| 2023-10-17 20:57:44,502 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:57:44,503 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=21, bias=True) | |
| (loss_function): CrossEntropyLoss() | |
| )" | |
| 2023-10-17 20:57:44,503 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:57:44,503 MultiCorpus: 5901 train + 1287 dev + 1505 test sentences | |
| - NER_HIPE_2022 Corpus: 5901 train + 1287 dev + 1505 test sentences - /root/.flair/datasets/ner_hipe_2022/v2.1/hipe2020/fr/with_doc_seperator | |
| 2023-10-17 20:57:44,503 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:57:44,503 Train: 5901 sentences | |
| 2023-10-17 20:57:44,503 (train_with_dev=False, train_with_test=False) | |
| 2023-10-17 20:57:44,503 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:57:44,503 Training Params: | |
| 2023-10-17 20:57:44,503 - learning_rate: "3e-05" | |
| 2023-10-17 20:57:44,503 - mini_batch_size: "4" | |
| 2023-10-17 20:57:44,503 - max_epochs: "10" | |
| 2023-10-17 20:57:44,503 - shuffle: "True" | |
| 2023-10-17 20:57:44,503 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:57:44,503 Plugins: | |
| 2023-10-17 20:57:44,503 - TensorboardLogger | |
| 2023-10-17 20:57:44,504 - LinearScheduler | warmup_fraction: '0.1' | |
| 2023-10-17 20:57:44,504 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:57:44,504 Final evaluation on model from best epoch (best-model.pt) | |
| 2023-10-17 20:57:44,504 - metric: "('micro avg', 'f1-score')" | |
| 2023-10-17 20:57:44,504 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:57:44,504 Computation: | |
| 2023-10-17 20:57:44,504 - compute on device: cuda:0 | |
| 2023-10-17 20:57:44,504 - embedding storage: none | |
| 2023-10-17 20:57:44,504 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:57:44,504 Model training base path: "hmbench-hipe2020/fr-hmteams/teams-base-historic-multilingual-discriminator-bs4-wsFalse-e10-lr3e-05-poolingfirst-layers-1-crfFalse-2" | |
| 2023-10-17 20:57:44,504 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:57:44,504 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:57:44,504 Logging anything other than scalars to TensorBoard is currently not supported. | |
| 2023-10-17 20:57:51,411 epoch 1 - iter 147/1476 - loss 3.24267368 - time (sec): 6.91 - samples/sec: 2332.85 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-17 20:57:58,675 epoch 1 - iter 294/1476 - loss 1.82965327 - time (sec): 14.17 - samples/sec: 2490.20 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-17 20:58:05,460 epoch 1 - iter 441/1476 - loss 1.42129099 - time (sec): 20.96 - samples/sec: 2394.03 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-17 20:58:12,685 epoch 1 - iter 588/1476 - loss 1.16200279 - time (sec): 28.18 - samples/sec: 2378.23 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-17 20:58:19,657 epoch 1 - iter 735/1476 - loss 0.99879079 - time (sec): 35.15 - samples/sec: 2365.20 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-17 20:58:26,769 epoch 1 - iter 882/1476 - loss 0.87692872 - time (sec): 42.26 - samples/sec: 2358.50 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-17 20:58:33,988 epoch 1 - iter 1029/1476 - loss 0.78427069 - time (sec): 49.48 - samples/sec: 2354.88 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-17 20:58:40,899 epoch 1 - iter 1176/1476 - loss 0.71213649 - time (sec): 56.39 - samples/sec: 2343.92 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-17 20:58:47,798 epoch 1 - iter 1323/1476 - loss 0.65488116 - time (sec): 63.29 - samples/sec: 2353.75 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-17 20:58:55,056 epoch 1 - iter 1470/1476 - loss 0.60740596 - time (sec): 70.55 - samples/sec: 2348.91 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-17 20:58:55,367 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:58:55,367 EPOCH 1 done: loss 0.6056 - lr: 0.000030 | |
| 2023-10-17 20:59:02,301 DEV : loss 0.14250747859477997 - f1-score (micro avg) 0.7374 | |
| 2023-10-17 20:59:02,336 saving best model | |
| 2023-10-17 20:59:02,722 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:59:09,759 epoch 2 - iter 147/1476 - loss 0.12242529 - time (sec): 7.04 - samples/sec: 2131.27 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-17 20:59:17,375 epoch 2 - iter 294/1476 - loss 0.13734809 - time (sec): 14.65 - samples/sec: 2278.80 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-17 20:59:24,597 epoch 2 - iter 441/1476 - loss 0.14198341 - time (sec): 21.87 - samples/sec: 2309.55 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-17 20:59:32,115 epoch 2 - iter 588/1476 - loss 0.14279736 - time (sec): 29.39 - samples/sec: 2333.99 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-17 20:59:39,293 epoch 2 - iter 735/1476 - loss 0.14080823 - time (sec): 36.57 - samples/sec: 2363.39 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-17 20:59:46,457 epoch 2 - iter 882/1476 - loss 0.13838234 - time (sec): 43.73 - samples/sec: 2356.46 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-17 20:59:53,143 epoch 2 - iter 1029/1476 - loss 0.13757509 - time (sec): 50.42 - samples/sec: 2345.39 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-17 21:00:00,041 epoch 2 - iter 1176/1476 - loss 0.13702648 - time (sec): 57.32 - samples/sec: 2328.66 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-17 21:00:07,044 epoch 2 - iter 1323/1476 - loss 0.13591803 - time (sec): 64.32 - samples/sec: 2326.15 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-17 21:00:13,996 epoch 2 - iter 1470/1476 - loss 0.13420153 - time (sec): 71.27 - samples/sec: 2326.32 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-17 21:00:14,273 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 21:00:14,273 EPOCH 2 done: loss 0.1341 - lr: 0.000027 | |
| 2023-10-17 21:00:25,898 DEV : loss 0.12737122178077698 - f1-score (micro avg) 0.8259 | |
| 2023-10-17 21:00:25,943 saving best model | |
| 2023-10-17 21:00:26,419 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 21:00:33,428 epoch 3 - iter 147/1476 - loss 0.07934414 - time (sec): 7.01 - samples/sec: 2159.00 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-17 21:00:40,523 epoch 3 - iter 294/1476 - loss 0.09609900 - time (sec): 14.10 - samples/sec: 2172.43 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-17 21:00:47,796 epoch 3 - iter 441/1476 - loss 0.09164912 - time (sec): 21.37 - samples/sec: 2234.61 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-17 21:00:55,154 epoch 3 - iter 588/1476 - loss 0.09089120 - time (sec): 28.73 - samples/sec: 2268.48 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-17 21:01:02,256 epoch 3 - iter 735/1476 - loss 0.08339538 - time (sec): 35.84 - samples/sec: 2250.66 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-17 21:01:09,257 epoch 3 - iter 882/1476 - loss 0.08902747 - time (sec): 42.84 - samples/sec: 2262.89 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-17 21:01:16,813 epoch 3 - iter 1029/1476 - loss 0.08671360 - time (sec): 50.39 - samples/sec: 2294.45 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-17 21:01:23,764 epoch 3 - iter 1176/1476 - loss 0.08659255 - time (sec): 57.34 - samples/sec: 2313.83 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-17 21:01:30,803 epoch 3 - iter 1323/1476 - loss 0.08351285 - time (sec): 64.38 - samples/sec: 2321.06 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-17 21:01:37,894 epoch 3 - iter 1470/1476 - loss 0.08434125 - time (sec): 71.47 - samples/sec: 2319.81 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-17 21:01:38,165 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 21:01:38,166 EPOCH 3 done: loss 0.0846 - lr: 0.000023 | |
| 2023-10-17 21:01:49,589 DEV : loss 0.15964345633983612 - f1-score (micro avg) 0.8312 | |
| 2023-10-17 21:01:49,622 saving best model | |
| 2023-10-17 21:01:50,120 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 21:01:57,454 epoch 4 - iter 147/1476 - loss 0.04444733 - time (sec): 7.33 - samples/sec: 2324.92 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-17 21:02:04,946 epoch 4 - iter 294/1476 - loss 0.05274934 - time (sec): 14.82 - samples/sec: 2382.82 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-17 21:02:12,021 epoch 4 - iter 441/1476 - loss 0.05372551 - time (sec): 21.90 - samples/sec: 2369.97 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-17 21:02:19,177 epoch 4 - iter 588/1476 - loss 0.05933968 - time (sec): 29.06 - samples/sec: 2359.93 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-17 21:02:26,456 epoch 4 - iter 735/1476 - loss 0.06212474 - time (sec): 36.33 - samples/sec: 2312.29 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-17 21:02:33,665 epoch 4 - iter 882/1476 - loss 0.06178211 - time (sec): 43.54 - samples/sec: 2307.36 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-17 21:02:40,494 epoch 4 - iter 1029/1476 - loss 0.06100964 - time (sec): 50.37 - samples/sec: 2303.47 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-17 21:02:47,522 epoch 4 - iter 1176/1476 - loss 0.05940440 - time (sec): 57.40 - samples/sec: 2313.65 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-17 21:02:54,841 epoch 4 - iter 1323/1476 - loss 0.05790407 - time (sec): 64.72 - samples/sec: 2331.95 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-17 21:03:01,613 epoch 4 - iter 1470/1476 - loss 0.05665612 - time (sec): 71.49 - samples/sec: 2319.81 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-17 21:03:01,876 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 21:03:01,876 EPOCH 4 done: loss 0.0567 - lr: 0.000020 | |
| 2023-10-17 21:03:13,306 DEV : loss 0.17311468720436096 - f1-score (micro avg) 0.843 | |
| 2023-10-17 21:03:13,340 saving best model | |
| 2023-10-17 21:03:13,833 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 21:03:21,330 epoch 5 - iter 147/1476 - loss 0.04282800 - time (sec): 7.49 - samples/sec: 2344.93 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-17 21:03:28,482 epoch 5 - iter 294/1476 - loss 0.04004777 - time (sec): 14.65 - samples/sec: 2342.70 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-17 21:03:36,115 epoch 5 - iter 441/1476 - loss 0.03965920 - time (sec): 22.28 - samples/sec: 2354.71 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-17 21:03:43,279 epoch 5 - iter 588/1476 - loss 0.04080899 - time (sec): 29.44 - samples/sec: 2343.97 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-17 21:03:50,569 epoch 5 - iter 735/1476 - loss 0.03827681 - time (sec): 36.73 - samples/sec: 2337.14 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-17 21:03:57,752 epoch 5 - iter 882/1476 - loss 0.03780090 - time (sec): 43.92 - samples/sec: 2346.28 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-17 21:04:04,597 epoch 5 - iter 1029/1476 - loss 0.03994119 - time (sec): 50.76 - samples/sec: 2320.16 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-17 21:04:11,642 epoch 5 - iter 1176/1476 - loss 0.04187246 - time (sec): 57.81 - samples/sec: 2298.10 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-17 21:04:18,894 epoch 5 - iter 1323/1476 - loss 0.04077018 - time (sec): 65.06 - samples/sec: 2295.16 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-17 21:04:25,992 epoch 5 - iter 1470/1476 - loss 0.04145277 - time (sec): 72.16 - samples/sec: 2299.03 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-17 21:04:26,259 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 21:04:26,259 EPOCH 5 done: loss 0.0413 - lr: 0.000017 | |
| 2023-10-17 21:04:37,935 DEV : loss 0.17236292362213135 - f1-score (micro avg) 0.8485 | |
| 2023-10-17 21:04:37,966 saving best model | |
| 2023-10-17 21:04:38,435 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 21:04:45,721 epoch 6 - iter 147/1476 - loss 0.02321970 - time (sec): 7.28 - samples/sec: 2247.92 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-17 21:04:52,756 epoch 6 - iter 294/1476 - loss 0.02613525 - time (sec): 14.32 - samples/sec: 2259.85 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-17 21:04:59,642 epoch 6 - iter 441/1476 - loss 0.02587034 - time (sec): 21.20 - samples/sec: 2235.49 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-17 21:05:06,890 epoch 6 - iter 588/1476 - loss 0.02499643 - time (sec): 28.45 - samples/sec: 2252.81 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-17 21:05:14,135 epoch 6 - iter 735/1476 - loss 0.02538178 - time (sec): 35.70 - samples/sec: 2259.69 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-17 21:05:21,161 epoch 6 - iter 882/1476 - loss 0.02381428 - time (sec): 42.72 - samples/sec: 2261.17 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-17 21:05:28,064 epoch 6 - iter 1029/1476 - loss 0.02435506 - time (sec): 49.62 - samples/sec: 2263.86 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-17 21:05:35,139 epoch 6 - iter 1176/1476 - loss 0.02457862 - time (sec): 56.70 - samples/sec: 2255.84 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-17 21:05:43,291 epoch 6 - iter 1323/1476 - loss 0.02668096 - time (sec): 64.85 - samples/sec: 2291.48 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-17 21:05:51,405 epoch 6 - iter 1470/1476 - loss 0.02593758 - time (sec): 72.96 - samples/sec: 2262.54 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-17 21:05:51,855 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 21:05:51,855 EPOCH 6 done: loss 0.0264 - lr: 0.000013 | |
| 2023-10-17 21:06:03,471 DEV : loss 0.19792184233665466 - f1-score (micro avg) 0.8556 | |
| 2023-10-17 21:06:03,503 saving best model | |
| 2023-10-17 21:06:03,987 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 21:06:11,091 epoch 7 - iter 147/1476 - loss 0.01811113 - time (sec): 7.10 - samples/sec: 2159.54 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-17 21:06:17,921 epoch 7 - iter 294/1476 - loss 0.01490523 - time (sec): 13.93 - samples/sec: 2252.91 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-17 21:06:25,612 epoch 7 - iter 441/1476 - loss 0.01387370 - time (sec): 21.62 - samples/sec: 2127.64 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-17 21:06:32,793 epoch 7 - iter 588/1476 - loss 0.01461327 - time (sec): 28.80 - samples/sec: 2167.02 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-17 21:06:40,082 epoch 7 - iter 735/1476 - loss 0.01603147 - time (sec): 36.09 - samples/sec: 2180.74 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-17 21:06:47,260 epoch 7 - iter 882/1476 - loss 0.01529605 - time (sec): 43.27 - samples/sec: 2231.67 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-17 21:06:54,953 epoch 7 - iter 1029/1476 - loss 0.01843807 - time (sec): 50.96 - samples/sec: 2301.89 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-17 21:07:01,899 epoch 7 - iter 1176/1476 - loss 0.01924003 - time (sec): 57.91 - samples/sec: 2299.36 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-17 21:07:08,912 epoch 7 - iter 1323/1476 - loss 0.01951725 - time (sec): 64.92 - samples/sec: 2305.74 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-17 21:07:16,073 epoch 7 - iter 1470/1476 - loss 0.01948374 - time (sec): 72.08 - samples/sec: 2303.28 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-17 21:07:16,337 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 21:07:16,337 EPOCH 7 done: loss 0.0195 - lr: 0.000010 | |
| 2023-10-17 21:07:27,797 DEV : loss 0.19168895483016968 - f1-score (micro avg) 0.8477 | |
| 2023-10-17 21:07:27,827 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 21:07:34,880 epoch 8 - iter 147/1476 - loss 0.00934227 - time (sec): 7.05 - samples/sec: 2231.59 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-17 21:07:41,878 epoch 8 - iter 294/1476 - loss 0.01061936 - time (sec): 14.05 - samples/sec: 2252.58 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-17 21:07:48,874 epoch 8 - iter 441/1476 - loss 0.00958806 - time (sec): 21.05 - samples/sec: 2265.87 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-17 21:07:55,968 epoch 8 - iter 588/1476 - loss 0.00935601 - time (sec): 28.14 - samples/sec: 2248.99 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-17 21:08:03,591 epoch 8 - iter 735/1476 - loss 0.01281493 - time (sec): 35.76 - samples/sec: 2346.33 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-17 21:08:11,023 epoch 8 - iter 882/1476 - loss 0.01188403 - time (sec): 43.19 - samples/sec: 2368.03 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-17 21:08:17,939 epoch 8 - iter 1029/1476 - loss 0.01101362 - time (sec): 50.11 - samples/sec: 2359.18 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-17 21:08:25,003 epoch 8 - iter 1176/1476 - loss 0.01167092 - time (sec): 57.17 - samples/sec: 2360.59 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-17 21:08:31,942 epoch 8 - iter 1323/1476 - loss 0.01217457 - time (sec): 64.11 - samples/sec: 2345.92 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-17 21:08:38,561 epoch 8 - iter 1470/1476 - loss 0.01223428 - time (sec): 70.73 - samples/sec: 2341.08 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-17 21:08:38,858 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 21:08:38,859 EPOCH 8 done: loss 0.0122 - lr: 0.000007 | |
| 2023-10-17 21:08:50,366 DEV : loss 0.21457839012145996 - f1-score (micro avg) 0.8464 | |
| 2023-10-17 21:08:50,399 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 21:08:57,588 epoch 9 - iter 147/1476 - loss 0.01782838 - time (sec): 7.19 - samples/sec: 2506.00 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-17 21:09:04,554 epoch 9 - iter 294/1476 - loss 0.01151611 - time (sec): 14.15 - samples/sec: 2447.27 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-17 21:09:11,392 epoch 9 - iter 441/1476 - loss 0.00978648 - time (sec): 20.99 - samples/sec: 2392.69 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-17 21:09:18,834 epoch 9 - iter 588/1476 - loss 0.00991456 - time (sec): 28.43 - samples/sec: 2375.92 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-17 21:09:25,871 epoch 9 - iter 735/1476 - loss 0.01023225 - time (sec): 35.47 - samples/sec: 2344.60 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-17 21:09:33,062 epoch 9 - iter 882/1476 - loss 0.00966054 - time (sec): 42.66 - samples/sec: 2357.99 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-17 21:09:40,162 epoch 9 - iter 1029/1476 - loss 0.01008829 - time (sec): 49.76 - samples/sec: 2357.56 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-17 21:09:47,248 epoch 9 - iter 1176/1476 - loss 0.01025552 - time (sec): 56.85 - samples/sec: 2370.39 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-17 21:09:54,306 epoch 9 - iter 1323/1476 - loss 0.00963061 - time (sec): 63.91 - samples/sec: 2359.79 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-17 21:10:01,693 epoch 9 - iter 1470/1476 - loss 0.00908092 - time (sec): 71.29 - samples/sec: 2327.44 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-17 21:10:01,964 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 21:10:01,964 EPOCH 9 done: loss 0.0091 - lr: 0.000003 | |
| 2023-10-17 21:10:13,701 DEV : loss 0.2243947833776474 - f1-score (micro avg) 0.8475 | |
| 2023-10-17 21:10:13,751 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 21:10:21,899 epoch 10 - iter 147/1476 - loss 0.00275969 - time (sec): 8.15 - samples/sec: 2031.82 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-17 21:10:30,507 epoch 10 - iter 294/1476 - loss 0.00846906 - time (sec): 16.75 - samples/sec: 2097.44 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-17 21:10:38,195 epoch 10 - iter 441/1476 - loss 0.00806670 - time (sec): 24.44 - samples/sec: 2080.66 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-17 21:10:45,362 epoch 10 - iter 588/1476 - loss 0.00753225 - time (sec): 31.61 - samples/sec: 2141.43 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-17 21:10:52,221 epoch 10 - iter 735/1476 - loss 0.00635976 - time (sec): 38.47 - samples/sec: 2173.07 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-17 21:10:59,111 epoch 10 - iter 882/1476 - loss 0.00703310 - time (sec): 45.36 - samples/sec: 2187.99 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-17 21:11:06,354 epoch 10 - iter 1029/1476 - loss 0.00633039 - time (sec): 52.60 - samples/sec: 2193.56 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-17 21:11:13,330 epoch 10 - iter 1176/1476 - loss 0.00586313 - time (sec): 59.58 - samples/sec: 2215.09 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-17 21:11:20,199 epoch 10 - iter 1323/1476 - loss 0.00585113 - time (sec): 66.45 - samples/sec: 2232.50 - lr: 0.000000 - momentum: 0.000000 | |
| 2023-10-17 21:11:27,533 epoch 10 - iter 1470/1476 - loss 0.00538743 - time (sec): 73.78 - samples/sec: 2248.65 - lr: 0.000000 - momentum: 0.000000 | |
| 2023-10-17 21:11:27,799 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 21:11:27,800 EPOCH 10 done: loss 0.0054 - lr: 0.000000 | |
| 2023-10-17 21:11:39,245 DEV : loss 0.22376643121242523 - f1-score (micro avg) 0.8539 | |
| 2023-10-17 21:11:39,633 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 21:11:39,634 Loading model from best epoch ... | |
| 2023-10-17 21:11:41,018 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 | |
| 2023-10-17 21:11:47,214 | |
| Results: | |
| - F-score (micro) 0.7986 | |
| - F-score (macro) 0.7013 | |
| - Accuracy 0.6844 | |
| By class: | |
| precision recall f1-score support | |
| loc 0.8515 0.8753 0.8632 858 | |
| pers 0.7638 0.8007 0.7818 537 | |
| org 0.5605 0.6667 0.6090 132 | |
| time 0.5410 0.6111 0.5739 54 | |
| prod 0.7451 0.6230 0.6786 61 | |
| micro avg 0.7818 0.8161 0.7986 1642 | |
| macro avg 0.6924 0.7154 0.7013 1642 | |
| weighted avg 0.7852 0.8161 0.7998 1642 | |
| 2023-10-17 21:11:47,214 ---------------------------------------------------------------------------------------------------- | |