| 2023-10-17 13:22:43,668 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 13:22:43,670 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 13:22:43,670 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 13:22:43,670 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 13:22:43,670 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 13:22:43,670 Train: 6183 sentences | |
| 2023-10-17 13:22:43,670 (train_with_dev=False, train_with_test=False) | |
| 2023-10-17 13:22:43,670 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 13:22:43,670 Training Params: | |
| 2023-10-17 13:22:43,670 - learning_rate: "5e-05" | |
| 2023-10-17 13:22:43,671 - mini_batch_size: "8" | |
| 2023-10-17 13:22:43,671 - max_epochs: "10" | |
| 2023-10-17 13:22:43,671 - shuffle: "True" | |
| 2023-10-17 13:22:43,671 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 13:22:43,671 Plugins: | |
| 2023-10-17 13:22:43,671 - TensorboardLogger | |
| 2023-10-17 13:22:43,671 - LinearScheduler | warmup_fraction: '0.1' | |
| 2023-10-17 13:22:43,671 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 13:22:43,671 Final evaluation on model from best epoch (best-model.pt) | |
| 2023-10-17 13:22:43,671 - metric: "('micro avg', 'f1-score')" | |
| 2023-10-17 13:22:43,671 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 13:22:43,671 Computation: | |
| 2023-10-17 13:22:43,671 - compute on device: cuda:0 | |
| 2023-10-17 13:22:43,671 - embedding storage: none | |
| 2023-10-17 13:22:43,671 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 13:22:43,671 Model training base path: "hmbench-topres19th/en-hmteams/teams-base-historic-multilingual-discriminator-bs8-wsFalse-e10-lr5e-05-poolingfirst-layers-1-crfFalse-4" | |
| 2023-10-17 13:22:43,672 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 13:22:43,672 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 13:22:43,672 Logging anything other than scalars to TensorBoard is currently not supported. | |
| 2023-10-17 13:22:50,667 epoch 1 - iter 77/773 - loss 2.65276957 - time (sec): 6.99 - samples/sec: 1714.39 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-17 13:22:58,785 epoch 1 - iter 154/773 - loss 1.50483396 - time (sec): 15.11 - samples/sec: 1552.80 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-17 13:23:07,010 epoch 1 - iter 231/773 - loss 1.04258462 - time (sec): 23.34 - samples/sec: 1532.79 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-17 13:23:14,617 epoch 1 - iter 308/773 - loss 0.81592386 - time (sec): 30.94 - samples/sec: 1544.05 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-17 13:23:21,831 epoch 1 - iter 385/773 - loss 0.66498214 - time (sec): 38.16 - samples/sec: 1600.85 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-17 13:23:29,252 epoch 1 - iter 462/773 - loss 0.57446633 - time (sec): 45.58 - samples/sec: 1615.99 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-17 13:23:36,947 epoch 1 - iter 539/773 - loss 0.51014535 - time (sec): 53.27 - samples/sec: 1611.30 - lr: 0.000035 - momentum: 0.000000 | |
| 2023-10-17 13:23:44,588 epoch 1 - iter 616/773 - loss 0.45806067 - time (sec): 60.91 - samples/sec: 1616.25 - lr: 0.000040 - momentum: 0.000000 | |
| 2023-10-17 13:23:52,202 epoch 1 - iter 693/773 - loss 0.41752980 - time (sec): 68.53 - samples/sec: 1619.91 - lr: 0.000045 - momentum: 0.000000 | |
| 2023-10-17 13:23:59,910 epoch 1 - iter 770/773 - loss 0.38405207 - time (sec): 76.24 - samples/sec: 1623.09 - lr: 0.000050 - momentum: 0.000000 | |
| 2023-10-17 13:24:00,248 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 13:24:00,248 EPOCH 1 done: loss 0.3827 - lr: 0.000050 | |
| 2023-10-17 13:24:03,117 DEV : loss 0.07178231328725815 - f1-score (micro avg) 0.7388 | |
| 2023-10-17 13:24:03,153 saving best model | |
| 2023-10-17 13:24:03,704 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 13:24:11,320 epoch 2 - iter 77/773 - loss 0.10166111 - time (sec): 7.61 - samples/sec: 1610.43 - lr: 0.000049 - momentum: 0.000000 | |
| 2023-10-17 13:24:19,934 epoch 2 - iter 154/773 - loss 0.09050508 - time (sec): 16.23 - samples/sec: 1543.22 - lr: 0.000049 - momentum: 0.000000 | |
| 2023-10-17 13:24:28,525 epoch 2 - iter 231/773 - loss 0.07988076 - time (sec): 24.82 - samples/sec: 1489.76 - lr: 0.000048 - momentum: 0.000000 | |
| 2023-10-17 13:24:36,766 epoch 2 - iter 308/773 - loss 0.08428363 - time (sec): 33.06 - samples/sec: 1488.34 - lr: 0.000048 - momentum: 0.000000 | |
| 2023-10-17 13:24:44,604 epoch 2 - iter 385/773 - loss 0.08289357 - time (sec): 40.90 - samples/sec: 1503.67 - lr: 0.000047 - momentum: 0.000000 | |
| 2023-10-17 13:24:52,380 epoch 2 - iter 462/773 - loss 0.08196435 - time (sec): 48.67 - samples/sec: 1511.52 - lr: 0.000047 - momentum: 0.000000 | |
| 2023-10-17 13:25:00,140 epoch 2 - iter 539/773 - loss 0.08262791 - time (sec): 56.43 - samples/sec: 1528.55 - lr: 0.000046 - momentum: 0.000000 | |
| 2023-10-17 13:25:07,168 epoch 2 - iter 616/773 - loss 0.08205644 - time (sec): 63.46 - samples/sec: 1544.80 - lr: 0.000046 - momentum: 0.000000 | |
| 2023-10-17 13:25:14,562 epoch 2 - iter 693/773 - loss 0.08432683 - time (sec): 70.86 - samples/sec: 1567.04 - lr: 0.000045 - momentum: 0.000000 | |
| 2023-10-17 13:25:22,493 epoch 2 - iter 770/773 - loss 0.08280984 - time (sec): 78.79 - samples/sec: 1573.85 - lr: 0.000044 - momentum: 0.000000 | |
| 2023-10-17 13:25:22,786 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 13:25:22,787 EPOCH 2 done: loss 0.0828 - lr: 0.000044 | |
| 2023-10-17 13:25:26,108 DEV : loss 0.06471428275108337 - f1-score (micro avg) 0.7308 | |
| 2023-10-17 13:25:26,148 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 13:25:33,242 epoch 3 - iter 77/773 - loss 0.04734008 - time (sec): 7.09 - samples/sec: 1914.14 - lr: 0.000044 - momentum: 0.000000 | |
| 2023-10-17 13:25:40,706 epoch 3 - iter 154/773 - loss 0.04641381 - time (sec): 14.56 - samples/sec: 1745.71 - lr: 0.000043 - momentum: 0.000000 | |
| 2023-10-17 13:25:48,038 epoch 3 - iter 231/773 - loss 0.04809967 - time (sec): 21.89 - samples/sec: 1733.65 - lr: 0.000043 - momentum: 0.000000 | |
| 2023-10-17 13:25:55,854 epoch 3 - iter 308/773 - loss 0.04990812 - time (sec): 29.70 - samples/sec: 1677.29 - lr: 0.000042 - momentum: 0.000000 | |
| 2023-10-17 13:26:03,686 epoch 3 - iter 385/773 - loss 0.05048319 - time (sec): 37.54 - samples/sec: 1699.50 - lr: 0.000042 - momentum: 0.000000 | |
| 2023-10-17 13:26:11,254 epoch 3 - iter 462/773 - loss 0.05159978 - time (sec): 45.10 - samples/sec: 1672.23 - lr: 0.000041 - momentum: 0.000000 | |
| 2023-10-17 13:26:19,097 epoch 3 - iter 539/773 - loss 0.05384271 - time (sec): 52.95 - samples/sec: 1658.86 - lr: 0.000041 - momentum: 0.000000 | |
| 2023-10-17 13:26:27,220 epoch 3 - iter 616/773 - loss 0.05339688 - time (sec): 61.07 - samples/sec: 1636.21 - lr: 0.000040 - momentum: 0.000000 | |
| 2023-10-17 13:26:34,983 epoch 3 - iter 693/773 - loss 0.05430285 - time (sec): 68.83 - samples/sec: 1628.32 - lr: 0.000039 - momentum: 0.000000 | |
| 2023-10-17 13:26:42,445 epoch 3 - iter 770/773 - loss 0.05408300 - time (sec): 76.29 - samples/sec: 1623.99 - lr: 0.000039 - momentum: 0.000000 | |
| 2023-10-17 13:26:42,713 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 13:26:42,713 EPOCH 3 done: loss 0.0539 - lr: 0.000039 | |
| 2023-10-17 13:26:45,984 DEV : loss 0.07156790047883987 - f1-score (micro avg) 0.7604 | |
| 2023-10-17 13:26:46,017 saving best model | |
| 2023-10-17 13:26:46,701 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 13:26:54,707 epoch 4 - iter 77/773 - loss 0.03412300 - time (sec): 8.00 - samples/sec: 1555.61 - lr: 0.000038 - momentum: 0.000000 | |
| 2023-10-17 13:27:02,413 epoch 4 - iter 154/773 - loss 0.03849885 - time (sec): 15.71 - samples/sec: 1595.13 - lr: 0.000038 - momentum: 0.000000 | |
| 2023-10-17 13:27:10,142 epoch 4 - iter 231/773 - loss 0.03711970 - time (sec): 23.44 - samples/sec: 1565.17 - lr: 0.000037 - momentum: 0.000000 | |
| 2023-10-17 13:27:17,871 epoch 4 - iter 308/773 - loss 0.03516844 - time (sec): 31.17 - samples/sec: 1585.88 - lr: 0.000037 - momentum: 0.000000 | |
| 2023-10-17 13:27:25,414 epoch 4 - iter 385/773 - loss 0.03362153 - time (sec): 38.71 - samples/sec: 1605.42 - lr: 0.000036 - momentum: 0.000000 | |
| 2023-10-17 13:27:33,440 epoch 4 - iter 462/773 - loss 0.03692177 - time (sec): 46.74 - samples/sec: 1601.94 - lr: 0.000036 - momentum: 0.000000 | |
| 2023-10-17 13:27:40,563 epoch 4 - iter 539/773 - loss 0.03726784 - time (sec): 53.86 - samples/sec: 1622.04 - lr: 0.000035 - momentum: 0.000000 | |
| 2023-10-17 13:27:48,205 epoch 4 - iter 616/773 - loss 0.04542885 - time (sec): 61.50 - samples/sec: 1615.02 - lr: 0.000034 - momentum: 0.000000 | |
| 2023-10-17 13:27:56,324 epoch 4 - iter 693/773 - loss 0.04596823 - time (sec): 69.62 - samples/sec: 1598.90 - lr: 0.000034 - momentum: 0.000000 | |
| 2023-10-17 13:28:03,402 epoch 4 - iter 770/773 - loss 0.04522777 - time (sec): 76.70 - samples/sec: 1614.88 - lr: 0.000033 - momentum: 0.000000 | |
| 2023-10-17 13:28:03,672 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 13:28:03,673 EPOCH 4 done: loss 0.0453 - lr: 0.000033 | |
| 2023-10-17 13:28:06,586 DEV : loss 0.07239558547735214 - f1-score (micro avg) 0.7909 | |
| 2023-10-17 13:28:06,616 saving best model | |
| 2023-10-17 13:28:08,029 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 13:28:15,411 epoch 5 - iter 77/773 - loss 0.02843471 - time (sec): 7.38 - samples/sec: 1753.59 - lr: 0.000033 - momentum: 0.000000 | |
| 2023-10-17 13:28:22,936 epoch 5 - iter 154/773 - loss 0.02395437 - time (sec): 14.90 - samples/sec: 1673.42 - lr: 0.000032 - momentum: 0.000000 | |
| 2023-10-17 13:28:30,854 epoch 5 - iter 231/773 - loss 0.02645457 - time (sec): 22.82 - samples/sec: 1620.38 - lr: 0.000032 - momentum: 0.000000 | |
| 2023-10-17 13:28:38,767 epoch 5 - iter 308/773 - loss 0.02834241 - time (sec): 30.73 - samples/sec: 1609.37 - lr: 0.000031 - momentum: 0.000000 | |
| 2023-10-17 13:28:46,449 epoch 5 - iter 385/773 - loss 0.02915922 - time (sec): 38.42 - samples/sec: 1588.49 - lr: 0.000031 - momentum: 0.000000 | |
| 2023-10-17 13:28:54,069 epoch 5 - iter 462/773 - loss 0.02818305 - time (sec): 46.04 - samples/sec: 1595.37 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-17 13:29:01,800 epoch 5 - iter 539/773 - loss 0.02922204 - time (sec): 53.77 - samples/sec: 1581.52 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-17 13:29:09,568 epoch 5 - iter 616/773 - loss 0.02941636 - time (sec): 61.53 - samples/sec: 1587.22 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-17 13:29:17,758 epoch 5 - iter 693/773 - loss 0.02871886 - time (sec): 69.72 - samples/sec: 1593.88 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-17 13:29:25,953 epoch 5 - iter 770/773 - loss 0.02810066 - time (sec): 77.92 - samples/sec: 1588.80 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-17 13:29:26,265 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 13:29:26,265 EPOCH 5 done: loss 0.0285 - lr: 0.000028 | |
| 2023-10-17 13:29:29,547 DEV : loss 0.09678769111633301 - f1-score (micro avg) 0.7579 | |
| 2023-10-17 13:29:29,578 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 13:29:37,484 epoch 6 - iter 77/773 - loss 0.02911176 - time (sec): 7.90 - samples/sec: 1494.95 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-17 13:29:44,833 epoch 6 - iter 154/773 - loss 0.02314913 - time (sec): 15.25 - samples/sec: 1620.87 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-17 13:29:52,208 epoch 6 - iter 231/773 - loss 0.02211935 - time (sec): 22.63 - samples/sec: 1654.38 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-17 13:29:59,974 epoch 6 - iter 308/773 - loss 0.01982596 - time (sec): 30.39 - samples/sec: 1657.08 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-17 13:30:07,513 epoch 6 - iter 385/773 - loss 0.01939127 - time (sec): 37.93 - samples/sec: 1633.05 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-17 13:30:14,978 epoch 6 - iter 462/773 - loss 0.02020479 - time (sec): 45.40 - samples/sec: 1624.45 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-17 13:30:22,704 epoch 6 - iter 539/773 - loss 0.01996966 - time (sec): 53.12 - samples/sec: 1610.55 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-17 13:30:30,362 epoch 6 - iter 616/773 - loss 0.01907375 - time (sec): 60.78 - samples/sec: 1610.86 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-17 13:30:38,021 epoch 6 - iter 693/773 - loss 0.01872125 - time (sec): 68.44 - samples/sec: 1621.15 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-17 13:30:45,781 epoch 6 - iter 770/773 - loss 0.01930353 - time (sec): 76.20 - samples/sec: 1624.68 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-17 13:30:46,080 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 13:30:46,080 EPOCH 6 done: loss 0.0192 - lr: 0.000022 | |
| 2023-10-17 13:30:49,469 DEV : loss 0.10031934082508087 - f1-score (micro avg) 0.7698 | |
| 2023-10-17 13:30:49,503 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 13:30:57,507 epoch 7 - iter 77/773 - loss 0.01926813 - time (sec): 8.00 - samples/sec: 1545.66 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-17 13:31:05,453 epoch 7 - iter 154/773 - loss 0.01404153 - time (sec): 15.95 - samples/sec: 1536.40 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-17 13:31:13,251 epoch 7 - iter 231/773 - loss 0.01790692 - time (sec): 23.74 - samples/sec: 1561.47 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-17 13:31:20,527 epoch 7 - iter 308/773 - loss 0.01596954 - time (sec): 31.02 - samples/sec: 1581.49 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-17 13:31:27,656 epoch 7 - iter 385/773 - loss 0.01481654 - time (sec): 38.15 - samples/sec: 1616.68 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-17 13:31:34,613 epoch 7 - iter 462/773 - loss 0.01463562 - time (sec): 45.11 - samples/sec: 1619.89 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-17 13:31:42,114 epoch 7 - iter 539/773 - loss 0.01492694 - time (sec): 52.61 - samples/sec: 1638.03 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-17 13:31:49,500 epoch 7 - iter 616/773 - loss 0.01420990 - time (sec): 59.99 - samples/sec: 1653.83 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-17 13:31:56,721 epoch 7 - iter 693/773 - loss 0.01390834 - time (sec): 67.21 - samples/sec: 1661.42 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-17 13:32:03,143 epoch 7 - iter 770/773 - loss 0.01406545 - time (sec): 73.64 - samples/sec: 1681.21 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-17 13:32:03,388 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 13:32:03,389 EPOCH 7 done: loss 0.0140 - lr: 0.000017 | |
| 2023-10-17 13:32:06,276 DEV : loss 0.11071208119392395 - f1-score (micro avg) 0.7683 | |
| 2023-10-17 13:32:06,305 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 13:32:13,130 epoch 8 - iter 77/773 - loss 0.00843154 - time (sec): 6.82 - samples/sec: 1807.24 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-17 13:32:20,080 epoch 8 - iter 154/773 - loss 0.00677113 - time (sec): 13.77 - samples/sec: 1766.95 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-17 13:32:27,329 epoch 8 - iter 231/773 - loss 0.00836479 - time (sec): 21.02 - samples/sec: 1728.27 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-17 13:32:34,265 epoch 8 - iter 308/773 - loss 0.00790711 - time (sec): 27.96 - samples/sec: 1729.60 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-17 13:32:41,366 epoch 8 - iter 385/773 - loss 0.00790440 - time (sec): 35.06 - samples/sec: 1735.15 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-17 13:32:48,613 epoch 8 - iter 462/773 - loss 0.00842461 - time (sec): 42.31 - samples/sec: 1731.46 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-17 13:32:56,661 epoch 8 - iter 539/773 - loss 0.00918393 - time (sec): 50.35 - samples/sec: 1726.83 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-17 13:33:04,126 epoch 8 - iter 616/773 - loss 0.00943817 - time (sec): 57.82 - samples/sec: 1724.76 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-17 13:33:11,859 epoch 8 - iter 693/773 - loss 0.00992381 - time (sec): 65.55 - samples/sec: 1705.82 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-17 13:33:19,708 epoch 8 - iter 770/773 - loss 0.01030405 - time (sec): 73.40 - samples/sec: 1688.12 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-17 13:33:20,005 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 13:33:20,005 EPOCH 8 done: loss 0.0104 - lr: 0.000011 | |
| 2023-10-17 13:33:23,104 DEV : loss 0.112131267786026 - f1-score (micro avg) 0.7789 | |
| 2023-10-17 13:33:23,141 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 13:33:30,765 epoch 9 - iter 77/773 - loss 0.00874412 - time (sec): 7.62 - samples/sec: 1611.31 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-17 13:33:38,513 epoch 9 - iter 154/773 - loss 0.00785734 - time (sec): 15.37 - samples/sec: 1621.77 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-17 13:33:46,462 epoch 9 - iter 231/773 - loss 0.00708825 - time (sec): 23.32 - samples/sec: 1644.66 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-17 13:33:54,388 epoch 9 - iter 308/773 - loss 0.00617174 - time (sec): 31.24 - samples/sec: 1655.71 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-17 13:34:02,210 epoch 9 - iter 385/773 - loss 0.00736950 - time (sec): 39.07 - samples/sec: 1594.91 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-17 13:34:09,935 epoch 9 - iter 462/773 - loss 0.00704324 - time (sec): 46.79 - samples/sec: 1584.76 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-17 13:34:17,149 epoch 9 - iter 539/773 - loss 0.00678870 - time (sec): 54.01 - samples/sec: 1599.87 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-17 13:34:24,344 epoch 9 - iter 616/773 - loss 0.00708850 - time (sec): 61.20 - samples/sec: 1608.61 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-17 13:34:31,470 epoch 9 - iter 693/773 - loss 0.00671587 - time (sec): 68.33 - samples/sec: 1616.86 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-17 13:34:39,709 epoch 9 - iter 770/773 - loss 0.00624570 - time (sec): 76.57 - samples/sec: 1615.20 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-17 13:34:40,011 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 13:34:40,012 EPOCH 9 done: loss 0.0062 - lr: 0.000006 | |
| 2023-10-17 13:34:43,192 DEV : loss 0.1130354106426239 - f1-score (micro avg) 0.804 | |
| 2023-10-17 13:34:43,224 saving best model | |
| 2023-10-17 13:34:44,723 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 13:34:52,444 epoch 10 - iter 77/773 - loss 0.00330740 - time (sec): 7.71 - samples/sec: 1678.74 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-17 13:35:00,074 epoch 10 - iter 154/773 - loss 0.00380506 - time (sec): 15.34 - samples/sec: 1652.24 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-17 13:35:07,781 epoch 10 - iter 231/773 - loss 0.00357509 - time (sec): 23.05 - samples/sec: 1681.37 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-17 13:35:15,374 epoch 10 - iter 308/773 - loss 0.00323943 - time (sec): 30.64 - samples/sec: 1665.77 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-17 13:35:23,448 epoch 10 - iter 385/773 - loss 0.00377474 - time (sec): 38.71 - samples/sec: 1632.78 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-17 13:35:31,104 epoch 10 - iter 462/773 - loss 0.00358345 - time (sec): 46.37 - samples/sec: 1635.38 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-17 13:35:39,051 epoch 10 - iter 539/773 - loss 0.00328378 - time (sec): 54.32 - samples/sec: 1615.54 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-17 13:35:46,804 epoch 10 - iter 616/773 - loss 0.00342164 - time (sec): 62.07 - samples/sec: 1596.22 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-17 13:35:54,614 epoch 10 - iter 693/773 - loss 0.00318027 - time (sec): 69.88 - samples/sec: 1588.59 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-17 13:36:02,805 epoch 10 - iter 770/773 - loss 0.00357272 - time (sec): 78.07 - samples/sec: 1585.49 - lr: 0.000000 - momentum: 0.000000 | |
| 2023-10-17 13:36:03,113 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 13:36:03,113 EPOCH 10 done: loss 0.0036 - lr: 0.000000 | |
| 2023-10-17 13:36:06,294 DEV : loss 0.11559101939201355 - f1-score (micro avg) 0.8032 | |
| 2023-10-17 13:36:06,911 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 13:36:06,913 Loading model from best epoch ... | |
| 2023-10-17 13:36:09,226 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 13:36:17,554 | |
| Results: | |
| - F-score (micro) 0.8142 | |
| - F-score (macro) 0.7437 | |
| - Accuracy 0.7039 | |
| By class: | |
| precision recall f1-score support | |
| LOC 0.8480 0.8668 0.8573 946 | |
| BUILDING 0.5990 0.6216 0.6101 185 | |
| STREET 0.7778 0.7500 0.7636 56 | |
| micro avg 0.8054 0.8231 0.8142 1187 | |
| macro avg 0.7416 0.7461 0.7437 1187 | |
| weighted avg 0.8059 0.8231 0.8143 1187 | |
| 2023-10-17 13:36:17,554 ---------------------------------------------------------------------------------------------------- | |