| 2023-10-17 11:13:56,603 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:13:56,605 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 11:13:56,605 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:13:56,606 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 11:13:56,606 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:13:56,606 Train: 6183 sentences | |
| 2023-10-17 11:13:56,606 (train_with_dev=False, train_with_test=False) | |
| 2023-10-17 11:13:56,606 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:13:56,606 Training Params: | |
| 2023-10-17 11:13:56,606 - learning_rate: "3e-05" | |
| 2023-10-17 11:13:56,606 - mini_batch_size: "4" | |
| 2023-10-17 11:13:56,606 - max_epochs: "10" | |
| 2023-10-17 11:13:56,606 - shuffle: "True" | |
| 2023-10-17 11:13:56,606 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:13:56,606 Plugins: | |
| 2023-10-17 11:13:56,607 - TensorboardLogger | |
| 2023-10-17 11:13:56,607 - LinearScheduler | warmup_fraction: '0.1' | |
| 2023-10-17 11:13:56,607 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:13:56,607 Final evaluation on model from best epoch (best-model.pt) | |
| 2023-10-17 11:13:56,607 - metric: "('micro avg', 'f1-score')" | |
| 2023-10-17 11:13:56,607 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:13:56,607 Computation: | |
| 2023-10-17 11:13:56,607 - compute on device: cuda:0 | |
| 2023-10-17 11:13:56,607 - embedding storage: none | |
| 2023-10-17 11:13:56,607 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:13:56,607 Model training base path: "hmbench-topres19th/en-hmteams/teams-base-historic-multilingual-discriminator-bs4-wsFalse-e10-lr3e-05-poolingfirst-layers-1-crfFalse-3" | |
| 2023-10-17 11:13:56,607 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:13:56,607 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:13:56,608 Logging anything other than scalars to TensorBoard is currently not supported. | |
| 2023-10-17 11:14:08,890 epoch 1 - iter 154/1546 - loss 2.29547994 - time (sec): 12.28 - samples/sec: 1002.18 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-17 11:14:21,057 epoch 1 - iter 308/1546 - loss 1.29346448 - time (sec): 24.45 - samples/sec: 1007.81 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-17 11:14:34,224 epoch 1 - iter 462/1546 - loss 0.90808138 - time (sec): 37.61 - samples/sec: 995.33 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-17 11:14:46,652 epoch 1 - iter 616/1546 - loss 0.70493184 - time (sec): 50.04 - samples/sec: 1001.84 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-17 11:14:59,593 epoch 1 - iter 770/1546 - loss 0.58385751 - time (sec): 62.98 - samples/sec: 992.94 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-17 11:15:12,599 epoch 1 - iter 924/1546 - loss 0.51470217 - time (sec): 75.99 - samples/sec: 975.42 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-17 11:15:25,294 epoch 1 - iter 1078/1546 - loss 0.46185738 - time (sec): 88.68 - samples/sec: 964.67 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-17 11:15:37,971 epoch 1 - iter 1232/1546 - loss 0.41727367 - time (sec): 101.36 - samples/sec: 968.07 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-17 11:15:50,195 epoch 1 - iter 1386/1546 - loss 0.38182017 - time (sec): 113.59 - samples/sec: 979.04 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-17 11:16:02,470 epoch 1 - iter 1540/1546 - loss 0.35440131 - time (sec): 125.86 - samples/sec: 982.92 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-17 11:16:02,944 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:16:02,945 EPOCH 1 done: loss 0.3530 - lr: 0.000030 | |
| 2023-10-17 11:16:05,529 DEV : loss 0.05910523235797882 - f1-score (micro avg) 0.7659 | |
| 2023-10-17 11:16:05,566 saving best model | |
| 2023-10-17 11:16:06,167 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:16:18,356 epoch 2 - iter 154/1546 - loss 0.08768355 - time (sec): 12.19 - samples/sec: 972.96 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-17 11:16:30,262 epoch 2 - iter 308/1546 - loss 0.08328678 - time (sec): 24.09 - samples/sec: 996.17 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-17 11:16:42,966 epoch 2 - iter 462/1546 - loss 0.08465471 - time (sec): 36.80 - samples/sec: 990.15 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-17 11:16:55,659 epoch 2 - iter 616/1546 - loss 0.08609058 - time (sec): 49.49 - samples/sec: 999.87 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-17 11:17:08,034 epoch 2 - iter 770/1546 - loss 0.08402493 - time (sec): 61.86 - samples/sec: 994.12 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-17 11:17:19,827 epoch 2 - iter 924/1546 - loss 0.08269652 - time (sec): 73.66 - samples/sec: 1011.66 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-17 11:17:32,826 epoch 2 - iter 1078/1546 - loss 0.08211590 - time (sec): 86.66 - samples/sec: 998.57 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-17 11:17:45,948 epoch 2 - iter 1232/1546 - loss 0.08093449 - time (sec): 99.78 - samples/sec: 983.42 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-17 11:17:58,852 epoch 2 - iter 1386/1546 - loss 0.08134950 - time (sec): 112.68 - samples/sec: 994.24 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-17 11:18:11,277 epoch 2 - iter 1540/1546 - loss 0.08052732 - time (sec): 125.11 - samples/sec: 990.05 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-17 11:18:11,777 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:18:11,777 EPOCH 2 done: loss 0.0812 - lr: 0.000027 | |
| 2023-10-17 11:18:14,902 DEV : loss 0.06066319718956947 - f1-score (micro avg) 0.7671 | |
| 2023-10-17 11:18:14,938 saving best model | |
| 2023-10-17 11:18:16,489 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:18:29,564 epoch 3 - iter 154/1546 - loss 0.05252984 - time (sec): 13.07 - samples/sec: 908.49 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-17 11:18:42,028 epoch 3 - iter 308/1546 - loss 0.05150808 - time (sec): 25.54 - samples/sec: 902.92 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-17 11:18:54,060 epoch 3 - iter 462/1546 - loss 0.05008931 - time (sec): 37.57 - samples/sec: 945.68 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-17 11:19:06,497 epoch 3 - iter 616/1546 - loss 0.05637854 - time (sec): 50.01 - samples/sec: 969.28 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-17 11:19:18,427 epoch 3 - iter 770/1546 - loss 0.05511052 - time (sec): 61.94 - samples/sec: 989.20 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-17 11:19:30,271 epoch 3 - iter 924/1546 - loss 0.05463507 - time (sec): 73.78 - samples/sec: 999.35 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-17 11:19:42,021 epoch 3 - iter 1078/1546 - loss 0.05491450 - time (sec): 85.53 - samples/sec: 1007.21 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-17 11:19:53,763 epoch 3 - iter 1232/1546 - loss 0.05459277 - time (sec): 97.27 - samples/sec: 1013.08 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-17 11:20:05,476 epoch 3 - iter 1386/1546 - loss 0.05518890 - time (sec): 108.98 - samples/sec: 1020.20 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-17 11:20:17,203 epoch 3 - iter 1540/1546 - loss 0.05554067 - time (sec): 120.71 - samples/sec: 1026.37 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-17 11:20:17,646 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:20:17,647 EPOCH 3 done: loss 0.0556 - lr: 0.000023 | |
| 2023-10-17 11:20:20,446 DEV : loss 0.08556292951107025 - f1-score (micro avg) 0.7732 | |
| 2023-10-17 11:20:20,475 saving best model | |
| 2023-10-17 11:20:21,890 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:20:33,722 epoch 4 - iter 154/1546 - loss 0.03577965 - time (sec): 11.83 - samples/sec: 1097.27 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-17 11:20:45,706 epoch 4 - iter 308/1546 - loss 0.03488418 - time (sec): 23.81 - samples/sec: 1107.14 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-17 11:20:58,160 epoch 4 - iter 462/1546 - loss 0.03705614 - time (sec): 36.27 - samples/sec: 1054.19 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-17 11:21:10,800 epoch 4 - iter 616/1546 - loss 0.03656234 - time (sec): 48.91 - samples/sec: 1031.28 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-17 11:21:22,899 epoch 4 - iter 770/1546 - loss 0.03807395 - time (sec): 61.00 - samples/sec: 1027.23 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-17 11:21:35,839 epoch 4 - iter 924/1546 - loss 0.03823139 - time (sec): 73.94 - samples/sec: 1013.14 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-17 11:21:47,505 epoch 4 - iter 1078/1546 - loss 0.03665500 - time (sec): 85.61 - samples/sec: 1012.27 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-17 11:21:59,565 epoch 4 - iter 1232/1546 - loss 0.03711619 - time (sec): 97.67 - samples/sec: 1006.84 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-17 11:22:11,925 epoch 4 - iter 1386/1546 - loss 0.03726587 - time (sec): 110.03 - samples/sec: 1012.36 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-17 11:22:24,289 epoch 4 - iter 1540/1546 - loss 0.03708960 - time (sec): 122.40 - samples/sec: 1010.95 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-17 11:22:24,761 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:22:24,762 EPOCH 4 done: loss 0.0369 - lr: 0.000020 | |
| 2023-10-17 11:22:27,688 DEV : loss 0.0917343944311142 - f1-score (micro avg) 0.8195 | |
| 2023-10-17 11:22:27,719 saving best model | |
| 2023-10-17 11:22:29,184 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:22:41,658 epoch 5 - iter 154/1546 - loss 0.02368522 - time (sec): 12.47 - samples/sec: 982.48 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-17 11:22:54,113 epoch 5 - iter 308/1546 - loss 0.01941446 - time (sec): 24.92 - samples/sec: 1027.45 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-17 11:23:06,811 epoch 5 - iter 462/1546 - loss 0.02121999 - time (sec): 37.62 - samples/sec: 984.80 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-17 11:23:19,317 epoch 5 - iter 616/1546 - loss 0.02123932 - time (sec): 50.13 - samples/sec: 974.54 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-17 11:23:31,434 epoch 5 - iter 770/1546 - loss 0.02250424 - time (sec): 62.25 - samples/sec: 979.67 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-17 11:23:43,680 epoch 5 - iter 924/1546 - loss 0.02230769 - time (sec): 74.49 - samples/sec: 984.33 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-17 11:23:56,140 epoch 5 - iter 1078/1546 - loss 0.02319952 - time (sec): 86.95 - samples/sec: 990.92 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-17 11:24:09,092 epoch 5 - iter 1232/1546 - loss 0.02412054 - time (sec): 99.90 - samples/sec: 989.89 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-17 11:24:21,282 epoch 5 - iter 1386/1546 - loss 0.02598636 - time (sec): 112.09 - samples/sec: 992.74 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-17 11:24:33,226 epoch 5 - iter 1540/1546 - loss 0.02551503 - time (sec): 124.04 - samples/sec: 995.81 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-17 11:24:33,716 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:24:33,716 EPOCH 5 done: loss 0.0257 - lr: 0.000017 | |
| 2023-10-17 11:24:36,785 DEV : loss 0.10130724310874939 - f1-score (micro avg) 0.7893 | |
| 2023-10-17 11:24:36,819 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:24:49,940 epoch 6 - iter 154/1546 - loss 0.01652449 - time (sec): 13.12 - samples/sec: 903.13 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-17 11:25:02,121 epoch 6 - iter 308/1546 - loss 0.01442618 - time (sec): 25.30 - samples/sec: 913.93 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-17 11:25:14,373 epoch 6 - iter 462/1546 - loss 0.01784155 - time (sec): 37.55 - samples/sec: 954.25 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-17 11:25:27,405 epoch 6 - iter 616/1546 - loss 0.01777913 - time (sec): 50.58 - samples/sec: 971.08 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-17 11:25:39,347 epoch 6 - iter 770/1546 - loss 0.01795534 - time (sec): 62.53 - samples/sec: 984.87 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-17 11:25:51,305 epoch 6 - iter 924/1546 - loss 0.01739042 - time (sec): 74.48 - samples/sec: 991.11 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-17 11:26:03,459 epoch 6 - iter 1078/1546 - loss 0.01775013 - time (sec): 86.64 - samples/sec: 998.09 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-17 11:26:16,160 epoch 6 - iter 1232/1546 - loss 0.01809639 - time (sec): 99.34 - samples/sec: 994.38 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-17 11:26:29,256 epoch 6 - iter 1386/1546 - loss 0.01849270 - time (sec): 112.43 - samples/sec: 990.80 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-17 11:26:41,336 epoch 6 - iter 1540/1546 - loss 0.01830477 - time (sec): 124.51 - samples/sec: 993.88 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-17 11:26:41,807 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:26:41,808 EPOCH 6 done: loss 0.0182 - lr: 0.000013 | |
| 2023-10-17 11:26:44,694 DEV : loss 0.10719826072454453 - f1-score (micro avg) 0.7934 | |
| 2023-10-17 11:26:44,728 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:26:57,550 epoch 7 - iter 154/1546 - loss 0.01081941 - time (sec): 12.82 - samples/sec: 918.18 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-17 11:27:10,095 epoch 7 - iter 308/1546 - loss 0.00812489 - time (sec): 25.36 - samples/sec: 946.51 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-17 11:27:22,185 epoch 7 - iter 462/1546 - loss 0.00814902 - time (sec): 37.45 - samples/sec: 979.98 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-17 11:27:34,148 epoch 7 - iter 616/1546 - loss 0.00838999 - time (sec): 49.42 - samples/sec: 982.44 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-17 11:27:46,310 epoch 7 - iter 770/1546 - loss 0.00970640 - time (sec): 61.58 - samples/sec: 979.40 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-17 11:27:58,186 epoch 7 - iter 924/1546 - loss 0.01186251 - time (sec): 73.46 - samples/sec: 991.95 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-17 11:28:10,494 epoch 7 - iter 1078/1546 - loss 0.01264509 - time (sec): 85.76 - samples/sec: 1016.31 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-17 11:28:22,874 epoch 7 - iter 1232/1546 - loss 0.01279804 - time (sec): 98.14 - samples/sec: 1010.40 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-17 11:28:35,168 epoch 7 - iter 1386/1546 - loss 0.01293158 - time (sec): 110.44 - samples/sec: 1007.01 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-17 11:28:47,480 epoch 7 - iter 1540/1546 - loss 0.01261237 - time (sec): 122.75 - samples/sec: 1006.53 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-17 11:28:47,956 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:28:47,956 EPOCH 7 done: loss 0.0127 - lr: 0.000010 | |
| 2023-10-17 11:28:50,876 DEV : loss 0.11056238412857056 - f1-score (micro avg) 0.7773 | |
| 2023-10-17 11:28:50,910 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:29:03,762 epoch 8 - iter 154/1546 - loss 0.01168277 - time (sec): 12.85 - samples/sec: 908.17 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-17 11:29:16,091 epoch 8 - iter 308/1546 - loss 0.00829209 - time (sec): 25.18 - samples/sec: 961.42 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-17 11:29:28,416 epoch 8 - iter 462/1546 - loss 0.00887281 - time (sec): 37.50 - samples/sec: 949.77 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-17 11:29:40,478 epoch 8 - iter 616/1546 - loss 0.00942431 - time (sec): 49.57 - samples/sec: 954.38 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-17 11:29:53,170 epoch 8 - iter 770/1546 - loss 0.00837839 - time (sec): 62.26 - samples/sec: 971.20 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-17 11:30:05,612 epoch 8 - iter 924/1546 - loss 0.00809697 - time (sec): 74.70 - samples/sec: 988.36 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-17 11:30:17,628 epoch 8 - iter 1078/1546 - loss 0.00792721 - time (sec): 86.72 - samples/sec: 994.36 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-17 11:30:29,873 epoch 8 - iter 1232/1546 - loss 0.00741324 - time (sec): 98.96 - samples/sec: 1001.21 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-17 11:30:42,467 epoch 8 - iter 1386/1546 - loss 0.00743982 - time (sec): 111.56 - samples/sec: 996.95 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-17 11:30:54,660 epoch 8 - iter 1540/1546 - loss 0.00794718 - time (sec): 123.75 - samples/sec: 999.99 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-17 11:30:55,169 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:30:55,169 EPOCH 8 done: loss 0.0079 - lr: 0.000007 | |
| 2023-10-17 11:30:58,242 DEV : loss 0.10748875141143799 - f1-score (micro avg) 0.8082 | |
| 2023-10-17 11:30:58,271 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:31:10,443 epoch 9 - iter 154/1546 - loss 0.00097898 - time (sec): 12.17 - samples/sec: 1034.89 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-17 11:31:22,828 epoch 9 - iter 308/1546 - loss 0.00288126 - time (sec): 24.56 - samples/sec: 1065.60 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-17 11:31:35,404 epoch 9 - iter 462/1546 - loss 0.00393364 - time (sec): 37.13 - samples/sec: 1023.72 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-17 11:31:47,705 epoch 9 - iter 616/1546 - loss 0.00335481 - time (sec): 49.43 - samples/sec: 1025.62 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-17 11:32:00,084 epoch 9 - iter 770/1546 - loss 0.00299308 - time (sec): 61.81 - samples/sec: 1019.06 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-17 11:32:12,334 epoch 9 - iter 924/1546 - loss 0.00368111 - time (sec): 74.06 - samples/sec: 1007.26 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-17 11:32:24,354 epoch 9 - iter 1078/1546 - loss 0.00488522 - time (sec): 86.08 - samples/sec: 1009.42 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-17 11:32:36,765 epoch 9 - iter 1232/1546 - loss 0.00490894 - time (sec): 98.49 - samples/sec: 1011.12 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-17 11:32:49,481 epoch 9 - iter 1386/1546 - loss 0.00510702 - time (sec): 111.21 - samples/sec: 1012.93 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-17 11:33:02,191 epoch 9 - iter 1540/1546 - loss 0.00513657 - time (sec): 123.92 - samples/sec: 998.79 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-17 11:33:02,652 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:33:02,653 EPOCH 9 done: loss 0.0051 - lr: 0.000003 | |
| 2023-10-17 11:33:05,592 DEV : loss 0.11327943950891495 - f1-score (micro avg) 0.8167 | |
| 2023-10-17 11:33:05,621 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:33:17,814 epoch 10 - iter 154/1546 - loss 0.00274619 - time (sec): 12.19 - samples/sec: 992.32 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-17 11:33:29,904 epoch 10 - iter 308/1546 - loss 0.00202981 - time (sec): 24.28 - samples/sec: 1061.96 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-17 11:33:42,176 epoch 10 - iter 462/1546 - loss 0.00201148 - time (sec): 36.55 - samples/sec: 1047.57 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-17 11:33:54,082 epoch 10 - iter 616/1546 - loss 0.00298200 - time (sec): 48.46 - samples/sec: 1034.92 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-17 11:34:06,280 epoch 10 - iter 770/1546 - loss 0.00292290 - time (sec): 60.66 - samples/sec: 1037.45 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-17 11:34:18,626 epoch 10 - iter 924/1546 - loss 0.00273291 - time (sec): 73.00 - samples/sec: 1038.34 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-17 11:34:30,882 epoch 10 - iter 1078/1546 - loss 0.00327913 - time (sec): 85.26 - samples/sec: 1033.74 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-17 11:34:43,145 epoch 10 - iter 1232/1546 - loss 0.00313428 - time (sec): 97.52 - samples/sec: 1014.51 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-17 11:34:55,365 epoch 10 - iter 1386/1546 - loss 0.00291812 - time (sec): 109.74 - samples/sec: 1019.93 - lr: 0.000000 - momentum: 0.000000 | |
| 2023-10-17 11:35:08,505 epoch 10 - iter 1540/1546 - loss 0.00316831 - time (sec): 122.88 - samples/sec: 1007.44 - lr: 0.000000 - momentum: 0.000000 | |
| 2023-10-17 11:35:08,964 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:35:08,965 EPOCH 10 done: loss 0.0032 - lr: 0.000000 | |
| 2023-10-17 11:35:11,979 DEV : loss 0.11607711017131805 - f1-score (micro avg) 0.7951 | |
| 2023-10-17 11:35:12,999 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:35:13,001 Loading model from best epoch ... | |
| 2023-10-17 11:35:15,647 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 11:35:24,658 | |
| Results: | |
| - F-score (micro) 0.8219 | |
| - F-score (macro) 0.7427 | |
| - Accuracy 0.7156 | |
| By class: | |
| precision recall f1-score support | |
| LOC 0.8829 0.8446 0.8633 946 | |
| BUILDING 0.6772 0.5784 0.6239 185 | |
| STREET 0.7692 0.7143 0.7407 56 | |
| micro avg 0.8484 0.7970 0.8219 1187 | |
| macro avg 0.7764 0.7124 0.7427 1187 | |
| weighted avg 0.8455 0.7970 0.8202 1187 | |
| 2023-10-17 11:35:24,659 ---------------------------------------------------------------------------------------------------- | |