| 2023-10-17 09:37:27,236 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 09:37:27,238 Model: "SequenceTagger( | |
| (embeddings): TransformerWordEmbeddings( | |
| (model): ElectraModel( | |
| (embeddings): ElectraEmbeddings( | |
| (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): ElectraEncoder( | |
| (layer): ModuleList( | |
| (0-11): 12 x ElectraLayer( | |
| (attention): ElectraAttention( | |
| (self): ElectraSelfAttention( | |
| (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): ElectraSelfOutput( | |
| (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): ElectraIntermediate( | |
| (dense): Linear(in_features=768, out_features=3072, bias=True) | |
| (intermediate_act_fn): GELUActivation() | |
| ) | |
| (output): ElectraOutput( | |
| (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) | |
| ) | |
| ) | |
| ) | |
| ) | |
| ) | |
| ) | |
| (locked_dropout): LockedDropout(p=0.5) | |
| (linear): Linear(in_features=768, out_features=13, bias=True) | |
| (loss_function): CrossEntropyLoss() | |
| )" | |
| 2023-10-17 09:37:27,238 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 09:37:27,238 MultiCorpus: 6183 train + 680 dev + 2113 test sentences | |
| - NER_HIPE_2022 Corpus: 6183 train + 680 dev + 2113 test sentences - /root/.flair/datasets/ner_hipe_2022/v2.1/topres19th/en/with_doc_seperator | |
| 2023-10-17 09:37:27,238 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 09:37:27,239 Train: 6183 sentences | |
| 2023-10-17 09:37:27,239 (train_with_dev=False, train_with_test=False) | |
| 2023-10-17 09:37:27,239 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 09:37:27,239 Training Params: | |
| 2023-10-17 09:37:27,239 - learning_rate: "3e-05" | |
| 2023-10-17 09:37:27,239 - mini_batch_size: "8" | |
| 2023-10-17 09:37:27,239 - max_epochs: "10" | |
| 2023-10-17 09:37:27,239 - shuffle: "True" | |
| 2023-10-17 09:37:27,239 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 09:37:27,239 Plugins: | |
| 2023-10-17 09:37:27,239 - TensorboardLogger | |
| 2023-10-17 09:37:27,239 - LinearScheduler | warmup_fraction: '0.1' | |
| 2023-10-17 09:37:27,239 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 09:37:27,239 Final evaluation on model from best epoch (best-model.pt) | |
| 2023-10-17 09:37:27,240 - metric: "('micro avg', 'f1-score')" | |
| 2023-10-17 09:37:27,240 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 09:37:27,240 Computation: | |
| 2023-10-17 09:37:27,240 - compute on device: cuda:0 | |
| 2023-10-17 09:37:27,240 - embedding storage: none | |
| 2023-10-17 09:37:27,240 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 09:37:27,240 Model training base path: "hmbench-topres19th/en-hmteams/teams-base-historic-multilingual-discriminator-bs8-wsFalse-e10-lr3e-05-poolingfirst-layers-1-crfFalse-1" | |
| 2023-10-17 09:37:27,240 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 09:37:27,240 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 09:37:27,240 Logging anything other than scalars to TensorBoard is currently not supported. | |
| 2023-10-17 09:37:34,576 epoch 1 - iter 77/773 - loss 2.33879566 - time (sec): 7.33 - samples/sec: 1752.72 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-17 09:37:41,584 epoch 1 - iter 154/773 - loss 1.42646834 - time (sec): 14.34 - samples/sec: 1749.19 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-17 09:37:48,222 epoch 1 - iter 231/773 - loss 1.01107736 - time (sec): 20.98 - samples/sec: 1783.57 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-17 09:37:55,237 epoch 1 - iter 308/773 - loss 0.78648939 - time (sec): 28.00 - samples/sec: 1800.87 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-17 09:38:02,692 epoch 1 - iter 385/773 - loss 0.65487679 - time (sec): 35.45 - samples/sec: 1767.05 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-17 09:38:09,721 epoch 1 - iter 462/773 - loss 0.56517862 - time (sec): 42.48 - samples/sec: 1763.85 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-17 09:38:17,445 epoch 1 - iter 539/773 - loss 0.50859951 - time (sec): 50.20 - samples/sec: 1727.34 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-17 09:38:24,994 epoch 1 - iter 616/773 - loss 0.46183259 - time (sec): 57.75 - samples/sec: 1710.88 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-17 09:38:32,538 epoch 1 - iter 693/773 - loss 0.41835378 - time (sec): 65.30 - samples/sec: 1708.79 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-17 09:38:39,593 epoch 1 - iter 770/773 - loss 0.38499874 - time (sec): 72.35 - samples/sec: 1713.83 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-17 09:38:39,844 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 09:38:39,844 EPOCH 1 done: loss 0.3842 - lr: 0.000030 | |
| 2023-10-17 09:38:42,623 DEV : loss 0.05754069611430168 - f1-score (micro avg) 0.7534 | |
| 2023-10-17 09:38:42,650 saving best model | |
| 2023-10-17 09:38:43,192 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 09:38:49,786 epoch 2 - iter 77/773 - loss 0.10261422 - time (sec): 6.59 - samples/sec: 1792.64 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-17 09:38:56,506 epoch 2 - iter 154/773 - loss 0.08620224 - time (sec): 13.31 - samples/sec: 1814.77 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-17 09:39:03,586 epoch 2 - iter 231/773 - loss 0.08217454 - time (sec): 20.39 - samples/sec: 1848.76 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-17 09:39:10,410 epoch 2 - iter 308/773 - loss 0.08124803 - time (sec): 27.22 - samples/sec: 1841.98 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-17 09:39:17,499 epoch 2 - iter 385/773 - loss 0.07988568 - time (sec): 34.31 - samples/sec: 1829.13 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-17 09:39:25,060 epoch 2 - iter 462/773 - loss 0.07997375 - time (sec): 41.87 - samples/sec: 1789.65 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-17 09:39:32,052 epoch 2 - iter 539/773 - loss 0.07763047 - time (sec): 48.86 - samples/sec: 1790.10 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-17 09:39:39,204 epoch 2 - iter 616/773 - loss 0.07703563 - time (sec): 56.01 - samples/sec: 1794.93 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-17 09:39:46,211 epoch 2 - iter 693/773 - loss 0.07619810 - time (sec): 63.02 - samples/sec: 1780.52 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-17 09:39:53,478 epoch 2 - iter 770/773 - loss 0.07711628 - time (sec): 70.28 - samples/sec: 1764.60 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-17 09:39:53,755 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 09:39:53,755 EPOCH 2 done: loss 0.0772 - lr: 0.000027 | |
| 2023-10-17 09:39:56,582 DEV : loss 0.047075219452381134 - f1-score (micro avg) 0.7597 | |
| 2023-10-17 09:39:56,610 saving best model | |
| 2023-10-17 09:39:57,996 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 09:40:05,357 epoch 3 - iter 77/773 - loss 0.04621094 - time (sec): 7.36 - samples/sec: 1588.98 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-17 09:40:13,046 epoch 3 - iter 154/773 - loss 0.04711698 - time (sec): 15.05 - samples/sec: 1650.32 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-17 09:40:20,395 epoch 3 - iter 231/773 - loss 0.04627990 - time (sec): 22.39 - samples/sec: 1705.13 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-17 09:40:27,418 epoch 3 - iter 308/773 - loss 0.04368407 - time (sec): 29.42 - samples/sec: 1719.86 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-17 09:40:34,373 epoch 3 - iter 385/773 - loss 0.04513632 - time (sec): 36.37 - samples/sec: 1716.82 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-17 09:40:41,366 epoch 3 - iter 462/773 - loss 0.04669092 - time (sec): 43.37 - samples/sec: 1731.18 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-17 09:40:48,481 epoch 3 - iter 539/773 - loss 0.04627462 - time (sec): 50.48 - samples/sec: 1726.60 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-17 09:40:55,508 epoch 3 - iter 616/773 - loss 0.04565734 - time (sec): 57.51 - samples/sec: 1730.70 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-17 09:41:02,972 epoch 3 - iter 693/773 - loss 0.04735239 - time (sec): 64.97 - samples/sec: 1698.13 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-17 09:41:10,809 epoch 3 - iter 770/773 - loss 0.04789770 - time (sec): 72.81 - samples/sec: 1701.70 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-17 09:41:11,097 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 09:41:11,097 EPOCH 3 done: loss 0.0479 - lr: 0.000023 | |
| 2023-10-17 09:41:14,193 DEV : loss 0.04879758879542351 - f1-score (micro avg) 0.804 | |
| 2023-10-17 09:41:14,221 saving best model | |
| 2023-10-17 09:41:15,684 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 09:41:23,490 epoch 4 - iter 77/773 - loss 0.02803532 - time (sec): 7.80 - samples/sec: 1647.61 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-17 09:41:31,172 epoch 4 - iter 154/773 - loss 0.02614174 - time (sec): 15.49 - samples/sec: 1583.78 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-17 09:41:38,912 epoch 4 - iter 231/773 - loss 0.02740037 - time (sec): 23.22 - samples/sec: 1615.22 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-17 09:41:46,418 epoch 4 - iter 308/773 - loss 0.02810327 - time (sec): 30.73 - samples/sec: 1627.11 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-17 09:41:54,017 epoch 4 - iter 385/773 - loss 0.02856760 - time (sec): 38.33 - samples/sec: 1628.38 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-17 09:42:02,005 epoch 4 - iter 462/773 - loss 0.03151706 - time (sec): 46.32 - samples/sec: 1625.94 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-17 09:42:09,711 epoch 4 - iter 539/773 - loss 0.03118289 - time (sec): 54.02 - samples/sec: 1629.16 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-17 09:42:17,213 epoch 4 - iter 616/773 - loss 0.03069938 - time (sec): 61.53 - samples/sec: 1620.50 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-17 09:42:24,916 epoch 4 - iter 693/773 - loss 0.03102882 - time (sec): 69.23 - samples/sec: 1610.69 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-17 09:42:32,858 epoch 4 - iter 770/773 - loss 0.03091728 - time (sec): 77.17 - samples/sec: 1606.19 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-17 09:42:33,116 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 09:42:33,116 EPOCH 4 done: loss 0.0311 - lr: 0.000020 | |
| 2023-10-17 09:42:36,004 DEV : loss 0.0732564851641655 - f1-score (micro avg) 0.7938 | |
| 2023-10-17 09:42:36,033 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 09:42:43,080 epoch 5 - iter 77/773 - loss 0.02562462 - time (sec): 7.04 - samples/sec: 1684.07 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-17 09:42:50,338 epoch 5 - iter 154/773 - loss 0.02186778 - time (sec): 14.30 - samples/sec: 1698.22 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-17 09:42:57,692 epoch 5 - iter 231/773 - loss 0.02197283 - time (sec): 21.66 - samples/sec: 1670.07 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-17 09:43:05,104 epoch 5 - iter 308/773 - loss 0.02085800 - time (sec): 29.07 - samples/sec: 1665.35 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-17 09:43:12,720 epoch 5 - iter 385/773 - loss 0.02066640 - time (sec): 36.68 - samples/sec: 1673.37 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-17 09:43:19,967 epoch 5 - iter 462/773 - loss 0.02032896 - time (sec): 43.93 - samples/sec: 1684.46 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-17 09:43:27,490 epoch 5 - iter 539/773 - loss 0.01942875 - time (sec): 51.45 - samples/sec: 1681.14 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-17 09:43:35,178 epoch 5 - iter 616/773 - loss 0.02036285 - time (sec): 59.14 - samples/sec: 1668.33 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-17 09:43:42,777 epoch 5 - iter 693/773 - loss 0.02050199 - time (sec): 66.74 - samples/sec: 1676.73 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-17 09:43:50,579 epoch 5 - iter 770/773 - loss 0.02101369 - time (sec): 74.54 - samples/sec: 1660.09 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-17 09:43:50,903 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 09:43:50,904 EPOCH 5 done: loss 0.0212 - lr: 0.000017 | |
| 2023-10-17 09:43:54,291 DEV : loss 0.09599114209413528 - f1-score (micro avg) 0.7787 | |
| 2023-10-17 09:43:54,321 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 09:44:02,198 epoch 6 - iter 77/773 - loss 0.01113512 - time (sec): 7.87 - samples/sec: 1629.16 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-17 09:44:09,915 epoch 6 - iter 154/773 - loss 0.01041077 - time (sec): 15.59 - samples/sec: 1650.97 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-17 09:44:17,666 epoch 6 - iter 231/773 - loss 0.01184309 - time (sec): 23.34 - samples/sec: 1629.14 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-17 09:44:25,575 epoch 6 - iter 308/773 - loss 0.01381827 - time (sec): 31.25 - samples/sec: 1617.95 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-17 09:44:32,527 epoch 6 - iter 385/773 - loss 0.01530116 - time (sec): 38.20 - samples/sec: 1663.06 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-17 09:44:39,617 epoch 6 - iter 462/773 - loss 0.01664026 - time (sec): 45.29 - samples/sec: 1658.96 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-17 09:44:46,872 epoch 6 - iter 539/773 - loss 0.01619538 - time (sec): 52.55 - samples/sec: 1653.81 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-17 09:44:54,077 epoch 6 - iter 616/773 - loss 0.01625589 - time (sec): 59.75 - samples/sec: 1652.08 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-17 09:45:01,550 epoch 6 - iter 693/773 - loss 0.01623770 - time (sec): 67.22 - samples/sec: 1656.58 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-17 09:45:09,080 epoch 6 - iter 770/773 - loss 0.01610707 - time (sec): 74.75 - samples/sec: 1657.18 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-17 09:45:09,364 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 09:45:09,364 EPOCH 6 done: loss 0.0161 - lr: 0.000013 | |
| 2023-10-17 09:45:12,313 DEV : loss 0.10213357210159302 - f1-score (micro avg) 0.7975 | |
| 2023-10-17 09:45:12,341 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 09:45:19,108 epoch 7 - iter 77/773 - loss 0.00659626 - time (sec): 6.77 - samples/sec: 1731.83 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-17 09:45:25,993 epoch 7 - iter 154/773 - loss 0.01050483 - time (sec): 13.65 - samples/sec: 1738.79 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-17 09:45:32,858 epoch 7 - iter 231/773 - loss 0.01031709 - time (sec): 20.52 - samples/sec: 1766.06 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-17 09:45:39,920 epoch 7 - iter 308/773 - loss 0.01094286 - time (sec): 27.58 - samples/sec: 1774.72 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-17 09:45:46,969 epoch 7 - iter 385/773 - loss 0.01060798 - time (sec): 34.63 - samples/sec: 1778.49 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-17 09:45:53,878 epoch 7 - iter 462/773 - loss 0.00964801 - time (sec): 41.53 - samples/sec: 1779.93 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-17 09:46:00,494 epoch 7 - iter 539/773 - loss 0.00899137 - time (sec): 48.15 - samples/sec: 1785.57 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-17 09:46:07,442 epoch 7 - iter 616/773 - loss 0.00899506 - time (sec): 55.10 - samples/sec: 1798.25 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-17 09:46:14,354 epoch 7 - iter 693/773 - loss 0.00947777 - time (sec): 62.01 - samples/sec: 1804.02 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-17 09:46:21,321 epoch 7 - iter 770/773 - loss 0.01042790 - time (sec): 68.98 - samples/sec: 1793.18 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-17 09:46:21,605 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 09:46:21,605 EPOCH 7 done: loss 0.0105 - lr: 0.000010 | |
| 2023-10-17 09:46:24,548 DEV : loss 0.10294033586978912 - f1-score (micro avg) 0.7984 | |
| 2023-10-17 09:46:24,575 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 09:46:31,444 epoch 8 - iter 77/773 - loss 0.01082701 - time (sec): 6.87 - samples/sec: 1802.66 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-17 09:46:38,217 epoch 8 - iter 154/773 - loss 0.00937227 - time (sec): 13.64 - samples/sec: 1852.12 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-17 09:46:44,941 epoch 8 - iter 231/773 - loss 0.01054096 - time (sec): 20.36 - samples/sec: 1835.19 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-17 09:46:51,562 epoch 8 - iter 308/773 - loss 0.00981916 - time (sec): 26.99 - samples/sec: 1833.97 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-17 09:46:58,389 epoch 8 - iter 385/773 - loss 0.00891815 - time (sec): 33.81 - samples/sec: 1819.33 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-17 09:47:05,424 epoch 8 - iter 462/773 - loss 0.00820688 - time (sec): 40.85 - samples/sec: 1827.76 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-17 09:47:12,186 epoch 8 - iter 539/773 - loss 0.00762464 - time (sec): 47.61 - samples/sec: 1840.44 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-17 09:47:18,915 epoch 8 - iter 616/773 - loss 0.00722670 - time (sec): 54.34 - samples/sec: 1830.88 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-17 09:47:26,084 epoch 8 - iter 693/773 - loss 0.00708273 - time (sec): 61.51 - samples/sec: 1804.20 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-17 09:47:33,076 epoch 8 - iter 770/773 - loss 0.00691715 - time (sec): 68.50 - samples/sec: 1809.37 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-17 09:47:33,365 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 09:47:33,366 EPOCH 8 done: loss 0.0069 - lr: 0.000007 | |
| 2023-10-17 09:47:36,625 DEV : loss 0.12377041578292847 - f1-score (micro avg) 0.7854 | |
| 2023-10-17 09:47:36,665 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 09:47:43,762 epoch 9 - iter 77/773 - loss 0.00448652 - time (sec): 7.09 - samples/sec: 1776.99 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-17 09:47:50,939 epoch 9 - iter 154/773 - loss 0.00413824 - time (sec): 14.27 - samples/sec: 1718.66 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-17 09:47:58,038 epoch 9 - iter 231/773 - loss 0.00450347 - time (sec): 21.37 - samples/sec: 1750.13 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-17 09:48:04,825 epoch 9 - iter 308/773 - loss 0.00438937 - time (sec): 28.16 - samples/sec: 1744.81 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-17 09:48:11,751 epoch 9 - iter 385/773 - loss 0.00389918 - time (sec): 35.08 - samples/sec: 1764.04 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-17 09:48:18,655 epoch 9 - iter 462/773 - loss 0.00409811 - time (sec): 41.99 - samples/sec: 1762.60 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-17 09:48:25,972 epoch 9 - iter 539/773 - loss 0.00408809 - time (sec): 49.30 - samples/sec: 1762.28 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-17 09:48:33,178 epoch 9 - iter 616/773 - loss 0.00422096 - time (sec): 56.51 - samples/sec: 1752.15 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-17 09:48:40,631 epoch 9 - iter 693/773 - loss 0.00424621 - time (sec): 63.96 - samples/sec: 1756.00 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-17 09:48:47,886 epoch 9 - iter 770/773 - loss 0.00460245 - time (sec): 71.22 - samples/sec: 1738.54 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-17 09:48:48,169 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 09:48:48,169 EPOCH 9 done: loss 0.0046 - lr: 0.000003 | |
| 2023-10-17 09:48:51,211 DEV : loss 0.11872641742229462 - f1-score (micro avg) 0.8089 | |
| 2023-10-17 09:48:51,241 saving best model | |
| 2023-10-17 09:48:51,815 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 09:48:58,687 epoch 10 - iter 77/773 - loss 0.00222354 - time (sec): 6.87 - samples/sec: 1822.68 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-17 09:49:05,736 epoch 10 - iter 154/773 - loss 0.00255318 - time (sec): 13.92 - samples/sec: 1781.09 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-17 09:49:12,757 epoch 10 - iter 231/773 - loss 0.00220584 - time (sec): 20.94 - samples/sec: 1807.28 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-17 09:49:19,469 epoch 10 - iter 308/773 - loss 0.00272066 - time (sec): 27.65 - samples/sec: 1817.54 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-17 09:49:26,263 epoch 10 - iter 385/773 - loss 0.00296102 - time (sec): 34.45 - samples/sec: 1814.48 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-17 09:49:32,975 epoch 10 - iter 462/773 - loss 0.00304331 - time (sec): 41.16 - samples/sec: 1803.57 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-17 09:49:40,073 epoch 10 - iter 539/773 - loss 0.00318944 - time (sec): 48.26 - samples/sec: 1803.54 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-17 09:49:47,138 epoch 10 - iter 616/773 - loss 0.00312936 - time (sec): 55.32 - samples/sec: 1786.57 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-17 09:49:54,283 epoch 10 - iter 693/773 - loss 0.00302278 - time (sec): 62.47 - samples/sec: 1784.02 - lr: 0.000000 - momentum: 0.000000 | |
| 2023-10-17 09:50:01,888 epoch 10 - iter 770/773 - loss 0.00307193 - time (sec): 70.07 - samples/sec: 1767.38 - lr: 0.000000 - momentum: 0.000000 | |
| 2023-10-17 09:50:02,150 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 09:50:02,150 EPOCH 10 done: loss 0.0031 - lr: 0.000000 | |
| 2023-10-17 09:50:05,066 DEV : loss 0.12313356250524521 - f1-score (micro avg) 0.7967 | |
| 2023-10-17 09:50:05,705 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 09:50:05,708 Loading model from best epoch ... | |
| 2023-10-17 09:50:08,303 SequenceTagger predicts: Dictionary with 13 tags: O, S-LOC, B-LOC, E-LOC, I-LOC, S-BUILDING, B-BUILDING, E-BUILDING, I-BUILDING, S-STREET, B-STREET, E-STREET, I-STREET | |
| 2023-10-17 09:50:17,304 | |
| Results: | |
| - F-score (micro) 0.8152 | |
| - F-score (macro) 0.7257 | |
| - Accuracy 0.7076 | |
| By class: | |
| precision recall f1-score support | |
| LOC 0.8495 0.8710 0.8601 946 | |
| BUILDING 0.6301 0.5892 0.6089 185 | |
| STREET 0.7018 0.7143 0.7080 56 | |
| micro avg 0.8108 0.8197 0.8152 1187 | |
| macro avg 0.7271 0.7248 0.7257 1187 | |
| weighted avg 0.8083 0.8197 0.8138 1187 | |
| 2023-10-17 09:50:17,304 ---------------------------------------------------------------------------------------------------- | |