFO:root:08:28:34 [Epoch 2 Batch 1370/11375] loss=0.2320, lr=0.0000172, metrics:accuracy:0.9033,f1:0.8704
INFO:root:08:28:35 [Epoch 2 Batch 1380/11375] loss=0.2014, lr=0.0000172, metrics:accuracy:0.9033,f1:0.8704
INFO:root:08:28:37 [Epoch 2 Batch 1390/11375] loss=0.2121, lr=0.0000172, metrics:accuracy:0.9034,f1:0.8705
INFO:root:08:28:38 [Epoch 2 Batch 1400/11375] loss=0.2128, lr=0.0000172, metrics:accuracy:0.9035,f1:0.8705
INFO:root:08:28:39 [Epoch 2 Batch 1410/11375] loss=0.2312, lr=0.0000172, metrics:accuracy:0.9036,f1:0.8707
INFO:root:08:28:40 [Epoch 2 Batch 1420/11375] loss=0.2534, lr=0.0000172, metrics:accuracy:0.9035,f1:0.8707
INFO:root:08:28:41 [Epoch 2 Batch 1430/11375] loss=0.2564, lr=0.0000172, metrics:accuracy:0.9035,f1:0.8708
INFO:root:08:28:43 [Epoch 2 Batch 1440/11375] loss=0.1808, lr=0.0000172, metrics:accuracy:0.9036,f1:0.8709
INFO:root:08:28:44 [Epoch 2 Batch 1450/11375] loss=0.2209, lr=0.0000172, metrics:accuracy:0.9037,f1:0.8710
INFO:root:08:28:45 [Epoch 2 Batch 1460/11375] loss=0.2196, lr=0.0000172, metrics:accuracy:0.9038,f1:0.8708
INFO:root:08:28:46 [Epoch 2 Batch 1470/11375] loss=0.2121, lr=0.0000172, metrics:accuracy:0.9038,f1:0.8710
INFO:root:08:28:48 [Epoch 2 Batch 1480/11375] loss=0.2733, lr=0.0000172, metrics:accuracy:0.9037,f1:0.8709
INFO:root:08:28:49 [Epoch 2 Batch 1490/11375] loss=0.2403, lr=0.0000172, metrics:accuracy:0.9038,f1:0.8708
INFO:root:08:28:50 [Epoch 2 Batch 1500/11375] loss=0.2284, lr=0.0000172, metrics:accuracy:0.9038,f1:0.8708
INFO:root:08:28:51 [Epoch 2 Batch 1510/11375] loss=0.1858, lr=0.0000172, metrics:accuracy:0.9040,f1:0.8710
INFO:root:08:28:53 [Epoch 2 Batch 1520/11375] loss=0.2084, lr=0.0000172, metrics:accuracy:0.9041,f1:0.8710
INFO:root:08:28:54 [Epoch 2 Batch 1530/11375] loss=0.2180, lr=0.0000172, metrics:accuracy:0.9041,f1:0.8711
INFO:root:08:28:55 [Epoch 2 Batch 1540/11375] loss=0.1772, lr=0.0000172, metrics:accuracy:0.9042,f1:0.8713
INFO:root:08:28:56 [Epoch 2 Batch 1550/11375] loss=0.1780, lr=0.0000172, metrics:accuracy:0.9044,f1:0.8716
INFO:root:08:28:57 [Epoch 2 Batch 1560/11375] loss=0.2076, lr=0.0000172, metrics:accuracy:0.9044,f1:0.8715
INFO:root:08:28:59 [Epoch 2 Batch 1570/11375] loss=0.2275, lr=0.0000172, metrics:accuracy:0.9045,f1:0.8715
INFO:root:08:29:00 [Epoch 2 Batch 1580/11375] loss=0.2150, lr=0.0000172, metrics:accuracy:0.9044,f1:0.8716
INFO:root:08:29:01 [Epoch 2 Batch 1590/11375] loss=0.1868, lr=0.0000172, metrics:accuracy:0.9045,f1:0.8716
INFO:root:08:29:02 [Epoch 2 Batch 1600/11375] loss=0.2798, lr=0.0000172, metrics:accuracy:0.9044,f1:0.8715
INFO:root:08:29:03 [Epoch 2 Batch 1610/11375] loss=0.2831, lr=0.0000171, metrics:accuracy:0.9044,f1:0.8714
INFO:root:08:29:05 [Epoch 2 Batch 1620/11375] loss=0.2256, lr=0.0000171, metrics:accuracy:0.9044,f1:0.8714
INFO:root:08:29:06 [Epoch 2 Batch 1630/11375] loss=0.2604, lr=0.0000171, metrics:accuracy:0.9044,f1:0.8713
INFO:root:08:29:07 [Epoch 2 Batch 1640/11375] loss=0.2274, lr=0.0000171, metrics:accuracy:0.9043,f1:0.8712
INFO:root:08:29:08 [Epoch 2 Batch 1650/11375] loss=0.2898, lr=0.0000171, metrics:accuracy:0.9042,f1:0.8710
INFO:root:08:29:09 [Epoch 2 Batch 1660/11375] loss=0.2231, lr=0.0000171, metrics:accuracy:0.9041,f1:0.8709
INFO:root:08:29:11 [Epoch 2 Batch 1670/11375] loss=0.2517, lr=0.0000171, metrics:accuracy:0.9041,f1:0.8709
INFO:root:08:29:12 [Epoch 2 Batch 1680/11375] loss=0.2342, lr=0.0000171, metrics:accuracy:0.9040,f1:0.8708
INFO:root:08:29:13 [Epoch 2 Batch 1690/11375] loss=0.2147, lr=0.0000171, metrics:accuracy:0.9041,f1:0.8709
INFO:root:08:29:14 [Epoch 2 Batch 1700/11375] loss=0.1933, lr=0.0000171, metrics:accuracy:0.9042,f1:0.8711
INFO:root:08:29:15 [Epoch 2 Batch 1710/11375] loss=0.1593, lr=0.0000171, metrics:accuracy:0.9043,f1:0.8714
INFO:root:08:29:16 [Epoch 2 Batch 1720/11375] loss=0.3271, lr=0.0000171, metrics:accuracy:0.9041,f1:0.8711
INFO:root:08:29:17 [Epoch 2 Batch 1730/11375] loss=0.2402, lr=0.0000171, metrics:accuracy:0.9041,f1:0.8712
INFO:root:08:29:19 [Epoch 2 Batch 1740/11375] loss=0.2733, lr=0.0000171, metrics:accuracy:0.9040,f1:0.8713
INFO:root:08:29:20 [Epoch 2 Batch 1750/11375] loss=0.1889, lr=0.0000171, metrics:accuracy:0.9041,f1:0.8714
INFO:root:08:29:21 [Epoch 2 Batch 1760/11375] loss=0.2788, lr=0.0000171, metrics:accuracy:0.9040,f1:0.8712
INFO:root:08:29:22 [Epoch 2 Batch 1770/11375] loss=0.2130, lr=0.0000171, metrics:accuracy:0.9040,f1:0.8711
INFO:root:08:29:23 [Epoch 2 Batch 1780/11375] loss=0.2007, lr=0.0000171, metrics:accuracy:0.9041,f1:0.8711
INFO:root:08:29:25 [Epoch 2 Batch 1790/11375] loss=0.2146, lr=0.0000171, metrics:accuracy:0.9041,f1:0.8713
INFO:root:08:29:26 [Epoch 2 Batch 1800/11375] loss=0.2211, lr=0.0000171, metrics:accuracy:0.9042,f1:0.8715
INFO:root:08:29:27 [Epoch 2 Batch 1810/11375] loss=0.2310, lr=0.0000171, metrics:accuracy:0.9042,f1:0.8716
INFO:root:08:29:28 [Epoch 2 Batch 1820/11375] loss=0.2557, lr=0.0000171, metrics:accuracy:0.9042,f1:0.8716
INFO:root:08:29:29 [Epoch 2 Batch 1830/11375] loss=0.1712, lr=0.0000171, metrics:accuracy:0.9043,f1:0.8716
INFO:root:08:29:30 [Epoch 2 Batch 1840/11375] loss=0.2593, lr=0.0000171, metrics:accuracy:0.9042,f1:0.8715
INFO:root:08:29:31 [Epoch 2 Batch 1850/11375] loss=0.2135, lr=0.0000171, metrics:accuracy:0.9043,f1:0.8717
INFO:root:08:29:33 [Epoch 2 Batch 1860/11375] loss=0.2041, lr=0.0000170, metrics:accuracy:0.9044,f1:0.8718
INFO:root:08:29:34 [Epoch 2 Batch 1870/11375] loss=0.2202, lr=0.0000170, metrics:accuracy:0.9045,f1:0.8719
INFO:root:08:29:35 [Epoch 2 Batch 1880/11375] loss=0.2183, lr=0.0000170, metrics:accuracy:0.9045,f1:0.8718
INFO:root:08:29:36 [Epoch 2 Batch 1890/11375] loss=0.2400, lr=0.0000170, metrics:accuracy:0.9044,f1:0.8717
INFO:root:08:29:38 [Epoch 2 Batch 1900/11375] loss=0.1759, lr=0.0000170, metrics:accuracy:0.9046,f1:0.8720
INFO:root:08:29:39 [Epoch 2 Batch 1910/11375] loss=0.2454, lr=0.0000170, metrics:accuracy:0.9045,f1:0.8718
INFO:root:08:29:40 [Epoch 2 Batch 1920/11375] loss=0.2303, lr=0.0000170, metrics:accuracy:0.9045,f1:0.8718
INFO:root:08:29:41 [Epoch 2 Batch 1930/11375] loss=0.2692, lr=0.0000170, metrics:accuracy:0.9043,f1:0.8716
INFO:root:08:29:42 [Epoch 2 Batch 1940/11375] loss=0.2184, lr=0.0000170, metrics:accuracy:0.9043,f1:0.8716
INFO:root:08:29:43 [Epoch 2 Batch 1950/11375] loss=0.2452, lr=0.0000170, metrics:accuracy:0.9043,f1:0.8715
INFO:root:08:29:45 [Epoch 2 Batch 1960/11375] loss=0.2599, lr=0.0000170, metrics:accuracy:0.9041,f1:0.8714
INFO:root:08:29:46 [Epoch 2 Batch 1970/11375] loss=0.2080, lr=0.0000170, metrics:accuracy:0.9041,f1:0.8713
INFO:root:08:29:47 [Epoch 2 Batch 1980/11375] loss=0.2743, lr=0.0000170, metrics:accuracy:0.9040,f1:0.8712
INFO:root:08:29:48 [Epoch 2 Batch 1990/11375] loss=0.2385, lr=0.0000170, metrics:accuracy:0.9040,f1:0.8713
INFO:root:08:29:49 [Epoch 2 Batch 2000/11375] loss=0.3088, lr=0.0000170, metrics:accuracy:0.9038,f1:0.8712
INFO:root:08:29:50 [Epoch 2 Batch 2010/11375] loss=0.2289, lr=0.0000170, metrics:accuracy:0.9038,f1:0.8711
INFO:root:08:29:52 [Epoch 2 Batch 2020/11375] loss=0.2397, lr=0.0000170, metrics:accuracy:0.9038,f1:0.8710
INFO:root:08:29:53 [Epoch 2 Batch 2030/11375] loss=0.2356, lr=0.0000170, metrics:accuracy:0.9038,f1:0.8711
INFO:root:08:29:54 [Epoch 2 Batch 2040/11375] loss=0.2340, lr=0.0000170, metrics:accuracy:0.9037,f1:0.8710
INFO:root:08:29:55 [Epoch 2 Batch 2050/11375] loss=0.2191, lr=0.0000170, metrics:accuracy:0.9037,f1:0.8710
INFO:root:08:29:56 [Epoch 2 Batch 2060/11375] loss=0.2338, lr=0.0000170, metrics:accuracy:0.9037,f1:0.8710
INFO:root:08:29:57 [Epoch 2 Batch 2070/11375] loss=0.2277, lr=0.0000170, metrics:accuracy:0.9037,f1:0.8711
INFO:root:08:29:59 [Epoch 2 Batch 2080/11375] loss=0.1482, lr=0.0000170, metrics:accuracy:0.9039,f1:0.8713
INFO:root:08:30:00 [Epoch 2 Batch 2090/11375] loss=0.1615, lr=0.0000170, metrics:accuracy:0.9040,f1:0.8713
INFO:root:08:30:01 [Epoch 2 Batch 2100/11375] loss=0.2760, lr=0.0000170, metrics:accuracy:0.9039,f1:0.8713
INFO:root:08:30:02 [Epoch 2 Batch 2110/11375] loss=0.2693, lr=0.0000170, metrics:accuracy:0.9039,f1:0.8713
INFO:root:08:30:04 [Epoch 2 Batch 2120/11375] loss=0.2364, lr=0.0000169, metrics:accuracy:0.9039,f1:0.8714
INFO:root:08:30:05 [Epoch 2 Batch 2130/11375] loss=0.2784, lr=0.0000169, metrics:accuracy:0.9038,f1:0.8713
INFO:root:08:30:06 [Epoch 2 Batch 2140/11375] loss=0.1928, lr=0.0000169, metrics:accuracy:0.9039,f1:0.8715
INFO:root:08:30:07 [Epoch 2 Batch 2150/11375] loss=0.2972, lr=0.0000169, metrics:accuracy:0.9038,f1:0.8714
INFO:root:08:30:08 [Epoch 2 Batch 2160/11375] loss=0.2387, lr=0.0000169, metrics:accuracy:0.9038,f1:0.8714
INFO:root:08:30:09 [Epoch 2 Batch 2170/11375] loss=0.2523, lr=0.0000169, metrics:accuracy:0.9039,f1:0.8715
INFO:root:08:30:10 [Epoch 2 Batch 2180/11375] loss=0.2195, lr=0.0000169, metrics:accuracy:0.9038,f1:0.8716
INFO:root:08:30:12 [Epoch 2 Batch 2190/11375] loss=0.2252, lr=0.0000169, metrics:accuracy:0.9039,f1:0.8717
INFO:root:08:30:13 [Epoch 2 Batch 2200/11375] loss=0.1746, lr=0.0000169, metrics:accuracy:0.9040,f1:0.8718
INFO:root:08:30:14 [Epoch 2 Batch 2210/11375] loss=0.2459, lr=0.0000169, metrics:accuracy:0.9039,f1:0.8717
INFO:root:08:30:15 [Epoch 2 Batch 2220/11375] loss=0.2439, lr=0.0000169, metrics:accuracy:0.9039,f1:0.8716
INFO:root:08:30:17 [Epoch 2 Batch 2230/11375] loss=0.1867, lr=0.0000169, metrics:accuracy:0.9040,f1:0.8716
INFO:root:08:30:18 [Epoch 2 Batch 2240/11375] loss=0.2471, lr=0.0000169, metrics:accuracy:0.9040,f1:0.8716
INFO:root:08:30:19 [Epoch 2 Batch 2250/11375] loss=0.2104, lr=0.0000169, metrics:accuracy:0.9040,f1:0.8714
INFO:root:08:30:20 [Epoch 2 Batch 2260/11375] loss=0.2881, lr=0.0000169, metrics:accuracy:0.9038,f1:0.8713
INFO:root:08:30:21 [Epoch 2 Batch 2270/11375] loss=0.2084, lr=0.0000169, metrics:accuracy:0.9038,f1:0.8712
INFO:root:08:30:23 [Epoch 2 Batch 2280/11375] loss=0.2216, lr=0.0000169, metrics:accuracy:0.9039,f1:0.8713
INFO:root:08:30:24 [Epoch 2 Batch 2290/11375] loss=0.2873, lr=0.0000169, metrics:accuracy:0.9038,f1:0.8711
INFO:root:08:30:25 [Epoch 2 Batch 2300/11375] loss=0.1731, lr=0.0000169, metrics:accuracy:0.9040,f1:0.8714
INFO:root:08:30:26 [Epoch 2 Batch 2310/11375] loss=0.2750, lr=0.0000169, metrics:accuracy:0.9040,f1:0.8713
INFO:root:08:30:27 [Epoch 2 Batch 2320/11375] loss=0.2236, lr=0.0000169, metrics:accuracy:0.9040,f1:0.8714
INFO:root:08:30:28 [Epoch 2 Batch 2330/11375] loss=0.2533, lr=0.0000169, metrics:accuracy:0.9039,f1:0.8714
INFO:root:08:30:30 [Epoch 2 Batch 2340/11375] loss=0.2479, lr=0.0000169, metrics:accuracy:0.9040,f1:0.8715
INFO:root:08:30:31 [Epoch 2 Batch 2350/11375] loss=0.2657, lr=0.0000169, metrics:accuracy:0.9039,f1:0.8715
INFO:root:08:30:32 [Epoch 2 Batch 2360/11375] loss=0.2525, lr=0.0000169, metrics:accuracy:0.9039,f1:0.8716
INFO:root:08:30:33 [Epoch 2 Batch 2370/11375] loss=0.2023, lr=0.0000168, metrics:accuracy:0.9039,f1:0.8718
INFO:root:08:30:34 [Epoch 2 Batch 2380/11375] loss=0.3148, lr=0.0000168, metrics:accuracy:0.9038,f1:0.8716
INFO:root:08:30:35 [Epoch 2 Batch 2390/11375] loss=0.2016, lr=0.0000168, metrics:accuracy:0.9039,f1:0.8717
INFO:root:08:30:37 [Epoch 2 Batch 2400/11375] loss=0.2027, lr=0.0000168, metrics:accuracy:0.9040,f1:0.8717
INFO:root:08:30:38 [Epoch 2 Batch 2410/11375] loss=0.2451, lr=0.0000168, metrics:accuracy:0.9040,f1:0.8718
INFO:root:08:30:39 [Epoch 2 Batch 2420/11375] loss=0.1539, lr=0.0000168, metrics:accuracy:0.9041,f1:0.8718
INFO:root:08:30:40 [Epoch 2 Batch 2430/11375] loss=0.1982, lr=0.0000168, metrics:accuracy:0.9042,f1:0.8719
INFO:root:08:30:41 [Epoch 2 Batch 2440/11375] loss=0.2559, lr=0.0000168, metrics:accuracy:0.9042,f1:0.8720
INFO:root:08:30:43 [Epoch 2 Batch 2450/11375] loss=0.2185, lr=0.0000168, metrics:accuracy:0.9042,f1:0.8721
INFO:root:08:30:44 [Epoch 2 Batch 2460/11375] loss=0.2493, lr=0.0000168, metrics:accuracy:0.9042,f1:0.8720
INFO:root:08:30:45 [Epoch 2 Batch 2470/11375] loss=0.2597, lr=0.0000168, metrics:accuracy:0.9041,f1:0.8720
INFO:root:08:30:46 [Epoch 2 Batch 2480/11375] loss=0.2461, lr=0.0000168, metrics:accuracy:0.9041,f1:0.8719
INFO:root:08:30:47 [Epoch 2 Batch 2490/11375] loss=0.2038, lr=0.0000168, metrics:accuracy:0.9041,f1:0.8719
INFO:root:08:30:48 [Epoch 2 Batch 2500/11375] loss=0.2702, lr=0.0000168, metrics:accuracy:0.9041,f1:0.8720
INFO:root:08:30:50 [Epoch 2 Batch 2510/11375] loss=0.1915, lr=0.0000168, metrics:accuracy:0.9042,f1:0.8719
INFO:root:08:30:51 [Epoch 2 Batch 2520/11375] loss=0.2081, lr=0.0000168, metrics:accuracy:0.9042,f1:0.8720
INFO:root:08:30:52 [Epoch 2 Batch 2530/11375] loss=0.2420, lr=0.0000168, metrics:accuracy:0.9043,f1:0.8719
INFO:root:08:30:53 [Epoch 2 Batch 2540/11375] loss=0.1925, lr=0.0000168, metrics:accuracy:0.9043,f1:0.8720
INFO:root:08:30:55 [Epoch 2 Batch 2550/11375] loss=0.2653, lr=0.0000168, metrics:accuracy:0.9044,f1:0.8720
INFO:root:08:30:56 [Epoch 2 Batch 2560/11375] loss=0.2724, lr=0.0000168, metrics:accuracy:0.9042,f1:0.8719
INFO:root:08:30:57 [Epoch 2 Batch 2570/11375] loss=0.2692, lr=0.0000168, metrics:accuracy:0.9042,f1:0.8718
INFO:root:08:30:58 [Epoch 2 Batch 2580/11375] loss=0.2076, lr=0.0000168, metrics:accuracy:0.9042,f1:0.8719
INFO:root:08:30:59 [Epoch 2 Batch 2590/11375] loss=0.2391, lr=0.0000168, metrics:accuracy:0.9042,f1:0.8719
INFO:root:08:31:00 [Epoch 2 Batch 2600/11375] loss=0.2746, lr=0.0000168, metrics:accuracy:0.9042,f1:0.8719
INFO:root:08:31:01 [Epoch 2 Batch 2610/11375] loss=0.2591, lr=0.0000168, metrics:accuracy:0.9041,f1:0.8718
INFO:root:08:31:03 [Epoch 2 Batch 2620/11375] loss=0.1999, lr=0.0000168, metrics:accuracy:0.9041,f1:0.8718
INFO:root:08:31:04 [Epoch 2 Batch 2630/11375] loss=0.1647, lr=0.0000167, metrics:accuracy:0.9044,f1:0.8720
INFO:root:08:31:05 [Epoch 2 Batch 2640/11375] loss=0.2276, lr=0.0000167, metrics:accuracy:0.9044,f1:0.8722
INFO:root:08:31:06 [Epoch 2 Batch 2650/11375] loss=0.1694, lr=0.0000167, metrics:accuracy:0.9046,f1:0.8723
INFO:root:08:31:08 [Epoch 2 Batch 2660/11375] loss=0.2336, lr=0.0000167, metrics:accuracy:0.9046,f1:0.8723
INFO:root:08:31:09 [Epoch 2 Batch 2670/11375] loss=0.2242, lr=0.0000167, metrics:accuracy:0.9046,f1:0.8723
INFO:root:08:31:10 [Epoch 2 Batch 2680/11375] loss=0.2263, lr=0.0000167, metrics:accuracy:0.9046,f1:0.8724
INFO:root:08:31:11 [Epoch 2 Batch 2690/11375] loss=0.2596, lr=0.0000167, metrics:accuracy:0.9046,f1:0.8724
INFO:root:08:31:12 [Epoch 2 Batch 2700/11375] loss=0.1549, lr=0.0000167, metrics:accuracy:0.9047,f1:0.8726
INFO:root:08:31:13 [Epoch 2 Batch 2710/11375] loss=0.1903, lr=0.0000167, metrics:accuracy:0.9048,f1:0.8726
INFO:root:08:31:15 [Epoch 2 Batch 2720/11375] loss=0.2942, lr=0.0000167, metrics:accuracy:0.9047,f1:0.8726
INFO:root:08:31:16 [Epoch 2 Batch 2730/11375] loss=0.2204, lr=0.0000167, metrics:accuracy:0.9048,f1:0.8727
INFO:root:08:31:17 [Epoch 2 Batch 2740/11375] loss=0.2069, lr=0.0000167, metrics:accuracy:0.9048,f1:0.8729
INFO:root:08:31:18 [Epoch 2 Batch 2750/11375] loss=0.2599, lr=0.0000167, metrics:accuracy:0.9048,f1:0.8728
INFO:root:08:31:19 [Epoch 2 Batch 2760/11375] loss=0.1889, lr=0.0000167, metrics:accuracy:0.9049,f1:0.8729
INFO:root:08:31:21 [Epoch 2 Batch 2770/11375] loss=0.2262, lr=0.0000167, metrics:accuracy:0.9049,f1:0.8729
INFO:root:08:31:22 [Epoch 2 Batch 2780/11375] loss=0.2310, lr=0.0000167, metrics:accuracy:0.9048,f1:0.8728
INFO:root:08:31:23 [Epoch 2 Batch 2790/11375] loss=0.2434, lr=0.0000167, metrics:accuracy:0.9049,f1:0.8729
INFO:root:08:31:24 [Epoch 2 Batch 2800/11375] loss=0.2218, lr=0.0000167, metrics:accuracy:0.9049,f1:0.8728
INFO:root:08:31:25 [Epoch 2 Batch 2810/11375] loss=0.2034, lr=0.0000167, metrics:accuracy:0.9049,f1:0.8729
INFO:root:08:31:26 [Epoch 2 Batch 2820/11375] loss=0.1646, lr=0.0000167, metrics:accuracy:0.9050,f1:0.8729
INFO:root:08:31:28 [Epoch 2 Batch 2830/11375] loss=0.3050, lr=0.0000167, metrics:accuracy:0.9049,f1:0.8728
INFO:root:08:31:29 [Epoch 2 Batch 2840/11375] loss=0.2134, lr=0.0000167, metrics:accuracy:0.9050,f1:0.8730
INFO:root:08:31:30 [Epoch 2 Batch 2850/11375] loss=0.2409, lr=0.0000167, metrics:accuracy:0.9050,f1:0.8731
INFO:root:08:31:31 [Epoch 2 Batch 2860/11375] loss=0.2607, lr=0.0000167, metrics:accuracy:0.9050,f1:0.8732
INFO:root:08:31:32 [Epoch 2 Batch 2870/11375] loss=0.2002, lr=0.0000167, metrics:accuracy:0.9050,f1:0.8733
INFO:root:08:31:33 [Epoch 2 Batch 2880/11375] loss=0.2953, lr=0.0000167, metrics:accuracy:0.9049,f1:0.8732
INFO:root:08:31:34 [Epoch 2 Batch 2890/11375] loss=0.2423, lr=0.0000166, metrics:accuracy:0.9049,f1:0.8733
INFO:root:08:31:36 [Epoch 2 Batch 2900/11375] loss=0.1934, lr=0.0000166, metrics:accuracy:0.9050,f1:0.8733
INFO:root:08:31:37 [Epoch 2 Batch 2910/11375] loss=0.2299, lr=0.0000166, metrics:accuracy:0.9050,f1:0.8734
INFO:root:08:31:38 [Epoch 2 Batch 2920/11375] loss=0.2480, lr=0.0000166, metrics:accuracy:0.9050,f1:0.8735
INFO:root:08:31:39 [Epoch 2 Batch 2930/11375] loss=0.2372, lr=0.0000166, metrics:accuracy:0.9050,f1:0.8734
INFO:root:08:31:40 [Epoch 2 Batch 2940/11375] loss=0.2105, lr=0.0000166, metrics:accuracy:0.9050,f1:0.8733
INFO:root:08:31:42 [Epoch 2 Batch 2950/11375] loss=0.2550, lr=0.0000166, metrics:accuracy:0.9050,f1:0.8732
INFO:root:08:31:43 [Epoch 2 Batch 2960/11375] loss=0.1981, lr=0.0000166, metrics:accuracy:0.9050,f1:0.8732
INFO:root:08:31:44 [Epoch 2 Batch 2970/11375] loss=0.2426, lr=0.0000166, metrics:accuracy:0.9050,f1:0.8731
INFO:root:08:31:45 [Epoch 2 Batch 2980/11375] loss=0.1760, lr=0.0000166, metrics:accuracy:0.9050,f1:0.8731
INFO:root:08:31:47 [Epoch 2 Batch 2990/11375] loss=0.2002, lr=0.0000166, metrics:accuracy:0.9051,f1:0.8731
INFO:root:08:31:48 [Epoch 2 Batch 3000/11375] loss=0.2429, lr=0.0000166, metrics:accuracy:0.9050,f1:0.8730
INFO:root:08:31:49 [Epoch 2 Batch 3010/11375] loss=0.2422, lr=0.0000166, metrics:accuracy:0.9050,f1:0.8730
INFO:root:08:31:50 [Epoch 2 Batch 3020/11375] loss=0.2868, lr=0.0000166, metrics:accuracy:0.9049,f1:0.8729
INFO:root:08:31:51 [Epoch 2 Batch 3030/11375] loss=0.2170, lr=0.0000166, metrics:accuracy:0.9049,f1:0.8729
INFO:root:08:31:52 [Epoch 2 Batch 3040/11375] loss=0.2248, lr=0.0000166, metrics:accuracy:0.9049,f1:0.8729
INFO:root:08:31:54 [Epoch 2 Batch 3050/11375] loss=0.1819, lr=0.0000166, metrics:accuracy:0.9050,f1:0.8730
INFO:root:08:31:55 [Epoch 2 Batch 3060/11375] loss=0.2020, lr=0.0000166, metrics:accuracy:0.9050,f1:0.8730
INFO:root:08:31:56 [Epoch 2 Batch 3070/11375] loss=0.1753, lr=0.0000166, metrics:accuracy:0.9051,f1:0.8730
INFO:root:08:31:57 [Epoch 2 Batch 3080/11375] loss=0.3074, lr=0.0000166, metrics:accuracy:0.9050,f1:0.8730
INFO:root:08:31:59 [Epoch 2 Batch 3090/11375] loss=0.1973, lr=0.0000166, metrics:accuracy:0.9051,f1:0.8731
INFO:root:08:32:00 [Epoch 2 Batch 3100/11375] loss=0.2035, lr=0.0000166, metrics:accuracy:0.9051,f1:0.8731
INFO:root:08:32:01 [Epoch 2 Batch 3110/11375] loss=0.1963, lr=0.0000166, metrics:accuracy:0.9052,f1:0.8731
INFO:root:08:32:02 [Epoch 2 Batch 3120/11375] loss=0.2729, lr=0.0000166, metrics:accuracy:0.9051,f1:0.8731
INFO:root:08:32:03 [Epoch 2 Batch 3130/11375] loss=0.2220, lr=0.0000166, metrics:accuracy:0.9051,f1:0.8732
INFO:root:08:32:04 [Epoch 2 Batch 3140/11375] loss=0.2172, lr=0.0000165, metrics:accuracy:0.9052,f1:0.8732
INFO:root:08:32:06 [Epoch 2 Batch 3150/11375] loss=0.2485, lr=0.0000165, metrics:accuracy:0.9051,f1:0.8731
INFO:root:08:32:07 [Epoch 2 Batch 3160/11375] loss=0.3396, lr=0.0000165, metrics:accuracy:0.9049,f1:0.8729
INFO:root:08:32:08 [Epoch 2 Batch 3170/11375] loss=0.1678, lr=0.0000165, metrics:accuracy:0.9050,f1:0.8729
INFO:root:08:32:09 [Epoch 2 Batch 3180/11375] loss=0.2195, lr=0.0000165, metrics:accuracy:0.9051,f1:0.8729
INFO:root:08:32:10 [Epoch 2 Batch 3190/11375] loss=0.2216, lr=0.0000165, metrics:accuracy:0.9051,f1:0.8730
INFO:root:08:32:12 [Epoch 2 Batch 3200/11375] loss=0.2754, lr=0.0000165, metrics:accuracy:0.9050,f1:0.8729
INFO:root:08:32:13 [Epoch 2 Batch 3210/11375] loss=0.2115, lr=0.0000165, metrics:accuracy:0.9050,f1:0.8729
INFO:root:08:32:14 [Epoch 2 Batch 3220/11375] loss=0.2706, lr=0.0000165, metrics:accuracy:0.9050,f1:0.8729
INFO:root:08:32:15 [Epoch 2 Batch 3230/11375] loss=0.2234, lr=0.0000165, metrics:accuracy:0.9050,f1:0.8729
INFO:root:08:32:16 [Epoch 2 Batch 3240/11375] loss=0.2309, lr=0.0000165, metrics:accuracy:0.9050,f1:0.8729
INFO:root:08:32:17 [Epoch 2 Batch 3250/11375] loss=0.1947, lr=0.0000165, metrics:accuracy:0.9050,f1:0.8729
INFO:root:08:32:19 [Epoch 2 Batch 3260/11375] loss=0.2743, lr=0.0000165, metrics:accuracy:0.9049,f1:0.8727
INFO:root:08:32:20 [Epoch 2 Batch 3270/11375] loss=0.1944, lr=0.0000165, metrics:accuracy:0.9050,f1:0.8727
INFO:root:08:32:21 [Epoch 2 Batch 3280/11375] loss=0.2630, lr=0.0000165, metrics:accuracy:0.9049,f1:0.8727
INFO:root:08:32:22 [Epoch 2 Batch 3290/11375] loss=0.2023, lr=0.0000165, metrics:accuracy:0.9051,f1:0.8729
INFO:root:08:32:23 [Epoch 2 Batch 3300/11375] loss=0.1873, lr=0.0000165, metrics:accuracy:0.9051,f1:0.8730
INFO:root:08:32:24 [Epoch 2 Batch 3310/11375] loss=0.2332, lr=0.0000165, metrics:accuracy:0.9051,f1:0.8730
INFO:root:08:32:26 [Epoch 2 Batch 3320/11375] loss=0.2118, lr=0.0000165, metrics:accuracy:0.9051,f1:0.8730
INFO:root:08:32:27 [Epoch 2 Batch 3330/11375] loss=0.2129, lr=0.0000165, metrics:accuracy:0.9051,f1:0.8730
INFO:root:08:32:28 [Epoch 2 Batch 3340/11375] loss=0.1424, lr=0.0000165, metrics:accuracy:0.9053,f1:0.8732
INFO:root:08:32:29 [Epoch 2 Batch 3350/11375] loss=0.2260, lr=0.0000165, metrics:accuracy:0.9053,f1:0.8732
INFO:root:08:32:31 [Epoch 2 Batch 3360/11375] loss=0.1869, lr=0.0000165, metrics:accuracy:0.9053,f1:0.8732
INFO:root:08:32:32 [Epoch 2 Batch 3370/11375] loss=0.1969, lr=0.0000165, metrics:accuracy:0.9054,f1:0.8733
INFO:root:08:32:33 [Epoch 2 Batch 3380/11375] loss=0.2445, lr=0.0000165, metrics:accuracy:0.9054,f1:0.8733
INFO:root:08:32:34 [Epoch 2 Batch 3390/11375] loss=0.2225, lr=0.0000165, metrics:accuracy:0.9055,f1:0.8733
INFO:root:08:32:35 [Epoch 2 Batch 3400/11375] loss=0.2359, lr=0.0000164, metrics:accuracy:0.9054,f1:0.8733
INFO:root:08:32:37 [Epoch 2 Batch 3410/11375] loss=0.2463, lr=0.0000164, metrics:accuracy:0.9054,f1:0.8733
INFO:root:08:32:38 [Epoch 2 Batch 3420/11375] loss=0.2242, lr=0.0000164, metrics:accuracy:0.9055,f1:0.8734
INFO:root:08:32:39 [Epoch 2 Batch 3430/11375] loss=0.2129, lr=0.0000164, metrics:accuracy:0.9055,f1:0.8735
INFO:root:08:32:40 [Epoch 2 Batch 3440/11375] loss=0.2083, lr=0.0000164, metrics:accuracy:0.9055,f1:0.8735
INFO:root:08:32:41 [Epoch 2 Batch 3450/11375] loss=0.1918, lr=0.0000164, metrics:accuracy:0.9056,f1:0.8737
INFO:root:08:32:43 [Epoch 2 Batch 3460/11375] loss=0.2414, lr=0.0000164, metrics:accuracy:0.9056,f1:0.8736
INFO:root:08:32:44 [Epoch 2 Batch 3470/11375] loss=0.2081, lr=0.0000164, metrics:accuracy:0.9056,f1:0.8736
INFO:root:08:32:45 [Epoch 2 Batch 3480/11375] loss=0.2177, lr=0.0000164, metrics:accuracy:0.9057,f1:0.8737
INFO:root:08:32:46 [Epoch 2 Batch 3490/11375] loss=0.2439, lr=0.0000164, metrics:accuracy:0.9057,f1:0.8737
INFO:root:08:32:47 [Epoch 2 Batch 3500/11375] loss=0.2759, lr=0.0000164, metrics:accuracy:0.9056,f1:0.8736
INFO:root:08:32:48 [Epoch 2 Batch 3510/11375] loss=0.2667, lr=0.0000164, metrics:accuracy:0.9056,f1:0.8736
INFO:root:08:32:50 [Epoch 2 Batch 3520/11375] loss=0.2705, lr=0.0000164, metrics:accuracy:0.9055,f1:0.8736
INFO:root:08:32:51 [Epoch 2 Batch 3530/11375] loss=0.2500, lr=0.0000164, metrics:accuracy:0.9055,f1:0.8736
INFO:root:08:32:52 [Epoch 2 Batch 3540/11375] loss=0.2318, lr=0.0000164, metrics:accuracy:0.9055,f1:0.8736
INFO:root:08:32:53 [Epoch 2 Batch 3550/11375] loss=0.1862, lr=0.0000164, metrics:accuracy:0.9056,f1:0.8736
INFO:root:08:32:55 [Epoch 2 Batch 3560/11375] loss=0.2104, lr=0.0000164, metrics:accuracy:0.9057,f1:0.8738
INFO:root:08:32:56 [Epoch 2 Batch 3570/11375] loss=0.2157, lr=0.0000164, metrics:accuracy:0.9057,f1:0.8739
INFO:root:08:32:57 [Epoch 2 Batch 3580/11375] loss=0.1884, lr=0.0000164, metrics:accuracy:0.9057,f1:0.8739
INFO:root:08:32:58 [Epoch 2 Batch 3590/11375] loss=0.2059, lr=0.0000164, metrics:accuracy:0.9058,f1:0.8740
INFO:root:08:32:59 [Epoch 2 Batch 3600/11375] loss=0.2547, lr=0.0000164, metrics:accuracy:0.9058,f1:0.8740
INFO:root:08:33:00 [Epoch 2 Batch 3610/11375] loss=0.2930, lr=0.0000164, metrics:accuracy:0.9057,f1:0.8739
INFO:root:08:33:01 [Epoch 2 Batch 3620/11375] loss=0.2274, lr=0.0000164, metrics:accuracy:0.9057,f1:0.8739
INFO:root:08:33:03 [Epoch 2 Batch 3630/11375] loss=0.2364, lr=0.0000164, metrics:accuracy:0.9057,f1:0.8738
INFO:root:08:33:04 [Epoch 2 Batch 3640/11375] loss=0.3180, lr=0.0000164, metrics:accuracy:0.9056,f1:0.8737
INFO:root:08:33:05 [Epoch 2 Batch 3650/11375] loss=0.2389, lr=0.0000163, metrics:accuracy:0.9056,f1:0.8736
INFO:root:08:33:06 [Epoch 2 Batch 3660/11375] loss=0.1832, lr=0.0000163, metrics:accuracy:0.9056,f1:0.8737
INFO:root:08:33:07 [Epoch 2 Batch 3670/11375] loss=0.2264, lr=0.0000163, metrics:accuracy:0.9056,f1:0.8738
INFO:root:08:33:09 [Epoch 2 Batch 3680/11375] loss=0.2756, lr=0.0000163, metrics:accuracy:0.9056,f1:0.8738
INFO:root:08:33:10 [Epoch 2 Batch 3690/11375] loss=0.1746, lr=0.0000163, metrics:accuracy:0.9057,f1:0.8738
INFO:root:08:33:11 [Epoch 2 Batch 3700/11375] loss=0.2170, lr=0.0000163, metrics:accuracy:0.9057,f1:0.8738
INFO:root:08:33:12 [Epoch 2 Batch 3710/11375] loss=0.2401, lr=0.0000163, metrics:accuracy:0.9057,f1:0.8738
INFO:root:08:33:13 [Epoch 2 Batch 3720/11375] loss=0.2547, lr=0.0000163, metrics:accuracy:0.9057,f1:0.8737
INFO:root:08:33:15 [Epoch 2 Batch 3730/11375] loss=0.1995, lr=0.0000163, metrics:accuracy:0.9057,f1:0.8737
INFO:root:08:33:16 [Epoch 2 Batch 3740/11375] loss=0.1471, lr=0.0000163, metrics:accuracy:0.9057,f1:0.8737
INFO:root:08:33:17 [Epoch 2 Batch 3750/11375] loss=0.2576, lr=0.0000163, metrics:accuracy:0.9057,f1:0.8737
INFO:root:08:33:18 [Epoch 2 Batch 3760/11375] loss=0.2713, lr=0.0000163, metrics:accuracy:0.9057,f1:0.8737
INFO:root:08:33:19 [Epoch 2 Batch 3770/11375] loss=0.2468, lr=0.0000163, metrics:accuracy:0.9057,f1:0.8737
INFO:root:08:33:21 [Epoch 2 Batch 3780/11375] loss=0.2687, lr=0.0000163, metrics:accuracy:0.9056,f1:0.8736
INFO:root:08:33:22 [Epoch 2 Batch 3790/11375] loss=0.2174, lr=0.0000163, metrics:accuracy:0.9056,f1:0.8736
INFO:root:08:33:23 [Epoch 2 Batch 3800/11375] loss=0.2321, lr=0.0000163, metrics:accuracy:0.9056,f1:0.8737
INFO:root:08:33:24 [Epoch 2 Batch 3810/11375] loss=0.2699, lr=0.0000163, metrics:accuracy:0.9055,f1:0.8736
INFO:root:08:33:25 [Epoch 2 Batch 3820/11375] loss=0.1758, lr=0.0000163, metrics:accuracy:0.9056,f1:0.8737
INFO:root:08:33:26 [Epoch 2 Batch 3830/11375] loss=0.1748, lr=0.0000163, metrics:accuracy:0.9056,f1:0.8738
INFO:root:08:33:28 [Epoch 2 Batch 3840/11375] loss=0.2943, lr=0.0000163, metrics:accuracy:0.9056,f1:0.8737
INFO:root:08:33:29 [Epoch 2 Batch 3850/11375] loss=0.2355, lr=0.0000163, metrics:accuracy:0.9056,f1:0.8737
INFO:root:08:33:30 [Epoch 2 Batch 3860/11375] loss=0.2343, lr=0.0000163, metrics:accuracy:0.9056,f1:0.8738
INFO:root:08:33:31 [Epoch 2 Batch 3870/11375] loss=0.1877, lr=0.0000163, metrics:accuracy:0.9057,f1:0.8738
INFO:root:08:33:32 [Epoch 2 Batch 3880/11375] loss=0.1591, lr=0.0000163, metrics:accuracy:0.9057,f1:0.8739
INFO:root:08:33:34 [Epoch 2 Batch 3890/11375] loss=0.2037, lr=0.0000163, metrics:accuracy:0.9057,f1:0.8739
INFO:root:08:33:35 [Epoch 2 Batch 3900/11375] loss=0.2746, lr=0.0000163, metrics:accuracy:0.9057,f1:0.8738
INFO:root:08:33:36 [Epoch 2 Batch 3910/11375] loss=0.2061, lr=0.0000162, metrics:accuracy:0.9057,f1:0.8738
INFO:root:08:33:37 [Epoch 2 Batch 3920/11375] loss=0.2356, lr=0.0000162, metrics:accuracy:0.9057,f1:0.8738
INFO:root:08:33:39 [Epoch 2 Batch 3930/11375] loss=0.2269, lr=0.0000162, metrics:accuracy:0.9057,f1:0.8738
INFO:root:08:33:40 [Epoch 2 Batch 3940/11375] loss=0.2207, lr=0.0000162, metrics:accuracy:0.9057,f1:0.8739
INFO:root:08:33:41 [Epoch 2 Batch 3950/11375] loss=0.1877, lr=0.0000162, metrics:accuracy:0.9057,f1:0.8738
INFO:root:08:33:42 [Epoch 2 Batch 3960/11375] loss=0.2451, lr=0.0000162, metrics:accuracy:0.9057,f1:0.8738
INFO:root:08:33:43 [Epoch 2 Batch 3970/11375] loss=0.2191, lr=0.0000162, metrics:accuracy:0.9057,f1:0.8738
INFO:root:08:33:44 [Epoch 2 Batch 3980/11375] loss=0.2450, lr=0.0000162, metrics:accuracy:0.9056,f1:0.8739
INFO:root:08:33:45 [Epoch 2 Batch 3990/11375] loss=0.2448, lr=0.0000162, metrics:accuracy:0.9056,f1:0.8738
INFO:root:08:33:47 [Epoch 2 Batch 4000/11375] loss=0.2030, lr=0.0000162, metrics:accuracy:0.9056,f1:0.8739
INFO:root:08:33:48 [Epoch 2 Batch 4010/11375] loss=0.1411, lr=0.0000162, metrics:accuracy:0.9057,f1:0.8739
INFO:root:08:33:49 [Epoch 2 Batch 4020/11375] loss=0.2311, lr=0.0000162, metrics:accuracy:0.9057,f1:0.8739
INFO:root:08:33:50 [Epoch 2 Batch 4030/11375] loss=0.2184, lr=0.0000162, metrics:accuracy:0.9057,f1:0.8739
INFO:root:08:33:52 [Epoch 2 Batch 4040/11375] loss=0.2191, lr=0.0000162, metrics:accuracy:0.9058,f1:0.8739
INFO:root:08:33:53 [Epoch 2 Batch 4050/11375] loss=0.2788, lr=0.0000162, metrics:accuracy:0.9057,f1:0.8738
INFO:root:08:33:54 [Epoch 2 Batch 4060/11375] loss=0.2192, lr=0.0000162, metrics:accuracy:0.9057,f1:0.8739
INFO:root:08:33:55 [Epoch 2 Batch 4070/11375] loss=0.2155, lr=0.0000162, metrics:accuracy:0.9057,f1:0.8739
INFO:root:08:33:56 [Epoch 2 Batch 4080/11375] loss=0.2385, lr=0.0000162, metrics:accuracy:0.9056,f1:0.8739
INFO:root:08:33:57 [Epoch 2 Batch 4090/11375] loss=0.2718, lr=0.0000162, metrics:accuracy:0.9055,f1:0.8737
INFO:root:08:33:59 [Epoch 2 Batch 4100/11375] loss=0.2009, lr=0.0000162, metrics:accuracy:0.9056,f1:0.8738
INFO:root:08:34:00 [Epoch 2 Batch 4110/11375] loss=0.2443, lr=0.0000162, metrics:accuracy:0.9055,f1:0.8737
INFO:root:08:34:01 [Epoch 2 Batch 4120/11375] loss=0.2401, lr=0.0000162, metrics:accuracy:0.9055,f1:0.8737
INFO:root:08:34:02 [Epoch 2 Batch 4130/11375] loss=0.2062, lr=0.0000162, metrics:accuracy:0.9055,f1:0.8737
INFO:root:08:34:03 [Epoch 2 Batch 4140/11375] loss=0.2075, lr=0.0000162, metrics:accuracy:0.9056,f1:0.8738
INFO:root:08:34:05 [Epoch 2 Batch 4150/11375] loss=0.2142, lr=0.0000162, metrics:accuracy:0.9056,f1:0.8738
INFO:root:08:34:06 [Epoch 2 Batch 4160/11375] loss=0.1629, lr=0.0000162, metrics:accuracy:0.9056,f1:0.8739
INFO:root:08:34:07 [Epoch 2 Batch 4170/11375] loss=0.2285, lr=0.0000161, metrics:accuracy:0.9057,f1:0.8739
INFO:root:08:34:08 [Epoch 2 Batch 4180/11375] loss=0.1855, lr=0.0000161, metrics:accuracy:0.9057,f1:0.8739
INFO:root:08:34:10 [Epoch 2 Batch 4190/11375] loss=0.2058, lr=0.0000161, metrics:accuracy:0.9057,f1:0.8740
INFO:root:08:34:11 [Epoch 2 Batch 4200/11375] loss=0.2893, lr=0.0000161, metrics:accuracy:0.9057,f1:0.8739
INFO:root:08:34:12 [Epoch 2 Batch 4210/11375] loss=0.1557, lr=0.0000161, metrics:accuracy:0.9058,f1:0.8740
INFO:root:08:34:13 [Epoch 2 Batch 4220/11375] loss=0.2574, lr=0.0000161, metrics:accuracy:0.9057,f1:0.8739
INFO:root:08:34:14 [Epoch 2 Batch 4230/11375] loss=0.2456, lr=0.0000161, metrics:accuracy:0.9057,f1:0.8739
INFO:root:08:34:16 [Epoch 2 Batch 4240/11375] loss=0.2092, lr=0.0000161, metrics:accuracy:0.9057,f1:0.8740
INFO:root:08:34:17 [Epoch 2 Batch 4250/11375] loss=0.2886, lr=0.0000161, metrics:accuracy:0.9057,f1:0.8739
INFO:root:08:34:18 [Epoch 2 Batch 4260/11375] loss=0.3006, lr=0.0000161, metrics:accuracy:0.9056,f1:0.8738
INFO:root:08:34:19 [Epoch 2 Batch 4270/11375] loss=0.2252, lr=0.0000161, metrics:accuracy:0.9056,f1:0.8738
INFO:root:08:34:20 [Epoch 2 Batch 4280/11375] loss=0.2420, lr=0.0000161, metrics:accuracy:0.9056,f1:0.8738
INFO:root:08:34:21 [Epoch 2 Batch 4290/11375] loss=0.2091, lr=0.0000161, metrics:accuracy:0.9056,f1:0.8739
INFO:root:08:34:22 [Epoch 2 Batch 4300/11375] loss=0.1473, lr=0.0000161, metrics:accuracy:0.9057,f1:0.8740
INFO:root:08:34:24 [Epoch 2 Batch 4310/11375] loss=0.2308, lr=0.0000161, metrics:accuracy:0.9057,f1:0.8740
INFO:root:08:34:25 [Epoch 2 Batch 4320/11375] loss=0.2454, lr=0.0000161, metrics:accuracy:0.9057,f1:0.8740
INFO:root:08:34:26 [Epoch 2 Batch 4330/11375] loss=0.2384, lr=0.0000161, metrics:accuracy:0.9056,f1:0.8740
INFO:root:08:34:27 [Epoch 2 Batch 4340/11375] loss=0.2709, lr=0.0000161, metrics:accuracy:0.9056,f1:0.8739
INFO:root:08:34:28 [Epoch 2 Batch 4350/11375] loss=0.2399, lr=0.0000161, metrics:accuracy:0.9056,f1:0.8740
INFO:root:08:34:29 [Epoch 2 Batch 4360/11375] loss=0.2304, lr=0.0000161, metrics:accuracy:0.9056,f1:0.8740
INFO:root:08:34:30 [Epoch 2 Batch 4370/11375] loss=0.2826, lr=0.0000161, metrics:accuracy:0.9055,f1:0.8740
INFO:root:08:34:31 [Epoch 2 Batch 4380/11375] loss=0.2695, lr=0.0000161, metrics:accuracy:0.9055,f1:0.8739
INFO:root:08:34:33 [Epoch 2 Batch 4390/11375] loss=0.1928, lr=0.0000161, metrics:accuracy:0.9055,f1:0.8739
INFO:root:08:34:34 [Epoch 2 Batch 4400/11375] loss=0.2579, lr=0.0000161, metrics:accuracy:0.9055,f1:0.8739
INFO:root:08:34:35 [Epoch 2 Batch 4410/11375] loss=0.2221, lr=0.0000161, metrics:accuracy:0.9055,f1:0.8739
INFO:root:08:34:36 [Epoch 2 Batch 4420/11375] loss=0.2192, lr=0.0000160, metrics:accuracy:0.9055,f1:0.8739
INFO:root:08:34:37 [Epoch 2 Batch 4430/11375] loss=0.1654, lr=0.0000160, metrics:accuracy:0.9055,f1:0.8739
INFO:root:08:34:38 [Epoch 2 Batch 4440/11375] loss=0.2840, lr=0.0000160, metrics:accuracy:0.9055,f1:0.8739
INFO:root:08:34:40 [Epoch 2 Batch 4450/11375] loss=0.2329, lr=0.0000160, metrics:accuracy:0.9054,f1:0.8739
INFO:root:08:34:41 [Epoch 2 Batch 4460/11375] loss=0.1993, lr=0.0000160, metrics:accuracy:0.9054,f1:0.8739
INFO:root:08:34:42 [Epoch 2 Batch 4470/11375] loss=0.2075, lr=0.0000160, metrics:accuracy:0.9055,f1:0.8739
INFO:root:08:34:43 [Epoch 2 Batch 4480/11375] loss=0.1703, lr=0.0000160, metrics:accuracy:0.9055,f1:0.8739
INFO:root:08:34:45 [Epoch 2 Batch 4490/11375] loss=0.1971, lr=0.0000160, metrics:accuracy:0.9055,f1:0.8740
INFO:root:08:34:46 [Epoch 2 Batch 4500/11375] loss=0.2395, lr=0.0000160, metrics:accuracy:0.9055,f1:0.8740
INFO:root:08:34:47 [Epoch 2 Batch 4510/11375] loss=0.2707, lr=0.0000160, metrics:accuracy:0.9055,f1:0.8739
INFO:root:08:34:48 [Epoch 2 Batch 4520/11375] loss=0.2502, lr=0.0000160, metrics:accuracy:0.9055,f1:0.8740
INFO:root:08:34:49 [Epoch 2 Batch 4530/11375] loss=0.2490, lr=0.0000160, metrics:accuracy:0.9054,f1:0.8739
INFO:root:08:34:50 [Epoch 2 Batch 4540/11375] loss=0.2680, lr=0.0000160, metrics:accuracy:0.9054,f1:0.8739
INFO:root:08:34:51 [Epoch 2 Batch 4550/11375] loss=0.1878, lr=0.0000160, metrics:accuracy:0.9054,f1:0.8739
INFO:root:08:34:53 [Epoch 2 Batch 4560/11375] loss=0.1620, lr=0.0000160, metrics:accuracy:0.9055,f1:0.8740
INFO:root:08:34:54 [Epoch 2 Batch 4570/11375] loss=0.2757, lr=0.0000160, metrics:accuracy:0.9054,f1:0.8739
INFO:root:08:34:55 [Epoch 2 Batch 4580/11375] loss=0.2616, lr=0.0000160, metrics:accuracy:0.9054,f1:0.8739
INFO:root:08:34:56 [Epoch 2 Batch 4590/11375] loss=0.1494, lr=0.0000160, metrics:accuracy:0.9055,f1:0.8739
INFO:root:08:34:57 [Epoch 2 Batch 4600/11375] loss=0.2339, lr=0.0000160, metrics:accuracy:0.9055,f1:0.8739
INFO:root:08:34:59 [Epoch 2 Batch 4610/11375] loss=0.2583, lr=0.0000160, metrics:accuracy:0.9055,f1:0.8739
INFO:root:08:35:00 [Epoch 2 Batch 4620/11375] loss=0.1705, lr=0.0000160, metrics:accuracy:0.9055,f1:0.8739
INFO:root:08:35:01 [Epoch 2 Batch 4630/11375] loss=0.3277, lr=0.0000160, metrics:accuracy:0.9054,f1:0.8738
INFO:root:08:35:02 [Epoch 2 Batch 4640/11375] loss=0.1966, lr=0.0000160, metrics:accuracy:0.9055,f1:0.8738
INFO:root:08:35:04 [Epoch 2 Batch 4650/11375] loss=0.2083, lr=0.0000160, metrics:accuracy:0.9055,f1:0.8738
INFO:root:08:35:05 [Epoch 2 Batch 4660/11375] loss=0.2140, lr=0.0000160, metrics:accuracy:0.9055,f1:0.8738
INFO:root:08:35:06 [Epoch 2 Batch 4670/11375] loss=0.1866, lr=0.0000160, metrics:accuracy:0.9056,f1:0.8739
INFO:root:08:35:07 [Epoch 2 Batch 4680/11375] loss=0.1899, lr=0.0000159, metrics:accuracy:0.9056,f1:0.8739
INFO:root:08:35:08 [Epoch 2 Batch 4690/11375] loss=0.2038, lr=0.0000159, metrics:accuracy:0.9056,f1:0.8739
INFO:root:08:35:10 [Epoch 2 Batch 4700/11375] loss=0.1912, lr=0.0000159, metrics:accuracy:0.9057,f1:0.8740
INFO:root:08:35:11 [Epoch 2 Batch 4710/11375] loss=0.2029, lr=0.0000159, metrics:accuracy:0.9057,f1:0.8739
INFO:root:08:35:12 [Epoch 2 Batch 4720/11375] loss=0.2502, lr=0.0000159, metrics:accuracy:0.9057,f1:0.8739
INFO:root:08:35:14 [Epoch 2 Batch 4730/11375] loss=0.1928, lr=0.0000159, metrics:accuracy:0.9057,f1:0.8739
INFO:root:08:35:15 [Epoch 2 Batch 4740/11375] loss=0.2475, lr=0.0000159, metrics:accuracy:0.9057,f1:0.8738
INFO:root:08:35:16 [Epoch 2 Batch 4750/11375] loss=0.1866, lr=0.0000159, metrics:accuracy:0.9057,f1:0.8738
INFO:root:08:35:17 [Epoch 2 Batch 4760/11375] loss=0.2341, lr=0.0000159, metrics:accuracy:0.9057,f1:0.8738
INFO:root:08:35:19 [Epoch 2 Batch 4770/11375] loss=0.2112, lr=0.0000159, metrics:accuracy:0.9057,f1:0.8738
INFO:root:08:35:20 [Epoch 2 Batch 4780/11375] loss=0.2577, lr=0.0000159, metrics:accuracy:0.9057,f1:0.8738
INFO:root:08:35:21 [Epoch 2 Batch 4790/11375] loss=0.2682, lr=0.0000159, metrics:accuracy:0.9057,f1:0.8737
INFO:root:08:35:22 [Epoch 2 Batch 4800/11375] loss=0.2209, lr=0.0000159, metrics:accuracy:0.9057,f1:0.8737
INFO:root:08:35:23 [Epoch 2 Batch 4810/11375] loss=0.1808, lr=0.0000159, metrics:accuracy:0.9057,f1:0.8738
INFO:root:08:35:25 [Epoch 2 Batch 4820/11375] loss=0.2282, lr=0.0000159, metrics:accuracy:0.9057,f1:0.8738
INFO:root:08:35:26 [Epoch 2 Batch 4830/11375] loss=0.2615, lr=0.0000159, metrics:accuracy:0.9057,f1:0.8738
INFO:root:08:35:27 [Epoch 2 Batch 4840/11375] loss=0.2226, lr=0.0000159, metrics:accuracy:0.9057,f1:0.8738
INFO:root:08:35:28 [Epoch 2 Batch 4850/11375] loss=0.2164, lr=0.0000159, metrics:accuracy:0.9057,f1:0.8738
INFO:root:08:35:29 [Epoch 2 Batch 4860/11375] loss=0.2200, lr=0.0000159, metrics:accuracy:0.9058,f1:0.8738
INFO:root:08:35:30 [Epoch 2 Batch 4870/11375] loss=0.2466, lr=0.0000159, metrics:accuracy:0.9057,f1:0.8738
INFO:root:08:35:32 [Epoch 2 Batch 4880/11375] loss=0.2480, lr=0.0000159, metrics:accuracy:0.9057,f1:0.8738
INFO:root:08:35:33 [Epoch 2 Batch 4890/11375] loss=0.2232, lr=0.0000159, metrics:accuracy:0.9057,f1:0.8739
INFO:root:08:35:34 [Epoch 2 Batch 4900/11375] loss=0.2815, lr=0.0000159, metrics:accuracy:0.9057,f1:0.8738
INFO:root:08:35:35 [Epoch 2 Batch 4910/11375] loss=0.2401, lr=0.0000159, metrics:accuracy:0.9056,f1:0.8737
INFO:root:08:35:36 [Epoch 2 Batch 4920/11375] loss=0.2277, lr=0.0000159, metrics:accuracy:0.9056,f1:0.8736
INFO:root:08:35:37 [Epoch 2 Batch 4930/11375] loss=0.2739, lr=0.0000158, metrics:accuracy:0.9056,f1:0.8737
INFO:root:08:35:39 [Epoch 2 Batch 4940/11375] loss=0.1927, lr=0.0000158, metrics:accuracy:0.9056,f1:0.8737
INFO:root:08:35:40 [Epoch 2 Batch 4950/11375] loss=0.1659, lr=0.0000158, metrics:accuracy:0.9057,f1:0.8738
INFO:root:08:35:41 [Epoch 2 Batch 4960/11375] loss=0.2558, lr=0.0000158, metrics:accuracy:0.9057,f1:0.8738
INFO:root:08:35:42 [Epoch 2 Batch 4970/11375] loss=0.2448, lr=0.0000158, metrics:accuracy:0.9056,f1:0.8737
INFO:root:08:35:43 [Epoch 2 Batch 4980/11375] loss=0.2230, lr=0.0000158, metrics:accuracy:0.9056,f1:0.8737
INFO:root:08:35:44 [Epoch 2 Batch 4990/11375] loss=0.2312, lr=0.0000158, metrics:accuracy:0.9056,f1:0.8737
INFO:root:08:35:45 [Epoch 2 Batch 5000/11375] loss=0.3053, lr=0.0000158, metrics:accuracy:0.9056,f1:0.8737
INFO:root:08:35:47 [Epoch 2 Batch 5010/11375] loss=0.2401, lr=0.0000158, metrics:accuracy:0.9055,f1:0.8737
INFO:root:08:35:48 [Epoch 2 Batch 5020/11375] loss=0.2284, lr=0.0000158, metrics:accuracy:0.9056,f1:0.8737
INFO:root:08:35:49 [Epoch 2 Batch 5030/11375] loss=0.1628, lr=0.0000158, metrics:accuracy:0.9056,f1:0.8737
INFO:root:08:35:50 [Epoch 2 Batch 5040/11375] loss=0.2195, lr=0.0000158, metrics:accuracy:0.9057,f1:0.8738
INFO:root:08:35:51 [Epoch 2 Batch 5050/11375] loss=0.2722, lr=0.0000158, metrics:accuracy:0.9056,f1:0.8737
INFO:root:08:35:53 [Epoch 2 Batch 5060/11375] loss=0.2363, lr=0.0000158, metrics:accuracy:0.9056,f1:0.8737
INFO:root:08:35:54 [Epoch 2 Batch 5070/11375] loss=0.2065, lr=0.0000158, metrics:accuracy:0.9056,f1:0.8737
INFO:root:08:35:55 [Epoch 2 Batch 5080/11375] loss=0.1777, lr=0.0000158, metrics:accuracy:0.9057,f1:0.8738
INFO:root:08:35:56 [Epoch 2 Batch 5090/11375] loss=0.2331, lr=0.0000158, metrics:accuracy:0.9057,f1:0.8738
INFO:root:08:35:57 [Epoch 2 Batch 5100/11375] loss=0.2303, lr=0.0000158, metrics:accuracy:0.9057,f1:0.8738
INFO:root:08:35:58 [Epoch 2 Batch 5110/11375] loss=0.3284, lr=0.0000158, metrics:accuracy:0.9056,f1:0.8737
INFO:root:08:35:59 [Epoch 2 Batch 5120/11375] loss=0.2062, lr=0.0000158, metrics:accuracy:0.9056,f1:0.8738
INFO:root:08:36:01 [Epoch 2 Batch 5130/11375] loss=0.2313, lr=0.0000158, metrics:accuracy:0.9056,f1:0.8738
INFO:root:08:36:02 [Epoch 2 Batch 5140/11375] loss=0.2500, lr=0.0000158, metrics:accuracy:0.9056,f1:0.8737
INFO:root:08:36:03 [Epoch 2 Batch 5150/11375] loss=0.2578, lr=0.0000158, metrics:accuracy:0.9055,f1:0.8737
INFO:root:08:36:04 [Epoch 2 Batch 5160/11375] loss=0.2235, lr=0.0000158, metrics:accuracy:0.9055,f1:0.8736
INFO:root:08:36:05 [Epoch 2 Batch 5170/11375] loss=0.1707, lr=0.0000158, metrics:accuracy:0.9055,f1:0.8737
INFO:root:08:36:06 [Epoch 2 Batch 5180/11375] loss=0.1711, lr=0.0000158, metrics:accuracy:0.9056,f1:0.8737
INFO:root:08:36:08 [Epoch 2 Batch 5190/11375] loss=0.1857, lr=0.0000157, metrics:accuracy:0.9056,f1:0.8738
INFO:root:08:36:09 [Epoch 2 Batch 5200/11375] loss=0.1833, lr=0.0000157, metrics:accuracy:0.9056,f1:0.8738
INFO:root:08:36:10 [Epoch 2 Batch 5210/11375] loss=0.1566, lr=0.0000157, metrics:accuracy:0.9057,f1:0.8739
INFO:root:08:36:11 [Epoch 2 Batch 5220/11375] loss=0.2542, lr=0.0000157, metrics:accuracy:0.9057,f1:0.8740
INFO:root:08:36:12 [Epoch 2 Batch 5230/11375] loss=0.2228, lr=0.0000157, metrics:accuracy:0.9057,f1:0.8740
INFO:root:08:36:13 [Epoch 2 Batch 5240/11375] loss=0.1942, lr=0.0000157, metrics:accuracy:0.9057,f1:0.8740
INFO:root:08:36:15 [Epoch 2 Batch 5250/11375] loss=0.2167, lr=0.0000157, metrics:accuracy:0.9057,f1:0.8740
INFO:root:08:36:16 [Epoch 2 Batch 5260/11375] loss=0.2465, lr=0.0000157, metrics:accuracy:0.9057,f1:0.8740
INFO:root:08:36:17 [Epoch 2 Batch 5270/11375] loss=0.2190, lr=0.0000157, metrics:accuracy:0.9057,f1:0.8740
INFO:root:08:36:18 [Epoch 2 Batch 5280/11375] loss=0.1771, lr=0.0000157, metrics:accuracy:0.9058,f1:0.8741
INFO:root:08:36:19 [Epoch 2 Batch 5290/11375] loss=0.2664, lr=0.0000157, metrics:accuracy:0.9058,f1:0.8741
INFO:root:08:36:21 [Epoch 2 Batch 5300/11375] loss=0.2250, lr=0.0000157, metrics:accuracy:0.9058,f1:0.8741
INFO:root:08:36:22 [Epoch 2 Batch 5310/11375] loss=0.1745, lr=0.0000157, metrics:accuracy:0.9058,f1:0.8741
INFO:root:08:36:23 [Epoch 2 Batch 5320/11375] loss=0.2529, lr=0.0000157, metrics:accuracy:0.9058,f1:0.8741
INFO:root:08:36:24 [Epoch 2 Batch 5330/11375] loss=0.2469, lr=0.0000157, metrics:accuracy:0.9058,f1:0.8741
INFO:root:08:36:25 [Epoch 2 Batch 5340/11375] loss=0.2005, lr=0.0000157, metrics:accuracy:0.9058,f1:0.8742
INFO:root:08:36:27 [Epoch 2 Batch 5350/11375] loss=0.1826, lr=0.0000157, metrics:accuracy:0.9059,f1:0.8742
INFO:root:08:36:28 [Epoch 2 Batch 5360/11375] loss=0.2064, lr=0.0000157, metrics:accuracy:0.9059,f1:0.8742
INFO:root:08:36:29 [Epoch 2 Batch 5370/11375] loss=0.2052, lr=0.0000157, metrics:accuracy:0.9059,f1:0.8742
INFO:root:08:36:30 [Epoch 2 Batch 5380/11375] loss=0.3059, lr=0.0000157, metrics:accuracy:0.9058,f1:0.8742
INFO:root:08:36:31 [Epoch 2 Batch 5390/11375] loss=0.1789, lr=0.0000157, metrics:accuracy:0.9059,f1:0.8742
INFO:root:08:36:32 [Epoch 2 Batch 5400/11375] loss=0.3267, lr=0.0000157, metrics:accuracy:0.9058,f1:0.8741
INFO:root:08:36:34 [Epoch 2 Batch 5410/11375] loss=0.2111, lr=0.0000157, metrics:accuracy:0.9058,f1:0.8741
INFO:root:08:36:35 [Epoch 2 Batch 5420/11375] loss=0.1746, lr=0.0000157, metrics:accuracy:0.9059,f1:0.8742
INFO:root:08:36:36 [Epoch 2 Batch 5430/11375] loss=0.2583, lr=0.0000157, metrics:accuracy:0.9058,f1:0.8742
INFO:root:08:36:37 [Epoch 2 Batch 5440/11375] loss=0.2077, lr=0.0000156, metrics:accuracy:0.9059,f1:0.8743
INFO:root:08:36:38 [Epoch 2 Batch 5450/11375] loss=0.2593, lr=0.0000156, metrics:accuracy:0.9058,f1:0.8742
INFO:root:08:36:40 [Epoch 2 Batch 5460/11375] loss=0.1846, lr=0.0000156, metrics:accuracy:0.9059,f1:0.8742
INFO:root:08:36:41 [Epoch 2 Batch 5470/11375] loss=0.3074, lr=0.0000156, metrics:accuracy:0.9058,f1:0.8741
INFO:root:08:36:42 [Epoch 2 Batch 5480/11375] loss=0.2204, lr=0.0000156, metrics:accuracy:0.9058,f1:0.8741
INFO:root:08:36:43 [Epoch 2 Batch 5490/11375] loss=0.2382, lr=0.0000156, metrics:accuracy:0.9058,f1:0.8741
INFO:root:08:36:45 [Epoch 2 Batch 5500/11375] loss=0.1760, lr=0.0000156, metrics:accuracy:0.9058,f1:0.8741
INFO:root:08:36:46 [Epoch 2 Batch 5510/11375] loss=0.2958, lr=0.0000156, metrics:accuracy:0.9058,f1:0.8741
INFO:root:08:36:47 [Epoch 2 Batch 5520/11375] loss=0.2007, lr=0.0000156, metrics:accuracy:0.9058,f1:0.8741
INFO:root:08:36:48 [Epoch 2 Batch 5530/11375] loss=0.2485, lr=0.0000156, metrics:accuracy:0.9058,f1:0.8741
INFO:root:08:36:50 [Epoch 2 Batch 5540/11375] loss=0.1915, lr=0.0000156, metrics:accuracy:0.9058,f1:0.8741
INFO:root:08:36:51 [Epoch 2 Batch 5550/11375] loss=0.2991, lr=0.0000156, metrics:accuracy:0.9057,f1:0.8741
INFO:root:08:36:52 [Epoch 2 Batch 5560/11375] loss=0.3032, lr=0.0000156, metrics:accuracy:0.9057,f1:0.8740
INFO:root:08:36:53 [Epoch 2 Batch 5570/11375] loss=0.1729, lr=0.0000156, metrics:accuracy:0.9057,f1:0.8741
INFO:root:08:36:54 [Epoch 2 Batch 5580/11375] loss=0.2083, lr=0.0000156, metrics:accuracy:0.9057,f1:0.8741
INFO:root:08:36:55 [Epoch 2 Batch 5590/11375] loss=0.2163, lr=0.0000156, metrics:accuracy:0.9057,f1:0.8741
INFO:root:08:36:57 [Epoch 2 Batch 5600/11375] loss=0.2389, lr=0.0000156, metrics:accuracy:0.9057,f1:0.8740
INFO:root:08:36:58 [Epoch 2 Batch 5610/11375] loss=0.2421, lr=0.0000156, metrics:accuracy:0.9057,f1:0.8741
INFO:root:08:36:59 [Epoch 2 Batch 5620/11375] loss=0.2467, lr=0.0000156, metrics:accuracy:0.9057,f1:0.8740
INFO:root:08:37:00 [Epoch 2 Batch 5630/11375] loss=0.2710, lr=0.0000156, metrics:accuracy:0.9057,f1:0.8740
INFO:root:08:37:02 [Epoch 2 Batch 5640/11375] loss=0.2043, lr=0.0000156, metrics:accuracy:0.9057,f1:0.8740
INFO:root:08:37:03 [Epoch 2 Batch 5650/11375] loss=0.2432, lr=0.0000156, metrics:accuracy:0.9057,f1:0.8740
INFO:root:08:37:04 [Epoch 2 Batch 5660/11375] loss=0.2285, lr=0.0000156, metrics:accuracy:0.9057,f1:0.8740
INFO:root:08:37:05 [Epoch 2 Batch 5670/11375] loss=0.2602, lr=0.0000156, metrics:accuracy:0.9057,f1:0.8740
INFO:root:08:37:06 [Epoch 2 Batch 5680/11375] loss=0.2388, lr=0.0000156, metrics:accuracy:0.9056,f1:0.8740
INFO:root:08:37:08 [Epoch 2 Batch 5690/11375] loss=0.1533, lr=0.0000156, metrics:accuracy:0.9057,f1:0.8740
INFO:root:08:37:09 [Epoch 2 Batch 5700/11375] loss=0.2185, lr=0.0000155, metrics:accuracy:0.9057,f1:0.8740
INFO:root:08:37:10 [Epoch 2 Batch 5710/11375] loss=0.2482, lr=0.0000155, metrics:accuracy:0.9057,f1:0.8739
INFO:root:08:37:11 [Epoch 2 Batch 5720/11375] loss=0.1995, lr=0.0000155, metrics:accuracy:0.9057,f1:0.8740
INFO:root:08:37:12 [Epoch 2 Batch 5730/11375] loss=0.2409, lr=0.0000155, metrics:accuracy:0.9057,f1:0.8741
INFO:root:08:37:14 [Epoch 2 Batch 5740/11375] loss=0.2115, lr=0.0000155, metrics:accuracy:0.9057,f1:0.8741
INFO:root:08:37:15 [Epoch 2 Batch 5750/11375] loss=0.1778, lr=0.0000155, metrics:accuracy:0.9058,f1:0.8741
INFO:root:08:37:16 [Epoch 2 Batch 5760/11375] loss=0.1475, lr=0.0000155, metrics:accuracy:0.9058,f1:0.8742
INFO:root:08:37:17 [Epoch 2 Batch 5770/11375] loss=0.3177, lr=0.0000155, metrics:accuracy:0.9058,f1:0.8742
INFO:root:08:37:18 [Epoch 2 Batch 5780/11375] loss=0.2218, lr=0.0000155, metrics:accuracy:0.9058,f1:0.8742
INFO:root:08:37:20 [Epoch 2 Batch 5790/11375] loss=0.1965, lr=0.0000155, metrics:accuracy:0.9058,f1:0.8742
INFO:root:08:37:21 [Epoch 2 Batch 5800/11375] loss=0.2627, lr=0.0000155, metrics:accuracy:0.9057,f1:0.8741
INFO:root:08:37:22 [Epoch 2 Batch 5810/11375] loss=0.2490, lr=0.0000155, metrics:accuracy:0.9057,f1:0.8740
INFO:root:08:37:24 [Epoch 2 Batch 5820/11375] loss=0.2780, lr=0.0000155, metrics:accuracy:0.9057,f1:0.8740
INFO:root:08:37:25 [Epoch 2 Batch 5830/11375] loss=0.2284, lr=0.0000155, metrics:accuracy:0.9057,f1:0.8741
INFO:root:08:37:26 [Epoch 2 Batch 5840/11375] loss=0.2273, lr=0.0000155, metrics:accuracy:0.9057,f1:0.8741
INFO:root:08:37:27 [Epoch 2 Batch 5850/11375] loss=0.2510, lr=0.0000155, metrics:accuracy:0.9057,f1:0.8740
INFO:root:08:37:28 [Epoch 2 Batch 5860/11375] loss=0.2243, lr=0.0000155, metrics:accuracy:0.9057,f1:0.8741
INFO:root:08:37:29 [Epoch 2 Batch 5870/11375] loss=0.1900, lr=0.0000155, metrics:accuracy:0.9057,f1:0.8741
INFO:root:08:37:30 [Epoch 2 Batch 5880/11375] loss=0.2380, lr=0.0000155, metrics:accuracy:0.9057,f1:0.8741
INFO:root:08:37:32 [Epoch 2 Batch 5890/11375] loss=0.2078, lr=0.0000155, metrics:accuracy:0.9057,f1:0.8741
INFO:root:08:37:33 [Epoch 2 Batch 5900/11375] loss=0.2027, lr=0.0000155, metrics:accuracy:0.9057,f1:0.8741
INFO:root:08:37:34 [Epoch 2 Batch 5910/11375] loss=0.2046, lr=0.0000155, metrics:accuracy:0.9058,f1:0.8741
INFO:root:08:37:35 [Epoch 2 Batch 5920/11375] loss=0.1848, lr=0.0000155, metrics:accuracy:0.9058,f1:0.8742
INFO:root:08:37:36 [Epoch 2 Batch 5930/11375] loss=0.2685, lr=0.0000155, metrics:accuracy:0.9058,f1:0.8742
INFO:root:08:37:38 [Epoch 2 Batch 5940/11375] loss=0.2051, lr=0.0000155, metrics:accuracy:0.9058,f1:0.8742
INFO:root:08:37:39 [Epoch 2 Batch 5950/11375] loss=0.2204, lr=0.0000155, metrics:accuracy:0.9058,f1:0.8742
INFO:root:08:37:40 [Epoch 2 Batch 5960/11375] loss=0.1899, lr=0.0000154, metrics:accuracy:0.9058,f1:0.8742
INFO:root:08:37:41 [Epoch 2 Batch 5970/11375] loss=0.1934, lr=0.0000154, metrics:accuracy:0.9059,f1:0.8743
INFO:root:08:37:42 [Epoch 2 Batch 5980/11375] loss=0.2555, lr=0.0000154, metrics:accuracy:0.9059,f1:0.8743
INFO:root:08:37:44 [Epoch 2 Batch 5990/11375] loss=0.1603, lr=0.0000154, metrics:accuracy:0.9059,f1:0.8743
INFO:root:08:37:45 [Epoch 2 Batch 6000/11375] loss=0.2435, lr=0.0000154, metrics:accuracy:0.9059,f1:0.8743
INFO:root:08:37:46 [Epoch 2 Batch 6010/11375] loss=0.2294, lr=0.0000154, metrics:accuracy:0.9059,f1:0.8743
INFO:root:08:37:47 [Epoch 2 Batch 6020/11375] loss=0.3029, lr=0.0000154, metrics:accuracy:0.9058,f1:0.8743
INFO:root:08:37:48 [Epoch 2 Batch 6030/11375] loss=0.2371, lr=0.0000154, metrics:accuracy:0.9058,f1:0.8742
INFO:root:08:37:50 [Epoch 2 Batch 6040/11375] loss=0.2088, lr=0.0000154, metrics:accuracy:0.9058,f1:0.8742
INFO:root:08:37:51 [Epoch 2 Batch 6050/11375] loss=0.2153, lr=0.0000154, metrics:accuracy:0.9058,f1:0.8742
INFO:root:08:37:52 [Epoch 2 Batch 6060/11375] loss=0.2772, lr=0.0000154, metrics:accuracy:0.9058,f1:0.8742
INFO:root:08:37:53 [Epoch 2 Batch 6070/11375] loss=0.2233, lr=0.0000154, metrics:accuracy:0.9058,f1:0.8742
INFO:root:08:37:54 [Epoch 2 Batch 6080/11375] loss=0.2037, lr=0.0000154, metrics:accuracy:0.9058,f1:0.8743
INFO:root:08:37:55 [Epoch 2 Batch 6090/11375] loss=0.1653, lr=0.0000154, metrics:accuracy:0.9059,f1:0.8743
INFO:root:08:37:57 [Epoch 2 Batch 6100/11375] loss=0.2145, lr=0.0000154, metrics:accuracy:0.9059,f1:0.8743
INFO:root:08:37:58 [Epoch 2 Batch 6110/11375] loss=0.1867, lr=0.0000154, metrics:accuracy:0.9059,f1:0.8743
INFO:root:08:37:59 [Epoch 2 Batch 6120/11375] loss=0.2205, lr=0.0000154, metrics:accuracy:0.9059,f1:0.8743
INFO:root:08:38:00 [Epoch 2 Batch 6130/11375] loss=0.2257, lr=0.0000154, metrics:accuracy:0.9059,f1:0.8744
INFO:root:08:38:01 [Epoch 2 Batch 6140/11375] loss=0.2059, lr=0.0000154, metrics:accuracy:0.9059,f1:0.8744
INFO:root:08:38:02 [Epoch 2 Batch 6150/11375] loss=0.1972, lr=0.0000154, metrics:accuracy:0.9059,f1:0.8745
INFO:root:08:38:03 [Epoch 2 Batch 6160/11375] loss=0.1970, lr=0.0000154, metrics:accuracy:0.9060,f1:0.8745
INFO:root:08:38:05 [Epoch 2 Batch 6170/11375] loss=0.2319, lr=0.0000154, metrics:accuracy:0.9060,f1:0.8746
INFO:root:08:38:06 [Epoch 2 Batch 6180/11375] loss=0.2362, lr=0.0000154, metrics:accuracy:0.9060,f1:0.8746
INFO:root:08:38:07 [Epoch 2 Batch 6190/11375] loss=0.2056, lr=0.0000154, metrics:accuracy:0.9060,f1:0.8745
INFO:root:08:38:09 [Epoch 2 Batch 6200/11375] loss=0.1897, lr=0.0000154, metrics:accuracy:0.9060,f1:0.8745
INFO:root:08:38:10 [Epoch 2 Batch 6210/11375] loss=0.3005, lr=0.0000153, metrics:accuracy:0.9060,f1:0.8745
INFO:root:08:38:11 [Epoch 2 Batch 6220/11375] loss=0.2449, lr=0.0000153, metrics:accuracy:0.9060,f1:0.8745
INFO:root:08:38:12 [Epoch 2 Batch 6230/11375] loss=0.1797, lr=0.0000153, metrics:accuracy:0.9060,f1:0.8746
INFO:root:08:38:13 [Epoch 2 Batch 6240/11375] loss=0.2208, lr=0.0000153, metrics:accuracy:0.9060,f1:0.8746
INFO:root:08:38:14 [Epoch 2 Batch 6250/11375] loss=0.2065, lr=0.0000153, metrics:accuracy:0.9060,f1:0.8745
INFO:root:08:38:16 [Epoch 2 Batch 6260/11375] loss=0.2664, lr=0.0000153, metrics:accuracy:0.9060,f1:0.8745
INFO:root:08:38:17 [Epoch 2 Batch 6270/11375] loss=0.2662, lr=0.0000153, metrics:accuracy:0.9060,f1:0.8745
INFO:root:08:38:18 [Epoch 2 Batch 6280/11375] loss=0.1826, lr=0.0000153, metrics:accuracy:0.9060,f1:0.8746
INFO:root:08:38:20 [Epoch 2 Batch 6290/11375] loss=0.2687, lr=0.0000153, metrics:accuracy:0.9060,f1:0.8746
INFO:root:08:38:21 [Epoch 2 Batch 6300/11375] loss=0.1506, lr=0.0000153, metrics:accuracy:0.9060,f1:0.8746
INFO:root:08:38:23 [Epoch 2 Batch 6310/11375] loss=0.2116, lr=0.0000153, metrics:accuracy:0.9061,f1:0.8747
INFO:root:08:38:24 [Epoch 2 Batch 6320/11375] loss=0.2364, lr=0.0000153, metrics:accuracy:0.9061,f1:0.8747
INFO:root:08:38:25 [Epoch 2 Batch 6330/11375] loss=0.2023, lr=0.0000153, metrics:accuracy:0.9061,f1:0.8748
INFO:root:08:38:26 [Epoch 2 Batch 6340/11375] loss=0.2405, lr=0.0000153, metrics:accuracy:0.9061,f1:0.8747
INFO:root:08:38:27 [Epoch 2 Batch 6350/11375] loss=0.2266, lr=0.0000153, metrics:accuracy:0.9061,f1:0.8747
INFO:root:08:38:29 [Epoch 2 Batch 6360/11375] loss=0.2517, lr=0.0000153, metrics:accuracy:0.9061,f1:0.8746
INFO:root:08:38:30 [Epoch 2 Batch 6370/11375] loss=0.1892, lr=0.0000153, metrics:accuracy:0.9061,f1:0.8746
INFO:root:08:38:31 [Epoch 2 Batch 6380/11375] loss=0.2197, lr=0.0000153, metrics:accuracy:0.9061,f1:0.8747
INFO:root:08:38:32 [Epoch 2 Batch 6390/11375] loss=0.2597, lr=0.0000153, metrics:accuracy:0.9061,f1:0.8746
INFO:root:08:38:33 [Epoch 2 Batch 6400/11375] loss=0.2485, lr=0.0000153, metrics:accuracy:0.9061,f1:0.8746
INFO:root:08:38:35 [Epoch 2 Batch 6410/11375] loss=0.1702, lr=0.0000153, metrics:accuracy:0.9061,f1:0.8746
INFO:root:08:38:36 [Epoch 2 Batch 6420/11375] loss=0.1644, lr=0.0000153, metrics:accuracy:0.9062,f1:0.8747
INFO:root:08:38:37 [Epoch 2 Batch 6430/11375] loss=0.2216, lr=0.0000153, metrics:accuracy:0.9062,f1:0.8747
INFO:root:08:38:39 [Epoch 2 Batch 6440/11375] loss=0.2419, lr=0.0000153, metrics:accuracy:0.9062,f1:0.8746
INFO:root:08:38:40 [Epoch 2 Batch 6450/11375] loss=0.2195, lr=0.0000153, metrics:accuracy:0.9062,f1:0.8746
INFO:root:08:38:41 [Epoch 2 Batch 6460/11375] loss=0.2636, lr=0.0000153, metrics:accuracy:0.9061,f1:0.8746
INFO:root:08:38:42 [Epoch 2 Batch 6470/11375] loss=0.1989, lr=0.0000152, metrics:accuracy:0.9061,f1:0.8746
INFO:root:08:38:44 [Epoch 2 Batch 6480/11375] loss=0.2012, lr=0.0000152, metrics:accuracy:0.9062,f1:0.8746
INFO:root:08:38:45 [Epoch 2 Batch 6490/11375] loss=0.1991, lr=0.0000152, metrics:accuracy:0.9062,f1:0.8746
INFO:root:08:38:46 [Epoch 2 Batch 6500/11375] loss=0.2304, lr=0.0000152, metrics:accuracy:0.9062,f1:0.8746
INFO:root:08:38:47 [Epoch 2 Batch 6510/11375] loss=0.2203, lr=0.0000152, metrics:accuracy:0.9062,f1:0.8746
INFO:root:08:38:48 [Epoch 2 Batch 6520/11375] loss=0.2406, lr=0.0000152, metrics:accuracy:0.9062,f1:0.8746
INFO:root:08:38:50 [Epoch 2 Batch 6530/11375] loss=0.1986, lr=0.0000152, metrics:accuracy:0.9062,f1:0.8746
INFO:root:08:38:51 [Epoch 2 Batch 6540/11375] loss=0.2204, lr=0.0000152, metrics:accuracy:0.9062,f1:0.8746
INFO:root:08:38:52 [Epoch 2 Batch 6550/11375] loss=0.2075, lr=0.0000152, metrics:accuracy:0.9062,f1:0.8746
INFO:root:08:38:53 [Epoch 2 Batch 6560/11375] loss=0.2446, lr=0.0000152, metrics:accuracy:0.9062,f1:0.8746
INFO:root:08:38:54 [Epoch 2 Batch 6570/11375] loss=0.2880, lr=0.0000152, metrics:accuracy:0.9061,f1:0.8745
INFO:root:08:38:56 [Epoch 2 Batch 6580/11375] loss=0.3041, lr=0.0000152, metrics:accuracy:0.9061,f1:0.8745
INFO:root:08:38:57 [Epoch 2 Batch 6590/11375] loss=0.2066, lr=0.0000152, metrics:accuracy:0.9061,f1:0.8745
INFO:root:08:38:58 [Epoch 2 Batch 6600/11375] loss=0.1602, lr=0.0000152, metrics:accuracy:0.9061,f1:0.8745
INFO:root:08:38:59 [Epoch 2 Batch 6610/11375] loss=0.2705, lr=0.0000152, metrics:accuracy:0.9061,f1:0.8745
INFO:root:08:39:00 [Epoch 2 Batch 6620/11375] loss=0.2391, lr=0.0000152, metrics:accuracy:0.9061,f1:0.8745
INFO:root:08:39:02 [Epoch 2 Batch 6630/11375] loss=0.2128, lr=0.0000152, metrics:accuracy:0.9061,f1:0.8744
INFO:root:08:39:03 [Epoch 2 Batch 6640/11375] loss=0.1841, lr=0.0000152, metrics:accuracy:0.9061,f1:0.8745
INFO:root:08:39:04 [Epoch 2 Batch 6650/11375] loss=0.1771, lr=0.0000152, metrics:accuracy:0.9061,f1:0.8745
INFO:root:08:39:05 [Epoch 2 Batch 6660/11375] loss=0.2197, lr=0.0000152, metrics:accuracy:0.9061,f1:0.8745
INFO:root:08:39:06 [Epoch 2 Batch 6670/11375] loss=0.2306, lr=0.0000152, metrics:accuracy:0.9061,f1:0.8744
INFO:root:08:39:08 [Epoch 2 Batch 6680/11375] loss=0.2234, lr=0.0000152, metrics:accuracy:0.9061,f1:0.8745
INFO:root:08:39:09 [Epoch 2 Batch 6690/11375] loss=0.2420, lr=0.0000152, metrics:accuracy:0.9061,f1:0.8745
INFO:root:08:39:10 [Epoch 2 Batch 6700/11375] loss=0.2145, lr=0.0000152, metrics:accuracy:0.9061,f1:0.8745
INFO:root:08:39:11 [Epoch 2 Batch 6710/11375] loss=0.2345, lr=0.0000152, metrics:accuracy:0.9061,f1:0.8745
INFO:root:08:39:12 [Epoch 2 Batch 6720/11375] loss=0.2399, lr=0.0000151, metrics:accuracy:0.9061,f1:0.8745
INFO:root:08:39:14 [Epoch 2 Batch 6730/11375] loss=0.2343, lr=0.0000151, metrics:accuracy:0.9061,f1:0.8745
INFO:root:08:39:15 [Epoch 2 Batch 6740/11375] loss=0.1717, lr=0.0000151, metrics:accuracy:0.9062,f1:0.8745
INFO:root:08:39:16 [Epoch 2 Batch 6750/11375] loss=0.1361, lr=0.0000151, metrics:accuracy:0.9062,f1:0.8745
INFO:root:08:39:18 [Epoch 2 Batch 6760/11375] loss=0.1860, lr=0.0000151, metrics:accuracy:0.9063,f1:0.8746
INFO:root:08:39:19 [Epoch 2 Batch 6770/11375] loss=0.2041, lr=0.0000151, metrics:accuracy:0.9063,f1:0.8746
INFO:root:08:39:20 [Epoch 2 Batch 6780/11375] loss=0.3000, lr=0.0000151, metrics:accuracy:0.9063,f1:0.8746
INFO:root:08:39:21 [Epoch 2 Batch 6790/11375] loss=0.2358, lr=0.0000151, metrics:accuracy:0.9062,f1:0.8746
INFO:root:08:39:22 [Epoch 2 Batch 6800/11375] loss=0.2315, lr=0.0000151, metrics:accuracy:0.9062,f1:0.8746
INFO:root:08:39:23 [Epoch 2 Batch 6810/11375] loss=0.1876, lr=0.0000151, metrics:accuracy:0.9062,f1:0.8746
INFO:root:08:39:25 [Epoch 2 Batch 6820/11375] loss=0.2035, lr=0.0000151, metrics:accuracy:0.9063,f1:0.8746
INFO:root:08:39:26 [Epoch 2 Batch 6830/11375] loss=0.2035, lr=0.0000151, metrics:accuracy:0.9063,f1:0.8746
INFO:root:08:39:27 [Epoch 2 Batch 6840/11375] loss=0.2519, lr=0.0000151, metrics:accuracy:0.9062,f1:0.8746
INFO:root:08:39:28 [Epoch 2 Batch 6850/11375] loss=0.2384, lr=0.0000151, metrics:accuracy:0.9062,f1:0.8745
INFO:root:08:39:29 [Epoch 2 Batch 6860/11375] loss=0.1977, lr=0.0000151, metrics:accuracy:0.9062,f1:0.8746
INFO:root:08:39:30 [Epoch 2 Batch 6870/11375] loss=0.2651, lr=0.0000151, metrics:accuracy:0.9062,f1:0.8745
INFO:root:08:39:32 [Epoch 2 Batch 6880/11375] loss=0.2012, lr=0.0000151, metrics:accuracy:0.9063,f1:0.8746
INFO:root:08:39:33 [Epoch 2 Batch 6890/11375] loss=0.2310, lr=0.0000151, metrics:accuracy:0.9062,f1:0.8746
INFO:root:08:39:34 [Epoch 2 Batch 6900/11375] loss=0.1623, lr=0.0000151, metrics:accuracy:0.9063,f1:0.8747
INFO:root:08:39:35 [Epoch 2 Batch 6910/11375] loss=0.2940, lr=0.0000151, metrics:accuracy:0.9063,f1:0.8747
INFO:root:08:39:36 [Epoch 2 Batch 6920/11375] loss=0.2134, lr=0.0000151, metrics:accuracy:0.9063,f1:0.8747
INFO:root:08:39:37 [Epoch 2 Batch 6930/11375] loss=0.1551, lr=0.0000151, metrics:accuracy:0.9063,f1:0.8748
INFO:root:08:39:39 [Epoch 2 Batch 6940/11375] loss=0.2297, lr=0.0000151, metrics:accuracy:0.9063,f1:0.8748
INFO:root:08:39:40 [Epoch 2 Batch 6950/11375] loss=0.2181, lr=0.0000151, metrics:accuracy:0.9063,f1:0.8748
INFO:root:08:39:41 [Epoch 2 Batch 6960/11375] loss=0.2138, lr=0.0000151, metrics:accuracy:0.9063,f1:0.8748
INFO:root:08:39:42 [Epoch 2 Batch 6970/11375] loss=0.1664, lr=0.0000151, metrics:accuracy:0.9064,f1:0.8748
INFO:root:08:39:43 [Epoch 2 Batch 6980/11375] loss=0.2560, lr=0.0000150, metrics:accuracy:0.9064,f1:0.8749
INFO:root:08:39:45 [Epoch 2 Batch 6990/11375] loss=0.2015, lr=0.0000150, metrics:accuracy:0.9064,f1:0.8748
INFO:root:08:39:46 [Epoch 2 Batch 7000/11375] loss=0.2361, lr=0.0000150, metrics:accuracy:0.9063,f1:0.8748
INFO:root:08:39:47 [Epoch 2 Batch 7010/11375] loss=0.2506, lr=0.0000150, metrics:accuracy:0.9063,f1:0.8748
INFO:root:08:39:48 [Epoch 2 Batch 7020/11375] loss=0.2697, lr=0.0000150, metrics:accuracy:0.9063,f1:0.8748
INFO:root:08:39:49 [Epoch 2 Batch 7030/11375] loss=0.1656, lr=0.0000150, metrics:accuracy:0.9063,f1:0.8748
INFO:root:08:39:50 [Epoch 2 Batch 7040/11375] loss=0.1784, lr=0.0000150, metrics:accuracy:0.9063,f1:0.8748
INFO:root:08:39:51 [Epoch 2 Batch 7050/11375] loss=0.2375, lr=0.0000150, metrics:accuracy:0.9063,f1:0.8748
INFO:root:08:39:53 [Epoch 2 Batch 7060/11375] loss=0.2130, lr=0.0000150, metrics:accuracy:0.9063,f1:0.8749
INFO:root:08:39:54 [Epoch 2 Batch 7070/11375] loss=0.2123, lr=0.0000150, metrics:accuracy:0.9063,f1:0.8749
INFO:root:08:39:55 [Epoch 2 Batch 7080/11375] loss=0.1313, lr=0.0000150, metrics:accuracy:0.9064,f1:0.8749
INFO:root:08:39:56 [Epoch 2 Batch 7090/11375] loss=0.2452, lr=0.0000150, metrics:accuracy:0.9064,f1:0.8749
INFO:root:08:39:57 [Epoch 2 Batch 7100/11375] loss=0.2771, lr=0.0000150, metrics:accuracy:0.9063,f1:0.8749
INFO:root:08:39:58 [Epoch 2 Batch 7110/11375] loss=0.1618, lr=0.0000150, metrics:accuracy:0.9064,f1:0.8749
INFO:root:08:40:00 [Epoch 2 Batch 7120/11375] loss=0.1859, lr=0.0000150, metrics:accuracy:0.9064,f1:0.8750
INFO:root:08:40:01 [Epoch 2 Batch 7130/11375] loss=0.1992, lr=0.0000150, metrics:accuracy:0.9064,f1:0.8750
INFO:root:08:40:02 [Epoch 2 Batch 7140/11375] loss=0.2088, lr=0.0000150, metrics:accuracy:0.9065,f1:0.8750
INFO:root:08:40:04 [Epoch 2 Batch 7150/11375] loss=0.2123, lr=0.0000150, metrics:accuracy:0.9065,f1:0.8750
INFO:root:08:40:05 [Epoch 2 Batch 7160/11375] loss=0.2373, lr=0.0000150, metrics:accuracy:0.9065,f1:0.8750
INFO:root:08:40:06 [Epoch 2 Batch 7170/11375] loss=0.2461, lr=0.0000150, metrics:accuracy:0.9065,f1:0.8750
INFO:root:08:40:07 [Epoch 2 Batch 7180/11375] loss=0.2611, lr=0.0000150, metrics:accuracy:0.9064,f1:0.8750
INFO:root:08:40:08 [Epoch 2 Batch 7190/11375] loss=0.2471, lr=0.0000150, metrics:accuracy:0.9064,f1:0.8749
INFO:root:08:40:09 [Epoch 2 Batch 7200/11375] loss=0.2668, lr=0.0000150, metrics:accuracy:0.9064,f1:0.8750
INFO:root:08:40:10 [Epoch 2 Batch 7210/11375] loss=0.1364, lr=0.0000150, metrics:accuracy:0.9064,f1:0.8750
INFO:root:08:40:12 [Epoch 2 Batch 7220/11375] loss=0.2321, lr=0.0000150, metrics:accuracy:0.9064,f1:0.8750
INFO:root:08:40:13 [Epoch 2 Batch 7230/11375] loss=0.2534, lr=0.0000150, metrics:accuracy:0.9064,f1:0.8749
INFO:root:08:40:14 [Epoch 2 Batch 7240/11375] loss=0.2462, lr=0.0000149, metrics:accuracy:0.9064,f1:0.8749
INFO:root:08:40:15 [Epoch 2 Batch 7250/11375] loss=0.2836, lr=0.0000149, metrics:accuracy:0.9064,f1:0.8749
INFO:root:08:40:16 [Epoch 2 Batch 7260/11375] loss=0.1900, lr=0.0000149, metrics:accuracy:0.9064,f1:0.8748
INFO:root:08:40:18 [Epoch 2 Batch 7270/11375] loss=0.2704, lr=0.0000149, metrics:accuracy:0.9063,f1:0.8748
INFO:root:08:40:19 [Epoch 2 Batch 7280/11375] loss=0.1757, lr=0.0000149, metrics:accuracy:0.9064,f1:0.8749
INFO:root:08:40:20 [Epoch 2 Batch 7290/11375] loss=0.2818, lr=0.0000149, metrics:accuracy:0.9064,f1:0.8748
INFO:root:08:40:21 [Epoch 2 Batch 7300/11375] loss=0.2712, lr=0.0000149, metrics:accuracy:0.9063,f1:0.8748
INFO:root:08:40:22 [Epoch 2 Batch 7310/11375] loss=0.2048, lr=0.0000149, metrics:accuracy:0.9064,f1:0.8749
INFO:root:08:40:23 [Epoch 2 Batch 7320/11375] loss=0.1839, lr=0.0000149, metrics:accuracy:0.9064,f1:0.8748
INFO:root:08:40:25 [Epoch 2 Batch 7330/11375] loss=0.2344, lr=0.0000149, metrics:accuracy:0.9064,f1:0.8748
INFO:root:08:40:26 [Epoch 2 Batch 7340/11375] loss=0.2322, lr=0.0000149, metrics:accuracy:0.9064,f1:0.8748
INFO:root:08:40:27 [Epoch 2 Batch 7350/11375] loss=0.2194, lr=0.0000149, metrics:accuracy:0.9064,f1:0.8749
INFO:root:08:40:28 [Epoch 2 Batch 7360/11375] loss=0.1882, lr=0.0000149, metrics:accuracy:0.9064,f1:0.8749
INFO:root:08:40:29 [Epoch 2 Batch 7370/11375] loss=0.2222, lr=0.0000149, metrics:accuracy:0.9064,f1:0.8750
INFO:root:08:40:30 [Epoch 2 Batch 7380/11375] loss=0.2624, lr=0.0000149, metrics:accuracy:0.9064,f1:0.8750
INFO:root:08:40:31 [Epoch 2 Batch 7390/11375] loss=0.2588, lr=0.0000149, metrics:accuracy:0.9064,f1:0.8749
INFO:root:08:40:33 [Epoch 2 Batch 7400/11375] loss=0.1688, lr=0.0000149, metrics:accuracy:0.9064,f1:0.8750
INFO:root:08:40:34 [Epoch 2 Batch 7410/11375] loss=0.2304, lr=0.0000149, metrics:accuracy:0.9064,f1:0.8749
INFO:root:08:40:35 [Epoch 2 Batch 7420/11375] loss=0.2530, lr=0.0000149, metrics:accuracy:0.9064,f1:0.8749
INFO:root:08:40:36 [Epoch 2 Batch 7430/11375] loss=0.1618, lr=0.0000149, metrics:accuracy:0.9064,f1:0.8750
INFO:root:08:40:38 [Epoch 2 Batch 7440/11375] loss=0.2166, lr=0.0000149, metrics:accuracy:0.9064,f1:0.8750
INFO:root:08:40:39 [Epoch 2 Batch 7450/11375] loss=0.1788, lr=0.0000149, metrics:accuracy:0.9065,f1:0.8750
INFO:root:08:40:40 [Epoch 2 Batch 7460/11375] loss=0.1926, lr=0.0000149, metrics:accuracy:0.9065,f1:0.8750
INFO:root:08:40:41 [Epoch 2 Batch 7470/11375] loss=0.2133, lr=0.0000149, metrics:accuracy:0.9065,f1:0.8751
INFO:root:08:40:42 [Epoch 2 Batch 7480/11375] loss=0.2008, lr=0.0000149, metrics:accuracy:0.9065,f1:0.8751
INFO:root:08:40:44 [Epoch 2 Batch 7490/11375] loss=0.2377, lr=0.0000148, metrics:accuracy:0.9065,f1:0.8751
INFO:root:08:40:45 [Epoch 2 Batch 7500/11375] loss=0.2019, lr=0.0000148, metrics:accuracy:0.9065,f1:0.8751
INFO:root:08:40:46 [Epoch 2 Batch 7510/11375] loss=0.2197, lr=0.0000148, metrics:accuracy:0.9065,f1:0.8751
INFO:root:08:40:47 [Epoch 2 Batch 7520/11375] loss=0.1902, lr=0.0000148, metrics:accuracy:0.9066,f1:0.8751
INFO:root:08:40:49 [Epoch 2 Batch 7530/11375] loss=0.1678, lr=0.0000148, metrics:accuracy:0.9066,f1:0.8751
INFO:root:08:40:50 [Epoch 2 Batch 7540/11375] loss=0.2497, lr=0.0000148, metrics:accuracy:0.9066,f1:0.8751
INFO:root:08:40:51 [Epoch 2 Batch 7550/11375] loss=0.2184, lr=0.0000148, metrics:accuracy:0.9066,f1:0.8752
INFO:root:08:40:52 [Epoch 2 Batch 7560/11375] loss=0.2583, lr=0.0000148, metrics:accuracy:0.9066,f1:0.8751
INFO:root:08:40:53 [Epoch 2 Batch 7570/11375] loss=0.3041, lr=0.0000148, metrics:accuracy:0.9065,f1:0.8751
INFO:root:08:40:54 [Epoch 2 Batch 7580/11375] loss=0.2591, lr=0.0000148, metrics:accuracy:0.9065,f1:0.8751
INFO:root:08:40:55 [Epoch 2 Batch 7590/11375] loss=0.2150, lr=0.0000148, metrics:accuracy:0.9065,f1:0.8752
INFO:root:08:40:57 [Epoch 2 Batch 7600/11375] loss=0.2056, lr=0.0000148, metrics:accuracy:0.9065,f1:0.8752
INFO:root:08:40:58 [Epoch 2 Batch 7610/11375] loss=0.2136, lr=0.0000148, metrics:accuracy:0.9065,f1:0.8752
INFO:root:08:40:59 [Epoch 2 Batch 7620/11375] loss=0.1931, lr=0.0000148, metrics:accuracy:0.9065,f1:0.8752
INFO:root:08:41:00 [Epoch 2 Batch 7630/11375] loss=0.2775, lr=0.0000148, metrics:accuracy:0.9065,f1:0.8751
INFO:root:08:41:01 [Epoch 2 Batch 7640/11375] loss=0.2005, lr=0.0000148, metrics:accuracy:0.9065,f1:0.8751
INFO:root:08:41:03 [Epoch 2 Batch 7650/11375] loss=0.2649, lr=0.0000148, metrics:accuracy:0.9064,f1:0.8751
INFO:root:08:41:04 [Epoch 2 Batch 7660/11375] loss=0.1952, lr=0.0000148, metrics:accuracy:0.9065,f1:0.8752
INFO:root:08:41:05 [Epoch 2 Batch 7670/11375] loss=0.1747, lr=0.0000148, metrics:accuracy:0.9065,f1:0.8752
INFO:root:08:41:06 [Epoch 2 Batch 7680/11375] loss=0.2369, lr=0.0000148, metrics:accuracy:0.9065,f1:0.8752
INFO:root:08:41:07 [Epoch 2 Batch 7690/11375] loss=0.1860, lr=0.0000148, metrics:accuracy:0.9065,f1:0.8752
INFO:root:08:41:08 [Epoch 2 Batch 7700/11375] loss=0.2917, lr=0.0000148, metrics:accuracy:0.9065,f1:0.8752
INFO:root:08:41:10 [Epoch 2 Batch 7710/11375] loss=0.2018, lr=0.0000148, metrics:accuracy:0.9065,f1:0.8752
INFO:root:08:41:11 [Epoch 2 Batch 7720/11375] loss=0.2896, lr=0.0000148, metrics:accuracy:0.9065,f1:0.8752
INFO:root:08:41:12 [Epoch 2 Batch 7730/11375] loss=0.1914, lr=0.0000148, metrics:accuracy:0.9065,f1:0.8753
INFO:root:08:41:13 [Epoch 2 Batch 7740/11375] loss=0.2648, lr=0.0000148, metrics:accuracy:0.9065,f1:0.8752
INFO:root:08:41:14 [Epoch 2 Batch 7750/11375] loss=0.2690, lr=0.0000147, metrics:accuracy:0.9064,f1:0.8752
INFO:root:08:41:15 [Epoch 2 Batch 7760/11375] loss=0.2482, lr=0.0000147, metrics:accuracy:0.9064,f1:0.8752
INFO:root:08:41:16 [Epoch 2 Batch 7770/11375] loss=0.2467, lr=0.0000147, metrics:accuracy:0.9064,f1:0.8752
INFO:root:08:41:18 [Epoch 2 Batch 7780/11375] loss=0.1717, lr=0.0000147, metrics:accuracy:0.9065,f1:0.8752
INFO:root:08:41:19 [Epoch 2 Batch 7790/11375] loss=0.2049, lr=0.0000147, metrics:accuracy:0.9065,f1:0.8753
INFO:root:08:41:20 [Epoch 2 Batch 7800/11375] loss=0.2744, lr=0.0000147, metrics:accuracy:0.9065,f1:0.8752
INFO:root:08:41:21 [Epoch 2 Batch 7810/11375] loss=0.1652, lr=0.0000147, metrics:accuracy:0.9065,f1:0.8753
INFO:root:08:41:22 [Epoch 2 Batch 7820/11375] loss=0.3024, lr=0.0000147, metrics:accuracy:0.9064,f1:0.8752
INFO:root:08:41:24 [Epoch 2 Batch 7830/11375] loss=0.2341, lr=0.0000147, metrics:accuracy:0.9065,f1:0.8753
INFO:root:08:41:25 [Epoch 2 Batch 7840/11375] loss=0.1861, lr=0.0000147, metrics:accuracy:0.9065,f1:0.8753
INFO:root:08:41:26 [Epoch 2 Batch 7850/11375] loss=0.1438, lr=0.0000147, metrics:accuracy:0.9065,f1:0.8753
INFO:root:08:41:27 [Epoch 2 Batch 7860/11375] loss=0.2582, lr=0.0000147, metrics:accuracy:0.9065,f1:0.8753
INFO:root:08:41:28 [Epoch 2 Batch 7870/11375] loss=0.2417, lr=0.0000147, metrics:accuracy:0.9065,f1:0.8753
INFO:root:08:41:30 [Epoch 2 Batch 7880/11375] loss=0.2721, lr=0.0000147, metrics:accuracy:0.9065,f1:0.8753
INFO:root:08:41:31 [Epoch 2 Batch 7890/11375] loss=0.2032, lr=0.0000147, metrics:accuracy:0.9065,f1:0.8753
INFO:root:08:41:32 [Epoch 2 Batch 7900/11375] loss=0.2284, lr=0.0000147, metrics:accuracy:0.9065,f1:0.8753
INFO:root:08:41:33 [Epoch 2 Batch 7910/11375] loss=0.2312, lr=0.0000147, metrics:accuracy:0.9065,f1:0.8753
INFO:root:08:41:34 [Epoch 2 Batch 7920/11375] loss=0.1424, lr=0.0000147, metrics:accuracy:0.9065,f1:0.8753
INFO:root:08:41:35 [Epoch 2 Batch 7930/11375] loss=0.2237, lr=0.0000147, metrics:accuracy:0.9065,f1:0.8753
INFO:root:08:41:37 [Epoch 2 Batch 7940/11375] loss=0.1681, lr=0.0000147, metrics:accuracy:0.9065,f1:0.8754
INFO:root:08:41:38 [Epoch 2 Batch 7950/11375] loss=0.2236, lr=0.0000147, metrics:accuracy:0.9065,f1:0.8754
INFO:root:08:41:39 [Epoch 2 Batch 7960/11375] loss=0.2862, lr=0.0000147, metrics:accuracy:0.9065,f1:0.8754
INFO:root:08:41:40 [Epoch 2 Batch 7970/11375] loss=0.1791, lr=0.0000147, metrics:accuracy:0.9066,f1:0.8754
INFO:root:08:41:41 [Epoch 2 Batch 7980/11375] loss=0.2005, lr=0.0000147, metrics:accuracy:0.9066,f1:0.8754
INFO:root:08:41:43 [Epoch 2 Batch 7990/11375] loss=0.1711, lr=0.0000147, metrics:accuracy:0.9066,f1:0.8755
INFO:root:08:41:44 [Epoch 2 Batch 8000/11375] loss=0.2853, lr=0.0000146, metrics:accuracy:0.9066,f1:0.8754
INFO:root:08:41:45 [Epoch 2 Batch 8010/11375] loss=0.2119, lr=0.0000146, metrics:accuracy:0.9066,f1:0.8755
INFO:root:08:41:46 [Epoch 2 Batch 8020/11375] loss=0.2478, lr=0.0000146, metrics:accuracy:0.9066,f1:0.8754
INFO:root:08:41:47 [Epoch 2 Batch 8030/11375] loss=0.2135, lr=0.0000146, metrics:accuracy:0.9066,f1:0.8754
INFO:root:08:41:49 [Epoch 2 Batch 8040/11375] loss=0.1944, lr=0.0000146, metrics:accuracy:0.9066,f1:0.8754
INFO:root:08:41:50 [Epoch 2 Batch 8050/11375] loss=0.2318, lr=0.0000146, metrics:accuracy:0.9066,f1:0.8755
INFO:root:08:41:51 [Epoch 2 Batch 8060/11375] loss=0.2194, lr=0.0000146, metrics:accuracy:0.9066,f1:0.8755
INFO:root:08:41:52 [Epoch 2 Batch 8070/11375] loss=0.2258, lr=0.0000146, metrics:accuracy:0.9066,f1:0.8755
INFO:root:08:41:53 [Epoch 2 Batch 8080/11375] loss=0.2726, lr=0.0000146, metrics:accuracy:0.9065,f1:0.8755
INFO:root:08:41:55 [Epoch 2 Batch 8090/11375] loss=0.1641, lr=0.0000146, metrics:accuracy:0.9066,f1:0.8755
INFO:root:08:41:56 [Epoch 2 Batch 8100/11375] loss=0.2006, lr=0.0000146, metrics:accuracy:0.9066,f1:0.8755
INFO:root:08:41:57 [Epoch 2 Batch 8110/11375] loss=0.2734, lr=0.0000146, metrics:accuracy:0.9065,f1:0.8755
INFO:root:08:41:58 [Epoch 2 Batch 8120/11375] loss=0.1931, lr=0.0000146, metrics:accuracy:0.9066,f1:0.8755
INFO:root:08:41:59 [Epoch 2 Batch 8130/11375] loss=0.2469, lr=0.0000146, metrics:accuracy:0.9066,f1:0.8755
INFO:root:08:42:00 [Epoch 2 Batch 8140/11375] loss=0.2575, lr=0.0000146, metrics:accuracy:0.9065,f1:0.8755
INFO:root:08:42:01 [Epoch 2 Batch 8150/11375] loss=0.2004, lr=0.0000146, metrics:accuracy:0.9065,f1:0.8755
INFO:root:08:42:02 [Epoch 2 Batch 8160/11375] loss=0.2448, lr=0.0000146, metrics:accuracy:0.9065,f1:0.8755
INFO:root:08:42:04 [Epoch 2 Batch 8170/11375] loss=0.1922, lr=0.0000146, metrics:accuracy:0.9065,f1:0.8755
INFO:root:08:42:05 [Epoch 2 Batch 8180/11375] loss=0.2781, lr=0.0000146, metrics:accuracy:0.9065,f1:0.8755
INFO:root:08:42:06 [Epoch 2 Batch 8190/11375] loss=0.2508, lr=0.0000146, metrics:accuracy:0.9065,f1:0.8755
INFO:root:08:42:07 [Epoch 2 Batch 8200/11375] loss=0.1489, lr=0.0000146, metrics:accuracy:0.9065,f1:0.8755
INFO:root:08:42:08 [Epoch 2 Batch 8210/11375] loss=0.2588, lr=0.0000146, metrics:accuracy:0.9065,f1:0.8755
INFO:root:08:42:09 [Epoch 2 Batch 8220/11375] loss=0.2192, lr=0.0000146, metrics:accuracy:0.9065,f1:0.8755
INFO:root:08:42:10 [Epoch 2 Batch 8230/11375] loss=0.1573, lr=0.0000146, metrics:accuracy:0.9065,f1:0.8756
INFO:root:08:42:12 [Epoch 2 Batch 8240/11375] loss=0.2234, lr=0.0000146, metrics:accuracy:0.9066,f1:0.8756
INFO:root:08:42:13 [Epoch 2 Batch 8250/11375] loss=0.2003, lr=0.0000146, metrics:accuracy:0.9066,f1:0.8756
INFO:root:08:42:14 [Epoch 2 Batch 8260/11375] loss=0.2552, lr=0.0000145, metrics:accuracy:0.9065,f1:0.8756
INFO:root:08:42:15 [Epoch 2 Batch 8270/11375] loss=0.2181, lr=0.0000145, metrics:accuracy:0.9066,f1:0.8756
INFO:root:08:42:16 [Epoch 2 Batch 8280/11375] loss=0.2199, lr=0.0000145, metrics:accuracy:0.9066,f1:0.8756
INFO:root:08:42:17 [Epoch 2 Batch 8290/11375] loss=0.1718, lr=0.0000145, metrics:accuracy:0.9066,f1:0.8756
INFO:root:08:42:19 [Epoch 2 Batch 8300/11375] loss=0.2198, lr=0.0000145, metrics:accuracy:0.9066,f1:0.8756
INFO:root:08:42:20 [Epoch 2 Batch 8310/11375] loss=0.1903, lr=0.0000145, metrics:accuracy:0.9066,f1:0.8756
INFO:root:08:42:21 [Epoch 2 Batch 8320/11375] loss=0.2297, lr=0.0000145, metrics:accuracy:0.9066,f1:0.8756
INFO:root:08:42:22 [Epoch 2 Batch 8330/11375] loss=0.2242, lr=0.0000145, metrics:accuracy:0.9066,f1:0.8756
INFO:root:08:42:23 [Epoch 2 Batch 8340/11375] loss=0.1991, lr=0.0000145, metrics:accuracy:0.9066,f1:0.8756
INFO:root:08:42:24 [Epoch 2 Batch 8350/11375] loss=0.2727, lr=0.0000145, metrics:accuracy:0.9066,f1:0.8756
INFO:root:08:42:26 [Epoch 2 Batch 8360/11375] loss=0.2490, lr=0.0000145, metrics:accuracy:0.9066,f1:0.8756
INFO:root:08:42:27 [Epoch 2 Batch 8370/11375] loss=0.2081, lr=0.0000145, metrics:accuracy:0.9066,f1:0.8755
INFO:root:08:42:28 [Epoch 2 Batch 8380/11375] loss=0.2192, lr=0.0000145, metrics:accuracy:0.9066,f1:0.8755
INFO:root:08:42:29 [Epoch 2 Batch 8390/11375] loss=0.1695, lr=0.0000145, metrics:accuracy:0.9066,f1:0.8756
INFO:root:08:42:30 [Epoch 2 Batch 8400/11375] loss=0.2363, lr=0.0000145, metrics:accuracy:0.9066,f1:0.8756
INFO:root:08:42:32 [Epoch 2 Batch 8410/11375] loss=0.1817, lr=0.0000145, metrics:accuracy:0.9066,f1:0.8756
INFO:root:08:42:33 [Epoch 2 Batch 8420/11375] loss=0.1838, lr=0.0000145, metrics:accuracy:0.9066,f1:0.8756
INFO:root:08:42:34 [Epoch 2 Batch 8430/11375] loss=0.2037, lr=0.0000145, metrics:accuracy:0.9067,f1:0.8756
INFO:root:08:42:35 [Epoch 2 Batch 8440/11375] loss=0.1711, lr=0.0000145, metrics:accuracy:0.9067,f1:0.8757
INFO:root:08:42:36 [Epoch 2 Batch 8450/11375] loss=0.1830, lr=0.0000145, metrics:accuracy:0.9067,f1:0.8757
INFO:root:08:42:38 [Epoch 2 Batch 8460/11375] loss=0.2619, lr=0.0000145, metrics:accuracy:0.9067,f1:0.8756
INFO:root:08:42:39 [Epoch 2 Batch 8470/11375] loss=0.1643, lr=0.0000145, metrics:accuracy:0.9067,f1:0.8757
INFO:root:08:42:40 [Epoch 2 Batch 8480/11375] loss=0.1544, lr=0.0000145, metrics:accuracy:0.9068,f1:0.8758
INFO:root:08:42:41 [Epoch 2 Batch 8490/11375] loss=0.1517, lr=0.0000145, metrics:accuracy:0.9068,f1:0.8758
INFO:root:08:42:42 [Epoch 2 Batch 8500/11375] loss=0.2198, lr=0.0000145, metrics:accuracy:0.9068,f1:0.8758
INFO:root:08:42:44 [Epoch 2 Batch 8510/11375] loss=0.2112, lr=0.0000144, metrics:accuracy:0.9068,f1:0.8758
INFO:root:08:42:45 [Epoch 2 Batch 8520/11375] loss=0.1894, lr=0.0000144, metrics:accuracy:0.9069,f1:0.8758
INFO:root:08:42:46 [Epoch 2 Batch 8530/11375] loss=0.2135, lr=0.0000144, metrics:accuracy:0.9069,f1:0.8758
INFO:root:08:42:47 [Epoch 2 Batch 8540/11375] loss=0.1949, lr=0.0000144, metrics:accuracy:0.9069,f1:0.8758
INFO:root:08:42:48 [Epoch 2 Batch 8550/11375] loss=0.2202, lr=0.0000144, metrics:accuracy:0.9069,f1:0.8759
INFO:root:08:42:50 [Epoch 2 Batch 8560/11375] loss=0.1769, lr=0.0000144, metrics:accuracy:0.9069,f1:0.8759
INFO:root:08:42:51 [Epoch 2 Batch 8570/11375] loss=0.2390, lr=0.0000144, metrics:accuracy:0.9069,f1:0.8759
INFO:root:08:42:52 [Epoch 2 Batch 8580/11375] loss=0.2175, lr=0.0000144, metrics:accuracy:0.9069,f1:0.8759
INFO:root:08:42:53 [Epoch 2 Batch 8590/11375] loss=0.2915, lr=0.0000144, metrics:accuracy:0.9068,f1:0.8758
INFO:root:08:42:54 [Epoch 2 Batch 8600/11375] loss=0.2535, lr=0.0000144, metrics:accuracy:0.9068,f1:0.8758
INFO:root:08:42:55 [Epoch 2 Batch 8610/11375] loss=0.2274, lr=0.0000144, metrics:accuracy:0.9068,f1:0.8758
INFO:root:08:42:57 [Epoch 2 Batch 8620/11375] loss=0.1790, lr=0.0000144, metrics:accuracy:0.9069,f1:0.8758
INFO:root:08:42:58 [Epoch 2 Batch 8630/11375] loss=0.2619, lr=0.0000144, metrics:accuracy:0.9068,f1:0.8758
INFO:root:08:42:59 [Epoch 2 Batch 8640/11375] loss=0.2401, lr=0.0000144, metrics:accuracy:0.9068,f1:0.8758
INFO:root:08:43:00 [Epoch 2 Batch 8650/11375] loss=0.2074, lr=0.0000144, metrics:accuracy:0.9069,f1:0.8758
INFO:root:08:43:01 [Epoch 2 Batch 8660/11375] loss=0.2528, lr=0.0000144, metrics:accuracy:0.9068,f1:0.8758
INFO:root:08:43:02 [Epoch 2 Batch 8670/11375] loss=0.2587, lr=0.0000144, metrics:accuracy:0.9068,f1:0.8759
INFO:root:08:43:04 [Epoch 2 Batch 8680/11375] loss=0.2169, lr=0.0000144, metrics:accuracy:0.9068,f1:0.8758
INFO:root:08:43:05 [Epoch 2 Batch 8690/11375] loss=0.2115, lr=0.0000144, metrics:accuracy:0.9069,f1:0.8759
INFO:root:08:43:06 [Epoch 2 Batch 8700/11375] loss=0.2291, lr=0.0000144, metrics:accuracy:0.9069,f1:0.8759
INFO:root:08:43:07 [Epoch 2 Batch 8710/11375] loss=0.2018, lr=0.0000144, metrics:accuracy:0.9069,f1:0.8759
INFO:root:08:43:08 [Epoch 2 Batch 8720/11375] loss=0.2288, lr=0.0000144, metrics:accuracy:0.9069,f1:0.8759
INFO:root:08:43:09 [Epoch 2 Batch 8730/11375] loss=0.2285, lr=0.0000144, metrics:accuracy:0.9068,f1:0.8759
INFO:root:08:43:11 [Epoch 2 Batch 8740/11375] loss=0.2378, lr=0.0000144, metrics:accuracy:0.9068,f1:0.8759
INFO:root:08:43:12 [Epoch 2 Batch 8750/11375] loss=0.2347, lr=0.0000144, metrics:accuracy:0.9068,f1:0.8759
INFO:root:08:43:13 [Epoch 2 Batch 8760/11375] loss=0.1469, lr=0.0000144, metrics:accuracy:0.9069,f1:0.8759
INFO:root:08:43:14 [Epoch 2 Batch 8770/11375] loss=0.2309, lr=0.0000143, metrics:accuracy:0.9069,f1:0.8759
INFO:root:08:43:15 [Epoch 2 Batch 8780/11375] loss=0.3132, lr=0.0000143, metrics:accuracy:0.9068,f1:0.8759
INFO:root:08:43:16 [Epoch 2 Batch 8790/11375] loss=0.2356, lr=0.0000143, metrics:accuracy:0.9068,f1:0.8759
INFO:root:08:43:17 [Epoch 2 Batch 8800/11375] loss=0.2886, lr=0.0000143, metrics:accuracy:0.9068,f1:0.8758
INFO:root:08:43:19 [Epoch 2 Batch 8810/11375] loss=0.2229, lr=0.0000143, metrics:accuracy:0.9068,f1:0.8758
INFO:root:08:43:20 [Epoch 2 Batch 8820/11375] loss=0.2134, lr=0.0000143, metrics:accuracy:0.9068,f1:0.8758
INFO:root:08:43:21 [Epoch 2 Batch 8830/11375] loss=0.2046, lr=0.0000143, metrics:accuracy:0.9068,f1:0.8758
INFO:root:08:43:22 [Epoch 2 Batch 8840/11375] loss=0.2082, lr=0.0000143, metrics:accuracy:0.9068,f1:0.8759
INFO:root:08:43:23 [Epoch 2 Batch 8850/11375] loss=0.2220, lr=0.0000143, metrics:accuracy:0.9068,f1:0.8759
INFO:root:08:43:24 [Epoch 2 Batch 8860/11375] loss=0.2171, lr=0.0000143, metrics:accuracy:0.9068,f1:0.8759
INFO:root:08:43:26 [Epoch 2 Batch 8870/11375] loss=0.1846, lr=0.0000143, metrics:accuracy:0.9068,f1:0.8759
INFO:root:08:43:27 [Epoch 2 Batch 8880/11375] loss=0.1600, lr=0.0000143, metrics:accuracy:0.9069,f1:0.8759
INFO:root:08:43:28 [Epoch 2 Batch 8890/11375] loss=0.2287, lr=0.0000143, metrics:accuracy:0.9069,f1:0.8759
INFO:root:08:43:29 [Epoch 2 Batch 8900/11375] loss=0.2118, lr=0.0000143, metrics:accuracy:0.9069,f1:0.8760
INFO:root:08:43:30 [Epoch 2 Batch 8910/11375] loss=0.3116, lr=0.0000143, metrics:accuracy:0.9069,f1:0.8760
INFO:root:08:43:31 [Epoch 2 Batch 8920/11375] loss=0.2216, lr=0.0000143, metrics:accuracy:0.9069,f1:0.8760
INFO:root:08:43:32 [Epoch 2 Batch 8930/11375] loss=0.2302, lr=0.0000143, metrics:accuracy:0.9068,f1:0.8760
INFO:root:08:43:34 [Epoch 2 Batch 8940/11375] loss=0.2534, lr=0.0000143, metrics:accuracy:0.9068,f1:0.8760
INFO:root:08:43:35 [Epoch 2 Batch 8950/11375] loss=0.2657, lr=0.0000143, metrics:accuracy:0.9068,f1:0.8760
INFO:root:08:43:36 [Epoch 2 Batch 8960/11375] loss=0.2348, lr=0.0000143, metrics:accuracy:0.9068,f1:0.8760
INFO:root:08:43:37 [Epoch 2 Batch 8970/11375] loss=0.2322, lr=0.0000143, metrics:accuracy:0.9068,f1:0.8760
INFO:root:08:43:38 [Epoch 2 Batch 8980/11375] loss=0.2465, lr=0.0000143, metrics:accuracy:0.9068,f1:0.8760
INFO:root:08:43:39 [Epoch 2 Batch 8990/11375] loss=0.2021, lr=0.0000143, metrics:accuracy:0.9068,f1:0.8760
INFO:root:08:43:41 [Epoch 2 Batch 9000/11375] loss=0.2509, lr=0.0000143, metrics:accuracy:0.9068,f1:0.8760
INFO:root:08:43:42 [Epoch 2 Batch 9010/11375] loss=0.1990, lr=0.0000143, metrics:accuracy:0.9068,f1:0.8760
INFO:root:08:43:43 [Epoch 2 Batch 9020/11375] loss=0.1660, lr=0.0000143, metrics:accuracy:0.9068,f1:0.8760
INFO:root:08:43:44 [Epoch 2 Batch 9030/11375] loss=0.2086, lr=0.0000142, metrics:accuracy:0.9068,f1:0.8760
INFO:root:08:43:45 [Epoch 2 Batch 9040/11375] loss=0.2472, lr=0.0000142, metrics:accuracy:0.9068,f1:0.8760
INFO:root:08:43:46 [Epoch 2 Batch 9050/11375] loss=0.2449, lr=0.0000142, metrics:accuracy:0.9068,f1:0.8760
INFO:root:08:43:48 [Epoch 2 Batch 9060/11375] loss=0.1771, lr=0.0000142, metrics:accuracy:0.9068,f1:0.8760
INFO:root:08:43:49 [Epoch 2 Batch 9070/11375] loss=0.2143, lr=0.0000142, metrics:accuracy:0.9068,f1:0.8760
INFO:root:08:43:50 [Epoch 2 Batch 9080/11375] loss=0.2603, lr=0.0000142, metrics:accuracy:0.9068,f1:0.8760
INFO:root:08:43:51 [Epoch 2 Batch 9090/11375] loss=0.2028, lr=0.0000142, metrics:accuracy:0.9068,f1:0.8759
INFO:root:08:43:53 [Epoch 2 Batch 9100/11375] loss=0.1740, lr=0.0000142, metrics:accuracy:0.9068,f1:0.8760
INFO:root:08:43:54 [Epoch 2 Batch 9110/11375] loss=0.1820, lr=0.0000142, metrics:accuracy:0.9068,f1:0.8760
INFO:root:08:43:55 [Epoch 2 Batch 9120/11375] loss=0.2441, lr=0.0000142, metrics:accuracy:0.9068,f1:0.8760
INFO:root:08:43:56 [Epoch 2 Batch 9130/11375] loss=0.2560, lr=0.0000142, metrics:accuracy:0.9068,f1:0.8760
INFO:root:08:43:57 [Epoch 2 Batch 9140/11375] loss=0.2761, lr=0.0000142, metrics:accuracy:0.9068,f1:0.8760
INFO:root:08:43:58 [Epoch 2 Batch 9150/11375] loss=0.2480, lr=0.0000142, metrics:accuracy:0.9068,f1:0.8760
INFO:root:08:44:00 [Epoch 2 Batch 9160/11375] loss=0.1512, lr=0.0000142, metrics:accuracy:0.9069,f1:0.8760
INFO:root:08:44:01 [Epoch 2 Batch 9170/11375] loss=0.2134, lr=0.0000142, metrics:accuracy:0.9069,f1:0.8760
INFO:root:08:44:02 [Epoch 2 Batch 9180/11375] loss=0.2490, lr=0.0000142, metrics:accuracy:0.9068,f1:0.8759
INFO:root:08:44:03 [Epoch 2 Batch 9190/11375] loss=0.2576, lr=0.0000142, metrics:accuracy:0.9068,f1:0.8759
INFO:root:08:44:04 [Epoch 2 Batch 9200/11375] loss=0.2432, lr=0.0000142, metrics:accuracy:0.9068,f1:0.8759
INFO:root:08:44:06 [Epoch 2 Batch 9210/11375] loss=0.2256, lr=0.0000142, metrics:accuracy:0.9068,f1:0.8759
INFO:root:08:44:07 [Epoch 2 Batch 9220/11375] loss=0.2377, lr=0.0000142, metrics:accuracy:0.9067,f1:0.8758
INFO:root:08:44:08 [Epoch 2 Batch 9230/11375] loss=0.2676, lr=0.0000142, metrics:accuracy:0.9067,f1:0.8758
INFO:root:08:44:09 [Epoch 2 Batch 9240/11375] loss=0.2067, lr=0.0000142, metrics:accuracy:0.9067,f1:0.8758
INFO:root:08:44:10 [Epoch 2 Batch 9250/11375] loss=0.2164, lr=0.0000142, metrics:accuracy:0.9067,f1:0.8758
INFO:root:08:44:11 [Epoch 2 Batch 9260/11375] loss=0.2364, lr=0.0000142, metrics:accuracy:0.9067,f1:0.8758
INFO:root:08:44:12 [Epoch 2 Batch 9270/11375] loss=0.2467, lr=0.0000142, metrics:accuracy:0.9067,f1:0.8758
INFO:root:08:44:13 [Epoch 2 Batch 9280/11375] loss=0.2030, lr=0.0000141, metrics:accuracy:0.9067,f1:0.8758
INFO:root:08:44:15 [Epoch 2 Batch 9290/11375] loss=0.2468, lr=0.0000141, metrics:accuracy:0.9067,f1:0.8759
INFO:root:08:44:16 [Epoch 2 Batch 9300/11375] loss=0.2163, lr=0.0000141, metrics:accuracy:0.9067,f1:0.8759
INFO:root:08:44:17 [Epoch 2 Batch 9310/11375] loss=0.1875, lr=0.0000141, metrics:accuracy:0.9067,f1:0.8759
INFO:root:08:44:18 [Epoch 2 Batch 9320/11375] loss=0.2275, lr=0.0000141, metrics:accuracy:0.9067,f1:0.8759
INFO:root:08:44:19 [Epoch 2 Batch 9330/11375] loss=0.2586, lr=0.0000141, metrics:accuracy:0.9067,f1:0.8759
INFO:root:08:44:20 [Epoch 2 Batch 9340/11375] loss=0.2527, lr=0.0000141, metrics:accuracy:0.9067,f1:0.8759
INFO:root:08:44:21 [Epoch 2 Batch 9350/11375] loss=0.2239, lr=0.0000141, metrics:accuracy:0.9067,f1:0.8759
INFO:root:08:44:23 [Epoch 2 Batch 9360/11375] loss=0.2738, lr=0.0000141, metrics:accuracy:0.9067,f1:0.8759
INFO:root:08:44:24 [Epoch 2 Batch 9370/11375] loss=0.2670, lr=0.0000141, metrics:accuracy:0.9067,f1:0.8759
INFO:root:08:44:25 [Epoch 2 Batch 9380/11375] loss=0.2445, lr=0.0000141, metrics:accuracy:0.9067,f1:0.8758
INFO:root:08:44:26 [Epoch 2 Batch 9390/11375] loss=0.2405, lr=0.0000141, metrics:accuracy:0.9066,f1:0.8758
INFO:root:08:44:27 [Epoch 2 Batch 9400/11375] loss=0.3094, lr=0.0000141, metrics:accuracy:0.9066,f1:0.8758
INFO:root:08:44:28 [Epoch 2 Batch 9410/11375] loss=0.1791, lr=0.0000141, metrics:accuracy:0.9066,f1:0.8758
INFO:root:08:44:30 [Epoch 2 Batch 9420/11375] loss=0.2539, lr=0.0000141, metrics:accuracy:0.9066,f1:0.8758
INFO:root:08:44:31 [Epoch 2 Batch 9430/11375] loss=0.2325, lr=0.0000141, metrics:accuracy:0.9066,f1:0.8758
INFO:root:08:44:32 [Epoch 2 Batch 9440/11375] loss=0.2418, lr=0.0000141, metrics:accuracy:0.9066,f1:0.8758
INFO:root:08:44:33 [Epoch 2 Batch 9450/11375] loss=0.2144, lr=0.0000141, metrics:accuracy:0.9066,f1:0.8758
INFO:root:08:44:34 [Epoch 2 Batch 9460/11375] loss=0.2171, lr=0.0000141, metrics:accuracy:0.9066,f1:0.8759
INFO:root:08:44:35 [Epoch 2 Batch 9470/11375] loss=0.2433, lr=0.0000141, metrics:accuracy:0.9066,f1:0.8758
INFO:root:08:44:37 [Epoch 2 Batch 9480/11375] loss=0.2202, lr=0.0000141, metrics:accuracy:0.9066,f1:0.8758
INFO:root:08:44:38 [Epoch 2 Batch 9490/11375] loss=0.2193, lr=0.0000141, metrics:accuracy:0.9066,f1:0.8759
INFO:root:08:44:39 [Epoch 2 Batch 9500/11375] loss=0.2232, lr=0.0000141, metrics:accuracy:0.9066,f1:0.8759
INFO:root:08:44:40 [Epoch 2 Batch 9510/11375] loss=0.2032, lr=0.0000141, metrics:accuracy:0.9066,f1:0.8759
INFO:root:08:44:41 [Epoch 2 Batch 9520/11375] loss=0.2122, lr=0.0000141, metrics:accuracy:0.9066,f1:0.8759
INFO:root:08:44:42 [Epoch 2 Batch 9530/11375] loss=0.2225, lr=0.0000141, metrics:accuracy:0.9067,f1:0.8759
INFO:root:08:44:44 [Epoch 2 Batch 9540/11375] loss=0.1972, lr=0.0000140, metrics:accuracy:0.9066,f1:0.8759
INFO:root:08:44:45 [Epoch 2 Batch 9550/11375] loss=0.2420, lr=0.0000140, metrics:accuracy:0.9067,f1:0.8758
INFO:root:08:44:46 [Epoch 2 Batch 9560/11375] loss=0.2069, lr=0.0000140, metrics:accuracy:0.9067,f1:0.8759
INFO:root:08:44:47 [Epoch 2 Batch 9570/11375] loss=0.2311, lr=0.0000140, metrics:accuracy:0.9067,f1:0.8759
INFO:root:08:44:49 [Epoch 2 Batch 9580/11375] loss=0.2314, lr=0.0000140, metrics:accuracy:0.9067,f1:0.8759
INFO:root:08:44:50 [Epoch 2 Batch 9590/11375] loss=0.2194, lr=0.0000140, metrics:accuracy:0.9067,f1:0.8758
INFO:root:08:44:51 [Epoch 2 Batch 9600/11375] loss=0.1175, lr=0.0000140, metrics:accuracy:0.9067,f1:0.8759
INFO:root:08:44:53 [Epoch 2 Batch 9610/11375] loss=0.1532, lr=0.0000140, metrics:accuracy:0.9068,f1:0.8759
INFO:root:08:44:54 [Epoch 2 Batch 9620/11375] loss=0.1902, lr=0.0000140, metrics:accuracy:0.9068,f1:0.8759
INFO:root:08:44:55 [Epoch 2 Batch 9630/11375] loss=0.1929, lr=0.0000140, metrics:accuracy:0.9068,f1:0.8760
INFO:root:08:44:56 [Epoch 2 Batch 9640/11375] loss=0.2665, lr=0.0000140, metrics:accuracy:0.9068,f1:0.8759
INFO:root:08:44:57 [Epoch 2 Batch 9650/11375] loss=0.1934, lr=0.0000140, metrics:accuracy:0.9068,f1:0.8760
INFO:root:08:44:58 [Epoch 2 Batch 9660/11375] loss=0.2034, lr=0.0000140, metrics:accuracy:0.9068,f1:0.8759
INFO:root:08:45:00 [Epoch 2 Batch 9670/11375] loss=0.2163, lr=0.0000140, metrics:accuracy:0.9068,f1:0.8759
INFO:root:08:45:01 [Epoch 2 Batch 9680/11375] loss=0.2216, lr=0.0000140, metrics:accuracy:0.9068,f1:0.8760
INFO:root:08:45:02 [Epoch 2 Batch 9690/11375] loss=0.2001, lr=0.0000140, metrics:accuracy:0.9068,f1:0.8760
INFO:root:08:45:03 [Epoch 2 Batch 9700/11375] loss=0.2395, lr=0.0000140, metrics:accuracy:0.9068,f1:0.8759
INFO:root:08:45:04 [Epoch 2 Batch 9710/11375] loss=0.2553, lr=0.0000140, metrics:accuracy:0.9068,f1:0.8759
INFO:root:08:45:05 [Epoch 2 Batch 9720/11375] loss=0.2379, lr=0.0000140, metrics:accuracy:0.9068,f1:0.8759
INFO:root:08:45:06 [Epoch 2 Batch 9730/11375] loss=0.2188, lr=0.0000140, metrics:accuracy:0.9068,f1:0.8760
INFO:root:08:45:08 [Epoch 2 Batch 9740/11375] loss=0.1771, lr=0.0000140, metrics:accuracy:0.9068,f1:0.8760
INFO:root:08:45:09 [Epoch 2 Batch 9750/11375] loss=0.1838, lr=0.0000140, metrics:accuracy:0.9068,f1:0.8760
INFO:root:08:45:10 [Epoch 2 Batch 9760/11375] loss=0.2580, lr=0.0000140, metrics:accuracy:0.9068,f1:0.8760
INFO:root:08:45:11 [Epoch 2 Batch 9770/11375] loss=0.2100, lr=0.0000140, metrics:accuracy:0.9068,f1:0.8760
INFO:root:08:45:12 [Epoch 2 Batch 9780/11375] loss=0.2652, lr=0.0000140, metrics:accuracy:0.9068,f1:0.8760
INFO:root:08:45:14 [Epoch 2 Batch 9790/11375] loss=0.1493, lr=0.0000139, metrics:accuracy:0.9068,f1:0.8760
INFO:root:08:45:15 [Epoch 2 Batch 9800/11375] loss=0.1973, lr=0.0000139, metrics:accuracy:0.9068,f1:0.8761
INFO:root:08:45:16 [Epoch 2 Batch 9810/11375] loss=0.1833, lr=0.0000139, metrics:accuracy:0.9069,f1:0.8761
INFO:root:08:45:17 [Epoch 2 Batch 9820/11375] loss=0.2728, lr=0.0000139, metrics:accuracy:0.9068,f1:0.8761
INFO:root:08:45:18 [Epoch 2 Batch 9830/11375] loss=0.2333, lr=0.0000139, metrics:accuracy:0.9068,f1:0.8761
INFO:root:08:45:19 [Epoch 2 Batch 9840/11375] loss=0.2189, lr=0.0000139, metrics:accuracy:0.9068,f1:0.8761
INFO:root:08:45:21 [Epoch 2 Batch 9850/11375] loss=0.2361, lr=0.0000139, metrics:accuracy:0.9069,f1:0.8761
INFO:root:08:45:22 [Epoch 2 Batch 9860/11375] loss=0.1651, lr=0.0000139, metrics:accuracy:0.9069,f1:0.8761
INFO:root:08:45:23 [Epoch 2 Batch 9870/11375] loss=0.1707, lr=0.0000139, metrics:accuracy:0.9069,f1:0.8761
INFO:root:08:45:24 [Epoch 2 Batch 9880/11375] loss=0.3307, lr=0.0000139, metrics:accuracy:0.9069,f1:0.8761
INFO:root:08:45:25 [Epoch 2 Batch 9890/11375] loss=0.2030, lr=0.0000139, metrics:accuracy:0.9069,f1:0.8761
INFO:root:08:45:26 [Epoch 2 Batch 9900/11375] loss=0.2597, lr=0.0000139, metrics:accuracy:0.9069,f1:0.8761
INFO:root:08:45:27 [Epoch 2 Batch 9910/11375] loss=0.2606, lr=0.0000139, metrics:accuracy:0.9068,f1:0.8761
INFO:root:08:45:29 [Epoch 2 Batch 9920/11375] loss=0.2078, lr=0.0000139, metrics:accuracy:0.9068,f1:0.8761
INFO:root:08:45:30 [Epoch 2 Batch 9930/11375] loss=0.2519, lr=0.0000139, metrics:accuracy:0.9068,f1:0.8761
INFO:root:08:45:31 [Epoch 2 Batch 9940/11375] loss=0.3010, lr=0.0000139, metrics:accuracy:0.9068,f1:0.8761
INFO:root:08:45:32 [Epoch 2 Batch 9950/11375] loss=0.1448, lr=0.0000139, metrics:accuracy:0.9068,f1:0.8761
INFO:root:08:45:33 [Epoch 2 Batch 9960/11375] loss=0.2054, lr=0.0000139, metrics:accuracy:0.9068,f1:0.8761
INFO:root:08:45:35 [Epoch 2 Batch 9970/11375] loss=0.1967, lr=0.0000139, metrics:accuracy:0.9068,f1:0.8761
INFO:root:08:45:36 [Epoch 2 Batch 9980/11375] loss=0.1775, lr=0.0000139, metrics:accuracy:0.9069,f1:0.8761
INFO:root:08:45:37 [Epoch 2 Batch 9990/11375] loss=0.1735, lr=0.0000139, metrics:accuracy:0.9069,f1:0.8762
INFO:root:08:45:38 [Epoch 2 Batch 10000/11375] loss=0.1851, lr=0.0000139, metrics:accuracy:0.9069,f1:0.8762
INFO:root:08:45:39 [Epoch 2 Batch 10010/11375] loss=0.3078, lr=0.0000139, metrics:accuracy:0.9069,f1:0.8761
INFO:root:08:45:41 [Epoch 2 Batch 10020/11375] loss=0.2089, lr=0.0000139, metrics:accuracy:0.9069,f1:0.8762
INFO:root:08:45:42 [Epoch 2 Batch 10030/11375] loss=0.2510, lr=0.0000139, metrics:accuracy:0.9069,f1:0.8761
INFO:root:08:45:43 [Epoch 2 Batch 10040/11375] loss=0.1624, lr=0.0000139, metrics:accuracy:0.9069,f1:0.8762
INFO:root:08:45:44 [Epoch 2 Batch 10050/11375] loss=0.2321, lr=0.0000138, metrics:accuracy:0.9069,f1:0.8761
INFO:root:08:45:45 [Epoch 2 Batch 10060/11375] loss=0.2305, lr=0.0000138, metrics:accuracy:0.9069,f1:0.8761
INFO:root:08:45:46 [Epoch 2 Batch 10070/11375] loss=0.2323, lr=0.0000138, metrics:accuracy:0.9069,f1:0.8761
INFO:root:08:45:48 [Epoch 2 Batch 10080/11375] loss=0.2202, lr=0.0000138, metrics:accuracy:0.9069,f1:0.8761
INFO:root:08:45:49 [Epoch 2 Batch 10090/11375] loss=0.1789, lr=0.0000138, metrics:accuracy:0.9069,f1:0.8761
INFO:root:08:45:50 [Epoch 2 Batch 10100/11375] loss=0.2507, lr=0.0000138, metrics:accuracy:0.9069,f1:0.8761
INFO:root:08:45:51 [Epoch 2 Batch 10110/11375] loss=0.2323, lr=0.0000138, metrics:accuracy:0.9069,f1:0.8761
INFO:root:08:45:53 [Epoch 2 Batch 10120/11375] loss=0.1908, lr=0.0000138, metrics:accuracy:0.9069,f1:0.8762
INFO:root:08:45:54 [Epoch 2 Batch 10130/11375] loss=0.1799, lr=0.0000138, metrics:accuracy:0.9070,f1:0.8762
INFO:root:08:45:55 [Epoch 2 Batch 10140/11375] loss=0.2203, lr=0.0000138, metrics:accuracy:0.9070,f1:0.8762
INFO:root:08:45:56 [Epoch 2 Batch 10150/11375] loss=0.2449, lr=0.0000138, metrics:accuracy:0.9070,f1:0.8762
INFO:root:08:45:57 [Epoch 2 Batch 10160/11375] loss=0.1699, lr=0.0000138, metrics:accuracy:0.9070,f1:0.8762
INFO:root:08:45:59 [Epoch 2 Batch 10170/11375] loss=0.2126, lr=0.0000138, metrics:accuracy:0.9070,f1:0.8762
INFO:root:08:46:00 [Epoch 2 Batch 10180/11375] loss=0.2711, lr=0.0000138, metrics:accuracy:0.9070,f1:0.8762
INFO:root:08:46:01 [Epoch 2 Batch 10190/11375] loss=0.1703, lr=0.0000138, metrics:accuracy:0.9070,f1:0.8763
INFO:root:08:46:02 [Epoch 2 Batch 10200/11375] loss=0.2019, lr=0.0000138, metrics:accuracy:0.9070,f1:0.8763
INFO:root:08:46:03 [Epoch 2 Batch 10210/11375] loss=0.1727, lr=0.0000138, metrics:accuracy:0.9070,f1:0.8763
INFO:root:08:46:05 [Epoch 2 Batch 10220/11375] loss=0.2495, lr=0.0000138, metrics:accuracy:0.9070,f1:0.8762
INFO:root:08:46:06 [Epoch 2 Batch 10230/11375] loss=0.2122, lr=0.0000138, metrics:accuracy:0.9070,f1:0.8762
INFO:root:08:46:07 [Epoch 2 Batch 10240/11375] loss=0.2003, lr=0.0000138, metrics:accuracy:0.9070,f1:0.8762
INFO:root:08:46:08 [Epoch 2 Batch 10250/11375] loss=0.2435, lr=0.0000138, metrics:accuracy:0.9070,f1:0.8762
INFO:root:08:46:09 [Epoch 2 Batch 10260/11375] loss=0.1608, lr=0.0000138, metrics:accuracy:0.9070,f1:0.8762
INFO:root:08:46:11 [Epoch 2 Batch 10270/11375] loss=0.1938, lr=0.0000138, metrics:accuracy:0.9070,f1:0.8763
INFO:root:08:46:12 [Epoch 2 Batch 10280/11375] loss=0.2271, lr=0.0000138, metrics:accuracy:0.9070,f1:0.8763
INFO:root:08:46:13 [Epoch 2 Batch 10290/11375] loss=0.1994, lr=0.0000138, metrics:accuracy:0.9071,f1:0.8763
INFO:root:08:46:14 [Epoch 2 Batch 10300/11375] loss=0.2549, lr=0.0000138, metrics:accuracy:0.9071,f1:0.8763
INFO:root:08:46:15 [Epoch 2 Batch 10310/11375] loss=0.2160, lr=0.0000137, metrics:accuracy:0.9071,f1:0.8763
INFO:root:08:46:16 [Epoch 2 Batch 10320/11375] loss=0.2142, lr=0.0000137, metrics:accuracy:0.9071,f1:0.8763
INFO:root:08:46:18 [Epoch 2 Batch 10330/11375] loss=0.2098, lr=0.0000137, metrics:accuracy:0.9071,f1:0.8764
INFO:root:08:46:19 [Epoch 2 Batch 10340/11375] loss=0.2328, lr=0.0000137, metrics:accuracy:0.9071,f1:0.8764
INFO:root:08:46:20 [Epoch 2 Batch 10350/11375] loss=0.2051, lr=0.0000137, metrics:accuracy:0.9071,f1:0.8764
INFO:root:08:46:21 [Epoch 2 Batch 10360/11375] loss=0.2286, lr=0.0000137, metrics:accuracy:0.9071,f1:0.8764
INFO:root:08:46:22 [Epoch 2 Batch 10370/11375] loss=0.1680, lr=0.0000137, metrics:accuracy:0.9071,f1:0.8764
INFO:root:08:46:23 [Epoch 2 Batch 10380/11375] loss=0.1697, lr=0.0000137, metrics:accuracy:0.9071,f1:0.8764
INFO:root:08:46:25 [Epoch 2 Batch 10390/11375] loss=0.2363, lr=0.0000137, metrics:accuracy:0.9071,f1:0.8764
INFO:root:08:46:26 [Epoch 2 Batch 10400/11375] loss=0.2576, lr=0.0000137, metrics:accuracy:0.9071,f1:0.8764
INFO:root:08:46:27 [Epoch 2 Batch 10410/11375] loss=0.2483, lr=0.0000137, metrics:accuracy:0.9071,f1:0.8764
INFO:root:08:46:28 [Epoch 2 Batch 10420/11375] loss=0.2236, lr=0.0000137, metrics:accuracy:0.9071,f1:0.8764
INFO:root:08:46:29 [Epoch 2 Batch 10430/11375] loss=0.1669, lr=0.0000137, metrics:accuracy:0.9071,f1:0.8764
INFO:root:08:46:31 [Epoch 2 Batch 10440/11375] loss=0.1880, lr=0.0000137, metrics:accuracy:0.9071,f1:0.8764
INFO:root:08:46:32 [Epoch 2 Batch 10450/11375] loss=0.2414, lr=0.0000137, metrics:accuracy:0.9071,f1:0.8764
INFO:root:08:46:33 [Epoch 2 Batch 10460/11375] loss=0.2102, lr=0.0000137, metrics:accuracy:0.9071,f1:0.8764
INFO:root:08:46:34 [Epoch 2 Batch 10470/11375] loss=0.2288, lr=0.0000137, metrics:accuracy:0.9071,f1:0.8764
INFO:root:08:46:35 [Epoch 2 Batch 10480/11375] loss=0.1997, lr=0.0000137, metrics:accuracy:0.9071,f1:0.8764
INFO:root:08:46:36 [Epoch 2 Batch 10490/11375] loss=0.2205, lr=0.0000137, metrics:accuracy:0.9071,f1:0.8764
INFO:root:08:46:37 [Epoch 2 Batch 10500/11375] loss=0.2511, lr=0.0000137, metrics:accuracy:0.9071,f1:0.8764
INFO:root:08:46:39 [Epoch 2 Batch 10510/11375] loss=0.1907, lr=0.0000137, metrics:accuracy:0.9071,f1:0.8764
INFO:root:08:46:40 [Epoch 2 Batch 10520/11375] loss=0.2056, lr=0.0000137, metrics:accuracy:0.9071,f1:0.8764
INFO:root:08:46:41 [Epoch 2 Batch 10530/11375] loss=0.2986, lr=0.0000137, metrics:accuracy:0.9070,f1:0.8764
INFO:root:08:46:42 [Epoch 2 Batch 10540/11375] loss=0.1863, lr=0.0000137, metrics:accuracy:0.9071,f1:0.8764
INFO:root:08:46:43 [Epoch 2 Batch 10550/11375] loss=0.2188, lr=0.0000137, metrics:accuracy:0.9071,f1:0.8764
INFO:root:08:46:45 [Epoch 2 Batch 10560/11375] loss=0.1850, lr=0.0000136, metrics:accuracy:0.9071,f1:0.8764
INFO:root:08:46:46 [Epoch 2 Batch 10570/11375] loss=0.2427, lr=0.0000136, metrics:accuracy:0.9071,f1:0.8765
INFO:root:08:46:47 [Epoch 2 Batch 10580/11375] loss=0.1730, lr=0.0000136, metrics:accuracy:0.9071,f1:0.8765
INFO:root:08:46:48 [Epoch 2 Batch 10590/11375] loss=0.2408, lr=0.0000136, metrics:accuracy:0.9071,f1:0.8764
INFO:root:08:46:49 [Epoch 2 Batch 10600/11375] loss=0.2055, lr=0.0000136, metrics:accuracy:0.9071,f1:0.8764
INFO:root:08:46:51 [Epoch 2 Batch 10610/11375] loss=0.2698, lr=0.0000136, metrics:accuracy:0.9071,f1:0.8764
INFO:root:08:46:52 [Epoch 2 Batch 10620/11375] loss=0.2723, lr=0.0000136, metrics:accuracy:0.9071,f1:0.8764
INFO:root:08:46:53 [Epoch 2 Batch 10630/11375] loss=0.2032, lr=0.0000136, metrics:accuracy:0.9071,f1:0.8764
INFO:root:08:46:54 [Epoch 2 Batch 10640/11375] loss=0.2219, lr=0.0000136, metrics:accuracy:0.9071,f1:0.8764
INFO:root:08:46:55 [Epoch 2 Batch 10650/11375] loss=0.1793, lr=0.0000136, metrics:accuracy:0.9071,f1:0.8765
INFO:root:08:46:56 [Epoch 2 Batch 10660/11375] loss=0.1753, lr=0.0000136, metrics:accuracy:0.9071,f1:0.8765
INFO:root:08:46:58 [Epoch 2 Batch 10670/11375] loss=0.2268, lr=0.0000136, metrics:accuracy:0.9071,f1:0.8765
INFO:root:08:46:59 [Epoch 2 Batch 10680/11375] loss=0.1765, lr=0.0000136, metrics:accuracy:0.9072,f1:0.8765
INFO:root:08:47:00 [Epoch 2 Batch 10690/11375] loss=0.1508, lr=0.0000136, metrics:accuracy:0.9072,f1:0.8766
INFO:root:08:47:01 [Epoch 2 Batch 10700/11375] loss=0.2200, lr=0.0000136, metrics:accuracy:0.9072,f1:0.8766
INFO:root:08:47:03 [Epoch 2 Batch 10710/11375] loss=0.2168, lr=0.0000136, metrics:accuracy:0.9072,f1:0.8766
INFO:root:08:47:04 [Epoch 2 Batch 10720/11375] loss=0.2706, lr=0.0000136, metrics:accuracy:0.9072,f1:0.8765
INFO:root:08:47:05 [Epoch 2 Batch 10730/11375] loss=0.1628, lr=0.0000136, metrics:accuracy:0.9072,f1:0.8766
INFO:root:08:47:06 [Epoch 2 Batch 10740/11375] loss=0.1989, lr=0.0000136, metrics:accuracy:0.9072,f1:0.8766
INFO:root:08:47:07 [Epoch 2 Batch 10750/11375] loss=0.2364, lr=0.0000136, metrics:accuracy:0.9072,f1:0.8766
INFO:root:08:47:08 [Epoch 2 Batch 10760/11375] loss=0.3017, lr=0.0000136, metrics:accuracy:0.9072,f1:0.8765
INFO:root:08:47:10 [Epoch 2 Batch 10770/11375] loss=0.2013, lr=0.0000136, metrics:accuracy:0.9072,f1:0.8766
INFO:root:08:47:11 [Epoch 2 Batch 10780/11375] loss=0.2478, lr=0.0000136, metrics:accuracy:0.9072,f1:0.8766
INFO:root:08:47:12 [Epoch 2 Batch 10790/11375] loss=0.1712, lr=0.0000136, metrics:accuracy:0.9072,f1:0.8766
INFO:root:08:47:13 [Epoch 2 Batch 10800/11375] loss=0.2102, lr=0.0000136, metrics:accuracy:0.9072,f1:0.8766
INFO:root:08:47:14 [Epoch 2 Batch 10810/11375] loss=0.2154, lr=0.0000136, metrics:accuracy:0.9072,f1:0.8766
INFO:root:08:47:15 [Epoch 2 Batch 10820/11375] loss=0.2222, lr=0.0000135, metrics:accuracy:0.9072,f1:0.8766
INFO:root:08:47:16 [Epoch 2 Batch 10830/11375] loss=0.2621, lr=0.0000135, metrics:accuracy:0.9072,f1:0.8766
INFO:root:08:47:18 [Epoch 2 Batch 10840/11375] loss=0.1588, lr=0.0000135, metrics:accuracy:0.9072,f1:0.8767
INFO:root:08:47:19 [Epoch 2 Batch 10850/11375] loss=0.2068, lr=0.0000135, metrics:accuracy:0.9072,f1:0.8767
INFO:root:08:47:20 [Epoch 2 Batch 10860/11375] loss=0.2557, lr=0.0000135, metrics:accuracy:0.9072,f1:0.8767
INFO:root:08:47:21 [Epoch 2 Batch 10870/11375] loss=0.2040, lr=0.0000135, metrics:accuracy:0.9072,f1:0.8767
INFO:root:08:47:22 [Epoch 2 Batch 10880/11375] loss=0.1826, lr=0.0000135, metrics:accuracy:0.9072,f1:0.8767
INFO:root:08:47:23 [Epoch 2 Batch 10890/11375] loss=0.2566, lr=0.0000135, metrics:accuracy:0.9072,f1:0.8767
INFO:root:08:47:25 [Epoch 2 Batch 10900/11375] loss=0.2136, lr=0.0000135, metrics:accuracy:0.9072,f1:0.8767
INFO:root:08:47:26 [Epoch 2 Batch 10910/11375] loss=0.2095, lr=0.0000135, metrics:accuracy:0.9072,f1:0.8767
INFO:root:08:47:27 [Epoch 2 Batch 10920/11375] loss=0.1568, lr=0.0000135, metrics:accuracy:0.9072,f1:0.8767
INFO:root:08:47:28 [Epoch 2 Batch 10930/11375] loss=0.2961, lr=0.0000135, metrics:accuracy:0.9072,f1:0.8767
INFO:root:08:47:29 [Epoch 2 Batch 10940/11375] loss=0.2311, lr=0.0000135, metrics:accuracy:0.9072,f1:0.8767
INFO:root:08:47:30 [Epoch 2 Batch 10950/11375] loss=0.2406, lr=0.0000135, metrics:accuracy:0.9072,f1:0.8767
INFO:root:08:47:32 [Epoch 2 Batch 10960/11375] loss=0.1714, lr=0.0000135, metrics:accuracy:0.9072,f1:0.8768
INFO:root:08:47:33 [Epoch 2 Batch 10970/11375] loss=0.1808, lr=0.0000135, metrics:accuracy:0.9073,f1:0.8768
INFO:root:08:47:34 [Epoch 2 Batch 10980/11375] loss=0.1809, lr=0.0000135, metrics:accuracy:0.9073,f1:0.8768
INFO:root:08:47:35 [Epoch 2 Batch 10990/11375] loss=0.1716, lr=0.0000135, metrics:accuracy:0.9073,f1:0.8768
INFO:root:08:47:36 [Epoch 2 Batch 11000/11375] loss=0.2325, lr=0.0000135, metrics:accuracy:0.9073,f1:0.8769
INFO:root:08:47:37 [Epoch 2 Batch 11010/11375] loss=0.2055, lr=0.0000135, metrics:accuracy:0.9073,f1:0.8769
INFO:root:08:47:38 [Epoch 2 Batch 11020/11375] loss=0.2418, lr=0.0000135, metrics:accuracy:0.9073,f1:0.8769
INFO:root:08:47:40 [Epoch 2 Batch 11030/11375] loss=0.1622, lr=0.0000135, metrics:accuracy:0.9073,f1:0.8769
INFO:root:08:47:41 [Epoch 2 Batch 11040/11375] loss=0.2496, lr=0.0000135, metrics:accuracy:0.9073,f1:0.8769