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2022-11-06 15:34:46,075 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 15:34:46,075 Model: "SequenceTagger( |
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(embeddings): StackedEmbeddings( |
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(list_embedding_0): FlairEmbeddings( |
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(lm): LanguageModel( |
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(drop): Dropout(p=0.1, inplace=False) |
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(encoder): Embedding(962, 100) |
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(rnn): LSTM(100, 1024) |
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(decoder): Linear(in_features=1024, out_features=962, bias=True) |
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) |
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) |
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(list_embedding_1): FlairEmbeddings( |
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(lm): LanguageModel( |
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(drop): Dropout(p=0.1, inplace=False) |
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(encoder): Embedding(962, 100) |
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(rnn): LSTM(100, 1024) |
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(decoder): Linear(in_features=1024, out_features=962, bias=True) |
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) |
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) |
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) |
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(dropout): Dropout(p=0.3380078963015963, inplace=False) |
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(word_dropout): WordDropout(p=0.05) |
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(locked_dropout): LockedDropout(p=0.5) |
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(embedding2nn): Linear(in_features=2048, out_features=2048, bias=True) |
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(rnn): LSTM(2048, 128, num_layers=2, batch_first=True, dropout=0.5, bidirectional=True) |
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(linear): Linear(in_features=256, out_features=19, bias=True) |
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(loss_function): ViterbiLoss() |
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(crf): CRF() |
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)" |
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2022-11-06 15:34:46,075 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 15:34:46,076 Corpus: "Corpus: 7886 train + 876 dev + 4045 test sentences" |
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2022-11-06 15:34:46,076 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 15:34:46,076 Parameters: |
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2022-11-06 15:34:46,076 - learning_rate: "0.100000" |
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2022-11-06 15:34:46,076 - mini_batch_size: "32" |
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2022-11-06 15:34:46,076 - patience: "3" |
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2022-11-06 15:34:46,076 - anneal_factor: "0.5" |
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2022-11-06 15:34:46,076 - max_epochs: "150" |
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2022-11-06 15:34:46,076 - shuffle: "True" |
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2022-11-06 15:34:46,076 - train_with_dev: "True" |
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2022-11-06 15:34:46,076 - batch_growth_annealing: "False" |
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2022-11-06 15:34:46,076 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 15:34:46,077 Model training base path: "ner-tests/uk.flairembeddings.champ" |
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2022-11-06 15:34:46,077 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 15:34:46,077 Device: cuda:0 |
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2022-11-06 15:34:46,077 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 15:34:46,077 Embeddings storage mode: cpu |
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2022-11-06 15:34:46,077 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 15:34:55,361 epoch 1 - iter 27/274 - loss 0.59321573 - samples/sec: 93.09 - lr: 0.100000 |
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2022-11-06 15:35:04,385 epoch 1 - iter 54/274 - loss 0.48716151 - samples/sec: 95.78 - lr: 0.100000 |
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2022-11-06 15:35:14,049 epoch 1 - iter 81/274 - loss 0.38801385 - samples/sec: 89.43 - lr: 0.100000 |
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2022-11-06 15:35:25,713 epoch 1 - iter 108/274 - loss 0.35179862 - samples/sec: 74.09 - lr: 0.100000 |
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2022-11-06 15:35:33,119 epoch 1 - iter 135/274 - loss 0.31056108 - samples/sec: 116.72 - lr: 0.100000 |
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2022-11-06 15:35:40,364 epoch 1 - iter 162/274 - loss 0.27554678 - samples/sec: 119.30 - lr: 0.100000 |
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2022-11-06 15:35:48,761 epoch 1 - iter 189/274 - loss 0.24648499 - samples/sec: 102.93 - lr: 0.100000 |
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2022-11-06 15:35:55,011 epoch 1 - iter 216/274 - loss 0.22834151 - samples/sec: 138.30 - lr: 0.100000 |
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2022-11-06 15:36:03,341 epoch 1 - iter 243/274 - loss 0.21155940 - samples/sec: 103.76 - lr: 0.100000 |
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2022-11-06 15:36:11,769 epoch 1 - iter 270/274 - loss 0.20285420 - samples/sec: 102.56 - lr: 0.100000 |
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2022-11-06 15:36:12,834 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 15:36:12,834 EPOCH 1 done: loss 0.2008 - lr 0.100000 |
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2022-11-06 15:37:00,413 Evaluating as a multi-label problem: False |
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2022-11-06 15:37:00,487 TEST : loss 0.12195425480604172 - f1-score (micro avg) 0.6446 |
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2022-11-06 15:37:00,974 BAD EPOCHS (no improvement): 0 |
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2022-11-06 15:37:01,122 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 15:37:07,944 epoch 2 - iter 27/274 - loss 0.10617612 - samples/sec: 126.74 - lr: 0.100000 |
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2022-11-06 15:37:14,883 epoch 2 - iter 54/274 - loss 0.10581527 - samples/sec: 124.56 - lr: 0.100000 |
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2022-11-06 15:37:22,249 epoch 2 - iter 81/274 - loss 0.10803741 - samples/sec: 117.35 - lr: 0.100000 |
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2022-11-06 15:37:29,097 epoch 2 - iter 108/274 - loss 0.10325620 - samples/sec: 126.23 - lr: 0.100000 |
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2022-11-06 15:37:36,384 epoch 2 - iter 135/274 - loss 0.10338215 - samples/sec: 118.63 - lr: 0.100000 |
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2022-11-06 15:37:43,245 epoch 2 - iter 162/274 - loss 0.09914864 - samples/sec: 126.00 - lr: 0.100000 |
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2022-11-06 15:37:50,576 epoch 2 - iter 189/274 - loss 0.09776149 - samples/sec: 117.90 - lr: 0.100000 |
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2022-11-06 15:37:57,212 epoch 2 - iter 216/274 - loss 0.09654818 - samples/sec: 130.26 - lr: 0.100000 |
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2022-11-06 15:38:03,927 epoch 2 - iter 243/274 - loss 0.09305997 - samples/sec: 128.74 - lr: 0.100000 |
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2022-11-06 15:38:11,119 epoch 2 - iter 270/274 - loss 0.09219545 - samples/sec: 120.18 - lr: 0.100000 |
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2022-11-06 15:38:12,113 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 15:38:12,113 EPOCH 2 done: loss 0.0924 - lr 0.100000 |
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2022-11-06 15:38:50,373 Evaluating as a multi-label problem: False |
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2022-11-06 15:38:50,400 TEST : loss 0.06683151423931122 - f1-score (micro avg) 0.7737 |
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2022-11-06 15:38:50,885 BAD EPOCHS (no improvement): 0 |
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2022-11-06 15:38:51,070 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 15:38:57,845 epoch 3 - iter 27/274 - loss 0.07387935 - samples/sec: 127.62 - lr: 0.100000 |
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2022-11-06 15:39:04,943 epoch 3 - iter 54/274 - loss 0.06792482 - samples/sec: 121.77 - lr: 0.100000 |
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2022-11-06 15:39:12,160 epoch 3 - iter 81/274 - loss 0.07438869 - samples/sec: 119.78 - lr: 0.100000 |
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2022-11-06 15:39:18,834 epoch 3 - iter 108/274 - loss 0.07109664 - samples/sec: 129.53 - lr: 0.100000 |
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2022-11-06 15:39:26,268 epoch 3 - iter 135/274 - loss 0.06940220 - samples/sec: 116.28 - lr: 0.100000 |
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2022-11-06 15:39:33,410 epoch 3 - iter 162/274 - loss 0.07122806 - samples/sec: 121.03 - lr: 0.100000 |
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2022-11-06 15:39:40,488 epoch 3 - iter 189/274 - loss 0.07076674 - samples/sec: 122.12 - lr: 0.100000 |
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2022-11-06 15:39:46,355 epoch 3 - iter 216/274 - loss 0.06970241 - samples/sec: 147.35 - lr: 0.100000 |
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2022-11-06 15:39:51,595 epoch 3 - iter 243/274 - loss 0.06863317 - samples/sec: 164.98 - lr: 0.100000 |
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2022-11-06 15:39:56,786 epoch 3 - iter 270/274 - loss 0.06710405 - samples/sec: 166.57 - lr: 0.100000 |
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2022-11-06 15:39:57,559 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 15:39:57,559 EPOCH 3 done: loss 0.0674 - lr 0.100000 |
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2022-11-06 15:40:27,851 Evaluating as a multi-label problem: False |
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2022-11-06 15:40:27,879 TEST : loss 0.059379346668720245 - f1-score (micro avg) 0.75 |
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2022-11-06 15:40:28,363 BAD EPOCHS (no improvement): 0 |
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2022-11-06 15:40:28,555 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 15:40:34,013 epoch 4 - iter 27/274 - loss 0.04549779 - samples/sec: 158.45 - lr: 0.100000 |
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2022-11-06 15:40:39,924 epoch 4 - iter 54/274 - loss 0.05683785 - samples/sec: 146.25 - lr: 0.100000 |
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2022-11-06 15:40:45,164 epoch 4 - iter 81/274 - loss 0.05429896 - samples/sec: 165.01 - lr: 0.100000 |
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2022-11-06 15:40:50,197 epoch 4 - iter 108/274 - loss 0.05303453 - samples/sec: 171.76 - lr: 0.100000 |
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2022-11-06 15:40:55,258 epoch 4 - iter 135/274 - loss 0.05437553 - samples/sec: 170.85 - lr: 0.100000 |
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2022-11-06 15:41:00,805 epoch 4 - iter 162/274 - loss 0.05787177 - samples/sec: 155.84 - lr: 0.100000 |
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2022-11-06 15:41:06,448 epoch 4 - iter 189/274 - loss 0.05841061 - samples/sec: 153.20 - lr: 0.100000 |
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2022-11-06 15:41:11,966 epoch 4 - iter 216/274 - loss 0.05980452 - samples/sec: 156.68 - lr: 0.100000 |
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2022-11-06 15:41:16,872 epoch 4 - iter 243/274 - loss 0.05926645 - samples/sec: 176.25 - lr: 0.100000 |
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2022-11-06 15:41:22,084 epoch 4 - iter 270/274 - loss 0.05806207 - samples/sec: 165.86 - lr: 0.100000 |
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2022-11-06 15:41:22,799 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 15:41:22,799 EPOCH 4 done: loss 0.0577 - lr 0.100000 |
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2022-11-06 15:41:53,160 Evaluating as a multi-label problem: False |
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2022-11-06 15:41:53,188 TEST : loss 0.049502115696668625 - f1-score (micro avg) 0.7914 |
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2022-11-06 15:41:53,669 BAD EPOCHS (no improvement): 0 |
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2022-11-06 15:41:53,863 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 15:41:58,837 epoch 5 - iter 27/274 - loss 0.04611893 - samples/sec: 173.87 - lr: 0.100000 |
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2022-11-06 15:42:03,736 epoch 5 - iter 54/274 - loss 0.04970445 - samples/sec: 176.51 - lr: 0.100000 |
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2022-11-06 15:42:09,197 epoch 5 - iter 81/274 - loss 0.05127046 - samples/sec: 158.29 - lr: 0.100000 |
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2022-11-06 15:42:14,546 epoch 5 - iter 108/274 - loss 0.05297562 - samples/sec: 161.65 - lr: 0.100000 |
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2022-11-06 15:42:19,811 epoch 5 - iter 135/274 - loss 0.05279157 - samples/sec: 164.20 - lr: 0.100000 |
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2022-11-06 15:42:25,658 epoch 5 - iter 162/274 - loss 0.05326809 - samples/sec: 147.84 - lr: 0.100000 |
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2022-11-06 15:42:30,832 epoch 5 - iter 189/274 - loss 0.05164310 - samples/sec: 167.11 - lr: 0.100000 |
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2022-11-06 15:42:36,139 epoch 5 - iter 216/274 - loss 0.05192735 - samples/sec: 162.88 - lr: 0.100000 |
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2022-11-06 15:42:41,230 epoch 5 - iter 243/274 - loss 0.05157005 - samples/sec: 169.84 - lr: 0.100000 |
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2022-11-06 15:42:46,754 epoch 5 - iter 270/274 - loss 0.05043757 - samples/sec: 156.50 - lr: 0.100000 |
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2022-11-06 15:42:47,801 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 15:42:47,802 EPOCH 5 done: loss 0.0501 - lr 0.100000 |
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2022-11-06 15:43:18,340 Evaluating as a multi-label problem: False |
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2022-11-06 15:43:18,366 TEST : loss 0.041369177401065826 - f1-score (micro avg) 0.829 |
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2022-11-06 15:43:18,853 BAD EPOCHS (no improvement): 0 |
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2022-11-06 15:43:19,044 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 15:43:24,292 epoch 6 - iter 27/274 - loss 0.04513706 - samples/sec: 164.78 - lr: 0.100000 |
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2022-11-06 15:43:29,559 epoch 6 - iter 54/274 - loss 0.04520187 - samples/sec: 164.16 - lr: 0.100000 |
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2022-11-06 15:43:35,357 epoch 6 - iter 81/274 - loss 0.04538206 - samples/sec: 149.11 - lr: 0.100000 |
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2022-11-06 15:43:41,144 epoch 6 - iter 108/274 - loss 0.04554187 - samples/sec: 149.38 - lr: 0.100000 |
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2022-11-06 15:43:46,451 epoch 6 - iter 135/274 - loss 0.04471338 - samples/sec: 162.92 - lr: 0.100000 |
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2022-11-06 15:43:51,894 epoch 6 - iter 162/274 - loss 0.04518209 - samples/sec: 158.83 - lr: 0.100000 |
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2022-11-06 15:43:56,778 epoch 6 - iter 189/274 - loss 0.04541590 - samples/sec: 177.01 - lr: 0.100000 |
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2022-11-06 15:44:02,451 epoch 6 - iter 216/274 - loss 0.04704355 - samples/sec: 152.40 - lr: 0.100000 |
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2022-11-06 15:44:07,536 epoch 6 - iter 243/274 - loss 0.04551856 - samples/sec: 170.02 - lr: 0.100000 |
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2022-11-06 15:44:13,040 epoch 6 - iter 270/274 - loss 0.04535913 - samples/sec: 157.07 - lr: 0.100000 |
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2022-11-06 15:44:14,151 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 15:44:14,151 EPOCH 6 done: loss 0.0454 - lr 0.100000 |
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2022-11-06 15:44:44,550 Evaluating as a multi-label problem: False |
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2022-11-06 15:44:44,577 TEST : loss 0.041055891662836075 - f1-score (micro avg) 0.8173 |
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2022-11-06 15:44:45,062 BAD EPOCHS (no improvement): 0 |
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2022-11-06 15:44:45,248 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 15:44:51,160 epoch 7 - iter 27/274 - loss 0.04878990 - samples/sec: 146.25 - lr: 0.100000 |
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2022-11-06 15:44:56,715 epoch 7 - iter 54/274 - loss 0.04800253 - samples/sec: 155.65 - lr: 0.100000 |
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2022-11-06 15:45:02,064 epoch 7 - iter 81/274 - loss 0.04541887 - samples/sec: 161.63 - lr: 0.100000 |
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2022-11-06 15:45:07,393 epoch 7 - iter 108/274 - loss 0.04497799 - samples/sec: 162.24 - lr: 0.100000 |
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2022-11-06 15:45:12,385 epoch 7 - iter 135/274 - loss 0.04659413 - samples/sec: 173.17 - lr: 0.100000 |
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2022-11-06 15:45:17,595 epoch 7 - iter 162/274 - loss 0.04628117 - samples/sec: 165.96 - lr: 0.100000 |
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2022-11-06 15:45:22,851 epoch 7 - iter 189/274 - loss 0.04589064 - samples/sec: 164.47 - lr: 0.100000 |
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2022-11-06 15:45:28,144 epoch 7 - iter 216/274 - loss 0.04517667 - samples/sec: 163.34 - lr: 0.100000 |
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2022-11-06 15:45:33,258 epoch 7 - iter 243/274 - loss 0.04462662 - samples/sec: 169.07 - lr: 0.100000 |
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2022-11-06 15:45:38,382 epoch 7 - iter 270/274 - loss 0.04362751 - samples/sec: 168.72 - lr: 0.100000 |
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2022-11-06 15:45:39,098 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 15:45:39,098 EPOCH 7 done: loss 0.0433 - lr 0.100000 |
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2022-11-06 15:46:09,474 Evaluating as a multi-label problem: False |
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2022-11-06 15:46:09,501 TEST : loss 0.04179549589753151 - f1-score (micro avg) 0.8315 |
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2022-11-06 15:46:09,985 BAD EPOCHS (no improvement): 0 |
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2022-11-06 15:46:10,174 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 15:46:15,222 epoch 8 - iter 27/274 - loss 0.03396046 - samples/sec: 171.33 - lr: 0.100000 |
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2022-11-06 15:46:20,352 epoch 8 - iter 54/274 - loss 0.03518666 - samples/sec: 168.52 - lr: 0.100000 |
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2022-11-06 15:46:25,603 epoch 8 - iter 81/274 - loss 0.03701020 - samples/sec: 164.65 - lr: 0.100000 |
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2022-11-06 15:46:30,963 epoch 8 - iter 108/274 - loss 0.03993933 - samples/sec: 161.30 - lr: 0.100000 |
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2022-11-06 15:46:37,269 epoch 8 - iter 135/274 - loss 0.04076812 - samples/sec: 137.08 - lr: 0.100000 |
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2022-11-06 15:46:41,985 epoch 8 - iter 162/274 - loss 0.03964813 - samples/sec: 183.34 - lr: 0.100000 |
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2022-11-06 15:46:47,735 epoch 8 - iter 189/274 - loss 0.04095653 - samples/sec: 150.34 - lr: 0.100000 |
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2022-11-06 15:46:53,106 epoch 8 - iter 216/274 - loss 0.04059537 - samples/sec: 160.97 - lr: 0.100000 |
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2022-11-06 15:46:58,536 epoch 8 - iter 243/274 - loss 0.04031854 - samples/sec: 159.53 - lr: 0.100000 |
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2022-11-06 15:47:03,886 epoch 8 - iter 270/274 - loss 0.04090647 - samples/sec: 161.58 - lr: 0.100000 |
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2022-11-06 15:47:04,725 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 15:47:04,726 EPOCH 8 done: loss 0.0410 - lr 0.100000 |
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2022-11-06 15:47:35,125 Evaluating as a multi-label problem: False |
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2022-11-06 15:47:35,153 TEST : loss 0.03513012081384659 - f1-score (micro avg) 0.8152 |
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2022-11-06 15:47:35,637 BAD EPOCHS (no improvement): 0 |
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2022-11-06 15:47:35,830 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 15:47:40,768 epoch 9 - iter 27/274 - loss 0.04363616 - samples/sec: 175.15 - lr: 0.100000 |
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2022-11-06 15:47:46,234 epoch 9 - iter 54/274 - loss 0.04133601 - samples/sec: 158.19 - lr: 0.100000 |
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2022-11-06 15:47:51,527 epoch 9 - iter 81/274 - loss 0.04014737 - samples/sec: 163.32 - lr: 0.100000 |
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2022-11-06 15:47:56,585 epoch 9 - iter 108/274 - loss 0.03981344 - samples/sec: 170.96 - lr: 0.100000 |
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2022-11-06 15:48:02,137 epoch 9 - iter 135/274 - loss 0.03979068 - samples/sec: 155.69 - lr: 0.100000 |
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2022-11-06 15:48:07,556 epoch 9 - iter 162/274 - loss 0.03974765 - samples/sec: 159.54 - lr: 0.100000 |
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2022-11-06 15:48:13,572 epoch 9 - iter 189/274 - loss 0.03867948 - samples/sec: 143.69 - lr: 0.100000 |
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2022-11-06 15:48:19,089 epoch 9 - iter 216/274 - loss 0.03852985 - samples/sec: 156.70 - lr: 0.100000 |
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2022-11-06 15:48:24,290 epoch 9 - iter 243/274 - loss 0.03835168 - samples/sec: 166.25 - lr: 0.100000 |
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2022-11-06 15:48:29,451 epoch 9 - iter 270/274 - loss 0.03803656 - samples/sec: 167.50 - lr: 0.100000 |
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2022-11-06 15:48:30,203 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 15:48:30,203 EPOCH 9 done: loss 0.0381 - lr 0.100000 |
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2022-11-06 15:49:00,536 Evaluating as a multi-label problem: False |
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2022-11-06 15:49:00,564 TEST : loss 0.03051774762570858 - f1-score (micro avg) 0.8377 |
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2022-11-06 15:49:01,048 BAD EPOCHS (no improvement): 0 |
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2022-11-06 15:49:01,232 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 15:49:06,209 epoch 10 - iter 27/274 - loss 0.03750373 - samples/sec: 173.79 - lr: 0.100000 |
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2022-11-06 15:49:11,269 epoch 10 - iter 54/274 - loss 0.03551327 - samples/sec: 171.79 - lr: 0.100000 |
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2022-11-06 15:49:16,329 epoch 10 - iter 81/274 - loss 0.03520153 - samples/sec: 170.88 - lr: 0.100000 |
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2022-11-06 15:49:22,078 epoch 10 - iter 108/274 - loss 0.03384319 - samples/sec: 150.37 - lr: 0.100000 |
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2022-11-06 15:49:27,253 epoch 10 - iter 135/274 - loss 0.03454667 - samples/sec: 168.03 - lr: 0.100000 |
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2022-11-06 15:49:33,066 epoch 10 - iter 162/274 - loss 0.03690282 - samples/sec: 148.72 - lr: 0.100000 |
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2022-11-06 15:49:38,156 epoch 10 - iter 189/274 - loss 0.03640468 - samples/sec: 169.85 - lr: 0.100000 |
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2022-11-06 15:49:43,672 epoch 10 - iter 216/274 - loss 0.03642463 - samples/sec: 156.74 - lr: 0.100000 |
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2022-11-06 15:49:49,129 epoch 10 - iter 243/274 - loss 0.03615499 - samples/sec: 158.43 - lr: 0.100000 |
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2022-11-06 15:49:54,326 epoch 10 - iter 270/274 - loss 0.03634573 - samples/sec: 166.36 - lr: 0.100000 |
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2022-11-06 15:49:55,323 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 15:49:55,323 EPOCH 10 done: loss 0.0363 - lr 0.100000 |
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2022-11-06 15:50:25,641 Evaluating as a multi-label problem: False |
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2022-11-06 15:50:25,668 TEST : loss 0.03244197368621826 - f1-score (micro avg) 0.8371 |
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2022-11-06 15:50:26,158 BAD EPOCHS (no improvement): 0 |
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2022-11-06 15:50:26,341 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 15:50:31,834 epoch 11 - iter 27/274 - loss 0.03150520 - samples/sec: 157.43 - lr: 0.100000 |
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2022-11-06 15:50:36,958 epoch 11 - iter 54/274 - loss 0.03241383 - samples/sec: 168.73 - lr: 0.100000 |
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2022-11-06 15:50:42,516 epoch 11 - iter 81/274 - loss 0.03450312 - samples/sec: 155.54 - lr: 0.100000 |
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2022-11-06 15:50:48,155 epoch 11 - iter 108/274 - loss 0.03653110 - samples/sec: 153.33 - lr: 0.100000 |
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2022-11-06 15:50:53,310 epoch 11 - iter 135/274 - loss 0.03571646 - samples/sec: 169.09 - lr: 0.100000 |
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2022-11-06 15:50:58,855 epoch 11 - iter 162/274 - loss 0.03598466 - samples/sec: 155.93 - lr: 0.100000 |
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2022-11-06 15:51:03,811 epoch 11 - iter 189/274 - loss 0.03605525 - samples/sec: 174.44 - lr: 0.100000 |
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2022-11-06 15:51:09,465 epoch 11 - iter 216/274 - loss 0.03568287 - samples/sec: 152.91 - lr: 0.100000 |
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2022-11-06 15:51:14,616 epoch 11 - iter 243/274 - loss 0.03511336 - samples/sec: 167.85 - lr: 0.100000 |
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2022-11-06 15:51:20,060 epoch 11 - iter 270/274 - loss 0.03506643 - samples/sec: 158.80 - lr: 0.100000 |
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2022-11-06 15:51:20,738 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 15:51:20,738 EPOCH 11 done: loss 0.0349 - lr 0.100000 |
|
2022-11-06 15:51:51,019 Evaluating as a multi-label problem: False |
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2022-11-06 15:51:51,046 TEST : loss 0.03070417419075966 - f1-score (micro avg) 0.8381 |
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2022-11-06 15:51:51,527 BAD EPOCHS (no improvement): 0 |
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2022-11-06 15:51:51,802 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 15:51:57,611 epoch 12 - iter 27/274 - loss 0.03444462 - samples/sec: 148.90 - lr: 0.100000 |
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2022-11-06 15:52:03,091 epoch 12 - iter 54/274 - loss 0.03133987 - samples/sec: 157.74 - lr: 0.100000 |
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2022-11-06 15:52:08,539 epoch 12 - iter 81/274 - loss 0.03294927 - samples/sec: 158.70 - lr: 0.100000 |
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2022-11-06 15:52:14,158 epoch 12 - iter 108/274 - loss 0.03495274 - samples/sec: 153.85 - lr: 0.100000 |
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2022-11-06 15:52:19,620 epoch 12 - iter 135/274 - loss 0.03537488 - samples/sec: 158.26 - lr: 0.100000 |
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2022-11-06 15:52:24,531 epoch 12 - iter 162/274 - loss 0.03434720 - samples/sec: 176.08 - lr: 0.100000 |
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2022-11-06 15:52:29,788 epoch 12 - iter 189/274 - loss 0.03469288 - samples/sec: 164.44 - lr: 0.100000 |
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2022-11-06 15:52:35,243 epoch 12 - iter 216/274 - loss 0.03436357 - samples/sec: 158.50 - lr: 0.100000 |
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2022-11-06 15:52:40,378 epoch 12 - iter 243/274 - loss 0.03457484 - samples/sec: 168.37 - lr: 0.100000 |
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2022-11-06 15:52:45,373 epoch 12 - iter 270/274 - loss 0.03445703 - samples/sec: 174.57 - lr: 0.100000 |
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2022-11-06 15:52:46,090 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 15:52:46,090 EPOCH 12 done: loss 0.0344 - lr 0.100000 |
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2022-11-06 15:53:16,452 Evaluating as a multi-label problem: False |
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2022-11-06 15:53:16,479 TEST : loss 0.030996335670351982 - f1-score (micro avg) 0.8424 |
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2022-11-06 15:53:16,961 BAD EPOCHS (no improvement): 0 |
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2022-11-06 15:53:17,150 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 15:53:22,301 epoch 13 - iter 27/274 - loss 0.03365013 - samples/sec: 167.89 - lr: 0.100000 |
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2022-11-06 15:53:27,641 epoch 13 - iter 54/274 - loss 0.03153036 - samples/sec: 161.89 - lr: 0.100000 |
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2022-11-06 15:53:32,949 epoch 13 - iter 81/274 - loss 0.03098350 - samples/sec: 162.89 - lr: 0.100000 |
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2022-11-06 15:53:38,836 epoch 13 - iter 108/274 - loss 0.03131598 - samples/sec: 146.83 - lr: 0.100000 |
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2022-11-06 15:53:44,380 epoch 13 - iter 135/274 - loss 0.03207890 - samples/sec: 155.95 - lr: 0.100000 |
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2022-11-06 15:53:49,558 epoch 13 - iter 162/274 - loss 0.03192553 - samples/sec: 166.96 - lr: 0.100000 |
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2022-11-06 15:53:54,893 epoch 13 - iter 189/274 - loss 0.03333380 - samples/sec: 162.05 - lr: 0.100000 |
|
2022-11-06 15:54:00,220 epoch 13 - iter 216/274 - loss 0.03343657 - samples/sec: 162.29 - lr: 0.100000 |
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2022-11-06 15:54:05,604 epoch 13 - iter 243/274 - loss 0.03368449 - samples/sec: 160.59 - lr: 0.100000 |
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2022-11-06 15:54:10,865 epoch 13 - iter 270/274 - loss 0.03369076 - samples/sec: 164.34 - lr: 0.100000 |
|
2022-11-06 15:54:11,568 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 15:54:11,568 EPOCH 13 done: loss 0.0340 - lr 0.100000 |
|
2022-11-06 15:54:41,930 Evaluating as a multi-label problem: False |
|
2022-11-06 15:54:41,957 TEST : loss 0.029288053512573242 - f1-score (micro avg) 0.8299 |
|
2022-11-06 15:54:42,442 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 15:54:42,629 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 15:54:47,783 epoch 14 - iter 27/274 - loss 0.02977866 - samples/sec: 167.78 - lr: 0.100000 |
|
2022-11-06 15:54:52,877 epoch 14 - iter 54/274 - loss 0.03196483 - samples/sec: 169.72 - lr: 0.100000 |
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2022-11-06 15:54:58,409 epoch 14 - iter 81/274 - loss 0.03196867 - samples/sec: 157.49 - lr: 0.100000 |
|
2022-11-06 15:55:04,520 epoch 14 - iter 108/274 - loss 0.03252995 - samples/sec: 141.45 - lr: 0.100000 |
|
2022-11-06 15:55:10,082 epoch 14 - iter 135/274 - loss 0.03218022 - samples/sec: 155.44 - lr: 0.100000 |
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2022-11-06 15:55:15,128 epoch 14 - iter 162/274 - loss 0.03227490 - samples/sec: 171.33 - lr: 0.100000 |
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2022-11-06 15:55:20,317 epoch 14 - iter 189/274 - loss 0.03184929 - samples/sec: 166.62 - lr: 0.100000 |
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2022-11-06 15:55:25,513 epoch 14 - iter 216/274 - loss 0.03206183 - samples/sec: 166.40 - lr: 0.100000 |
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2022-11-06 15:55:30,596 epoch 14 - iter 243/274 - loss 0.03177242 - samples/sec: 170.11 - lr: 0.100000 |
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2022-11-06 15:55:36,208 epoch 14 - iter 270/274 - loss 0.03198340 - samples/sec: 154.03 - lr: 0.100000 |
|
2022-11-06 15:55:36,952 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 15:55:36,952 EPOCH 14 done: loss 0.0320 - lr 0.100000 |
|
2022-11-06 15:56:07,327 Evaluating as a multi-label problem: False |
|
2022-11-06 15:56:07,355 TEST : loss 0.03270775079727173 - f1-score (micro avg) 0.8277 |
|
2022-11-06 15:56:07,842 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 15:56:08,024 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 15:56:13,566 epoch 15 - iter 27/274 - loss 0.03563398 - samples/sec: 156.05 - lr: 0.100000 |
|
2022-11-06 15:56:18,887 epoch 15 - iter 54/274 - loss 0.03282755 - samples/sec: 162.46 - lr: 0.100000 |
|
2022-11-06 15:56:24,185 epoch 15 - iter 81/274 - loss 0.03268187 - samples/sec: 163.20 - lr: 0.100000 |
|
2022-11-06 15:56:29,115 epoch 15 - iter 108/274 - loss 0.03269617 - samples/sec: 175.37 - lr: 0.100000 |
|
2022-11-06 15:56:34,592 epoch 15 - iter 135/274 - loss 0.03357008 - samples/sec: 157.83 - lr: 0.100000 |
|
2022-11-06 15:56:40,439 epoch 15 - iter 162/274 - loss 0.03380551 - samples/sec: 147.87 - lr: 0.100000 |
|
2022-11-06 15:56:45,617 epoch 15 - iter 189/274 - loss 0.03331763 - samples/sec: 166.98 - lr: 0.100000 |
|
2022-11-06 15:56:51,191 epoch 15 - iter 216/274 - loss 0.03268010 - samples/sec: 155.09 - lr: 0.100000 |
|
2022-11-06 15:56:56,641 epoch 15 - iter 243/274 - loss 0.03226809 - samples/sec: 158.62 - lr: 0.100000 |
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2022-11-06 15:57:01,510 epoch 15 - iter 270/274 - loss 0.03186487 - samples/sec: 177.55 - lr: 0.100000 |
|
2022-11-06 15:57:02,246 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 15:57:02,247 EPOCH 15 done: loss 0.0318 - lr 0.100000 |
|
2022-11-06 15:57:32,568 Evaluating as a multi-label problem: False |
|
2022-11-06 15:57:32,595 TEST : loss 0.03125728294253349 - f1-score (micro avg) 0.8514 |
|
2022-11-06 15:57:33,080 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 15:57:33,271 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 15:57:38,516 epoch 16 - iter 27/274 - loss 0.03170152 - samples/sec: 164.88 - lr: 0.100000 |
|
2022-11-06 15:57:43,882 epoch 16 - iter 54/274 - loss 0.03070640 - samples/sec: 161.13 - lr: 0.100000 |
|
2022-11-06 15:57:49,576 epoch 16 - iter 81/274 - loss 0.03177272 - samples/sec: 151.82 - lr: 0.100000 |
|
2022-11-06 15:57:55,103 epoch 16 - iter 108/274 - loss 0.03030676 - samples/sec: 156.44 - lr: 0.100000 |
|
2022-11-06 15:58:00,498 epoch 16 - iter 135/274 - loss 0.03104558 - samples/sec: 161.11 - lr: 0.100000 |
|
2022-11-06 15:58:05,767 epoch 16 - iter 162/274 - loss 0.03092946 - samples/sec: 164.10 - lr: 0.100000 |
|
2022-11-06 15:58:11,095 epoch 16 - iter 189/274 - loss 0.03056373 - samples/sec: 162.25 - lr: 0.100000 |
|
2022-11-06 15:58:16,297 epoch 16 - iter 216/274 - loss 0.03034550 - samples/sec: 166.20 - lr: 0.100000 |
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2022-11-06 15:58:21,591 epoch 16 - iter 243/274 - loss 0.03035053 - samples/sec: 163.30 - lr: 0.100000 |
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2022-11-06 15:58:26,772 epoch 16 - iter 270/274 - loss 0.03062837 - samples/sec: 166.86 - lr: 0.100000 |
|
2022-11-06 15:58:27,519 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 15:58:27,519 EPOCH 16 done: loss 0.0308 - lr 0.100000 |
|
2022-11-06 15:58:57,892 Evaluating as a multi-label problem: False |
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2022-11-06 15:58:57,919 TEST : loss 0.030985970050096512 - f1-score (micro avg) 0.8344 |
|
2022-11-06 15:58:58,404 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 15:58:58,592 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 15:59:03,852 epoch 17 - iter 27/274 - loss 0.02721503 - samples/sec: 164.44 - lr: 0.100000 |
|
2022-11-06 15:59:09,118 epoch 17 - iter 54/274 - loss 0.03006200 - samples/sec: 164.18 - lr: 0.100000 |
|
2022-11-06 15:59:14,606 epoch 17 - iter 81/274 - loss 0.02881095 - samples/sec: 157.52 - lr: 0.100000 |
|
2022-11-06 15:59:19,811 epoch 17 - iter 108/274 - loss 0.02899773 - samples/sec: 166.11 - lr: 0.100000 |
|
2022-11-06 15:59:24,699 epoch 17 - iter 135/274 - loss 0.02906021 - samples/sec: 176.87 - lr: 0.100000 |
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2022-11-06 15:59:29,944 epoch 17 - iter 162/274 - loss 0.02935913 - samples/sec: 164.85 - lr: 0.100000 |
|
2022-11-06 15:59:36,013 epoch 17 - iter 189/274 - loss 0.02972123 - samples/sec: 142.44 - lr: 0.100000 |
|
2022-11-06 15:59:41,656 epoch 17 - iter 216/274 - loss 0.03001223 - samples/sec: 153.18 - lr: 0.100000 |
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2022-11-06 15:59:47,171 epoch 17 - iter 243/274 - loss 0.03092766 - samples/sec: 156.77 - lr: 0.100000 |
|
2022-11-06 15:59:51,999 epoch 17 - iter 270/274 - loss 0.03096630 - samples/sec: 179.07 - lr: 0.100000 |
|
2022-11-06 15:59:52,810 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 15:59:52,810 EPOCH 17 done: loss 0.0310 - lr 0.100000 |
|
2022-11-06 16:00:23,255 Evaluating as a multi-label problem: False |
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2022-11-06 16:00:23,282 TEST : loss 0.02839544788002968 - f1-score (micro avg) 0.8291 |
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2022-11-06 16:00:23,765 BAD EPOCHS (no improvement): 1 |
|
2022-11-06 16:00:23,949 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 16:00:29,276 epoch 18 - iter 27/274 - loss 0.02786044 - samples/sec: 162.35 - lr: 0.100000 |
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2022-11-06 16:00:34,738 epoch 18 - iter 54/274 - loss 0.02984826 - samples/sec: 158.27 - lr: 0.100000 |
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2022-11-06 16:00:40,413 epoch 18 - iter 81/274 - loss 0.03107334 - samples/sec: 152.36 - lr: 0.100000 |
|
2022-11-06 16:00:45,475 epoch 18 - iter 108/274 - loss 0.03069842 - samples/sec: 170.79 - lr: 0.100000 |
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2022-11-06 16:00:50,876 epoch 18 - iter 135/274 - loss 0.03029660 - samples/sec: 160.07 - lr: 0.100000 |
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2022-11-06 16:00:56,514 epoch 18 - iter 162/274 - loss 0.03065821 - samples/sec: 153.32 - lr: 0.100000 |
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2022-11-06 16:01:01,402 epoch 18 - iter 189/274 - loss 0.03009030 - samples/sec: 176.90 - lr: 0.100000 |
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2022-11-06 16:01:07,110 epoch 18 - iter 216/274 - loss 0.02976895 - samples/sec: 151.44 - lr: 0.100000 |
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2022-11-06 16:01:12,653 epoch 18 - iter 243/274 - loss 0.02988190 - samples/sec: 155.98 - lr: 0.100000 |
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2022-11-06 16:01:17,932 epoch 18 - iter 270/274 - loss 0.02970089 - samples/sec: 163.78 - lr: 0.100000 |
|
2022-11-06 16:01:18,664 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:01:18,664 EPOCH 18 done: loss 0.0297 - lr 0.100000 |
|
2022-11-06 16:01:49,013 Evaluating as a multi-label problem: False |
|
2022-11-06 16:01:49,041 TEST : loss 0.030549418181180954 - f1-score (micro avg) 0.8375 |
|
2022-11-06 16:01:49,528 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 16:01:49,714 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 16:01:55,141 epoch 19 - iter 27/274 - loss 0.02873273 - samples/sec: 159.36 - lr: 0.100000 |
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2022-11-06 16:02:00,197 epoch 19 - iter 54/274 - loss 0.02947910 - samples/sec: 170.99 - lr: 0.100000 |
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2022-11-06 16:02:05,455 epoch 19 - iter 81/274 - loss 0.02898074 - samples/sec: 164.44 - lr: 0.100000 |
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2022-11-06 16:02:10,768 epoch 19 - iter 108/274 - loss 0.02951392 - samples/sec: 162.72 - lr: 0.100000 |
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2022-11-06 16:02:16,303 epoch 19 - iter 135/274 - loss 0.02908179 - samples/sec: 156.17 - lr: 0.100000 |
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2022-11-06 16:02:21,861 epoch 19 - iter 162/274 - loss 0.03001166 - samples/sec: 155.57 - lr: 0.100000 |
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2022-11-06 16:02:27,097 epoch 19 - iter 189/274 - loss 0.03008322 - samples/sec: 165.10 - lr: 0.100000 |
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2022-11-06 16:02:32,689 epoch 19 - iter 216/274 - loss 0.02972503 - samples/sec: 155.74 - lr: 0.100000 |
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2022-11-06 16:02:37,773 epoch 19 - iter 243/274 - loss 0.02936500 - samples/sec: 170.05 - lr: 0.100000 |
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2022-11-06 16:02:43,311 epoch 19 - iter 270/274 - loss 0.02962141 - samples/sec: 156.12 - lr: 0.100000 |
|
2022-11-06 16:02:43,938 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:02:43,938 EPOCH 19 done: loss 0.0296 - lr 0.100000 |
|
2022-11-06 16:03:14,269 Evaluating as a multi-label problem: False |
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2022-11-06 16:03:14,296 TEST : loss 0.03505885228514671 - f1-score (micro avg) 0.84 |
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2022-11-06 16:03:14,779 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 16:03:14,968 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:03:20,351 epoch 20 - iter 27/274 - loss 0.02962538 - samples/sec: 160.69 - lr: 0.100000 |
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2022-11-06 16:03:25,402 epoch 20 - iter 54/274 - loss 0.02685869 - samples/sec: 171.14 - lr: 0.100000 |
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2022-11-06 16:03:30,651 epoch 20 - iter 81/274 - loss 0.02668449 - samples/sec: 164.70 - lr: 0.100000 |
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2022-11-06 16:03:35,772 epoch 20 - iter 108/274 - loss 0.02692230 - samples/sec: 168.85 - lr: 0.100000 |
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2022-11-06 16:03:41,388 epoch 20 - iter 135/274 - loss 0.02744559 - samples/sec: 153.95 - lr: 0.100000 |
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2022-11-06 16:03:46,869 epoch 20 - iter 162/274 - loss 0.02710428 - samples/sec: 157.71 - lr: 0.100000 |
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2022-11-06 16:03:52,351 epoch 20 - iter 189/274 - loss 0.02715944 - samples/sec: 157.72 - lr: 0.100000 |
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2022-11-06 16:03:58,071 epoch 20 - iter 216/274 - loss 0.02762260 - samples/sec: 151.15 - lr: 0.100000 |
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2022-11-06 16:04:03,492 epoch 20 - iter 243/274 - loss 0.02843548 - samples/sec: 160.67 - lr: 0.100000 |
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2022-11-06 16:04:08,863 epoch 20 - iter 270/274 - loss 0.02849893 - samples/sec: 160.97 - lr: 0.100000 |
|
2022-11-06 16:04:09,539 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:04:09,539 EPOCH 20 done: loss 0.0286 - lr 0.100000 |
|
2022-11-06 16:04:39,930 Evaluating as a multi-label problem: False |
|
2022-11-06 16:04:39,958 TEST : loss 0.02962632104754448 - f1-score (micro avg) 0.8401 |
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2022-11-06 16:04:40,440 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 16:04:40,633 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 16:04:45,749 epoch 21 - iter 27/274 - loss 0.02760793 - samples/sec: 169.06 - lr: 0.100000 |
|
2022-11-06 16:04:51,087 epoch 21 - iter 54/274 - loss 0.02517772 - samples/sec: 161.96 - lr: 0.100000 |
|
2022-11-06 16:04:56,345 epoch 21 - iter 81/274 - loss 0.02711348 - samples/sec: 164.41 - lr: 0.100000 |
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2022-11-06 16:05:01,625 epoch 21 - iter 108/274 - loss 0.02741965 - samples/sec: 163.76 - lr: 0.100000 |
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2022-11-06 16:05:07,537 epoch 21 - iter 135/274 - loss 0.02841392 - samples/sec: 146.21 - lr: 0.100000 |
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2022-11-06 16:05:12,979 epoch 21 - iter 162/274 - loss 0.02717816 - samples/sec: 158.89 - lr: 0.100000 |
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2022-11-06 16:05:18,571 epoch 21 - iter 189/274 - loss 0.02757418 - samples/sec: 154.59 - lr: 0.100000 |
|
2022-11-06 16:05:24,056 epoch 21 - iter 216/274 - loss 0.02785333 - samples/sec: 157.63 - lr: 0.100000 |
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2022-11-06 16:05:29,595 epoch 21 - iter 243/274 - loss 0.02798193 - samples/sec: 156.08 - lr: 0.100000 |
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2022-11-06 16:05:35,075 epoch 21 - iter 270/274 - loss 0.02778040 - samples/sec: 157.74 - lr: 0.100000 |
|
2022-11-06 16:05:35,751 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:05:35,751 EPOCH 21 done: loss 0.0278 - lr 0.100000 |
|
2022-11-06 16:06:06,094 Evaluating as a multi-label problem: False |
|
2022-11-06 16:06:06,121 TEST : loss 0.032616037875413895 - f1-score (micro avg) 0.8422 |
|
2022-11-06 16:06:06,606 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 16:06:06,785 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 16:06:11,983 epoch 22 - iter 27/274 - loss 0.02348395 - samples/sec: 166.39 - lr: 0.100000 |
|
2022-11-06 16:06:17,782 epoch 22 - iter 54/274 - loss 0.02570963 - samples/sec: 149.07 - lr: 0.100000 |
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2022-11-06 16:06:23,174 epoch 22 - iter 81/274 - loss 0.02606028 - samples/sec: 160.35 - lr: 0.100000 |
|
2022-11-06 16:06:28,843 epoch 22 - iter 108/274 - loss 0.02604390 - samples/sec: 152.49 - lr: 0.100000 |
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2022-11-06 16:06:33,986 epoch 22 - iter 135/274 - loss 0.02645342 - samples/sec: 168.12 - lr: 0.100000 |
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2022-11-06 16:06:39,037 epoch 22 - iter 162/274 - loss 0.02700181 - samples/sec: 171.17 - lr: 0.100000 |
|
2022-11-06 16:06:44,320 epoch 22 - iter 189/274 - loss 0.02693238 - samples/sec: 163.65 - lr: 0.100000 |
|
2022-11-06 16:06:49,975 epoch 22 - iter 216/274 - loss 0.02745026 - samples/sec: 152.87 - lr: 0.100000 |
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2022-11-06 16:06:54,869 epoch 22 - iter 243/274 - loss 0.02713177 - samples/sec: 176.68 - lr: 0.100000 |
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2022-11-06 16:07:00,493 epoch 22 - iter 270/274 - loss 0.02742091 - samples/sec: 153.72 - lr: 0.100000 |
|
2022-11-06 16:07:01,167 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:07:01,168 EPOCH 22 done: loss 0.0274 - lr 0.100000 |
|
2022-11-06 16:07:31,511 Evaluating as a multi-label problem: False |
|
2022-11-06 16:07:31,539 TEST : loss 0.03170188143849373 - f1-score (micro avg) 0.8358 |
|
2022-11-06 16:07:32,024 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 16:07:32,209 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 16:07:37,438 epoch 23 - iter 27/274 - loss 0.02737619 - samples/sec: 165.38 - lr: 0.100000 |
|
2022-11-06 16:07:42,521 epoch 23 - iter 54/274 - loss 0.02546520 - samples/sec: 170.09 - lr: 0.100000 |
|
2022-11-06 16:07:47,780 epoch 23 - iter 81/274 - loss 0.02592985 - samples/sec: 164.38 - lr: 0.100000 |
|
2022-11-06 16:07:53,516 epoch 23 - iter 108/274 - loss 0.02616454 - samples/sec: 150.72 - lr: 0.100000 |
|
2022-11-06 16:07:58,556 epoch 23 - iter 135/274 - loss 0.02647822 - samples/sec: 171.55 - lr: 0.100000 |
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2022-11-06 16:08:03,962 epoch 23 - iter 162/274 - loss 0.02696597 - samples/sec: 159.92 - lr: 0.100000 |
|
2022-11-06 16:08:09,188 epoch 23 - iter 189/274 - loss 0.02704517 - samples/sec: 165.45 - lr: 0.100000 |
|
2022-11-06 16:08:14,403 epoch 23 - iter 216/274 - loss 0.02719587 - samples/sec: 165.77 - lr: 0.100000 |
|
2022-11-06 16:08:19,853 epoch 23 - iter 243/274 - loss 0.02732251 - samples/sec: 158.62 - lr: 0.100000 |
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2022-11-06 16:08:25,502 epoch 23 - iter 270/274 - loss 0.02735923 - samples/sec: 153.05 - lr: 0.100000 |
|
2022-11-06 16:08:26,350 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 16:08:26,350 EPOCH 23 done: loss 0.0273 - lr 0.100000 |
|
2022-11-06 16:08:56,778 Evaluating as a multi-label problem: False |
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2022-11-06 16:08:56,805 TEST : loss 0.03235173597931862 - f1-score (micro avg) 0.8389 |
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2022-11-06 16:08:57,287 BAD EPOCHS (no improvement): 0 |
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2022-11-06 16:08:57,481 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:09:02,713 epoch 24 - iter 27/274 - loss 0.02432970 - samples/sec: 165.31 - lr: 0.100000 |
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2022-11-06 16:09:08,242 epoch 24 - iter 54/274 - loss 0.02792046 - samples/sec: 156.36 - lr: 0.100000 |
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2022-11-06 16:09:13,866 epoch 24 - iter 81/274 - loss 0.02735755 - samples/sec: 153.73 - lr: 0.100000 |
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2022-11-06 16:09:19,107 epoch 24 - iter 108/274 - loss 0.02678236 - samples/sec: 164.96 - lr: 0.100000 |
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2022-11-06 16:09:24,380 epoch 24 - iter 135/274 - loss 0.02670707 - samples/sec: 163.94 - lr: 0.100000 |
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2022-11-06 16:09:30,542 epoch 24 - iter 162/274 - loss 0.02735696 - samples/sec: 140.30 - lr: 0.100000 |
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2022-11-06 16:09:35,944 epoch 24 - iter 189/274 - loss 0.02679295 - samples/sec: 160.05 - lr: 0.100000 |
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2022-11-06 16:09:40,852 epoch 24 - iter 216/274 - loss 0.02707606 - samples/sec: 176.16 - lr: 0.100000 |
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2022-11-06 16:09:45,899 epoch 24 - iter 243/274 - loss 0.02703989 - samples/sec: 171.30 - lr: 0.100000 |
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2022-11-06 16:09:51,182 epoch 24 - iter 270/274 - loss 0.02694537 - samples/sec: 163.66 - lr: 0.100000 |
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2022-11-06 16:09:51,974 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:09:51,974 EPOCH 24 done: loss 0.0269 - lr 0.100000 |
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2022-11-06 16:10:22,421 Evaluating as a multi-label problem: False |
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2022-11-06 16:10:22,448 TEST : loss 0.0330146886408329 - f1-score (micro avg) 0.841 |
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2022-11-06 16:10:22,932 BAD EPOCHS (no improvement): 0 |
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2022-11-06 16:10:23,127 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:10:28,414 epoch 25 - iter 27/274 - loss 0.03143444 - samples/sec: 163.58 - lr: 0.100000 |
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2022-11-06 16:10:33,845 epoch 25 - iter 54/274 - loss 0.02960131 - samples/sec: 159.18 - lr: 0.100000 |
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2022-11-06 16:10:39,062 epoch 25 - iter 81/274 - loss 0.02876453 - samples/sec: 165.73 - lr: 0.100000 |
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2022-11-06 16:10:44,359 epoch 25 - iter 108/274 - loss 0.02731169 - samples/sec: 163.20 - lr: 0.100000 |
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2022-11-06 16:10:49,592 epoch 25 - iter 135/274 - loss 0.02709646 - samples/sec: 165.22 - lr: 0.100000 |
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2022-11-06 16:10:54,874 epoch 25 - iter 162/274 - loss 0.02677724 - samples/sec: 163.68 - lr: 0.100000 |
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2022-11-06 16:10:59,781 epoch 25 - iter 189/274 - loss 0.02627221 - samples/sec: 176.20 - lr: 0.100000 |
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2022-11-06 16:11:05,136 epoch 25 - iter 216/274 - loss 0.02594192 - samples/sec: 161.45 - lr: 0.100000 |
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2022-11-06 16:11:10,831 epoch 25 - iter 243/274 - loss 0.02612075 - samples/sec: 151.81 - lr: 0.100000 |
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2022-11-06 16:11:16,587 epoch 25 - iter 270/274 - loss 0.02641718 - samples/sec: 150.18 - lr: 0.100000 |
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2022-11-06 16:11:17,269 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:11:17,269 EPOCH 25 done: loss 0.0264 - lr 0.100000 |
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2022-11-06 16:11:47,713 Evaluating as a multi-label problem: False |
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2022-11-06 16:11:47,741 TEST : loss 0.0296016838401556 - f1-score (micro avg) 0.8411 |
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2022-11-06 16:11:48,227 BAD EPOCHS (no improvement): 0 |
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2022-11-06 16:11:48,410 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:11:53,927 epoch 26 - iter 27/274 - loss 0.02822455 - samples/sec: 156.76 - lr: 0.100000 |
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2022-11-06 16:11:59,175 epoch 26 - iter 54/274 - loss 0.02869778 - samples/sec: 164.74 - lr: 0.100000 |
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2022-11-06 16:12:04,826 epoch 26 - iter 81/274 - loss 0.02800272 - samples/sec: 152.97 - lr: 0.100000 |
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2022-11-06 16:12:09,951 epoch 26 - iter 108/274 - loss 0.02770767 - samples/sec: 168.70 - lr: 0.100000 |
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2022-11-06 16:12:15,275 epoch 26 - iter 135/274 - loss 0.02730618 - samples/sec: 162.39 - lr: 0.100000 |
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2022-11-06 16:12:21,123 epoch 26 - iter 162/274 - loss 0.02748631 - samples/sec: 147.84 - lr: 0.100000 |
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2022-11-06 16:12:26,412 epoch 26 - iter 189/274 - loss 0.02710793 - samples/sec: 163.46 - lr: 0.100000 |
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2022-11-06 16:12:31,563 epoch 26 - iter 216/274 - loss 0.02712051 - samples/sec: 167.82 - lr: 0.100000 |
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2022-11-06 16:12:36,534 epoch 26 - iter 243/274 - loss 0.02691565 - samples/sec: 173.93 - lr: 0.100000 |
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2022-11-06 16:12:41,548 epoch 26 - iter 270/274 - loss 0.02638533 - samples/sec: 172.43 - lr: 0.100000 |
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2022-11-06 16:12:42,524 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:12:42,524 EPOCH 26 done: loss 0.0264 - lr 0.100000 |
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2022-11-06 16:13:13,116 Evaluating as a multi-label problem: False |
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2022-11-06 16:13:13,143 TEST : loss 0.028864704072475433 - f1-score (micro avg) 0.8374 |
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2022-11-06 16:13:13,626 BAD EPOCHS (no improvement): 1 |
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2022-11-06 16:13:13,808 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:13:19,376 epoch 27 - iter 27/274 - loss 0.02871045 - samples/sec: 155.32 - lr: 0.100000 |
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2022-11-06 16:13:25,192 epoch 27 - iter 54/274 - loss 0.02570850 - samples/sec: 148.63 - lr: 0.100000 |
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2022-11-06 16:13:30,457 epoch 27 - iter 81/274 - loss 0.02582387 - samples/sec: 164.22 - lr: 0.100000 |
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2022-11-06 16:13:35,757 epoch 27 - iter 108/274 - loss 0.02624385 - samples/sec: 163.14 - lr: 0.100000 |
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2022-11-06 16:13:41,010 epoch 27 - iter 135/274 - loss 0.02620915 - samples/sec: 164.56 - lr: 0.100000 |
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2022-11-06 16:13:46,095 epoch 27 - iter 162/274 - loss 0.02561898 - samples/sec: 171.45 - lr: 0.100000 |
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2022-11-06 16:13:51,235 epoch 27 - iter 189/274 - loss 0.02553513 - samples/sec: 168.20 - lr: 0.100000 |
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2022-11-06 16:13:56,802 epoch 27 - iter 216/274 - loss 0.02540689 - samples/sec: 155.31 - lr: 0.100000 |
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2022-11-06 16:14:01,960 epoch 27 - iter 243/274 - loss 0.02539935 - samples/sec: 167.61 - lr: 0.100000 |
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2022-11-06 16:14:07,509 epoch 27 - iter 270/274 - loss 0.02613303 - samples/sec: 155.80 - lr: 0.100000 |
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2022-11-06 16:14:08,381 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:14:08,381 EPOCH 27 done: loss 0.0262 - lr 0.100000 |
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2022-11-06 16:14:38,823 Evaluating as a multi-label problem: False |
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2022-11-06 16:14:38,850 TEST : loss 0.029708683490753174 - f1-score (micro avg) 0.8496 |
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2022-11-06 16:14:39,335 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 16:14:39,527 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:14:45,257 epoch 28 - iter 27/274 - loss 0.03049054 - samples/sec: 150.90 - lr: 0.100000 |
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2022-11-06 16:14:51,304 epoch 28 - iter 54/274 - loss 0.02789797 - samples/sec: 142.98 - lr: 0.100000 |
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2022-11-06 16:14:56,667 epoch 28 - iter 81/274 - loss 0.02590343 - samples/sec: 161.18 - lr: 0.100000 |
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2022-11-06 16:15:01,580 epoch 28 - iter 108/274 - loss 0.02504768 - samples/sec: 176.01 - lr: 0.100000 |
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2022-11-06 16:15:06,612 epoch 28 - iter 135/274 - loss 0.02529742 - samples/sec: 171.82 - lr: 0.100000 |
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2022-11-06 16:15:11,948 epoch 28 - iter 162/274 - loss 0.02524847 - samples/sec: 162.01 - lr: 0.100000 |
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2022-11-06 16:15:16,760 epoch 28 - iter 189/274 - loss 0.02511018 - samples/sec: 179.68 - lr: 0.100000 |
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2022-11-06 16:15:22,086 epoch 28 - iter 216/274 - loss 0.02487931 - samples/sec: 162.32 - lr: 0.100000 |
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2022-11-06 16:15:27,321 epoch 28 - iter 243/274 - loss 0.02471569 - samples/sec: 165.16 - lr: 0.100000 |
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2022-11-06 16:15:32,766 epoch 28 - iter 270/274 - loss 0.02483899 - samples/sec: 158.76 - lr: 0.100000 |
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2022-11-06 16:15:33,875 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:15:33,876 EPOCH 28 done: loss 0.0247 - lr 0.100000 |
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2022-11-06 16:16:04,301 Evaluating as a multi-label problem: False |
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2022-11-06 16:16:04,329 TEST : loss 0.03210555389523506 - f1-score (micro avg) 0.848 |
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2022-11-06 16:16:04,815 BAD EPOCHS (no improvement): 0 |
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2022-11-06 16:16:05,006 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:16:10,135 epoch 29 - iter 27/274 - loss 0.02344207 - samples/sec: 168.62 - lr: 0.100000 |
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2022-11-06 16:16:15,701 epoch 29 - iter 54/274 - loss 0.02457921 - samples/sec: 155.32 - lr: 0.100000 |
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2022-11-06 16:16:21,003 epoch 29 - iter 81/274 - loss 0.02480935 - samples/sec: 163.06 - lr: 0.100000 |
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2022-11-06 16:16:26,616 epoch 29 - iter 108/274 - loss 0.02606039 - samples/sec: 154.02 - lr: 0.100000 |
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2022-11-06 16:16:32,037 epoch 29 - iter 135/274 - loss 0.02570571 - samples/sec: 159.47 - lr: 0.100000 |
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2022-11-06 16:16:37,259 epoch 29 - iter 162/274 - loss 0.02557387 - samples/sec: 165.59 - lr: 0.100000 |
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2022-11-06 16:16:42,348 epoch 29 - iter 189/274 - loss 0.02549342 - samples/sec: 169.88 - lr: 0.100000 |
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2022-11-06 16:16:47,841 epoch 29 - iter 216/274 - loss 0.02527776 - samples/sec: 157.37 - lr: 0.100000 |
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2022-11-06 16:16:53,236 epoch 29 - iter 243/274 - loss 0.02552941 - samples/sec: 160.27 - lr: 0.100000 |
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2022-11-06 16:16:58,471 epoch 29 - iter 270/274 - loss 0.02558363 - samples/sec: 165.12 - lr: 0.100000 |
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2022-11-06 16:16:59,254 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:16:59,254 EPOCH 29 done: loss 0.0257 - lr 0.100000 |
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2022-11-06 16:17:29,686 Evaluating as a multi-label problem: False |
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2022-11-06 16:17:29,713 TEST : loss 0.028371913358569145 - f1-score (micro avg) 0.8469 |
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2022-11-06 16:17:30,197 BAD EPOCHS (no improvement): 1 |
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2022-11-06 16:17:30,379 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:17:35,368 epoch 30 - iter 27/274 - loss 0.02798108 - samples/sec: 173.33 - lr: 0.100000 |
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2022-11-06 16:17:40,343 epoch 30 - iter 54/274 - loss 0.02660047 - samples/sec: 173.81 - lr: 0.100000 |
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2022-11-06 16:17:45,469 epoch 30 - iter 81/274 - loss 0.02438145 - samples/sec: 168.67 - lr: 0.100000 |
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2022-11-06 16:17:50,759 epoch 30 - iter 108/274 - loss 0.02433871 - samples/sec: 163.42 - lr: 0.100000 |
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2022-11-06 16:17:56,049 epoch 30 - iter 135/274 - loss 0.02432981 - samples/sec: 163.44 - lr: 0.100000 |
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2022-11-06 16:18:02,002 epoch 30 - iter 162/274 - loss 0.02419547 - samples/sec: 145.21 - lr: 0.100000 |
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2022-11-06 16:18:07,393 epoch 30 - iter 189/274 - loss 0.02387651 - samples/sec: 160.38 - lr: 0.100000 |
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2022-11-06 16:18:12,260 epoch 30 - iter 216/274 - loss 0.02432185 - samples/sec: 177.65 - lr: 0.100000 |
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2022-11-06 16:18:18,008 epoch 30 - iter 243/274 - loss 0.02463235 - samples/sec: 150.40 - lr: 0.100000 |
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2022-11-06 16:18:23,789 epoch 30 - iter 270/274 - loss 0.02438101 - samples/sec: 149.54 - lr: 0.100000 |
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2022-11-06 16:18:24,620 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:18:24,620 EPOCH 30 done: loss 0.0248 - lr 0.100000 |
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2022-11-06 16:18:55,060 Evaluating as a multi-label problem: False |
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2022-11-06 16:18:55,088 TEST : loss 0.028511736541986465 - f1-score (micro avg) 0.8269 |
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2022-11-06 16:18:55,573 BAD EPOCHS (no improvement): 2 |
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2022-11-06 16:18:55,766 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:19:01,221 epoch 31 - iter 27/274 - loss 0.02101312 - samples/sec: 158.51 - lr: 0.100000 |
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2022-11-06 16:19:06,255 epoch 31 - iter 54/274 - loss 0.02296639 - samples/sec: 171.74 - lr: 0.100000 |
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2022-11-06 16:19:11,132 epoch 31 - iter 81/274 - loss 0.02361620 - samples/sec: 178.86 - lr: 0.100000 |
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2022-11-06 16:19:16,458 epoch 31 - iter 108/274 - loss 0.02492664 - samples/sec: 162.31 - lr: 0.100000 |
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2022-11-06 16:19:21,436 epoch 31 - iter 135/274 - loss 0.02420548 - samples/sec: 173.68 - lr: 0.100000 |
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2022-11-06 16:19:27,143 epoch 31 - iter 162/274 - loss 0.02463334 - samples/sec: 151.48 - lr: 0.100000 |
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2022-11-06 16:19:32,770 epoch 31 - iter 189/274 - loss 0.02415614 - samples/sec: 153.64 - lr: 0.100000 |
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2022-11-06 16:19:37,899 epoch 31 - iter 216/274 - loss 0.02407295 - samples/sec: 168.59 - lr: 0.100000 |
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2022-11-06 16:19:43,687 epoch 31 - iter 243/274 - loss 0.02377883 - samples/sec: 149.37 - lr: 0.100000 |
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2022-11-06 16:19:49,205 epoch 31 - iter 270/274 - loss 0.02411380 - samples/sec: 156.66 - lr: 0.100000 |
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2022-11-06 16:19:50,132 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:19:50,132 EPOCH 31 done: loss 0.0240 - lr 0.100000 |
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2022-11-06 16:20:20,654 Evaluating as a multi-label problem: False |
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2022-11-06 16:20:20,681 TEST : loss 0.030574096366763115 - f1-score (micro avg) 0.8447 |
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2022-11-06 16:20:21,163 BAD EPOCHS (no improvement): 0 |
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2022-11-06 16:20:21,355 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:20:26,757 epoch 32 - iter 27/274 - loss 0.02781246 - samples/sec: 160.09 - lr: 0.100000 |
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2022-11-06 16:20:32,255 epoch 32 - iter 54/274 - loss 0.02479696 - samples/sec: 157.22 - lr: 0.100000 |
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2022-11-06 16:20:37,336 epoch 32 - iter 81/274 - loss 0.02563759 - samples/sec: 170.17 - lr: 0.100000 |
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2022-11-06 16:20:42,605 epoch 32 - iter 108/274 - loss 0.02410592 - samples/sec: 164.07 - lr: 0.100000 |
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2022-11-06 16:20:48,671 epoch 32 - iter 135/274 - loss 0.02451412 - samples/sec: 142.53 - lr: 0.100000 |
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2022-11-06 16:20:54,061 epoch 32 - iter 162/274 - loss 0.02434660 - samples/sec: 160.39 - lr: 0.100000 |
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2022-11-06 16:20:58,858 epoch 32 - iter 189/274 - loss 0.02391541 - samples/sec: 180.23 - lr: 0.100000 |
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2022-11-06 16:21:04,444 epoch 32 - iter 216/274 - loss 0.02379934 - samples/sec: 154.77 - lr: 0.100000 |
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2022-11-06 16:21:09,872 epoch 32 - iter 243/274 - loss 0.02422990 - samples/sec: 159.29 - lr: 0.100000 |
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2022-11-06 16:21:15,080 epoch 32 - iter 270/274 - loss 0.02457500 - samples/sec: 166.00 - lr: 0.100000 |
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2022-11-06 16:21:15,978 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:21:15,979 EPOCH 32 done: loss 0.0248 - lr 0.100000 |
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2022-11-06 16:21:46,530 Evaluating as a multi-label problem: False |
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2022-11-06 16:21:46,557 TEST : loss 0.02866635099053383 - f1-score (micro avg) 0.8431 |
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2022-11-06 16:21:47,042 BAD EPOCHS (no improvement): 1 |
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2022-11-06 16:21:47,236 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:21:52,636 epoch 33 - iter 27/274 - loss 0.02865260 - samples/sec: 160.17 - lr: 0.100000 |
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2022-11-06 16:21:57,938 epoch 33 - iter 54/274 - loss 0.02666235 - samples/sec: 163.09 - lr: 0.100000 |
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2022-11-06 16:22:03,475 epoch 33 - iter 81/274 - loss 0.02474081 - samples/sec: 156.14 - lr: 0.100000 |
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2022-11-06 16:22:09,037 epoch 33 - iter 108/274 - loss 0.02515547 - samples/sec: 155.48 - lr: 0.100000 |
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2022-11-06 16:22:14,965 epoch 33 - iter 135/274 - loss 0.02530611 - samples/sec: 145.85 - lr: 0.100000 |
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2022-11-06 16:22:21,040 epoch 33 - iter 162/274 - loss 0.02492838 - samples/sec: 142.32 - lr: 0.100000 |
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2022-11-06 16:22:26,273 epoch 33 - iter 189/274 - loss 0.02452032 - samples/sec: 165.22 - lr: 0.100000 |
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2022-11-06 16:22:32,240 epoch 33 - iter 216/274 - loss 0.02491611 - samples/sec: 144.92 - lr: 0.100000 |
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2022-11-06 16:22:37,797 epoch 33 - iter 243/274 - loss 0.02479517 - samples/sec: 155.59 - lr: 0.100000 |
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2022-11-06 16:22:43,864 epoch 33 - iter 270/274 - loss 0.02472361 - samples/sec: 142.52 - lr: 0.100000 |
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2022-11-06 16:22:44,814 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:22:44,815 EPOCH 33 done: loss 0.0250 - lr 0.100000 |
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2022-11-06 16:23:16,371 Evaluating as a multi-label problem: False |
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2022-11-06 16:23:16,398 TEST : loss 0.028993723914027214 - f1-score (micro avg) 0.8459 |
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2022-11-06 16:23:16,883 BAD EPOCHS (no improvement): 2 |
|
2022-11-06 16:23:17,077 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:23:22,429 epoch 34 - iter 27/274 - loss 0.02239182 - samples/sec: 161.60 - lr: 0.100000 |
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2022-11-06 16:23:27,911 epoch 34 - iter 54/274 - loss 0.02416868 - samples/sec: 157.72 - lr: 0.100000 |
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2022-11-06 16:23:33,550 epoch 34 - iter 81/274 - loss 0.02374628 - samples/sec: 153.33 - lr: 0.100000 |
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2022-11-06 16:23:39,368 epoch 34 - iter 108/274 - loss 0.02380439 - samples/sec: 148.61 - lr: 0.100000 |
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2022-11-06 16:23:44,675 epoch 34 - iter 135/274 - loss 0.02360065 - samples/sec: 162.95 - lr: 0.100000 |
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2022-11-06 16:23:50,060 epoch 34 - iter 162/274 - loss 0.02354964 - samples/sec: 160.55 - lr: 0.100000 |
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2022-11-06 16:23:55,281 epoch 34 - iter 189/274 - loss 0.02309751 - samples/sec: 165.63 - lr: 0.100000 |
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2022-11-06 16:24:00,798 epoch 34 - iter 216/274 - loss 0.02310163 - samples/sec: 156.73 - lr: 0.100000 |
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2022-11-06 16:24:06,119 epoch 34 - iter 243/274 - loss 0.02324512 - samples/sec: 162.51 - lr: 0.100000 |
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2022-11-06 16:24:11,666 epoch 34 - iter 270/274 - loss 0.02329042 - samples/sec: 155.87 - lr: 0.100000 |
|
2022-11-06 16:24:12,463 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:24:12,464 EPOCH 34 done: loss 0.0235 - lr 0.100000 |
|
2022-11-06 16:24:43,280 Evaluating as a multi-label problem: False |
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2022-11-06 16:24:43,308 TEST : loss 0.028596550226211548 - f1-score (micro avg) 0.8429 |
|
2022-11-06 16:24:43,793 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 16:24:43,981 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 16:24:49,391 epoch 35 - iter 27/274 - loss 0.02168843 - samples/sec: 159.87 - lr: 0.100000 |
|
2022-11-06 16:24:55,208 epoch 35 - iter 54/274 - loss 0.02108781 - samples/sec: 148.63 - lr: 0.100000 |
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2022-11-06 16:25:00,440 epoch 35 - iter 81/274 - loss 0.02301830 - samples/sec: 165.27 - lr: 0.100000 |
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2022-11-06 16:25:06,407 epoch 35 - iter 108/274 - loss 0.02317393 - samples/sec: 144.91 - lr: 0.100000 |
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2022-11-06 16:25:11,868 epoch 35 - iter 135/274 - loss 0.02416664 - samples/sec: 158.31 - lr: 0.100000 |
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2022-11-06 16:25:16,789 epoch 35 - iter 162/274 - loss 0.02368299 - samples/sec: 175.73 - lr: 0.100000 |
|
2022-11-06 16:25:22,259 epoch 35 - iter 189/274 - loss 0.02379600 - samples/sec: 158.07 - lr: 0.100000 |
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2022-11-06 16:25:27,827 epoch 35 - iter 216/274 - loss 0.02345872 - samples/sec: 155.27 - lr: 0.100000 |
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2022-11-06 16:25:33,194 epoch 35 - iter 243/274 - loss 0.02373931 - samples/sec: 161.10 - lr: 0.100000 |
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2022-11-06 16:25:38,490 epoch 35 - iter 270/274 - loss 0.02434243 - samples/sec: 163.28 - lr: 0.100000 |
|
2022-11-06 16:25:39,144 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:25:39,144 EPOCH 35 done: loss 0.0242 - lr 0.100000 |
|
2022-11-06 16:26:10,068 Evaluating as a multi-label problem: False |
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2022-11-06 16:26:10,099 TEST : loss 0.033472731709480286 - f1-score (micro avg) 0.8457 |
|
2022-11-06 16:26:10,582 BAD EPOCHS (no improvement): 1 |
|
2022-11-06 16:26:10,785 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:26:17,497 epoch 36 - iter 27/274 - loss 0.02364353 - samples/sec: 128.83 - lr: 0.100000 |
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2022-11-06 16:26:23,183 epoch 36 - iter 54/274 - loss 0.02153287 - samples/sec: 152.09 - lr: 0.100000 |
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2022-11-06 16:26:28,475 epoch 36 - iter 81/274 - loss 0.02326202 - samples/sec: 163.39 - lr: 0.100000 |
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2022-11-06 16:26:33,844 epoch 36 - iter 108/274 - loss 0.02316080 - samples/sec: 161.06 - lr: 0.100000 |
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2022-11-06 16:26:39,100 epoch 36 - iter 135/274 - loss 0.02335356 - samples/sec: 164.49 - lr: 0.100000 |
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2022-11-06 16:26:44,131 epoch 36 - iter 162/274 - loss 0.02357097 - samples/sec: 171.82 - lr: 0.100000 |
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2022-11-06 16:26:50,011 epoch 36 - iter 189/274 - loss 0.02410531 - samples/sec: 147.65 - lr: 0.100000 |
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2022-11-06 16:26:55,418 epoch 36 - iter 216/274 - loss 0.02407270 - samples/sec: 159.89 - lr: 0.100000 |
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2022-11-06 16:27:00,688 epoch 36 - iter 243/274 - loss 0.02426518 - samples/sec: 164.12 - lr: 0.100000 |
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2022-11-06 16:27:06,326 epoch 36 - iter 270/274 - loss 0.02403961 - samples/sec: 153.35 - lr: 0.100000 |
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2022-11-06 16:27:06,963 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:27:06,964 EPOCH 36 done: loss 0.0240 - lr 0.100000 |
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2022-11-06 16:27:37,405 Evaluating as a multi-label problem: False |
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2022-11-06 16:27:37,432 TEST : loss 0.030064314603805542 - f1-score (micro avg) 0.8549 |
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2022-11-06 16:27:37,915 BAD EPOCHS (no improvement): 2 |
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2022-11-06 16:27:38,110 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:27:44,203 epoch 37 - iter 27/274 - loss 0.02699987 - samples/sec: 141.91 - lr: 0.100000 |
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2022-11-06 16:27:49,075 epoch 37 - iter 54/274 - loss 0.02321800 - samples/sec: 177.49 - lr: 0.100000 |
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2022-11-06 16:27:54,663 epoch 37 - iter 81/274 - loss 0.02509846 - samples/sec: 154.71 - lr: 0.100000 |
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2022-11-06 16:27:59,879 epoch 37 - iter 108/274 - loss 0.02406442 - samples/sec: 165.73 - lr: 0.100000 |
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2022-11-06 16:28:05,077 epoch 37 - iter 135/274 - loss 0.02368305 - samples/sec: 166.33 - lr: 0.100000 |
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2022-11-06 16:28:10,924 epoch 37 - iter 162/274 - loss 0.02370177 - samples/sec: 147.86 - lr: 0.100000 |
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2022-11-06 16:28:16,328 epoch 37 - iter 189/274 - loss 0.02334651 - samples/sec: 159.99 - lr: 0.100000 |
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2022-11-06 16:28:21,887 epoch 37 - iter 216/274 - loss 0.02355185 - samples/sec: 155.51 - lr: 0.100000 |
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2022-11-06 16:28:27,120 epoch 37 - iter 243/274 - loss 0.02319206 - samples/sec: 165.22 - lr: 0.100000 |
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2022-11-06 16:28:32,148 epoch 37 - iter 270/274 - loss 0.02290421 - samples/sec: 171.93 - lr: 0.100000 |
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2022-11-06 16:28:32,762 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:28:32,762 EPOCH 37 done: loss 0.0229 - lr 0.100000 |
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2022-11-06 16:29:03,408 Evaluating as a multi-label problem: False |
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2022-11-06 16:29:03,436 TEST : loss 0.03057018481194973 - f1-score (micro avg) 0.844 |
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2022-11-06 16:29:03,921 BAD EPOCHS (no improvement): 0 |
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2022-11-06 16:29:04,114 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:29:09,621 epoch 38 - iter 27/274 - loss 0.02408423 - samples/sec: 157.04 - lr: 0.100000 |
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2022-11-06 16:29:14,793 epoch 38 - iter 54/274 - loss 0.02249019 - samples/sec: 167.16 - lr: 0.100000 |
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2022-11-06 16:29:20,176 epoch 38 - iter 81/274 - loss 0.02285553 - samples/sec: 160.61 - lr: 0.100000 |
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2022-11-06 16:29:25,355 epoch 38 - iter 108/274 - loss 0.02271806 - samples/sec: 166.94 - lr: 0.100000 |
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2022-11-06 16:29:30,748 epoch 38 - iter 135/274 - loss 0.02290174 - samples/sec: 160.31 - lr: 0.100000 |
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2022-11-06 16:29:35,892 epoch 38 - iter 162/274 - loss 0.02294759 - samples/sec: 168.09 - lr: 0.100000 |
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2022-11-06 16:29:41,231 epoch 38 - iter 189/274 - loss 0.02241643 - samples/sec: 161.92 - lr: 0.100000 |
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2022-11-06 16:29:46,985 epoch 38 - iter 216/274 - loss 0.02297524 - samples/sec: 150.24 - lr: 0.100000 |
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2022-11-06 16:29:52,183 epoch 38 - iter 243/274 - loss 0.02279735 - samples/sec: 166.32 - lr: 0.100000 |
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2022-11-06 16:29:57,977 epoch 38 - iter 270/274 - loss 0.02293773 - samples/sec: 149.22 - lr: 0.100000 |
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2022-11-06 16:29:58,910 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:29:58,910 EPOCH 38 done: loss 0.0232 - lr 0.100000 |
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2022-11-06 16:30:29,808 Evaluating as a multi-label problem: False |
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2022-11-06 16:30:29,836 TEST : loss 0.03000396490097046 - f1-score (micro avg) 0.8452 |
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2022-11-06 16:30:30,319 BAD EPOCHS (no improvement): 1 |
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2022-11-06 16:30:30,506 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:30:35,955 epoch 39 - iter 27/274 - loss 0.01893323 - samples/sec: 158.70 - lr: 0.100000 |
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2022-11-06 16:30:41,624 epoch 39 - iter 54/274 - loss 0.02118483 - samples/sec: 152.52 - lr: 0.100000 |
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2022-11-06 16:30:47,051 epoch 39 - iter 81/274 - loss 0.02232038 - samples/sec: 159.30 - lr: 0.100000 |
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2022-11-06 16:30:52,756 epoch 39 - iter 108/274 - loss 0.02395982 - samples/sec: 151.54 - lr: 0.100000 |
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2022-11-06 16:30:58,538 epoch 39 - iter 135/274 - loss 0.02373342 - samples/sec: 149.52 - lr: 0.100000 |
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2022-11-06 16:31:03,985 epoch 39 - iter 162/274 - loss 0.02356291 - samples/sec: 158.72 - lr: 0.100000 |
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2022-11-06 16:31:09,220 epoch 39 - iter 189/274 - loss 0.02349041 - samples/sec: 165.14 - lr: 0.100000 |
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2022-11-06 16:31:14,429 epoch 39 - iter 216/274 - loss 0.02387970 - samples/sec: 165.99 - lr: 0.100000 |
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2022-11-06 16:31:19,620 epoch 39 - iter 243/274 - loss 0.02325435 - samples/sec: 166.54 - lr: 0.100000 |
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2022-11-06 16:31:24,652 epoch 39 - iter 270/274 - loss 0.02339966 - samples/sec: 171.82 - lr: 0.100000 |
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2022-11-06 16:31:25,689 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:31:25,689 EPOCH 39 done: loss 0.0233 - lr 0.100000 |
|
2022-11-06 16:31:56,422 Evaluating as a multi-label problem: False |
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2022-11-06 16:31:56,449 TEST : loss 0.031386326998472214 - f1-score (micro avg) 0.853 |
|
2022-11-06 16:31:56,935 BAD EPOCHS (no improvement): 2 |
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2022-11-06 16:31:57,129 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:32:02,556 epoch 40 - iter 27/274 - loss 0.02241416 - samples/sec: 159.36 - lr: 0.100000 |
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2022-11-06 16:32:07,624 epoch 40 - iter 54/274 - loss 0.02153208 - samples/sec: 170.61 - lr: 0.100000 |
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2022-11-06 16:32:13,232 epoch 40 - iter 81/274 - loss 0.02212247 - samples/sec: 154.16 - lr: 0.100000 |
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2022-11-06 16:32:18,782 epoch 40 - iter 108/274 - loss 0.02325963 - samples/sec: 155.77 - lr: 0.100000 |
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2022-11-06 16:32:24,128 epoch 40 - iter 135/274 - loss 0.02375707 - samples/sec: 161.72 - lr: 0.100000 |
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2022-11-06 16:32:29,630 epoch 40 - iter 162/274 - loss 0.02374767 - samples/sec: 157.14 - lr: 0.100000 |
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2022-11-06 16:32:35,025 epoch 40 - iter 189/274 - loss 0.02357913 - samples/sec: 160.24 - lr: 0.100000 |
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2022-11-06 16:32:40,488 epoch 40 - iter 216/274 - loss 0.02328130 - samples/sec: 158.27 - lr: 0.100000 |
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2022-11-06 16:32:45,652 epoch 40 - iter 243/274 - loss 0.02294437 - samples/sec: 167.41 - lr: 0.100000 |
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2022-11-06 16:32:51,052 epoch 40 - iter 270/274 - loss 0.02291437 - samples/sec: 161.37 - lr: 0.100000 |
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2022-11-06 16:32:51,750 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:32:51,750 EPOCH 40 done: loss 0.0229 - lr 0.100000 |
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2022-11-06 16:33:22,446 Evaluating as a multi-label problem: False |
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2022-11-06 16:33:22,474 TEST : loss 0.029127517715096474 - f1-score (micro avg) 0.8558 |
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2022-11-06 16:33:22,957 BAD EPOCHS (no improvement): 0 |
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2022-11-06 16:33:23,153 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:33:28,526 epoch 41 - iter 27/274 - loss 0.02215677 - samples/sec: 160.96 - lr: 0.100000 |
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2022-11-06 16:33:33,956 epoch 41 - iter 54/274 - loss 0.02387369 - samples/sec: 159.21 - lr: 0.100000 |
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2022-11-06 16:33:39,128 epoch 41 - iter 81/274 - loss 0.02405334 - samples/sec: 167.17 - lr: 0.100000 |
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2022-11-06 16:33:44,369 epoch 41 - iter 108/274 - loss 0.02373568 - samples/sec: 164.97 - lr: 0.100000 |
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2022-11-06 16:33:49,619 epoch 41 - iter 135/274 - loss 0.02313503 - samples/sec: 164.68 - lr: 0.100000 |
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2022-11-06 16:33:54,960 epoch 41 - iter 162/274 - loss 0.02257297 - samples/sec: 161.85 - lr: 0.100000 |
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2022-11-06 16:33:59,784 epoch 41 - iter 189/274 - loss 0.02276199 - samples/sec: 179.24 - lr: 0.100000 |
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2022-11-06 16:34:05,131 epoch 41 - iter 216/274 - loss 0.02278488 - samples/sec: 161.69 - lr: 0.100000 |
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2022-11-06 16:34:10,803 epoch 41 - iter 243/274 - loss 0.02252815 - samples/sec: 152.43 - lr: 0.100000 |
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2022-11-06 16:34:16,783 epoch 41 - iter 270/274 - loss 0.02244280 - samples/sec: 144.56 - lr: 0.100000 |
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2022-11-06 16:34:17,566 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:34:17,566 EPOCH 41 done: loss 0.0223 - lr 0.100000 |
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2022-11-06 16:34:48,287 Evaluating as a multi-label problem: False |
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2022-11-06 16:34:48,314 TEST : loss 0.031170489266514778 - f1-score (micro avg) 0.8446 |
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2022-11-06 16:34:48,797 BAD EPOCHS (no improvement): 0 |
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2022-11-06 16:34:48,991 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:34:54,223 epoch 42 - iter 27/274 - loss 0.02163016 - samples/sec: 165.30 - lr: 0.100000 |
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2022-11-06 16:35:00,234 epoch 42 - iter 54/274 - loss 0.02131129 - samples/sec: 143.81 - lr: 0.100000 |
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2022-11-06 16:35:05,604 epoch 42 - iter 81/274 - loss 0.02146281 - samples/sec: 161.01 - lr: 0.100000 |
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2022-11-06 16:35:10,797 epoch 42 - iter 108/274 - loss 0.02166560 - samples/sec: 166.50 - lr: 0.100000 |
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2022-11-06 16:35:16,278 epoch 42 - iter 135/274 - loss 0.02174595 - samples/sec: 157.74 - lr: 0.100000 |
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2022-11-06 16:35:21,840 epoch 42 - iter 162/274 - loss 0.02188162 - samples/sec: 155.43 - lr: 0.100000 |
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2022-11-06 16:35:27,026 epoch 42 - iter 189/274 - loss 0.02196282 - samples/sec: 168.06 - lr: 0.100000 |
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2022-11-06 16:35:32,426 epoch 42 - iter 216/274 - loss 0.02181431 - samples/sec: 160.12 - lr: 0.100000 |
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2022-11-06 16:35:37,217 epoch 42 - iter 243/274 - loss 0.02192696 - samples/sec: 180.45 - lr: 0.100000 |
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2022-11-06 16:35:42,668 epoch 42 - iter 270/274 - loss 0.02200339 - samples/sec: 158.59 - lr: 0.100000 |
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2022-11-06 16:35:43,431 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:35:43,431 EPOCH 42 done: loss 0.0221 - lr 0.100000 |
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2022-11-06 16:36:14,169 Evaluating as a multi-label problem: False |
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2022-11-06 16:36:14,196 TEST : loss 0.0294171292334795 - f1-score (micro avg) 0.8504 |
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2022-11-06 16:36:14,679 BAD EPOCHS (no improvement): 0 |
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2022-11-06 16:36:14,864 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:36:20,163 epoch 43 - iter 27/274 - loss 0.01710942 - samples/sec: 163.23 - lr: 0.100000 |
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2022-11-06 16:36:25,610 epoch 43 - iter 54/274 - loss 0.02029393 - samples/sec: 158.72 - lr: 0.100000 |
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2022-11-06 16:36:30,951 epoch 43 - iter 81/274 - loss 0.02097961 - samples/sec: 161.85 - lr: 0.100000 |
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2022-11-06 16:36:36,086 epoch 43 - iter 108/274 - loss 0.02062345 - samples/sec: 168.38 - lr: 0.100000 |
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2022-11-06 16:36:41,206 epoch 43 - iter 135/274 - loss 0.02188550 - samples/sec: 168.86 - lr: 0.100000 |
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2022-11-06 16:36:46,584 epoch 43 - iter 162/274 - loss 0.02247212 - samples/sec: 160.76 - lr: 0.100000 |
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2022-11-06 16:36:51,835 epoch 43 - iter 189/274 - loss 0.02216251 - samples/sec: 164.65 - lr: 0.100000 |
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2022-11-06 16:36:56,984 epoch 43 - iter 216/274 - loss 0.02277374 - samples/sec: 167.89 - lr: 0.100000 |
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2022-11-06 16:37:02,380 epoch 43 - iter 243/274 - loss 0.02316744 - samples/sec: 160.24 - lr: 0.100000 |
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2022-11-06 16:37:08,486 epoch 43 - iter 270/274 - loss 0.02320475 - samples/sec: 141.57 - lr: 0.100000 |
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2022-11-06 16:37:09,417 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:37:09,417 EPOCH 43 done: loss 0.0233 - lr 0.100000 |
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2022-11-06 16:37:40,207 Evaluating as a multi-label problem: False |
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2022-11-06 16:37:40,235 TEST : loss 0.030061138793826103 - f1-score (micro avg) 0.8411 |
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2022-11-06 16:37:40,719 BAD EPOCHS (no improvement): 1 |
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2022-11-06 16:37:40,911 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:37:46,168 epoch 44 - iter 27/274 - loss 0.02247054 - samples/sec: 164.52 - lr: 0.100000 |
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2022-11-06 16:37:50,994 epoch 44 - iter 54/274 - loss 0.02094728 - samples/sec: 179.17 - lr: 0.100000 |
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2022-11-06 16:37:56,507 epoch 44 - iter 81/274 - loss 0.02310860 - samples/sec: 156.82 - lr: 0.100000 |
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2022-11-06 16:38:02,136 epoch 44 - iter 108/274 - loss 0.02301794 - samples/sec: 153.58 - lr: 0.100000 |
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2022-11-06 16:38:07,478 epoch 44 - iter 135/274 - loss 0.02313154 - samples/sec: 161.86 - lr: 0.100000 |
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2022-11-06 16:38:13,135 epoch 44 - iter 162/274 - loss 0.02323457 - samples/sec: 152.82 - lr: 0.100000 |
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2022-11-06 16:38:18,871 epoch 44 - iter 189/274 - loss 0.02333556 - samples/sec: 151.82 - lr: 0.100000 |
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2022-11-06 16:38:24,199 epoch 44 - iter 216/274 - loss 0.02307567 - samples/sec: 162.28 - lr: 0.100000 |
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2022-11-06 16:38:29,696 epoch 44 - iter 243/274 - loss 0.02353973 - samples/sec: 157.27 - lr: 0.100000 |
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2022-11-06 16:38:34,653 epoch 44 - iter 270/274 - loss 0.02287918 - samples/sec: 174.42 - lr: 0.100000 |
|
2022-11-06 16:38:35,544 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:38:35,544 EPOCH 44 done: loss 0.0227 - lr 0.100000 |
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2022-11-06 16:39:06,345 Evaluating as a multi-label problem: False |
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2022-11-06 16:39:06,372 TEST : loss 0.032110828906297684 - f1-score (micro avg) 0.8425 |
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2022-11-06 16:39:06,855 BAD EPOCHS (no improvement): 2 |
|
2022-11-06 16:39:07,051 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:39:12,479 epoch 45 - iter 27/274 - loss 0.01719875 - samples/sec: 159.32 - lr: 0.100000 |
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2022-11-06 16:39:18,046 epoch 45 - iter 54/274 - loss 0.01995671 - samples/sec: 155.31 - lr: 0.100000 |
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2022-11-06 16:39:23,387 epoch 45 - iter 81/274 - loss 0.02137920 - samples/sec: 162.79 - lr: 0.100000 |
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2022-11-06 16:39:28,114 epoch 45 - iter 108/274 - loss 0.02053238 - samples/sec: 182.93 - lr: 0.100000 |
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2022-11-06 16:39:33,298 epoch 45 - iter 135/274 - loss 0.02077647 - samples/sec: 166.77 - lr: 0.100000 |
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2022-11-06 16:39:38,974 epoch 45 - iter 162/274 - loss 0.02154126 - samples/sec: 153.46 - lr: 0.100000 |
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2022-11-06 16:39:44,371 epoch 45 - iter 189/274 - loss 0.02142571 - samples/sec: 160.18 - lr: 0.100000 |
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2022-11-06 16:39:49,957 epoch 45 - iter 216/274 - loss 0.02160676 - samples/sec: 154.76 - lr: 0.100000 |
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2022-11-06 16:39:55,283 epoch 45 - iter 243/274 - loss 0.02227279 - samples/sec: 162.34 - lr: 0.100000 |
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2022-11-06 16:40:00,651 epoch 45 - iter 270/274 - loss 0.02248165 - samples/sec: 161.05 - lr: 0.100000 |
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2022-11-06 16:40:01,341 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:40:01,341 EPOCH 45 done: loss 0.0224 - lr 0.100000 |
|
2022-11-06 16:40:32,020 Evaluating as a multi-label problem: False |
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2022-11-06 16:40:32,047 TEST : loss 0.029743408784270287 - f1-score (micro avg) 0.8528 |
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2022-11-06 16:40:32,532 BAD EPOCHS (no improvement): 3 |
|
2022-11-06 16:40:32,729 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:40:38,071 epoch 46 - iter 27/274 - loss 0.02369543 - samples/sec: 161.88 - lr: 0.100000 |
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2022-11-06 16:40:43,480 epoch 46 - iter 54/274 - loss 0.02221139 - samples/sec: 159.84 - lr: 0.100000 |
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2022-11-06 16:40:48,659 epoch 46 - iter 81/274 - loss 0.02437997 - samples/sec: 166.94 - lr: 0.100000 |
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2022-11-06 16:40:54,781 epoch 46 - iter 108/274 - loss 0.02406782 - samples/sec: 141.21 - lr: 0.100000 |
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2022-11-06 16:40:59,803 epoch 46 - iter 135/274 - loss 0.02306502 - samples/sec: 172.16 - lr: 0.100000 |
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2022-11-06 16:41:04,939 epoch 46 - iter 162/274 - loss 0.02286038 - samples/sec: 168.35 - lr: 0.100000 |
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2022-11-06 16:41:10,097 epoch 46 - iter 189/274 - loss 0.02297700 - samples/sec: 167.61 - lr: 0.100000 |
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2022-11-06 16:41:15,243 epoch 46 - iter 216/274 - loss 0.02275416 - samples/sec: 168.00 - lr: 0.100000 |
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2022-11-06 16:41:20,925 epoch 46 - iter 243/274 - loss 0.02226171 - samples/sec: 152.15 - lr: 0.100000 |
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2022-11-06 16:41:26,275 epoch 46 - iter 270/274 - loss 0.02215267 - samples/sec: 161.59 - lr: 0.100000 |
|
2022-11-06 16:41:27,051 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:41:27,051 EPOCH 46 done: loss 0.0222 - lr 0.100000 |
|
2022-11-06 16:41:57,780 Evaluating as a multi-label problem: False |
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2022-11-06 16:41:57,808 TEST : loss 0.031050119549036026 - f1-score (micro avg) 0.8531 |
|
2022-11-06 16:41:58,293 Epoch 46: reducing learning rate of group 0 to 5.0000e-02. |
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2022-11-06 16:41:58,294 BAD EPOCHS (no improvement): 4 |
|
2022-11-06 16:41:58,482 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 16:42:03,423 epoch 47 - iter 27/274 - loss 0.01892076 - samples/sec: 175.03 - lr: 0.050000 |
|
2022-11-06 16:42:08,622 epoch 47 - iter 54/274 - loss 0.01978271 - samples/sec: 167.25 - lr: 0.050000 |
|
2022-11-06 16:42:13,721 epoch 47 - iter 81/274 - loss 0.01979376 - samples/sec: 169.57 - lr: 0.050000 |
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2022-11-06 16:42:19,763 epoch 47 - iter 108/274 - loss 0.02010603 - samples/sec: 143.07 - lr: 0.050000 |
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2022-11-06 16:42:24,818 epoch 47 - iter 135/274 - loss 0.01994919 - samples/sec: 171.04 - lr: 0.050000 |
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2022-11-06 16:42:30,821 epoch 47 - iter 162/274 - loss 0.02047061 - samples/sec: 144.02 - lr: 0.050000 |
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2022-11-06 16:42:36,249 epoch 47 - iter 189/274 - loss 0.02002847 - samples/sec: 159.27 - lr: 0.050000 |
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2022-11-06 16:42:41,602 epoch 47 - iter 216/274 - loss 0.02026143 - samples/sec: 161.51 - lr: 0.050000 |
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2022-11-06 16:42:46,675 epoch 47 - iter 243/274 - loss 0.02036030 - samples/sec: 170.43 - lr: 0.050000 |
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2022-11-06 16:42:51,883 epoch 47 - iter 270/274 - loss 0.02037020 - samples/sec: 166.01 - lr: 0.050000 |
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2022-11-06 16:42:52,859 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:42:52,859 EPOCH 47 done: loss 0.0205 - lr 0.050000 |
|
2022-11-06 16:43:23,615 Evaluating as a multi-label problem: False |
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2022-11-06 16:43:23,643 TEST : loss 0.030249422416090965 - f1-score (micro avg) 0.8498 |
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2022-11-06 16:43:24,126 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 16:43:24,327 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:43:29,502 epoch 48 - iter 27/274 - loss 0.01915283 - samples/sec: 167.13 - lr: 0.050000 |
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2022-11-06 16:43:35,528 epoch 48 - iter 54/274 - loss 0.02134289 - samples/sec: 143.46 - lr: 0.050000 |
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2022-11-06 16:43:40,669 epoch 48 - iter 81/274 - loss 0.01957015 - samples/sec: 168.18 - lr: 0.050000 |
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2022-11-06 16:43:45,987 epoch 48 - iter 108/274 - loss 0.01905330 - samples/sec: 162.57 - lr: 0.050000 |
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2022-11-06 16:43:51,214 epoch 48 - iter 135/274 - loss 0.02006627 - samples/sec: 165.39 - lr: 0.050000 |
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2022-11-06 16:43:56,242 epoch 48 - iter 162/274 - loss 0.01992972 - samples/sec: 171.97 - lr: 0.050000 |
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2022-11-06 16:44:01,471 epoch 48 - iter 189/274 - loss 0.02013159 - samples/sec: 165.35 - lr: 0.050000 |
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2022-11-06 16:44:06,792 epoch 48 - iter 216/274 - loss 0.02048566 - samples/sec: 162.48 - lr: 0.050000 |
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2022-11-06 16:44:12,734 epoch 48 - iter 243/274 - loss 0.02061460 - samples/sec: 145.48 - lr: 0.050000 |
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2022-11-06 16:44:18,143 epoch 48 - iter 270/274 - loss 0.02060224 - samples/sec: 159.84 - lr: 0.050000 |
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2022-11-06 16:44:19,005 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:44:19,005 EPOCH 48 done: loss 0.0205 - lr 0.050000 |
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2022-11-06 16:44:52,770 Evaluating as a multi-label problem: False |
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2022-11-06 16:44:52,799 TEST : loss 0.02784981019794941 - f1-score (micro avg) 0.8523 |
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2022-11-06 16:44:53,287 BAD EPOCHS (no improvement): 1 |
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2022-11-06 16:44:53,481 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:45:00,675 epoch 49 - iter 27/274 - loss 0.02057271 - samples/sec: 120.20 - lr: 0.050000 |
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2022-11-06 16:45:07,423 epoch 49 - iter 54/274 - loss 0.01963785 - samples/sec: 128.11 - lr: 0.050000 |
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2022-11-06 16:45:14,804 epoch 49 - iter 81/274 - loss 0.01981443 - samples/sec: 117.12 - lr: 0.050000 |
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2022-11-06 16:45:21,957 epoch 49 - iter 108/274 - loss 0.02005951 - samples/sec: 120.85 - lr: 0.050000 |
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2022-11-06 16:45:28,599 epoch 49 - iter 135/274 - loss 0.01993758 - samples/sec: 130.16 - lr: 0.050000 |
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2022-11-06 16:45:35,392 epoch 49 - iter 162/274 - loss 0.01982053 - samples/sec: 127.26 - lr: 0.050000 |
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2022-11-06 16:45:42,023 epoch 49 - iter 189/274 - loss 0.01972889 - samples/sec: 130.36 - lr: 0.050000 |
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2022-11-06 16:45:48,807 epoch 49 - iter 216/274 - loss 0.01972932 - samples/sec: 127.43 - lr: 0.050000 |
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2022-11-06 16:45:55,936 epoch 49 - iter 243/274 - loss 0.01967441 - samples/sec: 121.26 - lr: 0.050000 |
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2022-11-06 16:46:02,852 epoch 49 - iter 270/274 - loss 0.01925280 - samples/sec: 124.99 - lr: 0.050000 |
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2022-11-06 16:46:03,717 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:46:03,717 EPOCH 49 done: loss 0.0193 - lr 0.050000 |
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2022-11-06 16:46:42,562 Evaluating as a multi-label problem: False |
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2022-11-06 16:46:42,590 TEST : loss 0.02871915139257908 - f1-score (micro avg) 0.8565 |
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2022-11-06 16:46:43,077 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 16:46:43,273 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:46:50,472 epoch 50 - iter 27/274 - loss 0.02187429 - samples/sec: 120.10 - lr: 0.050000 |
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2022-11-06 16:46:57,580 epoch 50 - iter 54/274 - loss 0.01870923 - samples/sec: 121.62 - lr: 0.050000 |
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2022-11-06 16:47:04,617 epoch 50 - iter 81/274 - loss 0.01768404 - samples/sec: 122.85 - lr: 0.050000 |
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2022-11-06 16:47:11,154 epoch 50 - iter 108/274 - loss 0.01850040 - samples/sec: 132.24 - lr: 0.050000 |
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2022-11-06 16:47:18,487 epoch 50 - iter 135/274 - loss 0.01878059 - samples/sec: 117.89 - lr: 0.050000 |
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2022-11-06 16:47:25,359 epoch 50 - iter 162/274 - loss 0.01873312 - samples/sec: 125.82 - lr: 0.050000 |
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2022-11-06 16:47:31,574 epoch 50 - iter 189/274 - loss 0.01869845 - samples/sec: 139.09 - lr: 0.050000 |
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2022-11-06 16:47:38,590 epoch 50 - iter 216/274 - loss 0.01895120 - samples/sec: 123.21 - lr: 0.050000 |
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2022-11-06 16:47:45,500 epoch 50 - iter 243/274 - loss 0.01901111 - samples/sec: 125.12 - lr: 0.050000 |
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2022-11-06 16:47:53,548 epoch 50 - iter 270/274 - loss 0.01925134 - samples/sec: 107.40 - lr: 0.050000 |
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2022-11-06 16:47:54,706 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:47:54,745 EPOCH 50 done: loss 0.0192 - lr 0.050000 |
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2022-11-06 16:48:32,930 Evaluating as a multi-label problem: False |
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2022-11-06 16:48:32,958 TEST : loss 0.030805133283138275 - f1-score (micro avg) 0.8476 |
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2022-11-06 16:48:33,447 BAD EPOCHS (no improvement): 0 |
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2022-11-06 16:48:33,636 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 16:48:41,416 epoch 51 - iter 27/274 - loss 0.01635629 - samples/sec: 111.12 - lr: 0.050000 |
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2022-11-06 16:48:48,240 epoch 51 - iter 54/274 - loss 0.01715334 - samples/sec: 126.69 - lr: 0.050000 |
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2022-11-06 16:48:55,420 epoch 51 - iter 81/274 - loss 0.01838564 - samples/sec: 120.39 - lr: 0.050000 |
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2022-11-06 16:49:02,458 epoch 51 - iter 108/274 - loss 0.01897771 - samples/sec: 122.83 - lr: 0.050000 |
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2022-11-06 16:49:10,138 epoch 51 - iter 135/274 - loss 0.01911294 - samples/sec: 112.56 - lr: 0.050000 |
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2022-11-06 16:49:16,929 epoch 51 - iter 162/274 - loss 0.01912749 - samples/sec: 127.32 - lr: 0.050000 |
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2022-11-06 16:49:23,284 epoch 51 - iter 189/274 - loss 0.01944390 - samples/sec: 136.03 - lr: 0.050000 |
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2022-11-06 16:49:29,785 epoch 51 - iter 216/274 - loss 0.01905674 - samples/sec: 132.98 - lr: 0.050000 |
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2022-11-06 16:49:37,140 epoch 51 - iter 243/274 - loss 0.01939322 - samples/sec: 117.53 - lr: 0.050000 |
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2022-11-06 16:49:43,873 epoch 51 - iter 270/274 - loss 0.01960299 - samples/sec: 128.41 - lr: 0.050000 |
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2022-11-06 16:49:44,878 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:49:44,878 EPOCH 51 done: loss 0.0196 - lr 0.050000 |
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2022-11-06 16:50:23,953 Evaluating as a multi-label problem: False |
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2022-11-06 16:50:23,981 TEST : loss 0.031178493052721024 - f1-score (micro avg) 0.8492 |
|
2022-11-06 16:50:24,469 BAD EPOCHS (no improvement): 1 |
|
2022-11-06 16:50:24,667 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:50:31,725 epoch 52 - iter 27/274 - loss 0.02086634 - samples/sec: 122.50 - lr: 0.050000 |
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2022-11-06 16:50:38,930 epoch 52 - iter 54/274 - loss 0.02097455 - samples/sec: 119.98 - lr: 0.050000 |
|
2022-11-06 16:50:46,280 epoch 52 - iter 81/274 - loss 0.02027621 - samples/sec: 117.61 - lr: 0.050000 |
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2022-11-06 16:50:52,907 epoch 52 - iter 108/274 - loss 0.01916971 - samples/sec: 130.46 - lr: 0.050000 |
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2022-11-06 16:50:59,965 epoch 52 - iter 135/274 - loss 0.01915529 - samples/sec: 122.48 - lr: 0.050000 |
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2022-11-06 16:51:06,932 epoch 52 - iter 162/274 - loss 0.01916447 - samples/sec: 124.09 - lr: 0.050000 |
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2022-11-06 16:51:13,250 epoch 52 - iter 189/274 - loss 0.01843177 - samples/sec: 136.83 - lr: 0.050000 |
|
2022-11-06 16:51:19,958 epoch 52 - iter 216/274 - loss 0.01875700 - samples/sec: 128.86 - lr: 0.050000 |
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2022-11-06 16:51:26,860 epoch 52 - iter 243/274 - loss 0.01895607 - samples/sec: 125.26 - lr: 0.050000 |
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2022-11-06 16:51:34,160 epoch 52 - iter 270/274 - loss 0.01870382 - samples/sec: 118.42 - lr: 0.050000 |
|
2022-11-06 16:51:35,184 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:51:35,185 EPOCH 52 done: loss 0.0187 - lr 0.050000 |
|
2022-11-06 16:52:14,519 Evaluating as a multi-label problem: False |
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2022-11-06 16:52:14,547 TEST : loss 0.030038980767130852 - f1-score (micro avg) 0.8595 |
|
2022-11-06 16:52:15,033 BAD EPOCHS (no improvement): 0 |
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2022-11-06 16:52:15,228 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:52:22,463 epoch 53 - iter 27/274 - loss 0.02001975 - samples/sec: 119.50 - lr: 0.050000 |
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2022-11-06 16:52:29,132 epoch 53 - iter 54/274 - loss 0.01873727 - samples/sec: 129.64 - lr: 0.050000 |
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2022-11-06 16:52:36,745 epoch 53 - iter 81/274 - loss 0.01982174 - samples/sec: 113.54 - lr: 0.050000 |
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2022-11-06 16:52:43,905 epoch 53 - iter 108/274 - loss 0.01954032 - samples/sec: 120.75 - lr: 0.050000 |
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2022-11-06 16:52:51,637 epoch 53 - iter 135/274 - loss 0.01948013 - samples/sec: 111.80 - lr: 0.050000 |
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2022-11-06 16:52:58,111 epoch 53 - iter 162/274 - loss 0.01940424 - samples/sec: 133.52 - lr: 0.050000 |
|
2022-11-06 16:53:04,264 epoch 53 - iter 189/274 - loss 0.01905603 - samples/sec: 140.50 - lr: 0.050000 |
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2022-11-06 16:53:11,124 epoch 53 - iter 216/274 - loss 0.01898204 - samples/sec: 126.03 - lr: 0.050000 |
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2022-11-06 16:53:17,767 epoch 53 - iter 243/274 - loss 0.01851959 - samples/sec: 130.14 - lr: 0.050000 |
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2022-11-06 16:53:24,552 epoch 53 - iter 270/274 - loss 0.01851000 - samples/sec: 127.40 - lr: 0.050000 |
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2022-11-06 16:53:25,571 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:53:25,571 EPOCH 53 done: loss 0.0185 - lr 0.050000 |
|
2022-11-06 16:54:04,506 Evaluating as a multi-label problem: False |
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2022-11-06 16:54:04,534 TEST : loss 0.030869534239172935 - f1-score (micro avg) 0.8556 |
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2022-11-06 16:54:05,021 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 16:54:05,217 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:54:12,308 epoch 54 - iter 27/274 - loss 0.02156169 - samples/sec: 121.94 - lr: 0.050000 |
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2022-11-06 16:54:19,110 epoch 54 - iter 54/274 - loss 0.01951305 - samples/sec: 127.10 - lr: 0.050000 |
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2022-11-06 16:54:25,747 epoch 54 - iter 81/274 - loss 0.01873362 - samples/sec: 130.26 - lr: 0.050000 |
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2022-11-06 16:54:32,645 epoch 54 - iter 108/274 - loss 0.01751394 - samples/sec: 125.32 - lr: 0.050000 |
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2022-11-06 16:54:40,282 epoch 54 - iter 135/274 - loss 0.01918168 - samples/sec: 113.19 - lr: 0.050000 |
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2022-11-06 16:54:47,327 epoch 54 - iter 162/274 - loss 0.01825074 - samples/sec: 122.71 - lr: 0.050000 |
|
2022-11-06 16:54:54,029 epoch 54 - iter 189/274 - loss 0.01803231 - samples/sec: 128.98 - lr: 0.050000 |
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2022-11-06 16:55:00,074 epoch 54 - iter 216/274 - loss 0.01763326 - samples/sec: 143.01 - lr: 0.050000 |
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2022-11-06 16:55:07,459 epoch 54 - iter 243/274 - loss 0.01758116 - samples/sec: 117.06 - lr: 0.050000 |
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2022-11-06 16:55:15,114 epoch 54 - iter 270/274 - loss 0.01767042 - samples/sec: 112.93 - lr: 0.050000 |
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2022-11-06 16:55:15,998 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:55:15,998 EPOCH 54 done: loss 0.0177 - lr 0.050000 |
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2022-11-06 16:55:54,780 Evaluating as a multi-label problem: False |
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2022-11-06 16:55:54,808 TEST : loss 0.03118710406124592 - f1-score (micro avg) 0.8575 |
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2022-11-06 16:55:55,295 BAD EPOCHS (no improvement): 0 |
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2022-11-06 16:55:55,484 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:56:02,871 epoch 55 - iter 27/274 - loss 0.01843406 - samples/sec: 117.04 - lr: 0.050000 |
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2022-11-06 16:56:10,033 epoch 55 - iter 54/274 - loss 0.01830914 - samples/sec: 120.71 - lr: 0.050000 |
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2022-11-06 16:56:18,425 epoch 55 - iter 81/274 - loss 0.01847121 - samples/sec: 103.00 - lr: 0.050000 |
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2022-11-06 16:56:25,197 epoch 55 - iter 108/274 - loss 0.01759215 - samples/sec: 127.64 - lr: 0.050000 |
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2022-11-06 16:56:31,530 epoch 55 - iter 135/274 - loss 0.01771944 - samples/sec: 136.52 - lr: 0.050000 |
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2022-11-06 16:56:38,297 epoch 55 - iter 162/274 - loss 0.01767717 - samples/sec: 127.75 - lr: 0.050000 |
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2022-11-06 16:56:45,238 epoch 55 - iter 189/274 - loss 0.01786543 - samples/sec: 124.56 - lr: 0.050000 |
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2022-11-06 16:56:51,149 epoch 55 - iter 216/274 - loss 0.01767731 - samples/sec: 146.25 - lr: 0.050000 |
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2022-11-06 16:56:58,239 epoch 55 - iter 243/274 - loss 0.01771460 - samples/sec: 121.93 - lr: 0.050000 |
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2022-11-06 16:57:04,822 epoch 55 - iter 270/274 - loss 0.01783817 - samples/sec: 131.33 - lr: 0.050000 |
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2022-11-06 16:57:05,650 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:57:05,650 EPOCH 55 done: loss 0.0179 - lr 0.050000 |
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2022-11-06 16:57:44,711 Evaluating as a multi-label problem: False |
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2022-11-06 16:57:44,738 TEST : loss 0.030333157628774643 - f1-score (micro avg) 0.8606 |
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2022-11-06 16:57:45,224 BAD EPOCHS (no improvement): 1 |
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2022-11-06 16:57:45,411 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:57:52,671 epoch 56 - iter 27/274 - loss 0.01969216 - samples/sec: 119.10 - lr: 0.050000 |
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2022-11-06 16:58:00,247 epoch 56 - iter 54/274 - loss 0.01920118 - samples/sec: 114.10 - lr: 0.050000 |
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2022-11-06 16:58:07,062 epoch 56 - iter 81/274 - loss 0.01826768 - samples/sec: 126.85 - lr: 0.050000 |
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2022-11-06 16:58:14,006 epoch 56 - iter 108/274 - loss 0.01777826 - samples/sec: 124.50 - lr: 0.050000 |
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2022-11-06 16:58:20,686 epoch 56 - iter 135/274 - loss 0.01813031 - samples/sec: 129.42 - lr: 0.050000 |
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2022-11-06 16:58:28,336 epoch 56 - iter 162/274 - loss 0.01864515 - samples/sec: 112.99 - lr: 0.050000 |
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2022-11-06 16:58:35,159 epoch 56 - iter 189/274 - loss 0.01804029 - samples/sec: 126.71 - lr: 0.050000 |
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2022-11-06 16:58:41,717 epoch 56 - iter 216/274 - loss 0.01825324 - samples/sec: 131.83 - lr: 0.050000 |
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2022-11-06 16:58:48,231 epoch 56 - iter 243/274 - loss 0.01812045 - samples/sec: 132.72 - lr: 0.050000 |
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2022-11-06 16:58:55,350 epoch 56 - iter 270/274 - loss 0.01820080 - samples/sec: 121.42 - lr: 0.050000 |
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2022-11-06 16:58:56,294 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:58:56,294 EPOCH 56 done: loss 0.0183 - lr 0.050000 |
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2022-11-06 16:59:35,596 Evaluating as a multi-label problem: False |
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2022-11-06 16:59:35,624 TEST : loss 0.03127044439315796 - f1-score (micro avg) 0.8594 |
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2022-11-06 16:59:36,111 BAD EPOCHS (no improvement): 2 |
|
2022-11-06 16:59:36,304 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 16:59:43,178 epoch 57 - iter 27/274 - loss 0.01759224 - samples/sec: 125.79 - lr: 0.050000 |
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2022-11-06 16:59:50,221 epoch 57 - iter 54/274 - loss 0.01831683 - samples/sec: 122.73 - lr: 0.050000 |
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2022-11-06 16:59:57,176 epoch 57 - iter 81/274 - loss 0.01822114 - samples/sec: 124.31 - lr: 0.050000 |
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2022-11-06 17:00:03,647 epoch 57 - iter 108/274 - loss 0.01776786 - samples/sec: 133.59 - lr: 0.050000 |
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2022-11-06 17:00:10,512 epoch 57 - iter 135/274 - loss 0.01778582 - samples/sec: 125.93 - lr: 0.050000 |
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2022-11-06 17:00:17,434 epoch 57 - iter 162/274 - loss 0.01794400 - samples/sec: 124.89 - lr: 0.050000 |
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2022-11-06 17:00:24,282 epoch 57 - iter 189/274 - loss 0.01757674 - samples/sec: 126.23 - lr: 0.050000 |
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2022-11-06 17:00:31,157 epoch 57 - iter 216/274 - loss 0.01770841 - samples/sec: 125.74 - lr: 0.050000 |
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2022-11-06 17:00:38,097 epoch 57 - iter 243/274 - loss 0.01776382 - samples/sec: 124.56 - lr: 0.050000 |
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2022-11-06 17:00:45,622 epoch 57 - iter 270/274 - loss 0.01768437 - samples/sec: 114.87 - lr: 0.050000 |
|
2022-11-06 17:00:46,706 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:00:46,706 EPOCH 57 done: loss 0.0177 - lr 0.050000 |
|
2022-11-06 17:01:26,666 Evaluating as a multi-label problem: False |
|
2022-11-06 17:01:26,693 TEST : loss 0.031970299780368805 - f1-score (micro avg) 0.8588 |
|
2022-11-06 17:01:27,182 BAD EPOCHS (no improvement): 3 |
|
2022-11-06 17:01:27,378 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 17:01:33,736 epoch 58 - iter 27/274 - loss 0.01737039 - samples/sec: 135.99 - lr: 0.050000 |
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2022-11-06 17:01:40,671 epoch 58 - iter 54/274 - loss 0.01772992 - samples/sec: 124.67 - lr: 0.050000 |
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2022-11-06 17:01:47,695 epoch 58 - iter 81/274 - loss 0.01785145 - samples/sec: 123.07 - lr: 0.050000 |
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2022-11-06 17:01:55,129 epoch 58 - iter 108/274 - loss 0.01861589 - samples/sec: 116.28 - lr: 0.050000 |
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2022-11-06 17:02:01,544 epoch 58 - iter 135/274 - loss 0.01830026 - samples/sec: 134.76 - lr: 0.050000 |
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2022-11-06 17:02:08,971 epoch 58 - iter 162/274 - loss 0.01786728 - samples/sec: 116.39 - lr: 0.050000 |
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2022-11-06 17:02:15,728 epoch 58 - iter 189/274 - loss 0.01828590 - samples/sec: 127.95 - lr: 0.050000 |
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2022-11-06 17:02:22,664 epoch 58 - iter 216/274 - loss 0.01830113 - samples/sec: 124.63 - lr: 0.050000 |
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2022-11-06 17:02:29,336 epoch 58 - iter 243/274 - loss 0.01844889 - samples/sec: 129.56 - lr: 0.050000 |
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2022-11-06 17:02:36,319 epoch 58 - iter 270/274 - loss 0.01828605 - samples/sec: 123.80 - lr: 0.050000 |
|
2022-11-06 17:02:37,197 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:02:37,197 EPOCH 58 done: loss 0.0183 - lr 0.050000 |
|
2022-11-06 17:03:16,952 Evaluating as a multi-label problem: False |
|
2022-11-06 17:03:16,980 TEST : loss 0.02933284267783165 - f1-score (micro avg) 0.8563 |
|
2022-11-06 17:03:17,467 Epoch 58: reducing learning rate of group 0 to 2.5000e-02. |
|
2022-11-06 17:03:17,468 BAD EPOCHS (no improvement): 4 |
|
2022-11-06 17:03:17,664 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 17:03:24,040 epoch 59 - iter 27/274 - loss 0.01818196 - samples/sec: 135.63 - lr: 0.025000 |
|
2022-11-06 17:03:31,272 epoch 59 - iter 54/274 - loss 0.01765334 - samples/sec: 119.52 - lr: 0.025000 |
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2022-11-06 17:03:38,607 epoch 59 - iter 81/274 - loss 0.01793576 - samples/sec: 117.85 - lr: 0.025000 |
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2022-11-06 17:03:45,016 epoch 59 - iter 108/274 - loss 0.01732424 - samples/sec: 134.90 - lr: 0.025000 |
|
2022-11-06 17:03:53,030 epoch 59 - iter 135/274 - loss 0.01767106 - samples/sec: 107.86 - lr: 0.025000 |
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2022-11-06 17:03:59,921 epoch 59 - iter 162/274 - loss 0.01762930 - samples/sec: 125.46 - lr: 0.025000 |
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2022-11-06 17:04:07,255 epoch 59 - iter 189/274 - loss 0.01766409 - samples/sec: 117.87 - lr: 0.025000 |
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2022-11-06 17:04:14,069 epoch 59 - iter 216/274 - loss 0.01732257 - samples/sec: 126.87 - lr: 0.025000 |
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2022-11-06 17:04:20,168 epoch 59 - iter 243/274 - loss 0.01738389 - samples/sec: 141.74 - lr: 0.025000 |
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2022-11-06 17:04:26,636 epoch 59 - iter 270/274 - loss 0.01721085 - samples/sec: 133.66 - lr: 0.025000 |
|
2022-11-06 17:04:27,652 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:04:27,652 EPOCH 59 done: loss 0.0171 - lr 0.025000 |
|
2022-11-06 17:05:07,346 Evaluating as a multi-label problem: False |
|
2022-11-06 17:05:07,375 TEST : loss 0.03182924538850784 - f1-score (micro avg) 0.858 |
|
2022-11-06 17:05:07,866 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 17:05:08,054 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:05:14,706 epoch 60 - iter 27/274 - loss 0.01562910 - samples/sec: 129.98 - lr: 0.025000 |
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2022-11-06 17:05:21,550 epoch 60 - iter 54/274 - loss 0.01530772 - samples/sec: 126.32 - lr: 0.025000 |
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2022-11-06 17:05:28,999 epoch 60 - iter 81/274 - loss 0.01620627 - samples/sec: 116.05 - lr: 0.025000 |
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2022-11-06 17:05:35,459 epoch 60 - iter 108/274 - loss 0.01640443 - samples/sec: 133.82 - lr: 0.025000 |
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2022-11-06 17:05:41,994 epoch 60 - iter 135/274 - loss 0.01620174 - samples/sec: 132.29 - lr: 0.025000 |
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2022-11-06 17:05:49,220 epoch 60 - iter 162/274 - loss 0.01680609 - samples/sec: 119.64 - lr: 0.025000 |
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2022-11-06 17:05:56,388 epoch 60 - iter 189/274 - loss 0.01681290 - samples/sec: 120.60 - lr: 0.025000 |
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2022-11-06 17:06:03,844 epoch 60 - iter 216/274 - loss 0.01694250 - samples/sec: 115.93 - lr: 0.025000 |
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2022-11-06 17:06:10,258 epoch 60 - iter 243/274 - loss 0.01734382 - samples/sec: 134.79 - lr: 0.025000 |
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2022-11-06 17:06:17,291 epoch 60 - iter 270/274 - loss 0.01732942 - samples/sec: 122.92 - lr: 0.025000 |
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2022-11-06 17:06:18,215 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:06:18,216 EPOCH 60 done: loss 0.0173 - lr 0.025000 |
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2022-11-06 17:06:57,991 Evaluating as a multi-label problem: False |
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2022-11-06 17:06:58,019 TEST : loss 0.031502872705459595 - f1-score (micro avg) 0.86 |
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2022-11-06 17:06:58,504 BAD EPOCHS (no improvement): 1 |
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2022-11-06 17:06:58,701 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:07:04,874 epoch 61 - iter 27/274 - loss 0.01498040 - samples/sec: 140.09 - lr: 0.025000 |
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2022-11-06 17:07:11,705 epoch 61 - iter 54/274 - loss 0.01508750 - samples/sec: 126.57 - lr: 0.025000 |
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2022-11-06 17:07:18,212 epoch 61 - iter 81/274 - loss 0.01524963 - samples/sec: 132.85 - lr: 0.025000 |
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2022-11-06 17:07:25,088 epoch 61 - iter 108/274 - loss 0.01586900 - samples/sec: 125.73 - lr: 0.025000 |
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2022-11-06 17:07:32,052 epoch 61 - iter 135/274 - loss 0.01620896 - samples/sec: 124.13 - lr: 0.025000 |
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2022-11-06 17:07:39,599 epoch 61 - iter 162/274 - loss 0.01677026 - samples/sec: 114.54 - lr: 0.025000 |
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2022-11-06 17:07:46,222 epoch 61 - iter 189/274 - loss 0.01660999 - samples/sec: 130.53 - lr: 0.025000 |
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2022-11-06 17:07:52,777 epoch 61 - iter 216/274 - loss 0.01654429 - samples/sec: 131.88 - lr: 0.025000 |
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2022-11-06 17:08:00,282 epoch 61 - iter 243/274 - loss 0.01666333 - samples/sec: 115.18 - lr: 0.025000 |
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2022-11-06 17:08:07,088 epoch 61 - iter 270/274 - loss 0.01645526 - samples/sec: 127.02 - lr: 0.025000 |
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2022-11-06 17:08:08,051 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:08:08,051 EPOCH 61 done: loss 0.0166 - lr 0.025000 |
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2022-11-06 17:08:47,894 Evaluating as a multi-label problem: False |
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2022-11-06 17:08:47,922 TEST : loss 0.031147386878728867 - f1-score (micro avg) 0.8573 |
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2022-11-06 17:08:48,411 BAD EPOCHS (no improvement): 0 |
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2022-11-06 17:08:48,607 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:08:55,454 epoch 62 - iter 27/274 - loss 0.01467951 - samples/sec: 126.29 - lr: 0.025000 |
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2022-11-06 17:09:02,235 epoch 62 - iter 54/274 - loss 0.01492071 - samples/sec: 127.49 - lr: 0.025000 |
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2022-11-06 17:09:08,779 epoch 62 - iter 81/274 - loss 0.01568738 - samples/sec: 132.10 - lr: 0.025000 |
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2022-11-06 17:09:16,421 epoch 62 - iter 108/274 - loss 0.01595573 - samples/sec: 113.13 - lr: 0.025000 |
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2022-11-06 17:09:23,303 epoch 62 - iter 135/274 - loss 0.01617601 - samples/sec: 125.60 - lr: 0.025000 |
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2022-11-06 17:09:30,144 epoch 62 - iter 162/274 - loss 0.01631464 - samples/sec: 126.37 - lr: 0.025000 |
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2022-11-06 17:09:37,135 epoch 62 - iter 189/274 - loss 0.01633934 - samples/sec: 123.66 - lr: 0.025000 |
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2022-11-06 17:09:44,147 epoch 62 - iter 216/274 - loss 0.01648327 - samples/sec: 123.29 - lr: 0.025000 |
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2022-11-06 17:09:51,297 epoch 62 - iter 243/274 - loss 0.01677063 - samples/sec: 120.90 - lr: 0.025000 |
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2022-11-06 17:09:57,820 epoch 62 - iter 270/274 - loss 0.01677192 - samples/sec: 132.54 - lr: 0.025000 |
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2022-11-06 17:09:58,743 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:09:58,743 EPOCH 62 done: loss 0.0167 - lr 0.025000 |
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2022-11-06 17:10:38,260 Evaluating as a multi-label problem: False |
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2022-11-06 17:10:38,303 TEST : loss 0.032001152634620667 - f1-score (micro avg) 0.8587 |
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2022-11-06 17:10:38,939 BAD EPOCHS (no improvement): 1 |
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2022-11-06 17:10:39,136 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:10:46,062 epoch 63 - iter 27/274 - loss 0.01425313 - samples/sec: 124.85 - lr: 0.025000 |
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2022-11-06 17:10:52,800 epoch 63 - iter 54/274 - loss 0.01486578 - samples/sec: 128.30 - lr: 0.025000 |
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2022-11-06 17:10:59,977 epoch 63 - iter 81/274 - loss 0.01577871 - samples/sec: 120.45 - lr: 0.025000 |
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2022-11-06 17:11:06,953 epoch 63 - iter 108/274 - loss 0.01584291 - samples/sec: 123.92 - lr: 0.025000 |
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2022-11-06 17:11:14,138 epoch 63 - iter 135/274 - loss 0.01565203 - samples/sec: 120.31 - lr: 0.025000 |
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2022-11-06 17:11:20,740 epoch 63 - iter 162/274 - loss 0.01523300 - samples/sec: 130.94 - lr: 0.025000 |
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2022-11-06 17:11:27,758 epoch 63 - iter 189/274 - loss 0.01552535 - samples/sec: 123.19 - lr: 0.025000 |
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2022-11-06 17:11:34,183 epoch 63 - iter 216/274 - loss 0.01563264 - samples/sec: 134.56 - lr: 0.025000 |
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2022-11-06 17:11:41,646 epoch 63 - iter 243/274 - loss 0.01562896 - samples/sec: 115.83 - lr: 0.025000 |
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2022-11-06 17:11:48,846 epoch 63 - iter 270/274 - loss 0.01611587 - samples/sec: 120.06 - lr: 0.025000 |
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2022-11-06 17:11:49,841 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:11:49,842 EPOCH 63 done: loss 0.0161 - lr 0.025000 |
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2022-11-06 17:12:29,084 Evaluating as a multi-label problem: False |
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2022-11-06 17:12:29,113 TEST : loss 0.03202659264206886 - f1-score (micro avg) 0.8576 |
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2022-11-06 17:12:29,601 BAD EPOCHS (no improvement): 0 |
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2022-11-06 17:12:29,789 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:12:36,449 epoch 64 - iter 27/274 - loss 0.01600093 - samples/sec: 129.83 - lr: 0.025000 |
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2022-11-06 17:12:43,481 epoch 64 - iter 54/274 - loss 0.01676961 - samples/sec: 122.93 - lr: 0.025000 |
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2022-11-06 17:12:49,774 epoch 64 - iter 81/274 - loss 0.01718148 - samples/sec: 137.38 - lr: 0.025000 |
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2022-11-06 17:12:57,114 epoch 64 - iter 108/274 - loss 0.01580944 - samples/sec: 117.76 - lr: 0.025000 |
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2022-11-06 17:13:03,836 epoch 64 - iter 135/274 - loss 0.01588193 - samples/sec: 128.61 - lr: 0.025000 |
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2022-11-06 17:13:10,855 epoch 64 - iter 162/274 - loss 0.01624047 - samples/sec: 123.16 - lr: 0.025000 |
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2022-11-06 17:13:18,180 epoch 64 - iter 189/274 - loss 0.01663038 - samples/sec: 118.03 - lr: 0.025000 |
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2022-11-06 17:13:25,645 epoch 64 - iter 216/274 - loss 0.01655460 - samples/sec: 115.80 - lr: 0.025000 |
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2022-11-06 17:13:32,938 epoch 64 - iter 243/274 - loss 0.01653993 - samples/sec: 118.53 - lr: 0.025000 |
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2022-11-06 17:13:39,729 epoch 64 - iter 270/274 - loss 0.01689917 - samples/sec: 127.29 - lr: 0.025000 |
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2022-11-06 17:13:40,544 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:13:40,544 EPOCH 64 done: loss 0.0169 - lr 0.025000 |
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2022-11-06 17:14:19,638 Evaluating as a multi-label problem: False |
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2022-11-06 17:14:19,666 TEST : loss 0.03130580484867096 - f1-score (micro avg) 0.8584 |
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2022-11-06 17:14:20,149 BAD EPOCHS (no improvement): 1 |
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2022-11-06 17:14:20,344 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:14:27,554 epoch 65 - iter 27/274 - loss 0.01873267 - samples/sec: 119.93 - lr: 0.025000 |
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2022-11-06 17:14:34,187 epoch 65 - iter 54/274 - loss 0.01833620 - samples/sec: 130.34 - lr: 0.025000 |
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2022-11-06 17:14:40,400 epoch 65 - iter 81/274 - loss 0.01832764 - samples/sec: 139.13 - lr: 0.025000 |
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2022-11-06 17:14:47,258 epoch 65 - iter 108/274 - loss 0.01858252 - samples/sec: 126.06 - lr: 0.025000 |
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2022-11-06 17:14:54,330 epoch 65 - iter 135/274 - loss 0.01790253 - samples/sec: 122.24 - lr: 0.025000 |
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2022-11-06 17:15:01,105 epoch 65 - iter 162/274 - loss 0.01770917 - samples/sec: 127.59 - lr: 0.025000 |
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2022-11-06 17:15:08,234 epoch 65 - iter 189/274 - loss 0.01781079 - samples/sec: 121.27 - lr: 0.025000 |
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2022-11-06 17:15:15,690 epoch 65 - iter 216/274 - loss 0.01750733 - samples/sec: 115.94 - lr: 0.025000 |
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2022-11-06 17:15:22,320 epoch 65 - iter 243/274 - loss 0.01743766 - samples/sec: 130.39 - lr: 0.025000 |
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2022-11-06 17:15:30,071 epoch 65 - iter 270/274 - loss 0.01746325 - samples/sec: 111.52 - lr: 0.025000 |
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2022-11-06 17:15:30,885 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:15:30,885 EPOCH 65 done: loss 0.0175 - lr 0.025000 |
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2022-11-06 17:16:09,793 Evaluating as a multi-label problem: False |
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2022-11-06 17:16:09,821 TEST : loss 0.030667604878544807 - f1-score (micro avg) 0.8576 |
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2022-11-06 17:16:10,310 BAD EPOCHS (no improvement): 2 |
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2022-11-06 17:16:10,504 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:16:18,613 epoch 66 - iter 27/274 - loss 0.01518631 - samples/sec: 106.62 - lr: 0.025000 |
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2022-11-06 17:16:25,822 epoch 66 - iter 54/274 - loss 0.01578202 - samples/sec: 119.92 - lr: 0.025000 |
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2022-11-06 17:16:31,752 epoch 66 - iter 81/274 - loss 0.01571391 - samples/sec: 145.79 - lr: 0.025000 |
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2022-11-06 17:16:38,595 epoch 66 - iter 108/274 - loss 0.01600228 - samples/sec: 126.32 - lr: 0.025000 |
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2022-11-06 17:16:45,605 epoch 66 - iter 135/274 - loss 0.01599430 - samples/sec: 123.34 - lr: 0.025000 |
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2022-11-06 17:16:52,846 epoch 66 - iter 162/274 - loss 0.01604994 - samples/sec: 119.38 - lr: 0.025000 |
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2022-11-06 17:16:59,480 epoch 66 - iter 189/274 - loss 0.01629519 - samples/sec: 130.31 - lr: 0.025000 |
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2022-11-06 17:17:06,200 epoch 66 - iter 216/274 - loss 0.01668978 - samples/sec: 128.65 - lr: 0.025000 |
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2022-11-06 17:17:13,103 epoch 66 - iter 243/274 - loss 0.01648213 - samples/sec: 125.23 - lr: 0.025000 |
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2022-11-06 17:17:20,288 epoch 66 - iter 270/274 - loss 0.01658877 - samples/sec: 120.32 - lr: 0.025000 |
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2022-11-06 17:17:21,380 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:17:21,381 EPOCH 66 done: loss 0.0166 - lr 0.025000 |
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2022-11-06 17:18:00,429 Evaluating as a multi-label problem: False |
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2022-11-06 17:18:00,456 TEST : loss 0.03189327195286751 - f1-score (micro avg) 0.8558 |
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2022-11-06 17:18:00,944 BAD EPOCHS (no improvement): 3 |
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2022-11-06 17:18:01,140 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:18:08,017 epoch 67 - iter 27/274 - loss 0.01614744 - samples/sec: 125.74 - lr: 0.025000 |
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2022-11-06 17:18:15,055 epoch 67 - iter 54/274 - loss 0.01577274 - samples/sec: 122.83 - lr: 0.025000 |
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2022-11-06 17:18:21,379 epoch 67 - iter 81/274 - loss 0.01610790 - samples/sec: 136.70 - lr: 0.025000 |
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2022-11-06 17:18:27,920 epoch 67 - iter 108/274 - loss 0.01570924 - samples/sec: 132.17 - lr: 0.025000 |
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2022-11-06 17:18:34,952 epoch 67 - iter 135/274 - loss 0.01587380 - samples/sec: 122.93 - lr: 0.025000 |
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2022-11-06 17:18:42,233 epoch 67 - iter 162/274 - loss 0.01534622 - samples/sec: 118.71 - lr: 0.025000 |
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2022-11-06 17:18:49,773 epoch 67 - iter 189/274 - loss 0.01565263 - samples/sec: 114.66 - lr: 0.025000 |
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2022-11-06 17:18:57,125 epoch 67 - iter 216/274 - loss 0.01557078 - samples/sec: 117.57 - lr: 0.025000 |
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2022-11-06 17:19:03,785 epoch 67 - iter 243/274 - loss 0.01597505 - samples/sec: 129.81 - lr: 0.025000 |
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2022-11-06 17:19:10,487 epoch 67 - iter 270/274 - loss 0.01590830 - samples/sec: 128.99 - lr: 0.025000 |
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2022-11-06 17:19:11,488 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:19:11,488 EPOCH 67 done: loss 0.0160 - lr 0.025000 |
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2022-11-06 17:19:50,222 Evaluating as a multi-label problem: False |
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2022-11-06 17:19:50,250 TEST : loss 0.03241714462637901 - f1-score (micro avg) 0.8569 |
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2022-11-06 17:19:50,737 BAD EPOCHS (no improvement): 0 |
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2022-11-06 17:19:50,925 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:19:57,653 epoch 68 - iter 27/274 - loss 0.01719008 - samples/sec: 128.50 - lr: 0.025000 |
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2022-11-06 17:20:04,480 epoch 68 - iter 54/274 - loss 0.01538560 - samples/sec: 126.63 - lr: 0.025000 |
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2022-11-06 17:20:11,515 epoch 68 - iter 81/274 - loss 0.01561873 - samples/sec: 122.88 - lr: 0.025000 |
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2022-11-06 17:20:17,393 epoch 68 - iter 108/274 - loss 0.01605447 - samples/sec: 147.10 - lr: 0.025000 |
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2022-11-06 17:20:24,861 epoch 68 - iter 135/274 - loss 0.01583889 - samples/sec: 115.75 - lr: 0.025000 |
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2022-11-06 17:20:31,619 epoch 68 - iter 162/274 - loss 0.01641121 - samples/sec: 127.91 - lr: 0.025000 |
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2022-11-06 17:20:38,343 epoch 68 - iter 189/274 - loss 0.01606534 - samples/sec: 128.57 - lr: 0.025000 |
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2022-11-06 17:20:45,659 epoch 68 - iter 216/274 - loss 0.01589503 - samples/sec: 118.17 - lr: 0.025000 |
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2022-11-06 17:20:52,885 epoch 68 - iter 243/274 - loss 0.01615565 - samples/sec: 119.62 - lr: 0.025000 |
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2022-11-06 17:20:59,981 epoch 68 - iter 270/274 - loss 0.01610109 - samples/sec: 121.83 - lr: 0.025000 |
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2022-11-06 17:21:00,947 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:21:00,948 EPOCH 68 done: loss 0.0160 - lr 0.025000 |
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2022-11-06 17:21:39,842 Evaluating as a multi-label problem: False |
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2022-11-06 17:21:39,870 TEST : loss 0.032622434198856354 - f1-score (micro avg) 0.8575 |
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2022-11-06 17:21:40,356 BAD EPOCHS (no improvement): 1 |
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2022-11-06 17:21:40,552 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:21:47,697 epoch 69 - iter 27/274 - loss 0.01387498 - samples/sec: 121.01 - lr: 0.025000 |
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2022-11-06 17:21:54,467 epoch 69 - iter 54/274 - loss 0.01550035 - samples/sec: 127.69 - lr: 0.025000 |
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2022-11-06 17:22:01,699 epoch 69 - iter 81/274 - loss 0.01560574 - samples/sec: 119.54 - lr: 0.025000 |
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2022-11-06 17:22:08,192 epoch 69 - iter 108/274 - loss 0.01570065 - samples/sec: 133.15 - lr: 0.025000 |
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2022-11-06 17:22:14,797 epoch 69 - iter 135/274 - loss 0.01507302 - samples/sec: 130.89 - lr: 0.025000 |
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2022-11-06 17:22:21,810 epoch 69 - iter 162/274 - loss 0.01587846 - samples/sec: 123.26 - lr: 0.025000 |
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2022-11-06 17:22:28,404 epoch 69 - iter 189/274 - loss 0.01578548 - samples/sec: 131.12 - lr: 0.025000 |
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2022-11-06 17:22:35,831 epoch 69 - iter 216/274 - loss 0.01592534 - samples/sec: 116.38 - lr: 0.025000 |
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2022-11-06 17:22:43,273 epoch 69 - iter 243/274 - loss 0.01597793 - samples/sec: 116.17 - lr: 0.025000 |
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2022-11-06 17:22:50,041 epoch 69 - iter 270/274 - loss 0.01595590 - samples/sec: 127.72 - lr: 0.025000 |
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2022-11-06 17:22:51,040 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:22:51,040 EPOCH 69 done: loss 0.0160 - lr 0.025000 |
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2022-11-06 17:23:30,171 Evaluating as a multi-label problem: False |
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2022-11-06 17:23:30,198 TEST : loss 0.03283306211233139 - f1-score (micro avg) 0.8563 |
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2022-11-06 17:23:30,685 BAD EPOCHS (no improvement): 2 |
|
2022-11-06 17:23:30,880 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:23:37,590 epoch 70 - iter 27/274 - loss 0.01518963 - samples/sec: 128.86 - lr: 0.025000 |
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2022-11-06 17:23:45,185 epoch 70 - iter 54/274 - loss 0.01521270 - samples/sec: 113.81 - lr: 0.025000 |
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2022-11-06 17:23:51,860 epoch 70 - iter 81/274 - loss 0.01415152 - samples/sec: 129.51 - lr: 0.025000 |
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2022-11-06 17:23:58,634 epoch 70 - iter 108/274 - loss 0.01485497 - samples/sec: 127.63 - lr: 0.025000 |
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2022-11-06 17:24:04,940 epoch 70 - iter 135/274 - loss 0.01478926 - samples/sec: 137.08 - lr: 0.025000 |
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2022-11-06 17:24:11,824 epoch 70 - iter 162/274 - loss 0.01499592 - samples/sec: 125.59 - lr: 0.025000 |
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2022-11-06 17:24:18,705 epoch 70 - iter 189/274 - loss 0.01553102 - samples/sec: 125.62 - lr: 0.025000 |
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2022-11-06 17:24:25,548 epoch 70 - iter 216/274 - loss 0.01546902 - samples/sec: 126.33 - lr: 0.025000 |
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2022-11-06 17:24:33,334 epoch 70 - iter 243/274 - loss 0.01550453 - samples/sec: 111.03 - lr: 0.025000 |
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2022-11-06 17:24:40,619 epoch 70 - iter 270/274 - loss 0.01585683 - samples/sec: 118.65 - lr: 0.025000 |
|
2022-11-06 17:24:41,696 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:24:41,697 EPOCH 70 done: loss 0.0158 - lr 0.025000 |
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2022-11-06 17:25:20,722 Evaluating as a multi-label problem: False |
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2022-11-06 17:25:20,750 TEST : loss 0.03144649788737297 - f1-score (micro avg) 0.855 |
|
2022-11-06 17:25:21,241 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 17:25:21,439 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:25:27,844 epoch 71 - iter 27/274 - loss 0.01504591 - samples/sec: 135.00 - lr: 0.025000 |
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2022-11-06 17:25:35,499 epoch 71 - iter 54/274 - loss 0.01422305 - samples/sec: 112.92 - lr: 0.025000 |
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2022-11-06 17:25:42,181 epoch 71 - iter 81/274 - loss 0.01494925 - samples/sec: 129.38 - lr: 0.025000 |
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2022-11-06 17:25:49,252 epoch 71 - iter 108/274 - loss 0.01539012 - samples/sec: 122.26 - lr: 0.025000 |
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2022-11-06 17:25:55,911 epoch 71 - iter 135/274 - loss 0.01611038 - samples/sec: 129.82 - lr: 0.025000 |
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2022-11-06 17:26:02,422 epoch 71 - iter 162/274 - loss 0.01621456 - samples/sec: 132.78 - lr: 0.025000 |
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2022-11-06 17:26:09,489 epoch 71 - iter 189/274 - loss 0.01589587 - samples/sec: 122.32 - lr: 0.025000 |
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2022-11-06 17:26:16,222 epoch 71 - iter 216/274 - loss 0.01608586 - samples/sec: 128.41 - lr: 0.025000 |
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2022-11-06 17:26:22,942 epoch 71 - iter 243/274 - loss 0.01617530 - samples/sec: 128.65 - lr: 0.025000 |
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2022-11-06 17:26:30,577 epoch 71 - iter 270/274 - loss 0.01610688 - samples/sec: 113.21 - lr: 0.025000 |
|
2022-11-06 17:26:31,552 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:26:31,553 EPOCH 71 done: loss 0.0161 - lr 0.025000 |
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2022-11-06 17:27:10,634 Evaluating as a multi-label problem: False |
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2022-11-06 17:27:10,662 TEST : loss 0.032507773488759995 - f1-score (micro avg) 0.8589 |
|
2022-11-06 17:27:11,151 BAD EPOCHS (no improvement): 1 |
|
2022-11-06 17:27:11,346 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:27:18,618 epoch 72 - iter 27/274 - loss 0.01296401 - samples/sec: 118.91 - lr: 0.025000 |
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2022-11-06 17:27:25,321 epoch 72 - iter 54/274 - loss 0.01358941 - samples/sec: 128.97 - lr: 0.025000 |
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2022-11-06 17:27:32,061 epoch 72 - iter 81/274 - loss 0.01460165 - samples/sec: 128.27 - lr: 0.025000 |
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2022-11-06 17:27:39,502 epoch 72 - iter 108/274 - loss 0.01518859 - samples/sec: 116.17 - lr: 0.025000 |
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2022-11-06 17:27:46,064 epoch 72 - iter 135/274 - loss 0.01600572 - samples/sec: 131.75 - lr: 0.025000 |
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2022-11-06 17:27:53,068 epoch 72 - iter 162/274 - loss 0.01600137 - samples/sec: 123.42 - lr: 0.025000 |
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2022-11-06 17:28:00,233 epoch 72 - iter 189/274 - loss 0.01649032 - samples/sec: 120.66 - lr: 0.025000 |
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2022-11-06 17:28:06,844 epoch 72 - iter 216/274 - loss 0.01630591 - samples/sec: 130.77 - lr: 0.025000 |
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2022-11-06 17:28:14,389 epoch 72 - iter 243/274 - loss 0.01640176 - samples/sec: 114.57 - lr: 0.025000 |
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2022-11-06 17:28:21,097 epoch 72 - iter 270/274 - loss 0.01651928 - samples/sec: 128.89 - lr: 0.025000 |
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2022-11-06 17:28:22,048 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:28:22,048 EPOCH 72 done: loss 0.0166 - lr 0.025000 |
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2022-11-06 17:29:01,043 Evaluating as a multi-label problem: False |
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2022-11-06 17:29:01,071 TEST : loss 0.0317557118833065 - f1-score (micro avg) 0.8525 |
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2022-11-06 17:29:01,560 BAD EPOCHS (no improvement): 2 |
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2022-11-06 17:29:01,746 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:29:08,975 epoch 73 - iter 27/274 - loss 0.01498789 - samples/sec: 119.60 - lr: 0.025000 |
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2022-11-06 17:29:16,264 epoch 73 - iter 54/274 - loss 0.01459714 - samples/sec: 118.60 - lr: 0.025000 |
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2022-11-06 17:29:23,181 epoch 73 - iter 81/274 - loss 0.01406969 - samples/sec: 124.99 - lr: 0.025000 |
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2022-11-06 17:29:30,119 epoch 73 - iter 108/274 - loss 0.01434969 - samples/sec: 124.59 - lr: 0.025000 |
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2022-11-06 17:29:36,855 epoch 73 - iter 135/274 - loss 0.01409944 - samples/sec: 128.35 - lr: 0.025000 |
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2022-11-06 17:29:43,973 epoch 73 - iter 162/274 - loss 0.01484917 - samples/sec: 121.45 - lr: 0.025000 |
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2022-11-06 17:29:50,692 epoch 73 - iter 189/274 - loss 0.01467239 - samples/sec: 128.67 - lr: 0.025000 |
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2022-11-06 17:29:57,431 epoch 73 - iter 216/274 - loss 0.01479097 - samples/sec: 128.27 - lr: 0.025000 |
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2022-11-06 17:30:03,875 epoch 73 - iter 243/274 - loss 0.01487098 - samples/sec: 134.16 - lr: 0.025000 |
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2022-11-06 17:30:11,263 epoch 73 - iter 270/274 - loss 0.01497898 - samples/sec: 117.01 - lr: 0.025000 |
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2022-11-06 17:30:12,451 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:30:12,451 EPOCH 73 done: loss 0.0151 - lr 0.025000 |
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2022-11-06 17:30:51,446 Evaluating as a multi-label problem: False |
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2022-11-06 17:30:51,474 TEST : loss 0.03126273304224014 - f1-score (micro avg) 0.8584 |
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2022-11-06 17:30:51,963 BAD EPOCHS (no improvement): 0 |
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2022-11-06 17:30:52,157 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:30:58,747 epoch 74 - iter 27/274 - loss 0.01717599 - samples/sec: 131.21 - lr: 0.025000 |
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2022-11-06 17:31:05,728 epoch 74 - iter 54/274 - loss 0.01663389 - samples/sec: 123.83 - lr: 0.025000 |
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2022-11-06 17:31:12,702 epoch 74 - iter 81/274 - loss 0.01680313 - samples/sec: 123.95 - lr: 0.025000 |
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2022-11-06 17:31:19,465 epoch 74 - iter 108/274 - loss 0.01666603 - samples/sec: 127.83 - lr: 0.025000 |
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2022-11-06 17:31:26,337 epoch 74 - iter 135/274 - loss 0.01636185 - samples/sec: 125.81 - lr: 0.025000 |
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2022-11-06 17:31:32,882 epoch 74 - iter 162/274 - loss 0.01586108 - samples/sec: 132.09 - lr: 0.025000 |
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2022-11-06 17:31:39,702 epoch 74 - iter 189/274 - loss 0.01528822 - samples/sec: 126.76 - lr: 0.025000 |
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2022-11-06 17:31:46,629 epoch 74 - iter 216/274 - loss 0.01534615 - samples/sec: 124.79 - lr: 0.025000 |
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2022-11-06 17:31:53,951 epoch 74 - iter 243/274 - loss 0.01530002 - samples/sec: 118.07 - lr: 0.025000 |
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2022-11-06 17:32:01,499 epoch 74 - iter 270/274 - loss 0.01566712 - samples/sec: 114.52 - lr: 0.025000 |
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2022-11-06 17:32:02,508 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:32:02,508 EPOCH 74 done: loss 0.0158 - lr 0.025000 |
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2022-11-06 17:32:41,566 Evaluating as a multi-label problem: False |
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2022-11-06 17:32:41,594 TEST : loss 0.031216170638799667 - f1-score (micro avg) 0.8564 |
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2022-11-06 17:32:42,081 BAD EPOCHS (no improvement): 1 |
|
2022-11-06 17:32:42,278 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 17:32:49,513 epoch 75 - iter 27/274 - loss 0.01578720 - samples/sec: 119.50 - lr: 0.025000 |
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2022-11-06 17:32:56,426 epoch 75 - iter 54/274 - loss 0.01578182 - samples/sec: 125.05 - lr: 0.025000 |
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2022-11-06 17:33:03,985 epoch 75 - iter 81/274 - loss 0.01693581 - samples/sec: 114.36 - lr: 0.025000 |
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2022-11-06 17:33:11,608 epoch 75 - iter 108/274 - loss 0.01638865 - samples/sec: 113.40 - lr: 0.025000 |
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2022-11-06 17:33:18,681 epoch 75 - iter 135/274 - loss 0.01624836 - samples/sec: 122.22 - lr: 0.025000 |
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2022-11-06 17:33:24,468 epoch 75 - iter 162/274 - loss 0.01614484 - samples/sec: 149.40 - lr: 0.025000 |
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2022-11-06 17:33:30,697 epoch 75 - iter 189/274 - loss 0.01587570 - samples/sec: 138.80 - lr: 0.025000 |
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2022-11-06 17:33:37,431 epoch 75 - iter 216/274 - loss 0.01600820 - samples/sec: 128.38 - lr: 0.025000 |
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2022-11-06 17:33:44,261 epoch 75 - iter 243/274 - loss 0.01609265 - samples/sec: 126.56 - lr: 0.025000 |
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2022-11-06 17:33:51,067 epoch 75 - iter 270/274 - loss 0.01603705 - samples/sec: 127.02 - lr: 0.025000 |
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2022-11-06 17:33:52,118 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:33:52,118 EPOCH 75 done: loss 0.0160 - lr 0.025000 |
|
2022-11-06 17:34:32,638 Evaluating as a multi-label problem: False |
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2022-11-06 17:34:32,668 TEST : loss 0.03171336650848389 - f1-score (micro avg) 0.8626 |
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2022-11-06 17:34:33,161 BAD EPOCHS (no improvement): 2 |
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2022-11-06 17:34:33,358 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:34:40,777 epoch 76 - iter 27/274 - loss 0.01831154 - samples/sec: 116.55 - lr: 0.025000 |
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2022-11-06 17:34:48,604 epoch 76 - iter 54/274 - loss 0.01793034 - samples/sec: 110.44 - lr: 0.025000 |
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2022-11-06 17:34:56,298 epoch 76 - iter 81/274 - loss 0.01715389 - samples/sec: 112.35 - lr: 0.025000 |
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2022-11-06 17:35:03,642 epoch 76 - iter 108/274 - loss 0.01643277 - samples/sec: 117.70 - lr: 0.025000 |
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2022-11-06 17:35:10,764 epoch 76 - iter 135/274 - loss 0.01560754 - samples/sec: 121.39 - lr: 0.025000 |
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2022-11-06 17:35:17,966 epoch 76 - iter 162/274 - loss 0.01576625 - samples/sec: 120.03 - lr: 0.025000 |
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2022-11-06 17:35:25,598 epoch 76 - iter 189/274 - loss 0.01570138 - samples/sec: 113.27 - lr: 0.025000 |
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2022-11-06 17:35:33,866 epoch 76 - iter 216/274 - loss 0.01571511 - samples/sec: 104.54 - lr: 0.025000 |
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2022-11-06 17:35:41,556 epoch 76 - iter 243/274 - loss 0.01552739 - samples/sec: 112.42 - lr: 0.025000 |
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2022-11-06 17:35:48,253 epoch 76 - iter 270/274 - loss 0.01539358 - samples/sec: 129.08 - lr: 0.025000 |
|
2022-11-06 17:35:49,110 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:35:49,111 EPOCH 76 done: loss 0.0153 - lr 0.025000 |
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2022-11-06 17:36:29,131 Evaluating as a multi-label problem: False |
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2022-11-06 17:36:29,158 TEST : loss 0.032589372247457504 - f1-score (micro avg) 0.8561 |
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2022-11-06 17:36:29,645 BAD EPOCHS (no improvement): 3 |
|
2022-11-06 17:36:29,834 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 17:36:36,940 epoch 77 - iter 27/274 - loss 0.01386001 - samples/sec: 121.68 - lr: 0.025000 |
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2022-11-06 17:36:43,357 epoch 77 - iter 54/274 - loss 0.01306575 - samples/sec: 134.73 - lr: 0.025000 |
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2022-11-06 17:36:50,201 epoch 77 - iter 81/274 - loss 0.01517313 - samples/sec: 126.31 - lr: 0.025000 |
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2022-11-06 17:36:57,270 epoch 77 - iter 108/274 - loss 0.01532553 - samples/sec: 122.29 - lr: 0.025000 |
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2022-11-06 17:37:04,074 epoch 77 - iter 135/274 - loss 0.01486198 - samples/sec: 127.05 - lr: 0.025000 |
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2022-11-06 17:37:10,935 epoch 77 - iter 162/274 - loss 0.01456990 - samples/sec: 126.00 - lr: 0.025000 |
|
2022-11-06 17:37:18,016 epoch 77 - iter 189/274 - loss 0.01481667 - samples/sec: 122.09 - lr: 0.025000 |
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2022-11-06 17:37:25,328 epoch 77 - iter 216/274 - loss 0.01487554 - samples/sec: 118.22 - lr: 0.025000 |
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2022-11-06 17:37:31,999 epoch 77 - iter 243/274 - loss 0.01498806 - samples/sec: 129.60 - lr: 0.025000 |
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2022-11-06 17:37:38,993 epoch 77 - iter 270/274 - loss 0.01521675 - samples/sec: 123.59 - lr: 0.025000 |
|
2022-11-06 17:37:39,932 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 17:37:39,933 EPOCH 77 done: loss 0.0152 - lr 0.025000 |
|
2022-11-06 17:38:19,080 Evaluating as a multi-label problem: False |
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2022-11-06 17:38:19,108 TEST : loss 0.031240783631801605 - f1-score (micro avg) 0.8586 |
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2022-11-06 17:38:19,593 Epoch 77: reducing learning rate of group 0 to 1.2500e-02. |
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2022-11-06 17:38:19,593 BAD EPOCHS (no improvement): 4 |
|
2022-11-06 17:38:19,780 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:38:27,178 epoch 78 - iter 27/274 - loss 0.01335360 - samples/sec: 116.86 - lr: 0.012500 |
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2022-11-06 17:38:33,630 epoch 78 - iter 54/274 - loss 0.01493181 - samples/sec: 134.00 - lr: 0.012500 |
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2022-11-06 17:38:39,808 epoch 78 - iter 81/274 - loss 0.01481730 - samples/sec: 139.91 - lr: 0.012500 |
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2022-11-06 17:38:47,372 epoch 78 - iter 108/274 - loss 0.01475207 - samples/sec: 114.29 - lr: 0.012500 |
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2022-11-06 17:38:54,466 epoch 78 - iter 135/274 - loss 0.01483267 - samples/sec: 121.84 - lr: 0.012500 |
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2022-11-06 17:39:01,222 epoch 78 - iter 162/274 - loss 0.01512120 - samples/sec: 127.96 - lr: 0.012500 |
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2022-11-06 17:39:08,557 epoch 78 - iter 189/274 - loss 0.01557814 - samples/sec: 117.85 - lr: 0.012500 |
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2022-11-06 17:39:15,485 epoch 78 - iter 216/274 - loss 0.01538250 - samples/sec: 124.76 - lr: 0.012500 |
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2022-11-06 17:39:22,414 epoch 78 - iter 243/274 - loss 0.01562241 - samples/sec: 124.76 - lr: 0.012500 |
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2022-11-06 17:39:28,939 epoch 78 - iter 270/274 - loss 0.01583628 - samples/sec: 132.48 - lr: 0.012500 |
|
2022-11-06 17:39:29,838 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:39:29,838 EPOCH 78 done: loss 0.0157 - lr 0.012500 |
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2022-11-06 17:40:09,022 Evaluating as a multi-label problem: False |
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2022-11-06 17:40:09,050 TEST : loss 0.031696297228336334 - f1-score (micro avg) 0.8578 |
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2022-11-06 17:40:09,536 BAD EPOCHS (no improvement): 1 |
|
2022-11-06 17:40:09,729 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:40:16,293 epoch 79 - iter 27/274 - loss 0.01659307 - samples/sec: 131.73 - lr: 0.012500 |
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2022-11-06 17:40:23,082 epoch 79 - iter 54/274 - loss 0.01471363 - samples/sec: 127.33 - lr: 0.012500 |
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2022-11-06 17:40:29,332 epoch 79 - iter 81/274 - loss 0.01551638 - samples/sec: 138.30 - lr: 0.012500 |
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2022-11-06 17:40:37,063 epoch 79 - iter 108/274 - loss 0.01521622 - samples/sec: 111.82 - lr: 0.012500 |
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2022-11-06 17:40:43,734 epoch 79 - iter 135/274 - loss 0.01443179 - samples/sec: 129.57 - lr: 0.012500 |
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2022-11-06 17:40:50,744 epoch 79 - iter 162/274 - loss 0.01494722 - samples/sec: 123.32 - lr: 0.012500 |
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2022-11-06 17:40:57,748 epoch 79 - iter 189/274 - loss 0.01484071 - samples/sec: 123.42 - lr: 0.012500 |
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2022-11-06 17:41:05,079 epoch 79 - iter 216/274 - loss 0.01474732 - samples/sec: 117.91 - lr: 0.012500 |
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2022-11-06 17:41:11,870 epoch 79 - iter 243/274 - loss 0.01470988 - samples/sec: 127.29 - lr: 0.012500 |
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2022-11-06 17:41:18,318 epoch 79 - iter 270/274 - loss 0.01457411 - samples/sec: 134.07 - lr: 0.012500 |
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2022-11-06 17:41:19,532 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:41:19,532 EPOCH 79 done: loss 0.0147 - lr 0.012500 |
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2022-11-06 17:41:58,340 Evaluating as a multi-label problem: False |
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2022-11-06 17:41:58,368 TEST : loss 0.03271425515413284 - f1-score (micro avg) 0.8541 |
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2022-11-06 17:41:58,856 BAD EPOCHS (no improvement): 0 |
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2022-11-06 17:41:59,051 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:42:05,934 epoch 80 - iter 27/274 - loss 0.01371277 - samples/sec: 125.62 - lr: 0.012500 |
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2022-11-06 17:42:13,074 epoch 80 - iter 54/274 - loss 0.01282598 - samples/sec: 121.06 - lr: 0.012500 |
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2022-11-06 17:42:19,435 epoch 80 - iter 81/274 - loss 0.01254139 - samples/sec: 135.90 - lr: 0.012500 |
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2022-11-06 17:42:26,846 epoch 80 - iter 108/274 - loss 0.01285627 - samples/sec: 116.64 - lr: 0.012500 |
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2022-11-06 17:42:33,992 epoch 80 - iter 135/274 - loss 0.01362570 - samples/sec: 120.97 - lr: 0.012500 |
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2022-11-06 17:42:40,817 epoch 80 - iter 162/274 - loss 0.01380565 - samples/sec: 126.65 - lr: 0.012500 |
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2022-11-06 17:42:47,634 epoch 80 - iter 189/274 - loss 0.01368897 - samples/sec: 126.81 - lr: 0.012500 |
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2022-11-06 17:42:54,397 epoch 80 - iter 216/274 - loss 0.01366941 - samples/sec: 127.82 - lr: 0.012500 |
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2022-11-06 17:43:01,155 epoch 80 - iter 243/274 - loss 0.01379331 - samples/sec: 127.92 - lr: 0.012500 |
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2022-11-06 17:43:08,144 epoch 80 - iter 270/274 - loss 0.01369367 - samples/sec: 123.68 - lr: 0.012500 |
|
2022-11-06 17:43:08,939 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:43:08,939 EPOCH 80 done: loss 0.0138 - lr 0.012500 |
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2022-11-06 17:43:47,876 Evaluating as a multi-label problem: False |
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2022-11-06 17:43:47,903 TEST : loss 0.033087365329265594 - f1-score (micro avg) 0.8601 |
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2022-11-06 17:43:48,388 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 17:43:48,663 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:43:56,720 epoch 81 - iter 27/274 - loss 0.01472430 - samples/sec: 107.32 - lr: 0.012500 |
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2022-11-06 17:44:03,510 epoch 81 - iter 54/274 - loss 0.01558958 - samples/sec: 127.32 - lr: 0.012500 |
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2022-11-06 17:44:10,409 epoch 81 - iter 81/274 - loss 0.01529039 - samples/sec: 125.29 - lr: 0.012500 |
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2022-11-06 17:44:16,744 epoch 81 - iter 108/274 - loss 0.01520453 - samples/sec: 136.46 - lr: 0.012500 |
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2022-11-06 17:44:23,903 epoch 81 - iter 135/274 - loss 0.01485186 - samples/sec: 120.75 - lr: 0.012500 |
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2022-11-06 17:44:30,712 epoch 81 - iter 162/274 - loss 0.01457213 - samples/sec: 126.95 - lr: 0.012500 |
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2022-11-06 17:44:37,476 epoch 81 - iter 189/274 - loss 0.01430525 - samples/sec: 127.80 - lr: 0.012500 |
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2022-11-06 17:44:44,134 epoch 81 - iter 216/274 - loss 0.01407564 - samples/sec: 129.84 - lr: 0.012500 |
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2022-11-06 17:44:51,266 epoch 81 - iter 243/274 - loss 0.01436707 - samples/sec: 121.21 - lr: 0.012500 |
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2022-11-06 17:44:58,475 epoch 81 - iter 270/274 - loss 0.01421268 - samples/sec: 119.91 - lr: 0.012500 |
|
2022-11-06 17:44:59,402 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:44:59,402 EPOCH 81 done: loss 0.0141 - lr 0.012500 |
|
2022-11-06 17:45:38,325 Evaluating as a multi-label problem: False |
|
2022-11-06 17:45:38,353 TEST : loss 0.034334879368543625 - f1-score (micro avg) 0.8536 |
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2022-11-06 17:45:38,841 BAD EPOCHS (no improvement): 1 |
|
2022-11-06 17:45:39,029 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:45:45,813 epoch 82 - iter 27/274 - loss 0.01620736 - samples/sec: 127.46 - lr: 0.012500 |
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2022-11-06 17:45:52,832 epoch 82 - iter 54/274 - loss 0.01553044 - samples/sec: 123.16 - lr: 0.012500 |
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2022-11-06 17:45:59,814 epoch 82 - iter 81/274 - loss 0.01573572 - samples/sec: 123.81 - lr: 0.012500 |
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2022-11-06 17:46:06,004 epoch 82 - iter 108/274 - loss 0.01461916 - samples/sec: 139.66 - lr: 0.012500 |
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2022-11-06 17:46:13,432 epoch 82 - iter 135/274 - loss 0.01512387 - samples/sec: 116.36 - lr: 0.012500 |
|
2022-11-06 17:46:21,226 epoch 82 - iter 162/274 - loss 0.01514539 - samples/sec: 110.90 - lr: 0.012500 |
|
2022-11-06 17:46:27,976 epoch 82 - iter 189/274 - loss 0.01484884 - samples/sec: 128.07 - lr: 0.012500 |
|
2022-11-06 17:46:35,098 epoch 82 - iter 216/274 - loss 0.01475803 - samples/sec: 121.38 - lr: 0.012500 |
|
2022-11-06 17:46:42,072 epoch 82 - iter 243/274 - loss 0.01459842 - samples/sec: 123.95 - lr: 0.012500 |
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2022-11-06 17:46:48,466 epoch 82 - iter 270/274 - loss 0.01460797 - samples/sec: 135.19 - lr: 0.012500 |
|
2022-11-06 17:46:49,457 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:46:49,457 EPOCH 82 done: loss 0.0146 - lr 0.012500 |
|
2022-11-06 17:47:28,446 Evaluating as a multi-label problem: False |
|
2022-11-06 17:47:28,474 TEST : loss 0.03356759995222092 - f1-score (micro avg) 0.8607 |
|
2022-11-06 17:47:28,960 BAD EPOCHS (no improvement): 2 |
|
2022-11-06 17:47:29,156 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 17:47:36,204 epoch 83 - iter 27/274 - loss 0.01390934 - samples/sec: 122.69 - lr: 0.012500 |
|
2022-11-06 17:47:43,182 epoch 83 - iter 54/274 - loss 0.01342322 - samples/sec: 123.87 - lr: 0.012500 |
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2022-11-06 17:47:49,819 epoch 83 - iter 81/274 - loss 0.01510934 - samples/sec: 130.25 - lr: 0.012500 |
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2022-11-06 17:47:55,920 epoch 83 - iter 108/274 - loss 0.01466472 - samples/sec: 141.71 - lr: 0.012500 |
|
2022-11-06 17:48:02,838 epoch 83 - iter 135/274 - loss 0.01454476 - samples/sec: 124.95 - lr: 0.012500 |
|
2022-11-06 17:48:09,774 epoch 83 - iter 162/274 - loss 0.01431669 - samples/sec: 124.63 - lr: 0.012500 |
|
2022-11-06 17:48:17,014 epoch 83 - iter 189/274 - loss 0.01463776 - samples/sec: 119.40 - lr: 0.012500 |
|
2022-11-06 17:48:24,234 epoch 83 - iter 216/274 - loss 0.01425036 - samples/sec: 119.72 - lr: 0.012500 |
|
2022-11-06 17:48:31,204 epoch 83 - iter 243/274 - loss 0.01449536 - samples/sec: 124.03 - lr: 0.012500 |
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2022-11-06 17:48:38,392 epoch 83 - iter 270/274 - loss 0.01442531 - samples/sec: 120.26 - lr: 0.012500 |
|
2022-11-06 17:48:39,278 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 17:48:39,278 EPOCH 83 done: loss 0.0144 - lr 0.012500 |
|
2022-11-06 17:49:18,235 Evaluating as a multi-label problem: False |
|
2022-11-06 17:49:18,263 TEST : loss 0.03331308811903 - f1-score (micro avg) 0.8573 |
|
2022-11-06 17:49:18,750 BAD EPOCHS (no improvement): 3 |
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2022-11-06 17:49:18,946 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:49:26,652 epoch 84 - iter 27/274 - loss 0.01472939 - samples/sec: 112.18 - lr: 0.012500 |
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2022-11-06 17:49:33,375 epoch 84 - iter 54/274 - loss 0.01525577 - samples/sec: 128.58 - lr: 0.012500 |
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2022-11-06 17:49:40,197 epoch 84 - iter 81/274 - loss 0.01448478 - samples/sec: 126.72 - lr: 0.012500 |
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2022-11-06 17:49:47,269 epoch 84 - iter 108/274 - loss 0.01516433 - samples/sec: 122.22 - lr: 0.012500 |
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2022-11-06 17:49:54,347 epoch 84 - iter 135/274 - loss 0.01481793 - samples/sec: 122.13 - lr: 0.012500 |
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2022-11-06 17:50:01,260 epoch 84 - iter 162/274 - loss 0.01458997 - samples/sec: 125.05 - lr: 0.012500 |
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2022-11-06 17:50:08,048 epoch 84 - iter 189/274 - loss 0.01467858 - samples/sec: 127.35 - lr: 0.012500 |
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2022-11-06 17:50:14,725 epoch 84 - iter 216/274 - loss 0.01454278 - samples/sec: 129.45 - lr: 0.012500 |
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2022-11-06 17:50:21,758 epoch 84 - iter 243/274 - loss 0.01460313 - samples/sec: 122.92 - lr: 0.012500 |
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2022-11-06 17:50:28,307 epoch 84 - iter 270/274 - loss 0.01442134 - samples/sec: 131.98 - lr: 0.012500 |
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2022-11-06 17:50:29,435 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:50:29,435 EPOCH 84 done: loss 0.0144 - lr 0.012500 |
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2022-11-06 17:51:08,452 Evaluating as a multi-label problem: False |
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2022-11-06 17:51:08,480 TEST : loss 0.0335269495844841 - f1-score (micro avg) 0.8604 |
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2022-11-06 17:51:08,964 Epoch 84: reducing learning rate of group 0 to 6.2500e-03. |
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2022-11-06 17:51:08,965 BAD EPOCHS (no improvement): 4 |
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2022-11-06 17:51:09,160 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:51:16,107 epoch 85 - iter 27/274 - loss 0.01504540 - samples/sec: 124.48 - lr: 0.006250 |
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2022-11-06 17:51:23,227 epoch 85 - iter 54/274 - loss 0.01397214 - samples/sec: 121.41 - lr: 0.006250 |
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2022-11-06 17:51:30,006 epoch 85 - iter 81/274 - loss 0.01485455 - samples/sec: 127.50 - lr: 0.006250 |
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2022-11-06 17:51:36,798 epoch 85 - iter 108/274 - loss 0.01509272 - samples/sec: 127.27 - lr: 0.006250 |
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2022-11-06 17:51:43,360 epoch 85 - iter 135/274 - loss 0.01473064 - samples/sec: 131.74 - lr: 0.006250 |
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2022-11-06 17:51:50,704 epoch 85 - iter 162/274 - loss 0.01453354 - samples/sec: 117.70 - lr: 0.006250 |
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2022-11-06 17:51:58,454 epoch 85 - iter 189/274 - loss 0.01477549 - samples/sec: 111.54 - lr: 0.006250 |
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2022-11-06 17:52:05,259 epoch 85 - iter 216/274 - loss 0.01463444 - samples/sec: 127.02 - lr: 0.006250 |
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2022-11-06 17:52:12,109 epoch 85 - iter 243/274 - loss 0.01437277 - samples/sec: 126.20 - lr: 0.006250 |
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2022-11-06 17:52:18,986 epoch 85 - iter 270/274 - loss 0.01428756 - samples/sec: 125.69 - lr: 0.006250 |
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2022-11-06 17:52:19,804 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:52:19,804 EPOCH 85 done: loss 0.0142 - lr 0.006250 |
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2022-11-06 17:52:58,463 Evaluating as a multi-label problem: False |
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2022-11-06 17:52:58,491 TEST : loss 0.033432383090257645 - f1-score (micro avg) 0.8586 |
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2022-11-06 17:52:58,978 BAD EPOCHS (no improvement): 1 |
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2022-11-06 17:52:59,166 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:53:06,255 epoch 86 - iter 27/274 - loss 0.01443914 - samples/sec: 121.96 - lr: 0.006250 |
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2022-11-06 17:53:13,550 epoch 86 - iter 54/274 - loss 0.01410595 - samples/sec: 118.50 - lr: 0.006250 |
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2022-11-06 17:53:20,735 epoch 86 - iter 81/274 - loss 0.01405715 - samples/sec: 120.30 - lr: 0.006250 |
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2022-11-06 17:53:27,159 epoch 86 - iter 108/274 - loss 0.01447808 - samples/sec: 134.57 - lr: 0.006250 |
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2022-11-06 17:53:33,882 epoch 86 - iter 135/274 - loss 0.01453162 - samples/sec: 128.58 - lr: 0.006250 |
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2022-11-06 17:53:40,244 epoch 86 - iter 162/274 - loss 0.01429897 - samples/sec: 135.88 - lr: 0.006250 |
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2022-11-06 17:53:47,513 epoch 86 - iter 189/274 - loss 0.01421391 - samples/sec: 118.91 - lr: 0.006250 |
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2022-11-06 17:53:54,207 epoch 86 - iter 216/274 - loss 0.01425020 - samples/sec: 129.14 - lr: 0.006250 |
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2022-11-06 17:54:00,821 epoch 86 - iter 243/274 - loss 0.01420002 - samples/sec: 130.71 - lr: 0.006250 |
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2022-11-06 17:54:08,004 epoch 86 - iter 270/274 - loss 0.01423439 - samples/sec: 120.35 - lr: 0.006250 |
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2022-11-06 17:54:09,150 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:54:09,151 EPOCH 86 done: loss 0.0145 - lr 0.006250 |
|
2022-11-06 17:54:48,147 Evaluating as a multi-label problem: False |
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2022-11-06 17:54:48,175 TEST : loss 0.03346378728747368 - f1-score (micro avg) 0.8596 |
|
2022-11-06 17:54:48,662 BAD EPOCHS (no improvement): 2 |
|
2022-11-06 17:54:48,857 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 17:54:55,576 epoch 87 - iter 27/274 - loss 0.01408922 - samples/sec: 128.69 - lr: 0.006250 |
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2022-11-06 17:55:02,463 epoch 87 - iter 54/274 - loss 0.01484753 - samples/sec: 125.53 - lr: 0.006250 |
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2022-11-06 17:55:09,809 epoch 87 - iter 81/274 - loss 0.01507213 - samples/sec: 117.66 - lr: 0.006250 |
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2022-11-06 17:55:17,351 epoch 87 - iter 108/274 - loss 0.01424005 - samples/sec: 114.61 - lr: 0.006250 |
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2022-11-06 17:55:23,951 epoch 87 - iter 135/274 - loss 0.01455797 - samples/sec: 130.98 - lr: 0.006250 |
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2022-11-06 17:55:30,015 epoch 87 - iter 162/274 - loss 0.01417278 - samples/sec: 142.57 - lr: 0.006250 |
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2022-11-06 17:55:37,059 epoch 87 - iter 189/274 - loss 0.01439724 - samples/sec: 122.72 - lr: 0.006250 |
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2022-11-06 17:55:43,842 epoch 87 - iter 216/274 - loss 0.01482814 - samples/sec: 127.43 - lr: 0.006250 |
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2022-11-06 17:55:50,274 epoch 87 - iter 243/274 - loss 0.01444523 - samples/sec: 134.40 - lr: 0.006250 |
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2022-11-06 17:55:57,468 epoch 87 - iter 270/274 - loss 0.01458826 - samples/sec: 120.17 - lr: 0.006250 |
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2022-11-06 17:55:58,433 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:55:58,434 EPOCH 87 done: loss 0.0146 - lr 0.006250 |
|
2022-11-06 17:56:37,400 Evaluating as a multi-label problem: False |
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2022-11-06 17:56:37,428 TEST : loss 0.03315354138612747 - f1-score (micro avg) 0.8555 |
|
2022-11-06 17:56:37,914 BAD EPOCHS (no improvement): 3 |
|
2022-11-06 17:56:38,110 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:56:45,310 epoch 88 - iter 27/274 - loss 0.01554221 - samples/sec: 120.09 - lr: 0.006250 |
|
2022-11-06 17:56:52,810 epoch 88 - iter 54/274 - loss 0.01515614 - samples/sec: 115.25 - lr: 0.006250 |
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2022-11-06 17:56:59,856 epoch 88 - iter 81/274 - loss 0.01392380 - samples/sec: 122.69 - lr: 0.006250 |
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2022-11-06 17:57:06,736 epoch 88 - iter 108/274 - loss 0.01483885 - samples/sec: 125.64 - lr: 0.006250 |
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2022-11-06 17:57:13,932 epoch 88 - iter 135/274 - loss 0.01387559 - samples/sec: 120.13 - lr: 0.006250 |
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2022-11-06 17:57:20,521 epoch 88 - iter 162/274 - loss 0.01395838 - samples/sec: 131.18 - lr: 0.006250 |
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2022-11-06 17:57:27,598 epoch 88 - iter 189/274 - loss 0.01398869 - samples/sec: 122.16 - lr: 0.006250 |
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2022-11-06 17:57:34,085 epoch 88 - iter 216/274 - loss 0.01419572 - samples/sec: 133.26 - lr: 0.006250 |
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2022-11-06 17:57:41,030 epoch 88 - iter 243/274 - loss 0.01442811 - samples/sec: 124.46 - lr: 0.006250 |
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2022-11-06 17:57:47,480 epoch 88 - iter 270/274 - loss 0.01445280 - samples/sec: 134.04 - lr: 0.006250 |
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2022-11-06 17:57:48,418 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:57:48,418 EPOCH 88 done: loss 0.0144 - lr 0.006250 |
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2022-11-06 17:58:27,167 Evaluating as a multi-label problem: False |
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2022-11-06 17:58:27,194 TEST : loss 0.032923195511102676 - f1-score (micro avg) 0.8578 |
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2022-11-06 17:58:27,679 Epoch 88: reducing learning rate of group 0 to 3.1250e-03. |
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2022-11-06 17:58:27,680 BAD EPOCHS (no improvement): 4 |
|
2022-11-06 17:58:27,875 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:58:34,720 epoch 89 - iter 27/274 - loss 0.01555709 - samples/sec: 126.32 - lr: 0.003125 |
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2022-11-06 17:58:41,380 epoch 89 - iter 54/274 - loss 0.01417627 - samples/sec: 129.79 - lr: 0.003125 |
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2022-11-06 17:58:48,516 epoch 89 - iter 81/274 - loss 0.01538001 - samples/sec: 121.15 - lr: 0.003125 |
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2022-11-06 17:58:55,789 epoch 89 - iter 108/274 - loss 0.01481134 - samples/sec: 118.85 - lr: 0.003125 |
|
2022-11-06 17:59:02,716 epoch 89 - iter 135/274 - loss 0.01499577 - samples/sec: 124.79 - lr: 0.003125 |
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2022-11-06 17:59:09,838 epoch 89 - iter 162/274 - loss 0.01484335 - samples/sec: 121.37 - lr: 0.003125 |
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2022-11-06 17:59:16,445 epoch 89 - iter 189/274 - loss 0.01445447 - samples/sec: 130.84 - lr: 0.003125 |
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2022-11-06 17:59:23,544 epoch 89 - iter 216/274 - loss 0.01409136 - samples/sec: 121.77 - lr: 0.003125 |
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2022-11-06 17:59:30,386 epoch 89 - iter 243/274 - loss 0.01431538 - samples/sec: 126.35 - lr: 0.003125 |
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2022-11-06 17:59:37,209 epoch 89 - iter 270/274 - loss 0.01439537 - samples/sec: 126.68 - lr: 0.003125 |
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2022-11-06 17:59:38,253 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 17:59:38,253 EPOCH 89 done: loss 0.0144 - lr 0.003125 |
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2022-11-06 18:00:17,287 Evaluating as a multi-label problem: False |
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2022-11-06 18:00:17,314 TEST : loss 0.033024467527866364 - f1-score (micro avg) 0.8602 |
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2022-11-06 18:00:17,800 BAD EPOCHS (no improvement): 1 |
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2022-11-06 18:00:17,988 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 18:00:25,291 epoch 90 - iter 27/274 - loss 0.01682619 - samples/sec: 118.39 - lr: 0.003125 |
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2022-11-06 18:00:31,883 epoch 90 - iter 54/274 - loss 0.01399250 - samples/sec: 131.12 - lr: 0.003125 |
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2022-11-06 18:00:39,011 epoch 90 - iter 81/274 - loss 0.01455934 - samples/sec: 121.27 - lr: 0.003125 |
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2022-11-06 18:00:46,654 epoch 90 - iter 108/274 - loss 0.01423489 - samples/sec: 113.10 - lr: 0.003125 |
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2022-11-06 18:00:53,516 epoch 90 - iter 135/274 - loss 0.01426972 - samples/sec: 125.99 - lr: 0.003125 |
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2022-11-06 18:01:00,487 epoch 90 - iter 162/274 - loss 0.01489659 - samples/sec: 124.00 - lr: 0.003125 |
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2022-11-06 18:01:07,234 epoch 90 - iter 189/274 - loss 0.01435830 - samples/sec: 128.12 - lr: 0.003125 |
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2022-11-06 18:01:13,869 epoch 90 - iter 216/274 - loss 0.01372784 - samples/sec: 130.29 - lr: 0.003125 |
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2022-11-06 18:01:20,485 epoch 90 - iter 243/274 - loss 0.01375024 - samples/sec: 130.66 - lr: 0.003125 |
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2022-11-06 18:01:27,165 epoch 90 - iter 270/274 - loss 0.01391123 - samples/sec: 129.42 - lr: 0.003125 |
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2022-11-06 18:01:28,310 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 18:01:28,310 EPOCH 90 done: loss 0.0140 - lr 0.003125 |
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2022-11-06 18:02:07,346 Evaluating as a multi-label problem: False |
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2022-11-06 18:02:07,374 TEST : loss 0.03315744176506996 - f1-score (micro avg) 0.8611 |
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2022-11-06 18:02:07,860 BAD EPOCHS (no improvement): 2 |
|
2022-11-06 18:02:08,055 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 18:02:14,610 epoch 91 - iter 27/274 - loss 0.01485026 - samples/sec: 131.92 - lr: 0.003125 |
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2022-11-06 18:02:21,416 epoch 91 - iter 54/274 - loss 0.01399412 - samples/sec: 127.01 - lr: 0.003125 |
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2022-11-06 18:02:28,577 epoch 91 - iter 81/274 - loss 0.01414092 - samples/sec: 120.72 - lr: 0.003125 |
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2022-11-06 18:02:36,350 epoch 91 - iter 108/274 - loss 0.01405876 - samples/sec: 111.20 - lr: 0.003125 |
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2022-11-06 18:02:42,803 epoch 91 - iter 135/274 - loss 0.01455530 - samples/sec: 133.96 - lr: 0.003125 |
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2022-11-06 18:02:49,612 epoch 91 - iter 162/274 - loss 0.01445301 - samples/sec: 126.96 - lr: 0.003125 |
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2022-11-06 18:02:55,814 epoch 91 - iter 189/274 - loss 0.01438419 - samples/sec: 139.38 - lr: 0.003125 |
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2022-11-06 18:03:02,882 epoch 91 - iter 216/274 - loss 0.01417121 - samples/sec: 122.30 - lr: 0.003125 |
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2022-11-06 18:03:10,248 epoch 91 - iter 243/274 - loss 0.01415182 - samples/sec: 117.35 - lr: 0.003125 |
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2022-11-06 18:03:17,370 epoch 91 - iter 270/274 - loss 0.01441556 - samples/sec: 121.38 - lr: 0.003125 |
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2022-11-06 18:03:18,262 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 18:03:18,262 EPOCH 91 done: loss 0.0144 - lr 0.003125 |
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2022-11-06 18:03:57,372 Evaluating as a multi-label problem: False |
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2022-11-06 18:03:57,400 TEST : loss 0.03293454274535179 - f1-score (micro avg) 0.8585 |
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2022-11-06 18:03:57,886 BAD EPOCHS (no improvement): 3 |
|
2022-11-06 18:03:58,078 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 18:04:05,365 epoch 92 - iter 27/274 - loss 0.01414109 - samples/sec: 118.65 - lr: 0.003125 |
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2022-11-06 18:04:12,026 epoch 92 - iter 54/274 - loss 0.01393229 - samples/sec: 129.78 - lr: 0.003125 |
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2022-11-06 18:04:18,771 epoch 92 - iter 81/274 - loss 0.01423861 - samples/sec: 128.16 - lr: 0.003125 |
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2022-11-06 18:04:25,438 epoch 92 - iter 108/274 - loss 0.01365481 - samples/sec: 129.67 - lr: 0.003125 |
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2022-11-06 18:04:32,410 epoch 92 - iter 135/274 - loss 0.01366917 - samples/sec: 123.98 - lr: 0.003125 |
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2022-11-06 18:04:39,656 epoch 92 - iter 162/274 - loss 0.01416809 - samples/sec: 119.30 - lr: 0.003125 |
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2022-11-06 18:04:45,576 epoch 92 - iter 189/274 - loss 0.01414786 - samples/sec: 146.04 - lr: 0.003125 |
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2022-11-06 18:04:52,079 epoch 92 - iter 216/274 - loss 0.01389831 - samples/sec: 132.92 - lr: 0.003125 |
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2022-11-06 18:04:59,488 epoch 92 - iter 243/274 - loss 0.01410677 - samples/sec: 116.68 - lr: 0.003125 |
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2022-11-06 18:05:06,855 epoch 92 - iter 270/274 - loss 0.01411694 - samples/sec: 117.32 - lr: 0.003125 |
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2022-11-06 18:05:07,946 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 18:05:07,946 EPOCH 92 done: loss 0.0141 - lr 0.003125 |
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2022-11-06 18:05:46,789 Evaluating as a multi-label problem: False |
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2022-11-06 18:05:46,817 TEST : loss 0.03319080173969269 - f1-score (micro avg) 0.8597 |
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2022-11-06 18:05:47,305 Epoch 92: reducing learning rate of group 0 to 1.5625e-03. |
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2022-11-06 18:05:47,306 BAD EPOCHS (no improvement): 4 |
|
2022-11-06 18:05:47,503 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 18:05:54,734 epoch 93 - iter 27/274 - loss 0.01404453 - samples/sec: 119.57 - lr: 0.001563 |
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2022-11-06 18:06:02,242 epoch 93 - iter 54/274 - loss 0.01520985 - samples/sec: 115.14 - lr: 0.001563 |
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2022-11-06 18:06:09,231 epoch 93 - iter 81/274 - loss 0.01428365 - samples/sec: 123.69 - lr: 0.001563 |
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2022-11-06 18:06:16,170 epoch 93 - iter 108/274 - loss 0.01418739 - samples/sec: 124.57 - lr: 0.001563 |
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2022-11-06 18:06:22,642 epoch 93 - iter 135/274 - loss 0.01468654 - samples/sec: 133.57 - lr: 0.001563 |
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2022-11-06 18:06:29,811 epoch 93 - iter 162/274 - loss 0.01503371 - samples/sec: 120.59 - lr: 0.001563 |
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2022-11-06 18:06:35,860 epoch 93 - iter 189/274 - loss 0.01434111 - samples/sec: 142.90 - lr: 0.001563 |
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2022-11-06 18:06:42,080 epoch 93 - iter 216/274 - loss 0.01445581 - samples/sec: 139.00 - lr: 0.001563 |
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2022-11-06 18:06:49,319 epoch 93 - iter 243/274 - loss 0.01434473 - samples/sec: 119.41 - lr: 0.001563 |
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2022-11-06 18:06:56,628 epoch 93 - iter 270/274 - loss 0.01443864 - samples/sec: 118.27 - lr: 0.001563 |
|
2022-11-06 18:06:57,857 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 18:06:57,857 EPOCH 93 done: loss 0.0143 - lr 0.001563 |
|
2022-11-06 18:07:36,676 Evaluating as a multi-label problem: False |
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2022-11-06 18:07:36,704 TEST : loss 0.03328932076692581 - f1-score (micro avg) 0.8605 |
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2022-11-06 18:07:37,191 BAD EPOCHS (no improvement): 1 |
|
2022-11-06 18:07:37,379 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 18:07:44,008 epoch 94 - iter 27/274 - loss 0.01557933 - samples/sec: 130.44 - lr: 0.001563 |
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2022-11-06 18:07:50,720 epoch 94 - iter 54/274 - loss 0.01413440 - samples/sec: 128.79 - lr: 0.001563 |
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2022-11-06 18:07:57,727 epoch 94 - iter 81/274 - loss 0.01475105 - samples/sec: 123.38 - lr: 0.001563 |
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2022-11-06 18:08:04,926 epoch 94 - iter 108/274 - loss 0.01521216 - samples/sec: 120.07 - lr: 0.001563 |
|
2022-11-06 18:08:12,698 epoch 94 - iter 135/274 - loss 0.01632941 - samples/sec: 111.23 - lr: 0.001563 |
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2022-11-06 18:08:19,856 epoch 94 - iter 162/274 - loss 0.01560526 - samples/sec: 120.76 - lr: 0.001563 |
|
2022-11-06 18:08:26,828 epoch 94 - iter 189/274 - loss 0.01499817 - samples/sec: 123.99 - lr: 0.001563 |
|
2022-11-06 18:08:33,219 epoch 94 - iter 216/274 - loss 0.01483912 - samples/sec: 135.25 - lr: 0.001563 |
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2022-11-06 18:08:39,715 epoch 94 - iter 243/274 - loss 0.01486392 - samples/sec: 133.07 - lr: 0.001563 |
|
2022-11-06 18:08:46,222 epoch 94 - iter 270/274 - loss 0.01497467 - samples/sec: 132.84 - lr: 0.001563 |
|
2022-11-06 18:08:47,148 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 18:08:47,149 EPOCH 94 done: loss 0.0149 - lr 0.001563 |
|
2022-11-06 18:09:26,544 Evaluating as a multi-label problem: False |
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2022-11-06 18:09:26,572 TEST : loss 0.033291514962911606 - f1-score (micro avg) 0.8599 |
|
2022-11-06 18:09:27,060 BAD EPOCHS (no improvement): 2 |
|
2022-11-06 18:09:27,253 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 18:09:34,044 epoch 95 - iter 27/274 - loss 0.01317662 - samples/sec: 127.34 - lr: 0.001563 |
|
2022-11-06 18:09:41,073 epoch 95 - iter 54/274 - loss 0.01293760 - samples/sec: 122.98 - lr: 0.001563 |
|
2022-11-06 18:09:48,592 epoch 95 - iter 81/274 - loss 0.01330761 - samples/sec: 114.95 - lr: 0.001563 |
|
2022-11-06 18:09:55,710 epoch 95 - iter 108/274 - loss 0.01373439 - samples/sec: 121.46 - lr: 0.001563 |
|
2022-11-06 18:10:02,634 epoch 95 - iter 135/274 - loss 0.01415330 - samples/sec: 124.83 - lr: 0.001563 |
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2022-11-06 18:10:09,642 epoch 95 - iter 162/274 - loss 0.01427005 - samples/sec: 123.36 - lr: 0.001563 |
|
2022-11-06 18:10:16,585 epoch 95 - iter 189/274 - loss 0.01447179 - samples/sec: 124.50 - lr: 0.001563 |
|
2022-11-06 18:10:23,026 epoch 95 - iter 216/274 - loss 0.01430745 - samples/sec: 134.22 - lr: 0.001563 |
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2022-11-06 18:10:29,559 epoch 95 - iter 243/274 - loss 0.01444554 - samples/sec: 132.32 - lr: 0.001563 |
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2022-11-06 18:10:36,591 epoch 95 - iter 270/274 - loss 0.01460769 - samples/sec: 122.92 - lr: 0.001563 |
|
2022-11-06 18:10:37,580 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 18:10:37,580 EPOCH 95 done: loss 0.0146 - lr 0.001563 |
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2022-11-06 18:11:16,832 Evaluating as a multi-label problem: False |
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2022-11-06 18:11:16,860 TEST : loss 0.03295719251036644 - f1-score (micro avg) 0.8606 |
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2022-11-06 18:11:17,347 BAD EPOCHS (no improvement): 3 |
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2022-11-06 18:11:17,543 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 18:11:24,304 epoch 96 - iter 27/274 - loss 0.01514952 - samples/sec: 127.90 - lr: 0.001563 |
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2022-11-06 18:11:31,580 epoch 96 - iter 54/274 - loss 0.01473187 - samples/sec: 118.80 - lr: 0.001563 |
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2022-11-06 18:11:38,422 epoch 96 - iter 81/274 - loss 0.01449173 - samples/sec: 126.34 - lr: 0.001563 |
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2022-11-06 18:11:45,596 epoch 96 - iter 108/274 - loss 0.01358909 - samples/sec: 120.49 - lr: 0.001563 |
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2022-11-06 18:11:52,333 epoch 96 - iter 135/274 - loss 0.01316116 - samples/sec: 128.32 - lr: 0.001563 |
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2022-11-06 18:11:59,181 epoch 96 - iter 162/274 - loss 0.01250126 - samples/sec: 126.23 - lr: 0.001563 |
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2022-11-06 18:12:06,391 epoch 96 - iter 189/274 - loss 0.01303754 - samples/sec: 119.89 - lr: 0.001563 |
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2022-11-06 18:12:14,065 epoch 96 - iter 216/274 - loss 0.01342865 - samples/sec: 112.64 - lr: 0.001563 |
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2022-11-06 18:12:20,797 epoch 96 - iter 243/274 - loss 0.01409094 - samples/sec: 128.41 - lr: 0.001563 |
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2022-11-06 18:12:27,485 epoch 96 - iter 270/274 - loss 0.01388101 - samples/sec: 129.26 - lr: 0.001563 |
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2022-11-06 18:12:28,667 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 18:12:28,667 EPOCH 96 done: loss 0.0139 - lr 0.001563 |
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2022-11-06 18:13:08,563 Evaluating as a multi-label problem: False |
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2022-11-06 18:13:08,590 TEST : loss 0.03304421156644821 - f1-score (micro avg) 0.8606 |
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2022-11-06 18:13:09,072 Epoch 96: reducing learning rate of group 0 to 7.8125e-04. |
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2022-11-06 18:13:09,073 BAD EPOCHS (no improvement): 4 |
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2022-11-06 18:13:09,267 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 18:13:15,817 epoch 97 - iter 27/274 - loss 0.01631886 - samples/sec: 132.00 - lr: 0.000781 |
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2022-11-06 18:13:22,896 epoch 97 - iter 54/274 - loss 0.01535972 - samples/sec: 122.12 - lr: 0.000781 |
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2022-11-06 18:13:29,863 epoch 97 - iter 81/274 - loss 0.01559975 - samples/sec: 124.08 - lr: 0.000781 |
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2022-11-06 18:13:37,045 epoch 97 - iter 108/274 - loss 0.01552846 - samples/sec: 120.36 - lr: 0.000781 |
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2022-11-06 18:13:43,597 epoch 97 - iter 135/274 - loss 0.01504519 - samples/sec: 131.93 - lr: 0.000781 |
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2022-11-06 18:13:50,545 epoch 97 - iter 162/274 - loss 0.01474325 - samples/sec: 124.42 - lr: 0.000781 |
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2022-11-06 18:13:57,666 epoch 97 - iter 189/274 - loss 0.01400552 - samples/sec: 121.40 - lr: 0.000781 |
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2022-11-06 18:14:04,586 epoch 97 - iter 216/274 - loss 0.01384067 - samples/sec: 124.91 - lr: 0.000781 |
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2022-11-06 18:14:11,062 epoch 97 - iter 243/274 - loss 0.01404010 - samples/sec: 133.49 - lr: 0.000781 |
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2022-11-06 18:14:17,890 epoch 97 - iter 270/274 - loss 0.01404755 - samples/sec: 126.60 - lr: 0.000781 |
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2022-11-06 18:14:18,873 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 18:14:18,873 EPOCH 97 done: loss 0.0141 - lr 0.000781 |
|
2022-11-06 18:14:58,380 Evaluating as a multi-label problem: False |
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2022-11-06 18:14:58,408 TEST : loss 0.03304709866642952 - f1-score (micro avg) 0.861 |
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2022-11-06 18:14:58,894 BAD EPOCHS (no improvement): 1 |
|
2022-11-06 18:14:59,080 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 18:15:05,047 epoch 98 - iter 27/274 - loss 0.01350572 - samples/sec: 144.94 - lr: 0.000781 |
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2022-11-06 18:15:12,358 epoch 98 - iter 54/274 - loss 0.01212826 - samples/sec: 118.22 - lr: 0.000781 |
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2022-11-06 18:15:19,614 epoch 98 - iter 81/274 - loss 0.01310284 - samples/sec: 119.14 - lr: 0.000781 |
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2022-11-06 18:15:26,320 epoch 98 - iter 108/274 - loss 0.01301561 - samples/sec: 128.91 - lr: 0.000781 |
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2022-11-06 18:15:33,631 epoch 98 - iter 135/274 - loss 0.01368174 - samples/sec: 118.24 - lr: 0.000781 |
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2022-11-06 18:15:40,368 epoch 98 - iter 162/274 - loss 0.01402531 - samples/sec: 128.30 - lr: 0.000781 |
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2022-11-06 18:15:47,197 epoch 98 - iter 189/274 - loss 0.01392584 - samples/sec: 126.60 - lr: 0.000781 |
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2022-11-06 18:15:54,585 epoch 98 - iter 216/274 - loss 0.01368373 - samples/sec: 117.00 - lr: 0.000781 |
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2022-11-06 18:16:01,228 epoch 98 - iter 243/274 - loss 0.01388010 - samples/sec: 130.13 - lr: 0.000781 |
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2022-11-06 18:16:08,048 epoch 98 - iter 270/274 - loss 0.01391714 - samples/sec: 126.75 - lr: 0.000781 |
|
2022-11-06 18:16:08,947 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 18:16:08,947 EPOCH 98 done: loss 0.0139 - lr 0.000781 |
|
2022-11-06 18:16:48,480 Evaluating as a multi-label problem: False |
|
2022-11-06 18:16:48,508 TEST : loss 0.03312483802437782 - f1-score (micro avg) 0.8602 |
|
2022-11-06 18:16:48,994 BAD EPOCHS (no improvement): 2 |
|
2022-11-06 18:16:49,188 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 18:16:55,673 epoch 99 - iter 27/274 - loss 0.01303624 - samples/sec: 133.34 - lr: 0.000781 |
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2022-11-06 18:17:02,399 epoch 99 - iter 54/274 - loss 0.01388468 - samples/sec: 128.52 - lr: 0.000781 |
|
2022-11-06 18:17:09,003 epoch 99 - iter 81/274 - loss 0.01343001 - samples/sec: 130.90 - lr: 0.000781 |
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2022-11-06 18:17:15,821 epoch 99 - iter 108/274 - loss 0.01293737 - samples/sec: 126.79 - lr: 0.000781 |
|
2022-11-06 18:17:22,900 epoch 99 - iter 135/274 - loss 0.01313668 - samples/sec: 122.11 - lr: 0.000781 |
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2022-11-06 18:17:29,937 epoch 99 - iter 162/274 - loss 0.01360766 - samples/sec: 122.84 - lr: 0.000781 |
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2022-11-06 18:17:36,715 epoch 99 - iter 189/274 - loss 0.01328352 - samples/sec: 127.53 - lr: 0.000781 |
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2022-11-06 18:17:44,027 epoch 99 - iter 216/274 - loss 0.01336622 - samples/sec: 118.21 - lr: 0.000781 |
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2022-11-06 18:17:50,929 epoch 99 - iter 243/274 - loss 0.01332725 - samples/sec: 125.24 - lr: 0.000781 |
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2022-11-06 18:17:57,622 epoch 99 - iter 270/274 - loss 0.01354757 - samples/sec: 129.16 - lr: 0.000781 |
|
2022-11-06 18:17:58,599 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 18:17:58,599 EPOCH 99 done: loss 0.0135 - lr 0.000781 |
|
2022-11-06 18:18:38,149 Evaluating as a multi-label problem: False |
|
2022-11-06 18:18:38,176 TEST : loss 0.03310050442814827 - f1-score (micro avg) 0.8606 |
|
2022-11-06 18:18:38,662 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 18:18:38,858 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 18:18:45,478 epoch 100 - iter 27/274 - loss 0.01173419 - samples/sec: 130.62 - lr: 0.000781 |
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2022-11-06 18:18:51,890 epoch 100 - iter 54/274 - loss 0.01067812 - samples/sec: 134.80 - lr: 0.000781 |
|
2022-11-06 18:18:59,336 epoch 100 - iter 81/274 - loss 0.01119261 - samples/sec: 116.10 - lr: 0.000781 |
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2022-11-06 18:19:05,854 epoch 100 - iter 108/274 - loss 0.01196095 - samples/sec: 132.63 - lr: 0.000781 |
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2022-11-06 18:19:12,887 epoch 100 - iter 135/274 - loss 0.01302049 - samples/sec: 122.90 - lr: 0.000781 |
|
2022-11-06 18:19:19,651 epoch 100 - iter 162/274 - loss 0.01351319 - samples/sec: 127.82 - lr: 0.000781 |
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2022-11-06 18:19:26,365 epoch 100 - iter 189/274 - loss 0.01352599 - samples/sec: 128.74 - lr: 0.000781 |
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2022-11-06 18:19:33,829 epoch 100 - iter 216/274 - loss 0.01371320 - samples/sec: 115.81 - lr: 0.000781 |
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2022-11-06 18:19:40,623 epoch 100 - iter 243/274 - loss 0.01386506 - samples/sec: 127.24 - lr: 0.000781 |
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2022-11-06 18:19:47,322 epoch 100 - iter 270/274 - loss 0.01403802 - samples/sec: 129.04 - lr: 0.000781 |
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2022-11-06 18:19:48,107 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 18:19:48,107 EPOCH 100 done: loss 0.0142 - lr 0.000781 |
|
2022-11-06 18:20:27,758 Evaluating as a multi-label problem: False |
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2022-11-06 18:20:27,786 TEST : loss 0.033117882907390594 - f1-score (micro avg) 0.8606 |
|
2022-11-06 18:20:28,269 BAD EPOCHS (no improvement): 1 |
|
2022-11-06 18:20:28,463 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 18:20:35,509 epoch 101 - iter 27/274 - loss 0.01446495 - samples/sec: 122.71 - lr: 0.000781 |
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2022-11-06 18:20:41,986 epoch 101 - iter 54/274 - loss 0.01527659 - samples/sec: 133.46 - lr: 0.000781 |
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2022-11-06 18:20:48,980 epoch 101 - iter 81/274 - loss 0.01503021 - samples/sec: 123.60 - lr: 0.000781 |
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2022-11-06 18:20:56,316 epoch 101 - iter 108/274 - loss 0.01499355 - samples/sec: 117.84 - lr: 0.000781 |
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2022-11-06 18:21:03,299 epoch 101 - iter 135/274 - loss 0.01519732 - samples/sec: 123.78 - lr: 0.000781 |
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2022-11-06 18:21:09,737 epoch 101 - iter 162/274 - loss 0.01559284 - samples/sec: 134.27 - lr: 0.000781 |
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2022-11-06 18:21:16,568 epoch 101 - iter 189/274 - loss 0.01599842 - samples/sec: 126.55 - lr: 0.000781 |
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2022-11-06 18:21:22,989 epoch 101 - iter 216/274 - loss 0.01565725 - samples/sec: 134.64 - lr: 0.000781 |
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2022-11-06 18:21:30,602 epoch 101 - iter 243/274 - loss 0.01488667 - samples/sec: 113.54 - lr: 0.000781 |
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2022-11-06 18:21:37,041 epoch 101 - iter 270/274 - loss 0.01484699 - samples/sec: 134.25 - lr: 0.000781 |
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2022-11-06 18:21:37,898 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 18:21:37,899 EPOCH 101 done: loss 0.0148 - lr 0.000781 |
|
2022-11-06 18:22:16,521 Evaluating as a multi-label problem: False |
|
2022-11-06 18:22:16,548 TEST : loss 0.033024001866579056 - f1-score (micro avg) 0.8606 |
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2022-11-06 18:22:17,030 BAD EPOCHS (no improvement): 2 |
|
2022-11-06 18:22:17,216 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 18:22:24,215 epoch 102 - iter 27/274 - loss 0.01299900 - samples/sec: 123.52 - lr: 0.000781 |
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2022-11-06 18:22:31,180 epoch 102 - iter 54/274 - loss 0.01228057 - samples/sec: 124.12 - lr: 0.000781 |
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2022-11-06 18:22:37,763 epoch 102 - iter 81/274 - loss 0.01371390 - samples/sec: 131.32 - lr: 0.000781 |
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2022-11-06 18:22:44,491 epoch 102 - iter 108/274 - loss 0.01370075 - samples/sec: 128.48 - lr: 0.000781 |
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2022-11-06 18:22:51,216 epoch 102 - iter 135/274 - loss 0.01400902 - samples/sec: 128.54 - lr: 0.000781 |
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2022-11-06 18:22:57,791 epoch 102 - iter 162/274 - loss 0.01383236 - samples/sec: 131.47 - lr: 0.000781 |
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2022-11-06 18:23:04,621 epoch 102 - iter 189/274 - loss 0.01338305 - samples/sec: 126.56 - lr: 0.000781 |
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2022-11-06 18:23:11,771 epoch 102 - iter 216/274 - loss 0.01370954 - samples/sec: 120.90 - lr: 0.000781 |
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2022-11-06 18:23:18,425 epoch 102 - iter 243/274 - loss 0.01382908 - samples/sec: 129.92 - lr: 0.000781 |
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2022-11-06 18:23:25,157 epoch 102 - iter 270/274 - loss 0.01405057 - samples/sec: 128.41 - lr: 0.000781 |
|
2022-11-06 18:23:26,322 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 18:23:26,323 EPOCH 102 done: loss 0.0141 - lr 0.000781 |
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2022-11-06 18:24:04,519 Evaluating as a multi-label problem: False |
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2022-11-06 18:24:04,546 TEST : loss 0.03306020051240921 - f1-score (micro avg) 0.8612 |
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2022-11-06 18:24:05,027 BAD EPOCHS (no improvement): 3 |
|
2022-11-06 18:24:05,213 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 18:24:12,170 epoch 103 - iter 27/274 - loss 0.01666539 - samples/sec: 124.28 - lr: 0.000781 |
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2022-11-06 18:24:18,945 epoch 103 - iter 54/274 - loss 0.01602360 - samples/sec: 127.60 - lr: 0.000781 |
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2022-11-06 18:24:25,411 epoch 103 - iter 81/274 - loss 0.01555850 - samples/sec: 133.69 - lr: 0.000781 |
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2022-11-06 18:24:32,521 epoch 103 - iter 108/274 - loss 0.01530721 - samples/sec: 121.58 - lr: 0.000781 |
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2022-11-06 18:24:38,980 epoch 103 - iter 135/274 - loss 0.01543109 - samples/sec: 133.85 - lr: 0.000781 |
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2022-11-06 18:24:46,112 epoch 103 - iter 162/274 - loss 0.01540708 - samples/sec: 121.19 - lr: 0.000781 |
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2022-11-06 18:24:52,575 epoch 103 - iter 189/274 - loss 0.01474083 - samples/sec: 133.77 - lr: 0.000781 |
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2022-11-06 18:24:59,459 epoch 103 - iter 216/274 - loss 0.01510237 - samples/sec: 125.57 - lr: 0.000781 |
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2022-11-06 18:25:06,746 epoch 103 - iter 243/274 - loss 0.01458476 - samples/sec: 118.62 - lr: 0.000781 |
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2022-11-06 18:25:13,567 epoch 103 - iter 270/274 - loss 0.01434947 - samples/sec: 126.73 - lr: 0.000781 |
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2022-11-06 18:25:14,553 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 18:25:14,553 EPOCH 103 done: loss 0.0143 - lr 0.000781 |
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2022-11-06 18:25:52,758 Evaluating as a multi-label problem: False |
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2022-11-06 18:25:52,785 TEST : loss 0.03303169831633568 - f1-score (micro avg) 0.8606 |
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2022-11-06 18:25:53,266 Epoch 103: reducing learning rate of group 0 to 3.9063e-04. |
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2022-11-06 18:25:53,266 BAD EPOCHS (no improvement): 4 |
|
2022-11-06 18:25:53,461 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 18:26:00,301 epoch 104 - iter 27/274 - loss 0.01458720 - samples/sec: 126.39 - lr: 0.000391 |
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2022-11-06 18:26:06,870 epoch 104 - iter 54/274 - loss 0.01478208 - samples/sec: 131.60 - lr: 0.000391 |
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2022-11-06 18:26:13,471 epoch 104 - iter 81/274 - loss 0.01413977 - samples/sec: 130.96 - lr: 0.000391 |
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2022-11-06 18:26:20,493 epoch 104 - iter 108/274 - loss 0.01328514 - samples/sec: 123.09 - lr: 0.000391 |
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2022-11-06 18:26:27,511 epoch 104 - iter 135/274 - loss 0.01342123 - samples/sec: 123.17 - lr: 0.000391 |
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2022-11-06 18:26:34,557 epoch 104 - iter 162/274 - loss 0.01339805 - samples/sec: 122.68 - lr: 0.000391 |
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2022-11-06 18:26:41,102 epoch 104 - iter 189/274 - loss 0.01314734 - samples/sec: 132.07 - lr: 0.000391 |
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2022-11-06 18:26:47,901 epoch 104 - iter 216/274 - loss 0.01348532 - samples/sec: 127.15 - lr: 0.000391 |
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2022-11-06 18:26:55,123 epoch 104 - iter 243/274 - loss 0.01362798 - samples/sec: 119.68 - lr: 0.000391 |
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2022-11-06 18:27:01,560 epoch 104 - iter 270/274 - loss 0.01385963 - samples/sec: 134.30 - lr: 0.000391 |
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2022-11-06 18:27:02,395 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 18:27:02,395 EPOCH 104 done: loss 0.0140 - lr 0.000391 |
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2022-11-06 18:27:40,671 Evaluating as a multi-label problem: False |
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2022-11-06 18:27:40,698 TEST : loss 0.03300449624657631 - f1-score (micro avg) 0.8599 |
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2022-11-06 18:27:41,176 BAD EPOCHS (no improvement): 1 |
|
2022-11-06 18:27:41,381 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 18:27:48,520 epoch 105 - iter 27/274 - loss 0.01424921 - samples/sec: 121.13 - lr: 0.000391 |
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2022-11-06 18:27:55,181 epoch 105 - iter 54/274 - loss 0.01307246 - samples/sec: 129.79 - lr: 0.000391 |
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2022-11-06 18:28:02,057 epoch 105 - iter 81/274 - loss 0.01321091 - samples/sec: 125.74 - lr: 0.000391 |
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2022-11-06 18:28:09,527 epoch 105 - iter 108/274 - loss 0.01410278 - samples/sec: 115.72 - lr: 0.000391 |
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2022-11-06 18:28:17,162 epoch 105 - iter 135/274 - loss 0.01435593 - samples/sec: 113.23 - lr: 0.000391 |
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2022-11-06 18:28:24,461 epoch 105 - iter 162/274 - loss 0.01467838 - samples/sec: 118.44 - lr: 0.000391 |
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2022-11-06 18:28:31,847 epoch 105 - iter 189/274 - loss 0.01504003 - samples/sec: 117.04 - lr: 0.000391 |
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2022-11-06 18:28:39,460 epoch 105 - iter 216/274 - loss 0.01512150 - samples/sec: 113.56 - lr: 0.000391 |
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2022-11-06 18:28:46,262 epoch 105 - iter 243/274 - loss 0.01506319 - samples/sec: 127.10 - lr: 0.000391 |
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2022-11-06 18:28:53,624 epoch 105 - iter 270/274 - loss 0.01494025 - samples/sec: 117.43 - lr: 0.000391 |
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2022-11-06 18:28:54,507 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 18:28:54,508 EPOCH 105 done: loss 0.0148 - lr 0.000391 |
|
2022-11-06 18:29:33,247 Evaluating as a multi-label problem: False |
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2022-11-06 18:29:33,275 TEST : loss 0.03300108388066292 - f1-score (micro avg) 0.8602 |
|
2022-11-06 18:29:33,757 BAD EPOCHS (no improvement): 2 |
|
2022-11-06 18:29:33,950 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 18:29:40,637 epoch 106 - iter 27/274 - loss 0.01323771 - samples/sec: 129.31 - lr: 0.000391 |
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2022-11-06 18:29:47,600 epoch 106 - iter 54/274 - loss 0.01423093 - samples/sec: 124.15 - lr: 0.000391 |
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2022-11-06 18:29:54,650 epoch 106 - iter 81/274 - loss 0.01435088 - samples/sec: 122.63 - lr: 0.000391 |
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2022-11-06 18:30:00,781 epoch 106 - iter 108/274 - loss 0.01442826 - samples/sec: 141.01 - lr: 0.000391 |
|
2022-11-06 18:30:07,844 epoch 106 - iter 135/274 - loss 0.01447384 - samples/sec: 122.41 - lr: 0.000391 |
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2022-11-06 18:30:14,798 epoch 106 - iter 162/274 - loss 0.01458546 - samples/sec: 124.31 - lr: 0.000391 |
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2022-11-06 18:30:22,058 epoch 106 - iter 189/274 - loss 0.01454166 - samples/sec: 119.08 - lr: 0.000391 |
|
2022-11-06 18:30:29,202 epoch 106 - iter 216/274 - loss 0.01444348 - samples/sec: 121.01 - lr: 0.000391 |
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2022-11-06 18:30:35,688 epoch 106 - iter 243/274 - loss 0.01454994 - samples/sec: 133.29 - lr: 0.000391 |
|
2022-11-06 18:30:42,938 epoch 106 - iter 270/274 - loss 0.01468079 - samples/sec: 119.23 - lr: 0.000391 |
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2022-11-06 18:30:43,910 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 18:30:43,911 EPOCH 106 done: loss 0.0147 - lr 0.000391 |
|
2022-11-06 18:31:22,621 Evaluating as a multi-label problem: False |
|
2022-11-06 18:31:22,648 TEST : loss 0.03301873430609703 - f1-score (micro avg) 0.8597 |
|
2022-11-06 18:31:23,132 BAD EPOCHS (no improvement): 3 |
|
2022-11-06 18:31:23,326 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 18:31:30,158 epoch 107 - iter 27/274 - loss 0.01520691 - samples/sec: 126.57 - lr: 0.000391 |
|
2022-11-06 18:31:37,709 epoch 107 - iter 54/274 - loss 0.01351666 - samples/sec: 114.49 - lr: 0.000391 |
|
2022-11-06 18:31:43,929 epoch 107 - iter 81/274 - loss 0.01320954 - samples/sec: 138.99 - lr: 0.000391 |
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2022-11-06 18:31:50,154 epoch 107 - iter 108/274 - loss 0.01366281 - samples/sec: 138.89 - lr: 0.000391 |
|
2022-11-06 18:31:57,413 epoch 107 - iter 135/274 - loss 0.01426408 - samples/sec: 119.09 - lr: 0.000391 |
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2022-11-06 18:32:04,661 epoch 107 - iter 162/274 - loss 0.01424168 - samples/sec: 119.28 - lr: 0.000391 |
|
2022-11-06 18:32:11,598 epoch 107 - iter 189/274 - loss 0.01423995 - samples/sec: 124.63 - lr: 0.000391 |
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2022-11-06 18:32:19,167 epoch 107 - iter 216/274 - loss 0.01429583 - samples/sec: 114.21 - lr: 0.000391 |
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2022-11-06 18:32:25,850 epoch 107 - iter 243/274 - loss 0.01412370 - samples/sec: 129.35 - lr: 0.000391 |
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2022-11-06 18:32:33,094 epoch 107 - iter 270/274 - loss 0.01393433 - samples/sec: 119.33 - lr: 0.000391 |
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2022-11-06 18:32:34,257 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 18:32:34,257 EPOCH 107 done: loss 0.0141 - lr 0.000391 |
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2022-11-06 18:33:12,544 Evaluating as a multi-label problem: False |
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2022-11-06 18:33:12,571 TEST : loss 0.03307473659515381 - f1-score (micro avg) 0.8599 |
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2022-11-06 18:33:13,051 Epoch 107: reducing learning rate of group 0 to 1.9531e-04. |
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2022-11-06 18:33:13,052 BAD EPOCHS (no improvement): 4 |
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2022-11-06 18:33:13,238 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 18:33:20,221 epoch 108 - iter 27/274 - loss 0.01341064 - samples/sec: 123.81 - lr: 0.000195 |
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2022-11-06 18:33:27,208 epoch 108 - iter 54/274 - loss 0.01383712 - samples/sec: 123.73 - lr: 0.000195 |
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2022-11-06 18:33:33,586 epoch 108 - iter 81/274 - loss 0.01379724 - samples/sec: 135.53 - lr: 0.000195 |
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2022-11-06 18:33:39,724 epoch 108 - iter 108/274 - loss 0.01386903 - samples/sec: 140.85 - lr: 0.000195 |
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2022-11-06 18:33:46,853 epoch 108 - iter 135/274 - loss 0.01347630 - samples/sec: 121.24 - lr: 0.000195 |
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2022-11-06 18:33:53,684 epoch 108 - iter 162/274 - loss 0.01355865 - samples/sec: 126.55 - lr: 0.000195 |
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2022-11-06 18:34:00,437 epoch 108 - iter 189/274 - loss 0.01367054 - samples/sec: 128.00 - lr: 0.000195 |
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2022-11-06 18:34:07,227 epoch 108 - iter 216/274 - loss 0.01378129 - samples/sec: 127.32 - lr: 0.000195 |
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2022-11-06 18:34:14,006 epoch 108 - iter 243/274 - loss 0.01361853 - samples/sec: 127.51 - lr: 0.000195 |
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2022-11-06 18:34:21,311 epoch 108 - iter 270/274 - loss 0.01381685 - samples/sec: 118.32 - lr: 0.000195 |
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2022-11-06 18:34:22,258 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 18:34:22,259 EPOCH 108 done: loss 0.0138 - lr 0.000195 |
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2022-11-06 18:35:00,251 Evaluating as a multi-label problem: False |
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2022-11-06 18:35:00,278 TEST : loss 0.03307962417602539 - f1-score (micro avg) 0.8597 |
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2022-11-06 18:35:00,754 BAD EPOCHS (no improvement): 1 |
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2022-11-06 18:35:00,948 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 18:35:07,805 epoch 109 - iter 27/274 - loss 0.01662803 - samples/sec: 126.08 - lr: 0.000195 |
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2022-11-06 18:35:14,700 epoch 109 - iter 54/274 - loss 0.01484573 - samples/sec: 125.37 - lr: 0.000195 |
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2022-11-06 18:35:21,313 epoch 109 - iter 81/274 - loss 0.01494539 - samples/sec: 130.73 - lr: 0.000195 |
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2022-11-06 18:35:27,707 epoch 109 - iter 108/274 - loss 0.01471633 - samples/sec: 135.19 - lr: 0.000195 |
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2022-11-06 18:35:33,818 epoch 109 - iter 135/274 - loss 0.01508456 - samples/sec: 141.46 - lr: 0.000195 |
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2022-11-06 18:35:40,697 epoch 109 - iter 162/274 - loss 0.01442215 - samples/sec: 125.65 - lr: 0.000195 |
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2022-11-06 18:35:47,399 epoch 109 - iter 189/274 - loss 0.01444187 - samples/sec: 128.99 - lr: 0.000195 |
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2022-11-06 18:35:54,223 epoch 109 - iter 216/274 - loss 0.01456026 - samples/sec: 126.68 - lr: 0.000195 |
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2022-11-06 18:36:01,615 epoch 109 - iter 243/274 - loss 0.01457428 - samples/sec: 116.93 - lr: 0.000195 |
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2022-11-06 18:36:08,768 epoch 109 - iter 270/274 - loss 0.01423025 - samples/sec: 120.86 - lr: 0.000195 |
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2022-11-06 18:36:09,828 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 18:36:09,828 EPOCH 109 done: loss 0.0142 - lr 0.000195 |
|
2022-11-06 18:36:48,310 Evaluating as a multi-label problem: False |
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2022-11-06 18:36:48,337 TEST : loss 0.03311078995466232 - f1-score (micro avg) 0.8595 |
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2022-11-06 18:36:48,815 BAD EPOCHS (no improvement): 2 |
|
2022-11-06 18:36:49,009 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 18:36:56,107 epoch 110 - iter 27/274 - loss 0.01420081 - samples/sec: 121.82 - lr: 0.000195 |
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2022-11-06 18:37:02,664 epoch 110 - iter 54/274 - loss 0.01471469 - samples/sec: 131.83 - lr: 0.000195 |
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2022-11-06 18:37:09,423 epoch 110 - iter 81/274 - loss 0.01401599 - samples/sec: 127.90 - lr: 0.000195 |
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2022-11-06 18:37:16,249 epoch 110 - iter 108/274 - loss 0.01383453 - samples/sec: 126.62 - lr: 0.000195 |
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2022-11-06 18:37:22,420 epoch 110 - iter 135/274 - loss 0.01360067 - samples/sec: 140.10 - lr: 0.000195 |
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2022-11-06 18:37:29,478 epoch 110 - iter 162/274 - loss 0.01429213 - samples/sec: 122.48 - lr: 0.000195 |
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2022-11-06 18:37:36,520 epoch 110 - iter 189/274 - loss 0.01420927 - samples/sec: 122.75 - lr: 0.000195 |
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2022-11-06 18:37:43,579 epoch 110 - iter 216/274 - loss 0.01414622 - samples/sec: 122.44 - lr: 0.000195 |
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2022-11-06 18:37:50,248 epoch 110 - iter 243/274 - loss 0.01441753 - samples/sec: 129.63 - lr: 0.000195 |
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2022-11-06 18:37:57,514 epoch 110 - iter 270/274 - loss 0.01414675 - samples/sec: 118.96 - lr: 0.000195 |
|
2022-11-06 18:37:58,412 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 18:37:58,412 EPOCH 110 done: loss 0.0142 - lr 0.000195 |
|
2022-11-06 18:38:36,472 Evaluating as a multi-label problem: False |
|
2022-11-06 18:38:36,499 TEST : loss 0.03310991823673248 - f1-score (micro avg) 0.8595 |
|
2022-11-06 18:38:36,979 BAD EPOCHS (no improvement): 3 |
|
2022-11-06 18:38:37,171 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 18:38:43,854 epoch 111 - iter 27/274 - loss 0.01325495 - samples/sec: 129.37 - lr: 0.000195 |
|
2022-11-06 18:38:50,585 epoch 111 - iter 54/274 - loss 0.01480494 - samples/sec: 128.44 - lr: 0.000195 |
|
2022-11-06 18:38:56,968 epoch 111 - iter 81/274 - loss 0.01426950 - samples/sec: 135.43 - lr: 0.000195 |
|
2022-11-06 18:39:03,775 epoch 111 - iter 108/274 - loss 0.01357019 - samples/sec: 126.99 - lr: 0.000195 |
|
2022-11-06 18:39:10,371 epoch 111 - iter 135/274 - loss 0.01367704 - samples/sec: 131.05 - lr: 0.000195 |
|
2022-11-06 18:39:17,547 epoch 111 - iter 162/274 - loss 0.01362901 - samples/sec: 120.46 - lr: 0.000195 |
|
2022-11-06 18:39:24,202 epoch 111 - iter 189/274 - loss 0.01359315 - samples/sec: 129.88 - lr: 0.000195 |
|
2022-11-06 18:39:31,146 epoch 111 - iter 216/274 - loss 0.01350941 - samples/sec: 124.48 - lr: 0.000195 |
|
2022-11-06 18:39:38,281 epoch 111 - iter 243/274 - loss 0.01307953 - samples/sec: 121.16 - lr: 0.000195 |
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2022-11-06 18:39:45,320 epoch 111 - iter 270/274 - loss 0.01322726 - samples/sec: 122.80 - lr: 0.000195 |
|
2022-11-06 18:39:46,429 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 18:39:46,429 EPOCH 111 done: loss 0.0132 - lr 0.000195 |
|
2022-11-06 18:40:24,772 Evaluating as a multi-label problem: False |
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2022-11-06 18:40:24,799 TEST : loss 0.033106669783592224 - f1-score (micro avg) 0.8599 |
|
2022-11-06 18:40:25,282 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 18:40:25,471 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 18:40:32,143 epoch 112 - iter 27/274 - loss 0.01245997 - samples/sec: 129.59 - lr: 0.000195 |
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2022-11-06 18:40:38,614 epoch 112 - iter 54/274 - loss 0.01185445 - samples/sec: 133.59 - lr: 0.000195 |
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2022-11-06 18:40:45,107 epoch 112 - iter 81/274 - loss 0.01251068 - samples/sec: 133.12 - lr: 0.000195 |
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2022-11-06 18:40:51,963 epoch 112 - iter 108/274 - loss 0.01286266 - samples/sec: 126.10 - lr: 0.000195 |
|
2022-11-06 18:40:58,321 epoch 112 - iter 135/274 - loss 0.01254586 - samples/sec: 135.97 - lr: 0.000195 |
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2022-11-06 18:41:05,122 epoch 112 - iter 162/274 - loss 0.01277581 - samples/sec: 127.09 - lr: 0.000195 |
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2022-11-06 18:41:12,018 epoch 112 - iter 189/274 - loss 0.01289788 - samples/sec: 125.36 - lr: 0.000195 |
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2022-11-06 18:41:19,138 epoch 112 - iter 216/274 - loss 0.01301322 - samples/sec: 121.41 - lr: 0.000195 |
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2022-11-06 18:41:26,088 epoch 112 - iter 243/274 - loss 0.01336748 - samples/sec: 124.37 - lr: 0.000195 |
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2022-11-06 18:41:34,544 epoch 112 - iter 270/274 - loss 0.01361051 - samples/sec: 102.22 - lr: 0.000195 |
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2022-11-06 18:41:35,386 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 18:41:35,386 EPOCH 112 done: loss 0.0136 - lr 0.000195 |
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2022-11-06 18:42:12,805 Evaluating as a multi-label problem: False |
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2022-11-06 18:42:12,832 TEST : loss 0.0330953449010849 - f1-score (micro avg) 0.8599 |
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2022-11-06 18:42:13,312 BAD EPOCHS (no improvement): 1 |
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2022-11-06 18:42:13,502 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 18:42:20,764 epoch 113 - iter 27/274 - loss 0.01344772 - samples/sec: 119.06 - lr: 0.000195 |
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2022-11-06 18:42:27,690 epoch 113 - iter 54/274 - loss 0.01443830 - samples/sec: 124.80 - lr: 0.000195 |
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2022-11-06 18:42:34,662 epoch 113 - iter 81/274 - loss 0.01345180 - samples/sec: 124.00 - lr: 0.000195 |
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2022-11-06 18:42:41,177 epoch 113 - iter 108/274 - loss 0.01251339 - samples/sec: 132.68 - lr: 0.000195 |
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2022-11-06 18:42:48,073 epoch 113 - iter 135/274 - loss 0.01268490 - samples/sec: 125.34 - lr: 0.000195 |
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2022-11-06 18:42:55,169 epoch 113 - iter 162/274 - loss 0.01318989 - samples/sec: 121.82 - lr: 0.000195 |
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2022-11-06 18:43:01,527 epoch 113 - iter 189/274 - loss 0.01345892 - samples/sec: 135.96 - lr: 0.000195 |
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2022-11-06 18:43:08,435 epoch 113 - iter 216/274 - loss 0.01329989 - samples/sec: 125.13 - lr: 0.000195 |
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2022-11-06 18:43:15,278 epoch 113 - iter 243/274 - loss 0.01326442 - samples/sec: 126.32 - lr: 0.000195 |
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2022-11-06 18:43:22,318 epoch 113 - iter 270/274 - loss 0.01333745 - samples/sec: 122.79 - lr: 0.000195 |
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2022-11-06 18:43:23,256 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 18:43:23,257 EPOCH 113 done: loss 0.0133 - lr 0.000195 |
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2022-11-06 18:44:01,581 Evaluating as a multi-label problem: False |
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2022-11-06 18:44:01,608 TEST : loss 0.03308477625250816 - f1-score (micro avg) 0.8603 |
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2022-11-06 18:44:02,086 BAD EPOCHS (no improvement): 2 |
|
2022-11-06 18:44:02,278 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 18:44:09,469 epoch 114 - iter 27/274 - loss 0.01578122 - samples/sec: 120.23 - lr: 0.000195 |
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2022-11-06 18:44:16,088 epoch 114 - iter 54/274 - loss 0.01413436 - samples/sec: 130.61 - lr: 0.000195 |
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2022-11-06 18:44:22,746 epoch 114 - iter 81/274 - loss 0.01455526 - samples/sec: 129.84 - lr: 0.000195 |
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2022-11-06 18:44:30,070 epoch 114 - iter 108/274 - loss 0.01475374 - samples/sec: 118.01 - lr: 0.000195 |
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2022-11-06 18:44:37,009 epoch 114 - iter 135/274 - loss 0.01452364 - samples/sec: 124.58 - lr: 0.000195 |
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2022-11-06 18:44:42,974 epoch 114 - iter 162/274 - loss 0.01457320 - samples/sec: 144.94 - lr: 0.000195 |
|
2022-11-06 18:44:49,371 epoch 114 - iter 189/274 - loss 0.01454147 - samples/sec: 135.13 - lr: 0.000195 |
|
2022-11-06 18:44:56,395 epoch 114 - iter 216/274 - loss 0.01467951 - samples/sec: 123.06 - lr: 0.000195 |
|
2022-11-06 18:45:03,117 epoch 114 - iter 243/274 - loss 0.01463831 - samples/sec: 128.60 - lr: 0.000195 |
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2022-11-06 18:45:10,263 epoch 114 - iter 270/274 - loss 0.01451383 - samples/sec: 120.96 - lr: 0.000195 |
|
2022-11-06 18:45:11,203 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 18:45:11,203 EPOCH 114 done: loss 0.0144 - lr 0.000195 |
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2022-11-06 18:45:49,291 Evaluating as a multi-label problem: False |
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2022-11-06 18:45:49,318 TEST : loss 0.03305461257696152 - f1-score (micro avg) 0.8605 |
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2022-11-06 18:45:49,802 BAD EPOCHS (no improvement): 3 |
|
2022-11-06 18:45:49,995 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 18:45:56,404 epoch 115 - iter 27/274 - loss 0.01136031 - samples/sec: 134.93 - lr: 0.000195 |
|
2022-11-06 18:46:03,117 epoch 115 - iter 54/274 - loss 0.01181110 - samples/sec: 128.76 - lr: 0.000195 |
|
2022-11-06 18:46:09,705 epoch 115 - iter 81/274 - loss 0.01307147 - samples/sec: 131.21 - lr: 0.000195 |
|
2022-11-06 18:46:16,290 epoch 115 - iter 108/274 - loss 0.01254648 - samples/sec: 131.29 - lr: 0.000195 |
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2022-11-06 18:46:22,948 epoch 115 - iter 135/274 - loss 0.01322313 - samples/sec: 129.83 - lr: 0.000195 |
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2022-11-06 18:46:29,878 epoch 115 - iter 162/274 - loss 0.01396292 - samples/sec: 124.74 - lr: 0.000195 |
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2022-11-06 18:46:36,909 epoch 115 - iter 189/274 - loss 0.01351193 - samples/sec: 122.93 - lr: 0.000195 |
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2022-11-06 18:46:43,462 epoch 115 - iter 216/274 - loss 0.01383586 - samples/sec: 131.92 - lr: 0.000195 |
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2022-11-06 18:46:50,365 epoch 115 - iter 243/274 - loss 0.01381672 - samples/sec: 125.23 - lr: 0.000195 |
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2022-11-06 18:46:57,761 epoch 115 - iter 270/274 - loss 0.01364803 - samples/sec: 116.87 - lr: 0.000195 |
|
2022-11-06 18:46:58,844 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 18:46:58,844 EPOCH 115 done: loss 0.0137 - lr 0.000195 |
|
2022-11-06 18:47:36,834 Evaluating as a multi-label problem: False |
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2022-11-06 18:47:36,861 TEST : loss 0.03304998576641083 - f1-score (micro avg) 0.8605 |
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2022-11-06 18:47:37,342 Epoch 115: reducing learning rate of group 0 to 9.7656e-05. |
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2022-11-06 18:47:37,342 BAD EPOCHS (no improvement): 4 |
|
2022-11-06 18:47:37,529 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 18:47:37,530 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 18:47:37,530 learning rate too small - quitting training! |
|
2022-11-06 18:47:37,530 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 18:47:37,659 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 18:47:37,659 Testing using last state of model ... |
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2022-11-06 18:48:16,666 Evaluating as a multi-label problem: False |
|
2022-11-06 18:48:16,692 0.8616 0.8593 0.8605 0.8033 |
|
2022-11-06 18:48:16,692 |
|
Results: |
|
- F-score (micro) 0.8605 |
|
- F-score (macro) 0.7472 |
|
- Accuracy 0.8033 |
|
|
|
By class: |
|
precision recall f1-score support |
|
|
|
PERS 0.9305 0.9422 0.9363 1678 |
|
LOC 0.8150 0.8678 0.8406 401 |
|
ORG 0.6653 0.6092 0.6360 261 |
|
MISC 0.6202 0.5375 0.5759 240 |
|
|
|
micro avg 0.8616 0.8593 0.8605 2580 |
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macro avg 0.7577 0.7392 0.7472 2580 |
|
weighted avg 0.8569 0.8593 0.8575 2580 |
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|
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2022-11-06 18:48:16,693 ---------------------------------------------------------------------------------------------------- |
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