| 2023-09-04 18:01:02,696 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 18:01:02,697 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 18:01:02,698 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 18:01:02,698 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 18:01:02,698 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 18:01:02,698 Train: 5901 sentences | |
| 2023-09-04 18:01:02,698 (train_with_dev=False, train_with_test=False) | |
| 2023-09-04 18:01:02,698 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 18:01:02,698 Training Params: | |
| 2023-09-04 18:01:02,698 - learning_rate: "3e-05" | |
| 2023-09-04 18:01:02,698 - mini_batch_size: "4" | |
| 2023-09-04 18:01:02,698 - max_epochs: "10" | |
| 2023-09-04 18:01:02,698 - shuffle: "True" | |
| 2023-09-04 18:01:02,698 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 18:01:02,698 Plugins: | |
| 2023-09-04 18:01:02,698 - LinearScheduler | warmup_fraction: '0.1' | |
| 2023-09-04 18:01:02,698 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 18:01:02,698 Final evaluation on model from best epoch (best-model.pt) | |
| 2023-09-04 18:01:02,699 - metric: "('micro avg', 'f1-score')" | |
| 2023-09-04 18:01:02,699 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 18:01:02,699 Computation: | |
| 2023-09-04 18:01:02,699 - compute on device: cuda:0 | |
| 2023-09-04 18:01:02,699 - embedding storage: none | |
| 2023-09-04 18:01:02,699 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 18:01:02,699 Model training base path: "hmbench-hipe2020/fr-dbmdz/bert-base-historic-multilingual-cased-bs4-wsFalse-e10-lr3e-05-poolingfirst-layers-1-crfFalse-5" | |
| 2023-09-04 18:01:02,699 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 18:01:02,699 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 18:01:18,094 epoch 1 - iter 147/1476 - loss 2.44376377 - time (sec): 15.39 - samples/sec: 1055.91 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-09-04 18:01:33,845 epoch 1 - iter 294/1476 - loss 1.52151398 - time (sec): 31.15 - samples/sec: 1050.94 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-09-04 18:01:49,471 epoch 1 - iter 441/1476 - loss 1.15461415 - time (sec): 46.77 - samples/sec: 1043.42 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-09-04 18:02:05,099 epoch 1 - iter 588/1476 - loss 0.94850083 - time (sec): 62.40 - samples/sec: 1041.15 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-09-04 18:02:21,896 epoch 1 - iter 735/1476 - loss 0.82532013 - time (sec): 79.20 - samples/sec: 1036.04 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-09-04 18:02:36,710 epoch 1 - iter 882/1476 - loss 0.73671035 - time (sec): 94.01 - samples/sec: 1030.80 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-09-04 18:02:53,060 epoch 1 - iter 1029/1476 - loss 0.66213797 - time (sec): 110.36 - samples/sec: 1036.86 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-09-04 18:03:09,409 epoch 1 - iter 1176/1476 - loss 0.60019447 - time (sec): 126.71 - samples/sec: 1042.95 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-09-04 18:03:24,876 epoch 1 - iter 1323/1476 - loss 0.55657173 - time (sec): 142.18 - samples/sec: 1045.22 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-09-04 18:03:41,637 epoch 1 - iter 1470/1476 - loss 0.51947340 - time (sec): 158.94 - samples/sec: 1043.39 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-09-04 18:03:42,206 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 18:03:42,207 EPOCH 1 done: loss 0.5185 - lr: 0.000030 | |
| 2023-09-04 18:03:56,790 DEV : loss 0.15415577590465546 - f1-score (micro avg) 0.6856 | |
| 2023-09-04 18:03:56,837 saving best model | |
| 2023-09-04 18:03:57,328 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 18:04:13,436 epoch 2 - iter 147/1476 - loss 0.13762875 - time (sec): 16.11 - samples/sec: 1041.34 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-09-04 18:04:29,294 epoch 2 - iter 294/1476 - loss 0.14049549 - time (sec): 31.96 - samples/sec: 1038.45 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-09-04 18:04:45,489 epoch 2 - iter 441/1476 - loss 0.13824014 - time (sec): 48.16 - samples/sec: 1037.93 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-09-04 18:05:00,555 epoch 2 - iter 588/1476 - loss 0.13296353 - time (sec): 63.23 - samples/sec: 1035.21 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-09-04 18:05:16,929 epoch 2 - iter 735/1476 - loss 0.12947844 - time (sec): 79.60 - samples/sec: 1052.53 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-09-04 18:05:35,682 epoch 2 - iter 882/1476 - loss 0.13359823 - time (sec): 98.35 - samples/sec: 1063.30 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-09-04 18:05:50,461 epoch 2 - iter 1029/1476 - loss 0.13133894 - time (sec): 113.13 - samples/sec: 1058.87 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-09-04 18:06:06,506 epoch 2 - iter 1176/1476 - loss 0.13058551 - time (sec): 129.18 - samples/sec: 1059.23 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-09-04 18:06:20,816 epoch 2 - iter 1323/1476 - loss 0.13091216 - time (sec): 143.49 - samples/sec: 1053.59 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-09-04 18:06:35,935 epoch 2 - iter 1470/1476 - loss 0.12972873 - time (sec): 158.61 - samples/sec: 1046.77 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-09-04 18:06:36,455 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 18:06:36,455 EPOCH 2 done: loss 0.1295 - lr: 0.000027 | |
| 2023-09-04 18:06:54,283 DEV : loss 0.13132880628108978 - f1-score (micro avg) 0.7834 | |
| 2023-09-04 18:06:54,312 saving best model | |
| 2023-09-04 18:06:55,664 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 18:07:12,339 epoch 3 - iter 147/1476 - loss 0.06202239 - time (sec): 16.67 - samples/sec: 1111.70 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-09-04 18:07:28,604 epoch 3 - iter 294/1476 - loss 0.06649857 - time (sec): 32.94 - samples/sec: 1070.17 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-09-04 18:07:44,511 epoch 3 - iter 441/1476 - loss 0.06984059 - time (sec): 48.85 - samples/sec: 1065.42 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-09-04 18:08:01,651 epoch 3 - iter 588/1476 - loss 0.07783875 - time (sec): 65.99 - samples/sec: 1064.77 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-09-04 18:08:16,965 epoch 3 - iter 735/1476 - loss 0.07932757 - time (sec): 81.30 - samples/sec: 1054.93 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-09-04 18:08:32,668 epoch 3 - iter 882/1476 - loss 0.07615306 - time (sec): 97.00 - samples/sec: 1049.99 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-09-04 18:08:48,048 epoch 3 - iter 1029/1476 - loss 0.07522442 - time (sec): 112.38 - samples/sec: 1045.01 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-09-04 18:09:03,784 epoch 3 - iter 1176/1476 - loss 0.07465154 - time (sec): 128.12 - samples/sec: 1043.48 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-09-04 18:09:19,691 epoch 3 - iter 1323/1476 - loss 0.07700065 - time (sec): 144.03 - samples/sec: 1041.14 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-09-04 18:09:34,988 epoch 3 - iter 1470/1476 - loss 0.07972797 - time (sec): 159.32 - samples/sec: 1041.18 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-09-04 18:09:35,518 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 18:09:35,518 EPOCH 3 done: loss 0.0799 - lr: 0.000023 | |
| 2023-09-04 18:09:53,055 DEV : loss 0.14578530192375183 - f1-score (micro avg) 0.7994 | |
| 2023-09-04 18:09:53,083 saving best model | |
| 2023-09-04 18:09:54,422 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 18:10:10,140 epoch 4 - iter 147/1476 - loss 0.05746252 - time (sec): 15.72 - samples/sec: 1026.05 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-09-04 18:10:27,722 epoch 4 - iter 294/1476 - loss 0.06102346 - time (sec): 33.30 - samples/sec: 1071.19 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-09-04 18:10:43,854 epoch 4 - iter 441/1476 - loss 0.05967365 - time (sec): 49.43 - samples/sec: 1047.86 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-09-04 18:10:58,746 epoch 4 - iter 588/1476 - loss 0.06001754 - time (sec): 64.32 - samples/sec: 1030.36 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-09-04 18:11:15,070 epoch 4 - iter 735/1476 - loss 0.05838120 - time (sec): 80.65 - samples/sec: 1034.71 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-09-04 18:11:30,504 epoch 4 - iter 882/1476 - loss 0.05932716 - time (sec): 96.08 - samples/sec: 1036.16 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-09-04 18:11:45,730 epoch 4 - iter 1029/1476 - loss 0.05890917 - time (sec): 111.31 - samples/sec: 1029.82 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-09-04 18:12:01,064 epoch 4 - iter 1176/1476 - loss 0.05796255 - time (sec): 126.64 - samples/sec: 1031.35 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-09-04 18:12:17,046 epoch 4 - iter 1323/1476 - loss 0.05817651 - time (sec): 142.62 - samples/sec: 1029.12 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-09-04 18:12:34,542 epoch 4 - iter 1470/1476 - loss 0.05645201 - time (sec): 160.12 - samples/sec: 1035.95 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-09-04 18:12:35,105 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 18:12:35,105 EPOCH 4 done: loss 0.0566 - lr: 0.000020 | |
| 2023-09-04 18:12:52,812 DEV : loss 0.18173334002494812 - f1-score (micro avg) 0.8055 | |
| 2023-09-04 18:12:52,842 saving best model | |
| 2023-09-04 18:12:54,191 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 18:13:09,997 epoch 5 - iter 147/1476 - loss 0.05138894 - time (sec): 15.80 - samples/sec: 1064.24 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-09-04 18:13:24,951 epoch 5 - iter 294/1476 - loss 0.04721485 - time (sec): 30.76 - samples/sec: 1027.23 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-09-04 18:13:41,035 epoch 5 - iter 441/1476 - loss 0.04141632 - time (sec): 46.84 - samples/sec: 1030.23 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-09-04 18:13:56,918 epoch 5 - iter 588/1476 - loss 0.03965347 - time (sec): 62.73 - samples/sec: 1034.00 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-09-04 18:14:13,476 epoch 5 - iter 735/1476 - loss 0.04115344 - time (sec): 79.28 - samples/sec: 1035.68 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-09-04 18:14:29,425 epoch 5 - iter 882/1476 - loss 0.04010953 - time (sec): 95.23 - samples/sec: 1038.19 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-09-04 18:14:46,066 epoch 5 - iter 1029/1476 - loss 0.03987999 - time (sec): 111.87 - samples/sec: 1037.38 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-09-04 18:15:02,228 epoch 5 - iter 1176/1476 - loss 0.04089865 - time (sec): 128.04 - samples/sec: 1036.12 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-09-04 18:15:18,305 epoch 5 - iter 1323/1476 - loss 0.04058762 - time (sec): 144.11 - samples/sec: 1038.65 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-09-04 18:15:33,710 epoch 5 - iter 1470/1476 - loss 0.04089062 - time (sec): 159.52 - samples/sec: 1039.41 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-09-04 18:15:34,350 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 18:15:34,351 EPOCH 5 done: loss 0.0407 - lr: 0.000017 | |
| 2023-09-04 18:15:52,045 DEV : loss 0.17798171937465668 - f1-score (micro avg) 0.8282 | |
| 2023-09-04 18:15:52,073 saving best model | |
| 2023-09-04 18:15:53,401 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 18:16:09,370 epoch 6 - iter 147/1476 - loss 0.03077746 - time (sec): 15.97 - samples/sec: 1068.35 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-09-04 18:16:24,765 epoch 6 - iter 294/1476 - loss 0.02870391 - time (sec): 31.36 - samples/sec: 1035.23 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-09-04 18:16:40,709 epoch 6 - iter 441/1476 - loss 0.02709286 - time (sec): 47.31 - samples/sec: 1033.40 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-09-04 18:16:56,794 epoch 6 - iter 588/1476 - loss 0.02749007 - time (sec): 63.39 - samples/sec: 1030.11 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-09-04 18:17:12,164 epoch 6 - iter 735/1476 - loss 0.02642923 - time (sec): 78.76 - samples/sec: 1024.79 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-09-04 18:17:27,358 epoch 6 - iter 882/1476 - loss 0.02612535 - time (sec): 93.96 - samples/sec: 1022.85 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-09-04 18:17:43,902 epoch 6 - iter 1029/1476 - loss 0.02662349 - time (sec): 110.50 - samples/sec: 1029.41 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-09-04 18:17:59,949 epoch 6 - iter 1176/1476 - loss 0.02660086 - time (sec): 126.55 - samples/sec: 1029.02 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-09-04 18:18:16,060 epoch 6 - iter 1323/1476 - loss 0.02752760 - time (sec): 142.66 - samples/sec: 1028.15 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-09-04 18:18:32,511 epoch 6 - iter 1470/1476 - loss 0.02784187 - time (sec): 159.11 - samples/sec: 1037.65 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-09-04 18:18:33,705 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 18:18:33,706 EPOCH 6 done: loss 0.0278 - lr: 0.000013 | |
| 2023-09-04 18:18:51,348 DEV : loss 0.2169143557548523 - f1-score (micro avg) 0.8137 | |
| 2023-09-04 18:18:51,377 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 18:19:07,437 epoch 7 - iter 147/1476 - loss 0.02004925 - time (sec): 16.06 - samples/sec: 1087.97 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-09-04 18:19:25,106 epoch 7 - iter 294/1476 - loss 0.01928499 - time (sec): 33.73 - samples/sec: 1067.37 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-09-04 18:19:41,853 epoch 7 - iter 441/1476 - loss 0.01863859 - time (sec): 50.47 - samples/sec: 1059.56 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-09-04 18:19:58,276 epoch 7 - iter 588/1476 - loss 0.02152433 - time (sec): 66.90 - samples/sec: 1068.83 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-09-04 18:20:12,850 epoch 7 - iter 735/1476 - loss 0.02091597 - time (sec): 81.47 - samples/sec: 1061.81 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-09-04 18:20:29,285 epoch 7 - iter 882/1476 - loss 0.02099112 - time (sec): 97.91 - samples/sec: 1056.78 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-09-04 18:20:44,364 epoch 7 - iter 1029/1476 - loss 0.02043229 - time (sec): 112.99 - samples/sec: 1051.36 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-09-04 18:20:59,863 epoch 7 - iter 1176/1476 - loss 0.01948168 - time (sec): 128.48 - samples/sec: 1046.27 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-09-04 18:21:15,257 epoch 7 - iter 1323/1476 - loss 0.02009420 - time (sec): 143.88 - samples/sec: 1043.76 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-09-04 18:21:30,772 epoch 7 - iter 1470/1476 - loss 0.01960339 - time (sec): 159.39 - samples/sec: 1040.65 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-09-04 18:21:31,414 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 18:21:31,415 EPOCH 7 done: loss 0.0196 - lr: 0.000010 | |
| 2023-09-04 18:21:49,585 DEV : loss 0.20429323613643646 - f1-score (micro avg) 0.8278 | |
| 2023-09-04 18:21:49,614 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 18:22:05,738 epoch 8 - iter 147/1476 - loss 0.01227334 - time (sec): 16.12 - samples/sec: 1097.99 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-09-04 18:22:20,978 epoch 8 - iter 294/1476 - loss 0.00862639 - time (sec): 31.36 - samples/sec: 1054.47 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-09-04 18:22:38,095 epoch 8 - iter 441/1476 - loss 0.01267560 - time (sec): 48.48 - samples/sec: 1069.95 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-09-04 18:22:53,899 epoch 8 - iter 588/1476 - loss 0.01122963 - time (sec): 64.28 - samples/sec: 1049.34 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-09-04 18:23:08,476 epoch 8 - iter 735/1476 - loss 0.01313610 - time (sec): 78.86 - samples/sec: 1037.64 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-09-04 18:23:25,524 epoch 8 - iter 882/1476 - loss 0.01420155 - time (sec): 95.91 - samples/sec: 1040.54 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-09-04 18:23:41,088 epoch 8 - iter 1029/1476 - loss 0.01313444 - time (sec): 111.47 - samples/sec: 1040.35 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-09-04 18:23:56,612 epoch 8 - iter 1176/1476 - loss 0.01285575 - time (sec): 127.00 - samples/sec: 1037.89 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-09-04 18:24:12,668 epoch 8 - iter 1323/1476 - loss 0.01287226 - time (sec): 143.05 - samples/sec: 1036.18 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-09-04 18:24:29,072 epoch 8 - iter 1470/1476 - loss 0.01249485 - time (sec): 159.46 - samples/sec: 1040.11 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-09-04 18:24:29,617 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 18:24:29,617 EPOCH 8 done: loss 0.0125 - lr: 0.000007 | |
| 2023-09-04 18:24:47,345 DEV : loss 0.21515436470508575 - f1-score (micro avg) 0.8236 | |
| 2023-09-04 18:24:47,374 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 18:25:03,113 epoch 9 - iter 147/1476 - loss 0.01194312 - time (sec): 15.74 - samples/sec: 1021.80 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-09-04 18:25:18,626 epoch 9 - iter 294/1476 - loss 0.01113643 - time (sec): 31.25 - samples/sec: 1034.37 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-09-04 18:25:33,931 epoch 9 - iter 441/1476 - loss 0.00892407 - time (sec): 46.56 - samples/sec: 1010.97 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-09-04 18:25:50,615 epoch 9 - iter 588/1476 - loss 0.01054983 - time (sec): 63.24 - samples/sec: 1015.46 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-09-04 18:26:05,989 epoch 9 - iter 735/1476 - loss 0.01020447 - time (sec): 78.61 - samples/sec: 1014.85 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-09-04 18:26:21,846 epoch 9 - iter 882/1476 - loss 0.00970575 - time (sec): 94.47 - samples/sec: 1016.08 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-09-04 18:26:38,280 epoch 9 - iter 1029/1476 - loss 0.00972550 - time (sec): 110.90 - samples/sec: 1026.61 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-09-04 18:26:55,525 epoch 9 - iter 1176/1476 - loss 0.01059971 - time (sec): 128.15 - samples/sec: 1031.92 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-09-04 18:27:10,728 epoch 9 - iter 1323/1476 - loss 0.01001943 - time (sec): 143.35 - samples/sec: 1029.52 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-09-04 18:27:26,756 epoch 9 - iter 1470/1476 - loss 0.00955175 - time (sec): 159.38 - samples/sec: 1035.45 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-09-04 18:27:27,865 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 18:27:27,866 EPOCH 9 done: loss 0.0095 - lr: 0.000003 | |
| 2023-09-04 18:27:45,558 DEV : loss 0.20868642628192902 - f1-score (micro avg) 0.8292 | |
| 2023-09-04 18:27:45,587 saving best model | |
| 2023-09-04 18:27:46,955 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 18:28:02,137 epoch 10 - iter 147/1476 - loss 0.00101060 - time (sec): 15.18 - samples/sec: 1010.93 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-09-04 18:28:18,974 epoch 10 - iter 294/1476 - loss 0.00390884 - time (sec): 32.02 - samples/sec: 1028.47 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-09-04 18:28:35,317 epoch 10 - iter 441/1476 - loss 0.00447299 - time (sec): 48.36 - samples/sec: 1024.21 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-09-04 18:28:51,711 epoch 10 - iter 588/1476 - loss 0.00417455 - time (sec): 64.75 - samples/sec: 1030.00 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-09-04 18:29:08,401 epoch 10 - iter 735/1476 - loss 0.00470003 - time (sec): 81.44 - samples/sec: 1039.68 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-09-04 18:29:23,342 epoch 10 - iter 882/1476 - loss 0.00479490 - time (sec): 96.38 - samples/sec: 1041.02 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-09-04 18:29:38,135 epoch 10 - iter 1029/1476 - loss 0.00653311 - time (sec): 111.18 - samples/sec: 1041.64 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-09-04 18:29:54,398 epoch 10 - iter 1176/1476 - loss 0.00644572 - time (sec): 127.44 - samples/sec: 1038.01 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-09-04 18:30:10,831 epoch 10 - iter 1323/1476 - loss 0.00614733 - time (sec): 143.87 - samples/sec: 1044.88 - lr: 0.000000 - momentum: 0.000000 | |
| 2023-09-04 18:30:26,129 epoch 10 - iter 1470/1476 - loss 0.00651115 - time (sec): 159.17 - samples/sec: 1041.46 - lr: 0.000000 - momentum: 0.000000 | |
| 2023-09-04 18:30:26,732 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 18:30:26,732 EPOCH 10 done: loss 0.0065 - lr: 0.000000 | |
| 2023-09-04 18:30:44,728 DEV : loss 0.22322718799114227 - f1-score (micro avg) 0.8291 | |
| 2023-09-04 18:30:45,239 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-04 18:30:45,241 Loading model from best epoch ... | |
| 2023-09-04 18:30:47,124 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 18:31:01,874 | |
| Results: | |
| - F-score (micro) 0.7899 | |
| - F-score (macro) 0.6984 | |
| - Accuracy 0.6764 | |
| By class: | |
| precision recall f1-score support | |
| loc 0.8319 0.8765 0.8536 858 | |
| pers 0.7709 0.7896 0.7801 537 | |
| org 0.5034 0.5606 0.5305 132 | |
| time 0.5645 0.6481 0.6034 54 | |
| prod 0.7636 0.6885 0.7241 61 | |
| micro avg 0.7724 0.8082 0.7899 1642 | |
| macro avg 0.6869 0.7127 0.6984 1642 | |
| weighted avg 0.7742 0.8082 0.7905 1642 | |
| 2023-09-04 18:31:01,875 ---------------------------------------------------------------------------------------------------- | |