| 2023-09-04 14:37:10,223 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 14:37:10,224 Model: "SequenceTagger( | |
| (embeddings): TransformerWordEmbeddings( | |
| (model): BertModel( | |
| (embeddings): BertEmbeddings( | |
| (word_embeddings): Embedding(32001, 768) | |
| (position_embeddings): Embedding(512, 768) | |
| (token_type_embeddings): Embedding(2, 768) | |
| (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| (encoder): BertEncoder( | |
| (layer): ModuleList( | |
| (0-11): 12 x BertLayer( | |
| (attention): BertAttention( | |
| (self): BertSelfAttention( | |
| (query): Linear(in_features=768, out_features=768, bias=True) | |
| (key): Linear(in_features=768, out_features=768, bias=True) | |
| (value): Linear(in_features=768, out_features=768, bias=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| (output): BertSelfOutput( | |
| (dense): Linear(in_features=768, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (intermediate): BertIntermediate( | |
| (dense): Linear(in_features=768, out_features=3072, bias=True) | |
| (intermediate_act_fn): GELUActivation() | |
| ) | |
| (output): BertOutput( | |
| (dense): Linear(in_features=3072, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| ) | |
| ) | |
| (pooler): BertPooler( | |
| (dense): Linear(in_features=768, out_features=768, bias=True) | |
| (activation): Tanh() | |
| ) | |
| ) | |
| ) | |
| (locked_dropout): LockedDropout(p=0.5) | |
| (linear): Linear(in_features=768, out_features=21, bias=True) | |
| (loss_function): CrossEntropyLoss() | |
| )" | |
| 2023-09-04 14:37:10,224 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 14:37:10,224 MultiCorpus: 5901 train + 1287 dev + 1505 test sentences | |
| - NER_HIPE_2022 Corpus: 5901 train + 1287 dev + 1505 test sentences - /app/.flair/datasets/ner_hipe_2022/v2.1/hipe2020/fr/with_doc_seperator | |
| 2023-09-04 14:37:10,224 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 14:37:10,224 Train: 5901 sentences | |
| 2023-09-04 14:37:10,224 (train_with_dev=False, train_with_test=False) | |
| 2023-09-04 14:37:10,224 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 14:37:10,224 Training Params: | |
| 2023-09-04 14:37:10,225 - learning_rate: "5e-05" | |
| 2023-09-04 14:37:10,225 - mini_batch_size: "4" | |
| 2023-09-04 14:37:10,225 - max_epochs: "10" | |
| 2023-09-04 14:37:10,225 - shuffle: "True" | |
| 2023-09-04 14:37:10,225 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 14:37:10,225 Plugins: | |
| 2023-09-04 14:37:10,225 - LinearScheduler | warmup_fraction: '0.1' | |
| 2023-09-04 14:37:10,225 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 14:37:10,225 Final evaluation on model from best epoch (best-model.pt) | |
| 2023-09-04 14:37:10,225 - metric: "('micro avg', 'f1-score')" | |
| 2023-09-04 14:37:10,225 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 14:37:10,225 Computation: | |
| 2023-09-04 14:37:10,225 - compute on device: cuda:0 | |
| 2023-09-04 14:37:10,225 - embedding storage: none | |
| 2023-09-04 14:37:10,225 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 14:37:10,225 Model training base path: "hmbench-hipe2020/fr-dbmdz/bert-base-historic-multilingual-cased-bs4-wsFalse-e10-lr5e-05-poolingfirst-layers-1-crfFalse-3" | |
| 2023-09-04 14:37:10,225 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 14:37:10,225 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 14:37:24,926 epoch 1 - iter 147/1476 - loss 2.05618754 - time (sec): 14.70 - samples/sec: 1042.48 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-09-04 14:37:40,726 epoch 1 - iter 294/1476 - loss 1.24591273 - time (sec): 30.50 - samples/sec: 1073.51 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-09-04 14:37:55,882 epoch 1 - iter 441/1476 - loss 0.96595507 - time (sec): 45.66 - samples/sec: 1053.60 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-09-04 14:38:11,770 epoch 1 - iter 588/1476 - loss 0.79301248 - time (sec): 61.54 - samples/sec: 1048.20 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-09-04 14:38:27,739 epoch 1 - iter 735/1476 - loss 0.68162646 - time (sec): 77.51 - samples/sec: 1050.21 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-09-04 14:38:44,370 epoch 1 - iter 882/1476 - loss 0.59898767 - time (sec): 94.14 - samples/sec: 1052.37 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-09-04 14:39:01,175 epoch 1 - iter 1029/1476 - loss 0.54029039 - time (sec): 110.95 - samples/sec: 1049.30 - lr: 0.000035 - momentum: 0.000000 | |
| 2023-09-04 14:39:16,723 epoch 1 - iter 1176/1476 - loss 0.49996949 - time (sec): 126.50 - samples/sec: 1045.64 - lr: 0.000040 - momentum: 0.000000 | |
| 2023-09-04 14:39:33,925 epoch 1 - iter 1323/1476 - loss 0.46069672 - time (sec): 143.70 - samples/sec: 1044.79 - lr: 0.000045 - momentum: 0.000000 | |
| 2023-09-04 14:39:49,637 epoch 1 - iter 1470/1476 - loss 0.43367918 - time (sec): 159.41 - samples/sec: 1040.69 - lr: 0.000050 - momentum: 0.000000 | |
| 2023-09-04 14:39:50,208 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 14:39:50,208 EPOCH 1 done: loss 0.4331 - lr: 0.000050 | |
| 2023-09-04 14:40:04,539 DEV : loss 0.14273743331432343 - f1-score (micro avg) 0.7029 | |
| 2023-09-04 14:40:04,567 saving best model | |
| 2023-09-04 14:40:05,059 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 14:40:20,954 epoch 2 - iter 147/1476 - loss 0.15116667 - time (sec): 15.89 - samples/sec: 1053.78 - lr: 0.000049 - momentum: 0.000000 | |
| 2023-09-04 14:40:37,208 epoch 2 - iter 294/1476 - loss 0.15377335 - time (sec): 32.15 - samples/sec: 1047.39 - lr: 0.000049 - momentum: 0.000000 | |
| 2023-09-04 14:40:54,506 epoch 2 - iter 441/1476 - loss 0.15144934 - time (sec): 49.44 - samples/sec: 1055.90 - lr: 0.000048 - momentum: 0.000000 | |
| 2023-09-04 14:41:09,751 epoch 2 - iter 588/1476 - loss 0.14514190 - time (sec): 64.69 - samples/sec: 1048.12 - lr: 0.000048 - momentum: 0.000000 | |
| 2023-09-04 14:41:24,951 epoch 2 - iter 735/1476 - loss 0.14434703 - time (sec): 79.89 - samples/sec: 1044.53 - lr: 0.000047 - momentum: 0.000000 | |
| 2023-09-04 14:41:42,059 epoch 2 - iter 882/1476 - loss 0.14095490 - time (sec): 97.00 - samples/sec: 1047.48 - lr: 0.000047 - momentum: 0.000000 | |
| 2023-09-04 14:41:58,137 epoch 2 - iter 1029/1476 - loss 0.13849409 - time (sec): 113.08 - samples/sec: 1045.08 - lr: 0.000046 - momentum: 0.000000 | |
| 2023-09-04 14:42:13,722 epoch 2 - iter 1176/1476 - loss 0.13600706 - time (sec): 128.66 - samples/sec: 1042.32 - lr: 0.000046 - momentum: 0.000000 | |
| 2023-09-04 14:42:29,232 epoch 2 - iter 1323/1476 - loss 0.13703274 - time (sec): 144.17 - samples/sec: 1040.78 - lr: 0.000045 - momentum: 0.000000 | |
| 2023-09-04 14:42:44,323 epoch 2 - iter 1470/1476 - loss 0.13820196 - time (sec): 159.26 - samples/sec: 1041.95 - lr: 0.000044 - momentum: 0.000000 | |
| 2023-09-04 14:42:44,869 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 14:42:44,870 EPOCH 2 done: loss 0.1381 - lr: 0.000044 | |
| 2023-09-04 14:43:02,487 DEV : loss 0.14158931374549866 - f1-score (micro avg) 0.745 | |
| 2023-09-04 14:43:02,516 saving best model | |
| 2023-09-04 14:43:03,854 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 14:43:18,808 epoch 3 - iter 147/1476 - loss 0.07909018 - time (sec): 14.95 - samples/sec: 1023.67 - lr: 0.000044 - momentum: 0.000000 | |
| 2023-09-04 14:43:34,437 epoch 3 - iter 294/1476 - loss 0.08191834 - time (sec): 30.58 - samples/sec: 1045.44 - lr: 0.000043 - momentum: 0.000000 | |
| 2023-09-04 14:43:50,338 epoch 3 - iter 441/1476 - loss 0.08482425 - time (sec): 46.48 - samples/sec: 1047.71 - lr: 0.000043 - momentum: 0.000000 | |
| 2023-09-04 14:44:07,807 epoch 3 - iter 588/1476 - loss 0.08414229 - time (sec): 63.95 - samples/sec: 1063.02 - lr: 0.000042 - momentum: 0.000000 | |
| 2023-09-04 14:44:23,918 epoch 3 - iter 735/1476 - loss 0.09109558 - time (sec): 80.06 - samples/sec: 1055.09 - lr: 0.000042 - momentum: 0.000000 | |
| 2023-09-04 14:44:39,104 epoch 3 - iter 882/1476 - loss 0.08957885 - time (sec): 95.25 - samples/sec: 1049.41 - lr: 0.000041 - momentum: 0.000000 | |
| 2023-09-04 14:44:55,966 epoch 3 - iter 1029/1476 - loss 0.09154050 - time (sec): 112.11 - samples/sec: 1050.53 - lr: 0.000041 - momentum: 0.000000 | |
| 2023-09-04 14:45:11,162 epoch 3 - iter 1176/1476 - loss 0.09076679 - time (sec): 127.31 - samples/sec: 1047.21 - lr: 0.000040 - momentum: 0.000000 | |
| 2023-09-04 14:45:27,181 epoch 3 - iter 1323/1476 - loss 0.09308992 - time (sec): 143.33 - samples/sec: 1044.41 - lr: 0.000039 - momentum: 0.000000 | |
| 2023-09-04 14:45:42,897 epoch 3 - iter 1470/1476 - loss 0.09133680 - time (sec): 159.04 - samples/sec: 1042.38 - lr: 0.000039 - momentum: 0.000000 | |
| 2023-09-04 14:45:43,490 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 14:45:43,490 EPOCH 3 done: loss 0.0911 - lr: 0.000039 | |
| 2023-09-04 14:46:01,014 DEV : loss 0.17265217006206512 - f1-score (micro avg) 0.8048 | |
| 2023-09-04 14:46:01,044 saving best model | |
| 2023-09-04 14:46:02,399 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 14:46:18,579 epoch 4 - iter 147/1476 - loss 0.05488287 - time (sec): 16.18 - samples/sec: 1072.38 - lr: 0.000038 - momentum: 0.000000 | |
| 2023-09-04 14:46:34,303 epoch 4 - iter 294/1476 - loss 0.05976011 - time (sec): 31.90 - samples/sec: 1069.41 - lr: 0.000038 - momentum: 0.000000 | |
| 2023-09-04 14:46:50,518 epoch 4 - iter 441/1476 - loss 0.06373628 - time (sec): 48.12 - samples/sec: 1061.96 - lr: 0.000037 - momentum: 0.000000 | |
| 2023-09-04 14:47:06,011 epoch 4 - iter 588/1476 - loss 0.06645004 - time (sec): 63.61 - samples/sec: 1051.93 - lr: 0.000037 - momentum: 0.000000 | |
| 2023-09-04 14:47:21,374 epoch 4 - iter 735/1476 - loss 0.06599255 - time (sec): 78.97 - samples/sec: 1038.79 - lr: 0.000036 - momentum: 0.000000 | |
| 2023-09-04 14:47:38,022 epoch 4 - iter 882/1476 - loss 0.06576644 - time (sec): 95.62 - samples/sec: 1036.93 - lr: 0.000036 - momentum: 0.000000 | |
| 2023-09-04 14:47:55,574 epoch 4 - iter 1029/1476 - loss 0.06729119 - time (sec): 113.17 - samples/sec: 1046.71 - lr: 0.000035 - momentum: 0.000000 | |
| 2023-09-04 14:48:10,738 epoch 4 - iter 1176/1476 - loss 0.06894602 - time (sec): 128.34 - samples/sec: 1041.22 - lr: 0.000034 - momentum: 0.000000 | |
| 2023-09-04 14:48:26,358 epoch 4 - iter 1323/1476 - loss 0.06675886 - time (sec): 143.96 - samples/sec: 1037.88 - lr: 0.000034 - momentum: 0.000000 | |
| 2023-09-04 14:48:42,090 epoch 4 - iter 1470/1476 - loss 0.06721274 - time (sec): 159.69 - samples/sec: 1039.16 - lr: 0.000033 - momentum: 0.000000 | |
| 2023-09-04 14:48:42,677 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 14:48:42,677 EPOCH 4 done: loss 0.0671 - lr: 0.000033 | |
| 2023-09-04 14:49:00,334 DEV : loss 0.16335846483707428 - f1-score (micro avg) 0.8012 | |
| 2023-09-04 14:49:00,363 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 14:49:17,015 epoch 5 - iter 147/1476 - loss 0.06622027 - time (sec): 16.65 - samples/sec: 1101.78 - lr: 0.000033 - momentum: 0.000000 | |
| 2023-09-04 14:49:33,050 epoch 5 - iter 294/1476 - loss 0.06049103 - time (sec): 32.69 - samples/sec: 1066.31 - lr: 0.000032 - momentum: 0.000000 | |
| 2023-09-04 14:49:49,544 epoch 5 - iter 441/1476 - loss 0.06035344 - time (sec): 49.18 - samples/sec: 1053.86 - lr: 0.000032 - momentum: 0.000000 | |
| 2023-09-04 14:50:04,750 epoch 5 - iter 588/1476 - loss 0.05825611 - time (sec): 64.39 - samples/sec: 1044.43 - lr: 0.000031 - momentum: 0.000000 | |
| 2023-09-04 14:50:20,107 epoch 5 - iter 735/1476 - loss 0.05285723 - time (sec): 79.74 - samples/sec: 1040.13 - lr: 0.000031 - momentum: 0.000000 | |
| 2023-09-04 14:50:35,859 epoch 5 - iter 882/1476 - loss 0.05168682 - time (sec): 95.50 - samples/sec: 1033.23 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-09-04 14:50:51,736 epoch 5 - iter 1029/1476 - loss 0.05200072 - time (sec): 111.37 - samples/sec: 1033.81 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-09-04 14:51:07,167 epoch 5 - iter 1176/1476 - loss 0.05045599 - time (sec): 126.80 - samples/sec: 1030.80 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-09-04 14:51:22,293 epoch 5 - iter 1323/1476 - loss 0.04917480 - time (sec): 141.93 - samples/sec: 1032.43 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-09-04 14:51:39,898 epoch 5 - iter 1470/1476 - loss 0.04897805 - time (sec): 159.53 - samples/sec: 1039.41 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-09-04 14:51:40,447 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 14:51:40,447 EPOCH 5 done: loss 0.0493 - lr: 0.000028 | |
| 2023-09-04 14:51:58,018 DEV : loss 0.20086710155010223 - f1-score (micro avg) 0.8012 | |
| 2023-09-04 14:51:58,049 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 14:52:14,830 epoch 6 - iter 147/1476 - loss 0.04119602 - time (sec): 16.78 - samples/sec: 1079.19 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-09-04 14:52:31,506 epoch 6 - iter 294/1476 - loss 0.03794587 - time (sec): 33.46 - samples/sec: 1062.89 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-09-04 14:52:48,721 epoch 6 - iter 441/1476 - loss 0.03922280 - time (sec): 50.67 - samples/sec: 1069.35 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-09-04 14:53:04,208 epoch 6 - iter 588/1476 - loss 0.03951086 - time (sec): 66.16 - samples/sec: 1059.47 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-09-04 14:53:19,700 epoch 6 - iter 735/1476 - loss 0.03815692 - time (sec): 81.65 - samples/sec: 1054.77 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-09-04 14:53:35,869 epoch 6 - iter 882/1476 - loss 0.03838285 - time (sec): 97.82 - samples/sec: 1048.69 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-09-04 14:53:51,797 epoch 6 - iter 1029/1476 - loss 0.03735327 - time (sec): 113.75 - samples/sec: 1043.81 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-09-04 14:54:06,862 epoch 6 - iter 1176/1476 - loss 0.03668080 - time (sec): 128.81 - samples/sec: 1039.34 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-09-04 14:54:22,232 epoch 6 - iter 1323/1476 - loss 0.03692170 - time (sec): 144.18 - samples/sec: 1037.47 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-09-04 14:54:37,600 epoch 6 - iter 1470/1476 - loss 0.03657753 - time (sec): 159.55 - samples/sec: 1039.55 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-09-04 14:54:38,166 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 14:54:38,167 EPOCH 6 done: loss 0.0365 - lr: 0.000022 | |
| 2023-09-04 14:54:55,735 DEV : loss 0.2203623205423355 - f1-score (micro avg) 0.8002 | |
| 2023-09-04 14:54:55,763 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 14:55:10,434 epoch 7 - iter 147/1476 - loss 0.01642304 - time (sec): 14.67 - samples/sec: 1057.19 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-09-04 14:55:27,264 epoch 7 - iter 294/1476 - loss 0.01866675 - time (sec): 31.50 - samples/sec: 1055.62 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-09-04 14:55:41,753 epoch 7 - iter 441/1476 - loss 0.02584884 - time (sec): 45.99 - samples/sec: 1044.53 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-09-04 14:55:58,660 epoch 7 - iter 588/1476 - loss 0.02482793 - time (sec): 62.90 - samples/sec: 1044.61 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-09-04 14:56:13,767 epoch 7 - iter 735/1476 - loss 0.02488488 - time (sec): 78.00 - samples/sec: 1040.00 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-09-04 14:56:28,980 epoch 7 - iter 882/1476 - loss 0.02516712 - time (sec): 93.22 - samples/sec: 1035.35 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-09-04 14:56:48,543 epoch 7 - iter 1029/1476 - loss 0.02511757 - time (sec): 112.78 - samples/sec: 1050.84 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-09-04 14:57:03,738 epoch 7 - iter 1176/1476 - loss 0.02533099 - time (sec): 127.97 - samples/sec: 1045.97 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-09-04 14:57:19,755 epoch 7 - iter 1323/1476 - loss 0.02626783 - time (sec): 143.99 - samples/sec: 1043.52 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-09-04 14:57:35,009 epoch 7 - iter 1470/1476 - loss 0.02547683 - time (sec): 159.24 - samples/sec: 1041.10 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-09-04 14:57:35,579 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 14:57:35,579 EPOCH 7 done: loss 0.0255 - lr: 0.000017 | |
| 2023-09-04 14:57:53,132 DEV : loss 0.22496868669986725 - f1-score (micro avg) 0.8145 | |
| 2023-09-04 14:57:53,160 saving best model | |
| 2023-09-04 14:57:54,555 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 14:58:10,369 epoch 8 - iter 147/1476 - loss 0.01023728 - time (sec): 15.81 - samples/sec: 1072.20 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-09-04 14:58:26,766 epoch 8 - iter 294/1476 - loss 0.01604023 - time (sec): 32.21 - samples/sec: 1066.02 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-09-04 14:58:43,662 epoch 8 - iter 441/1476 - loss 0.02054301 - time (sec): 49.11 - samples/sec: 1072.53 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-09-04 14:58:59,911 epoch 8 - iter 588/1476 - loss 0.02120702 - time (sec): 65.35 - samples/sec: 1066.61 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-09-04 14:59:15,831 epoch 8 - iter 735/1476 - loss 0.01961425 - time (sec): 81.27 - samples/sec: 1057.21 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-09-04 14:59:32,105 epoch 8 - iter 882/1476 - loss 0.01762423 - time (sec): 97.55 - samples/sec: 1056.12 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-09-04 14:59:47,161 epoch 8 - iter 1029/1476 - loss 0.01750371 - time (sec): 112.60 - samples/sec: 1053.32 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-09-04 15:00:02,623 epoch 8 - iter 1176/1476 - loss 0.01730821 - time (sec): 128.07 - samples/sec: 1047.60 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-09-04 15:00:17,134 epoch 8 - iter 1323/1476 - loss 0.01677759 - time (sec): 142.58 - samples/sec: 1043.05 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-09-04 15:00:33,610 epoch 8 - iter 1470/1476 - loss 0.01729207 - time (sec): 159.05 - samples/sec: 1042.65 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-09-04 15:00:34,162 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 15:00:34,162 EPOCH 8 done: loss 0.0172 - lr: 0.000011 | |
| 2023-09-04 15:00:51,816 DEV : loss 0.20783096551895142 - f1-score (micro avg) 0.824 | |
| 2023-09-04 15:00:51,845 saving best model | |
| 2023-09-04 15:00:53,192 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 15:01:10,602 epoch 9 - iter 147/1476 - loss 0.01460204 - time (sec): 17.41 - samples/sec: 1033.48 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-09-04 15:01:26,925 epoch 9 - iter 294/1476 - loss 0.01077039 - time (sec): 33.73 - samples/sec: 1040.12 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-09-04 15:01:42,542 epoch 9 - iter 441/1476 - loss 0.01075809 - time (sec): 49.35 - samples/sec: 1025.31 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-09-04 15:01:58,486 epoch 9 - iter 588/1476 - loss 0.01065765 - time (sec): 65.29 - samples/sec: 1027.65 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-09-04 15:02:13,294 epoch 9 - iter 735/1476 - loss 0.01255226 - time (sec): 80.10 - samples/sec: 1020.74 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-09-04 15:02:29,925 epoch 9 - iter 882/1476 - loss 0.01202051 - time (sec): 96.73 - samples/sec: 1023.62 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-09-04 15:02:46,444 epoch 9 - iter 1029/1476 - loss 0.01258727 - time (sec): 113.25 - samples/sec: 1030.10 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-09-04 15:03:01,498 epoch 9 - iter 1176/1476 - loss 0.01267641 - time (sec): 128.30 - samples/sec: 1035.35 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-09-04 15:03:16,907 epoch 9 - iter 1323/1476 - loss 0.01223326 - time (sec): 143.71 - samples/sec: 1036.81 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-09-04 15:03:33,731 epoch 9 - iter 1470/1476 - loss 0.01227625 - time (sec): 160.54 - samples/sec: 1033.07 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-09-04 15:03:34,325 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 15:03:34,325 EPOCH 9 done: loss 0.0122 - lr: 0.000006 | |
| 2023-09-04 15:03:52,069 DEV : loss 0.21233657002449036 - f1-score (micro avg) 0.8289 | |
| 2023-09-04 15:03:52,098 saving best model | |
| 2023-09-04 15:03:53,446 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 15:04:09,986 epoch 10 - iter 147/1476 - loss 0.00749491 - time (sec): 16.54 - samples/sec: 1086.47 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-09-04 15:04:25,082 epoch 10 - iter 294/1476 - loss 0.00470430 - time (sec): 31.64 - samples/sec: 1045.80 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-09-04 15:04:41,524 epoch 10 - iter 441/1476 - loss 0.00519274 - time (sec): 48.08 - samples/sec: 1044.30 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-09-04 15:04:57,211 epoch 10 - iter 588/1476 - loss 0.00563998 - time (sec): 63.76 - samples/sec: 1028.16 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-09-04 15:05:14,292 epoch 10 - iter 735/1476 - loss 0.00672732 - time (sec): 80.85 - samples/sec: 1045.90 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-09-04 15:05:29,635 epoch 10 - iter 882/1476 - loss 0.00659474 - time (sec): 96.19 - samples/sec: 1044.69 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-09-04 15:05:45,611 epoch 10 - iter 1029/1476 - loss 0.00694730 - time (sec): 112.16 - samples/sec: 1044.52 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-09-04 15:06:01,416 epoch 10 - iter 1176/1476 - loss 0.00708200 - time (sec): 127.97 - samples/sec: 1049.01 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-09-04 15:06:16,546 epoch 10 - iter 1323/1476 - loss 0.00670365 - time (sec): 143.10 - samples/sec: 1047.88 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-09-04 15:06:32,906 epoch 10 - iter 1470/1476 - loss 0.00690620 - time (sec): 159.46 - samples/sec: 1040.07 - lr: 0.000000 - momentum: 0.000000 | |
| 2023-09-04 15:06:33,489 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 15:06:33,489 EPOCH 10 done: loss 0.0069 - lr: 0.000000 | |
| 2023-09-04 15:06:51,186 DEV : loss 0.22755871713161469 - f1-score (micro avg) 0.8257 | |
| 2023-09-04 15:06:51,686 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 15:06:51,687 Loading model from best epoch ... | |
| 2023-09-04 15:06:53,562 SequenceTagger predicts: Dictionary with 21 tags: O, S-loc, B-loc, E-loc, I-loc, S-pers, B-pers, E-pers, I-pers, S-org, B-org, E-org, I-org, S-time, B-time, E-time, I-time, S-prod, B-prod, E-prod, I-prod | |
| 2023-09-04 15:07:08,305 | |
| Results: | |
| - F-score (micro) 0.7862 | |
| - F-score (macro) 0.6798 | |
| - Accuracy 0.6733 | |
| By class: | |
| precision recall f1-score support | |
| loc 0.8512 0.8531 0.8522 858 | |
| pers 0.7548 0.8026 0.7780 537 | |
| org 0.5461 0.5833 0.5641 132 | |
| time 0.5224 0.6481 0.5785 54 | |
| prod 0.6667 0.5902 0.6261 61 | |
| micro avg 0.7744 0.7984 0.7862 1642 | |
| macro avg 0.6682 0.6955 0.6798 1642 | |
| weighted avg 0.7775 0.7984 0.7873 1642 | |
| 2023-09-04 15:07:08,305 ---------------------------------------------------------------------------------------------------- | |