| 2023-10-17 16:51:50,595 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:51:50,596 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 16:51:50,596 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:51:50,596 MultiCorpus: 5777 train + 722 dev + 723 test sentences | |
| - NER_ICDAR_EUROPEANA Corpus: 5777 train + 722 dev + 723 test sentences - /root/.flair/datasets/ner_icdar_europeana/nl | |
| 2023-10-17 16:51:50,596 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:51:50,596 Train: 5777 sentences | |
| 2023-10-17 16:51:50,596 (train_with_dev=False, train_with_test=False) | |
| 2023-10-17 16:51:50,596 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:51:50,596 Training Params: | |
| 2023-10-17 16:51:50,596 - learning_rate: "3e-05" | |
| 2023-10-17 16:51:50,596 - mini_batch_size: "4" | |
| 2023-10-17 16:51:50,596 - max_epochs: "10" | |
| 2023-10-17 16:51:50,596 - shuffle: "True" | |
| 2023-10-17 16:51:50,596 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:51:50,596 Plugins: | |
| 2023-10-17 16:51:50,596 - TensorboardLogger | |
| 2023-10-17 16:51:50,596 - LinearScheduler | warmup_fraction: '0.1' | |
| 2023-10-17 16:51:50,596 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:51:50,596 Final evaluation on model from best epoch (best-model.pt) | |
| 2023-10-17 16:51:50,596 - metric: "('micro avg', 'f1-score')" | |
| 2023-10-17 16:51:50,596 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:51:50,596 Computation: | |
| 2023-10-17 16:51:50,596 - compute on device: cuda:0 | |
| 2023-10-17 16:51:50,596 - embedding storage: none | |
| 2023-10-17 16:51:50,596 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:51:50,596 Model training base path: "hmbench-icdar/nl-hmteams/teams-base-historic-multilingual-discriminator-bs4-wsFalse-e10-lr3e-05-poolingfirst-layers-1-crfFalse-3" | |
| 2023-10-17 16:51:50,596 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:51:50,597 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:51:50,597 Logging anything other than scalars to TensorBoard is currently not supported. | |
| 2023-10-17 16:51:57,734 epoch 1 - iter 144/1445 - loss 2.51964113 - time (sec): 7.14 - samples/sec: 2407.06 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-17 16:52:04,801 epoch 1 - iter 288/1445 - loss 1.46886525 - time (sec): 14.20 - samples/sec: 2396.44 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-17 16:52:11,824 epoch 1 - iter 432/1445 - loss 1.03580590 - time (sec): 21.23 - samples/sec: 2436.57 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-17 16:52:18,859 epoch 1 - iter 576/1445 - loss 0.82263272 - time (sec): 28.26 - samples/sec: 2459.21 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-17 16:52:26,087 epoch 1 - iter 720/1445 - loss 0.67840038 - time (sec): 35.49 - samples/sec: 2485.64 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-17 16:52:33,197 epoch 1 - iter 864/1445 - loss 0.58315275 - time (sec): 42.60 - samples/sec: 2500.11 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-17 16:52:40,137 epoch 1 - iter 1008/1445 - loss 0.51794596 - time (sec): 49.54 - samples/sec: 2498.80 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-17 16:52:47,253 epoch 1 - iter 1152/1445 - loss 0.46799546 - time (sec): 56.66 - samples/sec: 2495.94 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-17 16:52:54,086 epoch 1 - iter 1296/1445 - loss 0.43471267 - time (sec): 63.49 - samples/sec: 2473.24 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-17 16:53:01,099 epoch 1 - iter 1440/1445 - loss 0.40016424 - time (sec): 70.50 - samples/sec: 2488.40 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-17 16:53:01,370 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:53:01,371 EPOCH 1 done: loss 0.3987 - lr: 0.000030 | |
| 2023-10-17 16:53:03,993 DEV : loss 0.12171746790409088 - f1-score (micro avg) 0.7585 | |
| 2023-10-17 16:53:04,008 saving best model | |
| 2023-10-17 16:53:04,339 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:53:11,206 epoch 2 - iter 144/1445 - loss 0.09547817 - time (sec): 6.87 - samples/sec: 2527.57 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-17 16:53:18,194 epoch 2 - iter 288/1445 - loss 0.10207718 - time (sec): 13.85 - samples/sec: 2511.05 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-17 16:53:25,162 epoch 2 - iter 432/1445 - loss 0.10574612 - time (sec): 20.82 - samples/sec: 2486.76 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-17 16:53:32,148 epoch 2 - iter 576/1445 - loss 0.10231456 - time (sec): 27.81 - samples/sec: 2484.41 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-17 16:53:39,311 epoch 2 - iter 720/1445 - loss 0.09986497 - time (sec): 34.97 - samples/sec: 2513.27 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-17 16:53:46,749 epoch 2 - iter 864/1445 - loss 0.09794746 - time (sec): 42.41 - samples/sec: 2537.18 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-17 16:53:53,859 epoch 2 - iter 1008/1445 - loss 0.09611171 - time (sec): 49.52 - samples/sec: 2529.21 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-17 16:54:01,602 epoch 2 - iter 1152/1445 - loss 0.09333721 - time (sec): 57.26 - samples/sec: 2481.95 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-17 16:54:09,733 epoch 2 - iter 1296/1445 - loss 0.09231752 - time (sec): 65.39 - samples/sec: 2426.32 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-17 16:54:17,227 epoch 2 - iter 1440/1445 - loss 0.09139074 - time (sec): 72.89 - samples/sec: 2408.27 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-17 16:54:17,477 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:54:17,478 EPOCH 2 done: loss 0.0913 - lr: 0.000027 | |
| 2023-10-17 16:54:21,098 DEV : loss 0.08095023036003113 - f1-score (micro avg) 0.8018 | |
| 2023-10-17 16:54:21,115 saving best model | |
| 2023-10-17 16:54:21,557 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:54:28,597 epoch 3 - iter 144/1445 - loss 0.07907593 - time (sec): 7.03 - samples/sec: 2471.23 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-17 16:54:35,963 epoch 3 - iter 288/1445 - loss 0.06930842 - time (sec): 14.40 - samples/sec: 2491.47 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-17 16:54:42,970 epoch 3 - iter 432/1445 - loss 0.06547744 - time (sec): 21.41 - samples/sec: 2533.28 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-17 16:54:49,929 epoch 3 - iter 576/1445 - loss 0.06189547 - time (sec): 28.37 - samples/sec: 2537.73 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-17 16:54:56,792 epoch 3 - iter 720/1445 - loss 0.06117221 - time (sec): 35.23 - samples/sec: 2510.04 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-17 16:55:04,122 epoch 3 - iter 864/1445 - loss 0.06199025 - time (sec): 42.56 - samples/sec: 2503.89 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-17 16:55:11,617 epoch 3 - iter 1008/1445 - loss 0.06500361 - time (sec): 50.05 - samples/sec: 2487.30 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-17 16:55:18,545 epoch 3 - iter 1152/1445 - loss 0.06477948 - time (sec): 56.98 - samples/sec: 2477.01 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-17 16:55:25,742 epoch 3 - iter 1296/1445 - loss 0.06476144 - time (sec): 64.18 - samples/sec: 2466.25 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-17 16:55:32,997 epoch 3 - iter 1440/1445 - loss 0.06672483 - time (sec): 71.43 - samples/sec: 2462.82 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-17 16:55:33,220 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:55:33,221 EPOCH 3 done: loss 0.0667 - lr: 0.000023 | |
| 2023-10-17 16:55:36,446 DEV : loss 0.07555373758077621 - f1-score (micro avg) 0.8639 | |
| 2023-10-17 16:55:36,464 saving best model | |
| 2023-10-17 16:55:36,902 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:55:43,816 epoch 4 - iter 144/1445 - loss 0.04753253 - time (sec): 6.91 - samples/sec: 2416.67 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-17 16:55:51,351 epoch 4 - iter 288/1445 - loss 0.04514475 - time (sec): 14.44 - samples/sec: 2398.27 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-17 16:55:58,535 epoch 4 - iter 432/1445 - loss 0.04852100 - time (sec): 21.63 - samples/sec: 2392.92 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-17 16:56:05,540 epoch 4 - iter 576/1445 - loss 0.05156722 - time (sec): 28.63 - samples/sec: 2418.03 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-17 16:56:12,372 epoch 4 - iter 720/1445 - loss 0.05036006 - time (sec): 35.47 - samples/sec: 2433.19 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-17 16:56:19,508 epoch 4 - iter 864/1445 - loss 0.05094762 - time (sec): 42.60 - samples/sec: 2438.61 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-17 16:56:26,524 epoch 4 - iter 1008/1445 - loss 0.05000499 - time (sec): 49.62 - samples/sec: 2453.87 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-17 16:56:33,720 epoch 4 - iter 1152/1445 - loss 0.05036806 - time (sec): 56.81 - samples/sec: 2481.30 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-17 16:56:40,708 epoch 4 - iter 1296/1445 - loss 0.04919696 - time (sec): 63.80 - samples/sec: 2475.63 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-17 16:56:47,668 epoch 4 - iter 1440/1445 - loss 0.04959858 - time (sec): 70.76 - samples/sec: 2483.70 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-17 16:56:47,903 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:56:47,903 EPOCH 4 done: loss 0.0496 - lr: 0.000020 | |
| 2023-10-17 16:56:51,737 DEV : loss 0.08526481688022614 - f1-score (micro avg) 0.8661 | |
| 2023-10-17 16:56:51,757 saving best model | |
| 2023-10-17 16:56:52,198 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:56:59,878 epoch 5 - iter 144/1445 - loss 0.02983267 - time (sec): 7.68 - samples/sec: 2338.64 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-17 16:57:06,651 epoch 5 - iter 288/1445 - loss 0.02587426 - time (sec): 14.45 - samples/sec: 2423.26 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-17 16:57:13,811 epoch 5 - iter 432/1445 - loss 0.03178345 - time (sec): 21.61 - samples/sec: 2453.21 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-17 16:57:20,904 epoch 5 - iter 576/1445 - loss 0.03049647 - time (sec): 28.70 - samples/sec: 2478.29 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-17 16:57:27,751 epoch 5 - iter 720/1445 - loss 0.02973021 - time (sec): 35.55 - samples/sec: 2474.24 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-17 16:57:34,537 epoch 5 - iter 864/1445 - loss 0.03342990 - time (sec): 42.34 - samples/sec: 2504.53 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-17 16:57:41,369 epoch 5 - iter 1008/1445 - loss 0.03551324 - time (sec): 49.17 - samples/sec: 2522.36 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-17 16:57:48,235 epoch 5 - iter 1152/1445 - loss 0.03569568 - time (sec): 56.03 - samples/sec: 2512.81 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-17 16:57:55,333 epoch 5 - iter 1296/1445 - loss 0.03592580 - time (sec): 63.13 - samples/sec: 2500.90 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-17 16:58:03,284 epoch 5 - iter 1440/1445 - loss 0.03540825 - time (sec): 71.08 - samples/sec: 2471.52 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-17 16:58:03,556 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:58:03,556 EPOCH 5 done: loss 0.0353 - lr: 0.000017 | |
| 2023-10-17 16:58:06,848 DEV : loss 0.12203659117221832 - f1-score (micro avg) 0.831 | |
| 2023-10-17 16:58:06,868 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:58:14,955 epoch 6 - iter 144/1445 - loss 0.02842518 - time (sec): 8.09 - samples/sec: 2318.05 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-17 16:58:22,926 epoch 6 - iter 288/1445 - loss 0.02055464 - time (sec): 16.06 - samples/sec: 2226.37 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-17 16:58:31,227 epoch 6 - iter 432/1445 - loss 0.02489207 - time (sec): 24.36 - samples/sec: 2229.50 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-17 16:58:38,990 epoch 6 - iter 576/1445 - loss 0.02645244 - time (sec): 32.12 - samples/sec: 2259.49 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-17 16:58:45,907 epoch 6 - iter 720/1445 - loss 0.02618404 - time (sec): 39.04 - samples/sec: 2296.06 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-17 16:58:52,910 epoch 6 - iter 864/1445 - loss 0.02602900 - time (sec): 46.04 - samples/sec: 2339.43 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-17 16:58:59,842 epoch 6 - iter 1008/1445 - loss 0.02750063 - time (sec): 52.97 - samples/sec: 2349.00 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-17 16:59:06,963 epoch 6 - iter 1152/1445 - loss 0.02837136 - time (sec): 60.09 - samples/sec: 2363.19 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-17 16:59:13,986 epoch 6 - iter 1296/1445 - loss 0.02684921 - time (sec): 67.12 - samples/sec: 2363.48 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-17 16:59:20,726 epoch 6 - iter 1440/1445 - loss 0.02655197 - time (sec): 73.86 - samples/sec: 2379.68 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-17 16:59:20,957 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:59:20,957 EPOCH 6 done: loss 0.0265 - lr: 0.000013 | |
| 2023-10-17 16:59:24,232 DEV : loss 0.1185513511300087 - f1-score (micro avg) 0.8581 | |
| 2023-10-17 16:59:24,251 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:59:31,348 epoch 7 - iter 144/1445 - loss 0.01592139 - time (sec): 7.10 - samples/sec: 2420.48 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-17 16:59:38,719 epoch 7 - iter 288/1445 - loss 0.01953479 - time (sec): 14.47 - samples/sec: 2385.00 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-17 16:59:45,900 epoch 7 - iter 432/1445 - loss 0.01960054 - time (sec): 21.65 - samples/sec: 2414.78 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-17 16:59:53,535 epoch 7 - iter 576/1445 - loss 0.02108098 - time (sec): 29.28 - samples/sec: 2404.40 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-17 17:00:00,596 epoch 7 - iter 720/1445 - loss 0.01990454 - time (sec): 36.34 - samples/sec: 2412.16 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-17 17:00:07,764 epoch 7 - iter 864/1445 - loss 0.02048029 - time (sec): 43.51 - samples/sec: 2438.92 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-17 17:00:14,808 epoch 7 - iter 1008/1445 - loss 0.01953974 - time (sec): 50.56 - samples/sec: 2460.86 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-17 17:00:21,791 epoch 7 - iter 1152/1445 - loss 0.01979941 - time (sec): 57.54 - samples/sec: 2460.68 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-17 17:00:28,760 epoch 7 - iter 1296/1445 - loss 0.01839308 - time (sec): 64.51 - samples/sec: 2453.29 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-17 17:00:35,846 epoch 7 - iter 1440/1445 - loss 0.01795360 - time (sec): 71.59 - samples/sec: 2449.53 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-17 17:00:36,194 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:00:36,194 EPOCH 7 done: loss 0.0180 - lr: 0.000010 | |
| 2023-10-17 17:00:39,469 DEV : loss 0.12616300582885742 - f1-score (micro avg) 0.8691 | |
| 2023-10-17 17:00:39,485 saving best model | |
| 2023-10-17 17:00:39,951 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:00:46,624 epoch 8 - iter 144/1445 - loss 0.01689844 - time (sec): 6.67 - samples/sec: 2504.32 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-17 17:00:53,857 epoch 8 - iter 288/1445 - loss 0.01100211 - time (sec): 13.90 - samples/sec: 2442.08 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-17 17:01:00,829 epoch 8 - iter 432/1445 - loss 0.01437202 - time (sec): 20.88 - samples/sec: 2452.85 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-17 17:01:07,822 epoch 8 - iter 576/1445 - loss 0.01241985 - time (sec): 27.87 - samples/sec: 2473.87 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-17 17:01:15,067 epoch 8 - iter 720/1445 - loss 0.01363731 - time (sec): 35.11 - samples/sec: 2465.52 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-17 17:01:22,117 epoch 8 - iter 864/1445 - loss 0.01368516 - time (sec): 42.16 - samples/sec: 2464.53 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-17 17:01:29,232 epoch 8 - iter 1008/1445 - loss 0.01357477 - time (sec): 49.28 - samples/sec: 2472.94 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-17 17:01:36,222 epoch 8 - iter 1152/1445 - loss 0.01410465 - time (sec): 56.27 - samples/sec: 2479.90 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-17 17:01:43,482 epoch 8 - iter 1296/1445 - loss 0.01364676 - time (sec): 63.53 - samples/sec: 2503.19 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-17 17:01:50,427 epoch 8 - iter 1440/1445 - loss 0.01339047 - time (sec): 70.47 - samples/sec: 2491.94 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-17 17:01:50,657 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:01:50,657 EPOCH 8 done: loss 0.0134 - lr: 0.000007 | |
| 2023-10-17 17:01:53,972 DEV : loss 0.12705564498901367 - f1-score (micro avg) 0.872 | |
| 2023-10-17 17:01:53,990 saving best model | |
| 2023-10-17 17:01:54,439 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:02:01,517 epoch 9 - iter 144/1445 - loss 0.00381457 - time (sec): 7.08 - samples/sec: 2421.87 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-17 17:02:08,664 epoch 9 - iter 288/1445 - loss 0.00734927 - time (sec): 14.22 - samples/sec: 2462.26 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-17 17:02:15,773 epoch 9 - iter 432/1445 - loss 0.00735271 - time (sec): 21.33 - samples/sec: 2461.35 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-17 17:02:23,175 epoch 9 - iter 576/1445 - loss 0.00769310 - time (sec): 28.73 - samples/sec: 2467.86 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-17 17:02:30,572 epoch 9 - iter 720/1445 - loss 0.00864776 - time (sec): 36.13 - samples/sec: 2470.49 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-17 17:02:38,094 epoch 9 - iter 864/1445 - loss 0.00916627 - time (sec): 43.65 - samples/sec: 2447.52 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-17 17:02:45,162 epoch 9 - iter 1008/1445 - loss 0.00973331 - time (sec): 50.72 - samples/sec: 2433.57 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-17 17:02:51,976 epoch 9 - iter 1152/1445 - loss 0.00925598 - time (sec): 57.53 - samples/sec: 2426.27 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-17 17:02:59,048 epoch 9 - iter 1296/1445 - loss 0.00914846 - time (sec): 64.61 - samples/sec: 2445.75 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-17 17:03:06,122 epoch 9 - iter 1440/1445 - loss 0.00948694 - time (sec): 71.68 - samples/sec: 2450.76 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-17 17:03:06,346 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:03:06,347 EPOCH 9 done: loss 0.0095 - lr: 0.000003 | |
| 2023-10-17 17:03:09,701 DEV : loss 0.14085045456886292 - f1-score (micro avg) 0.8698 | |
| 2023-10-17 17:03:09,724 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:03:16,841 epoch 10 - iter 144/1445 - loss 0.00996398 - time (sec): 7.12 - samples/sec: 2532.12 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-17 17:03:23,906 epoch 10 - iter 288/1445 - loss 0.00789760 - time (sec): 14.18 - samples/sec: 2449.41 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-17 17:03:31,192 epoch 10 - iter 432/1445 - loss 0.00862420 - time (sec): 21.47 - samples/sec: 2474.56 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-17 17:03:38,308 epoch 10 - iter 576/1445 - loss 0.00751122 - time (sec): 28.58 - samples/sec: 2490.18 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-17 17:03:45,506 epoch 10 - iter 720/1445 - loss 0.00674528 - time (sec): 35.78 - samples/sec: 2480.89 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-17 17:03:52,464 epoch 10 - iter 864/1445 - loss 0.00666326 - time (sec): 42.74 - samples/sec: 2488.41 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-17 17:03:59,509 epoch 10 - iter 1008/1445 - loss 0.00638795 - time (sec): 49.78 - samples/sec: 2479.99 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-17 17:04:06,580 epoch 10 - iter 1152/1445 - loss 0.00631451 - time (sec): 56.85 - samples/sec: 2480.07 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-17 17:04:13,723 epoch 10 - iter 1296/1445 - loss 0.00652823 - time (sec): 64.00 - samples/sec: 2482.67 - lr: 0.000000 - momentum: 0.000000 | |
| 2023-10-17 17:04:20,891 epoch 10 - iter 1440/1445 - loss 0.00649172 - time (sec): 71.17 - samples/sec: 2470.94 - lr: 0.000000 - momentum: 0.000000 | |
| 2023-10-17 17:04:21,133 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:04:21,134 EPOCH 10 done: loss 0.0065 - lr: 0.000000 | |
| 2023-10-17 17:04:24,372 DEV : loss 0.1461455523967743 - f1-score (micro avg) 0.8679 | |
| 2023-10-17 17:04:24,745 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:04:24,746 Loading model from best epoch ... | |
| 2023-10-17 17:04:26,084 SequenceTagger predicts: Dictionary with 13 tags: O, S-LOC, B-LOC, E-LOC, I-LOC, S-PER, B-PER, E-PER, I-PER, S-ORG, B-ORG, E-ORG, I-ORG | |
| 2023-10-17 17:04:28,840 | |
| Results: | |
| - F-score (micro) 0.8773 | |
| - F-score (macro) 0.7854 | |
| - Accuracy 0.7879 | |
| By class: | |
| precision recall f1-score support | |
| PER 0.8737 0.8755 0.8746 482 | |
| LOC 0.9603 0.8974 0.9278 458 | |
| ORG 0.5902 0.5217 0.5538 69 | |
| micro avg 0.8940 0.8612 0.8773 1009 | |
| macro avg 0.8081 0.7649 0.7854 1009 | |
| weighted avg 0.8936 0.8612 0.8768 1009 | |
| 2023-10-17 17:04:28,841 ---------------------------------------------------------------------------------------------------- | |