| 2023-10-19 20:37:47,501 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 20:37:47,501 Model: "SequenceTagger( | |
| (embeddings): TransformerWordEmbeddings( | |
| (model): BertModel( | |
| (embeddings): BertEmbeddings( | |
| (word_embeddings): Embedding(32001, 128) | |
| (position_embeddings): Embedding(512, 128) | |
| (token_type_embeddings): Embedding(2, 128) | |
| (LayerNorm): LayerNorm((128,), eps=1e-12, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| (encoder): BertEncoder( | |
| (layer): ModuleList( | |
| (0-1): 2 x BertLayer( | |
| (attention): BertAttention( | |
| (self): BertSelfAttention( | |
| (query): Linear(in_features=128, out_features=128, bias=True) | |
| (key): Linear(in_features=128, out_features=128, bias=True) | |
| (value): Linear(in_features=128, out_features=128, bias=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| (output): BertSelfOutput( | |
| (dense): Linear(in_features=128, out_features=128, bias=True) | |
| (LayerNorm): LayerNorm((128,), eps=1e-12, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (intermediate): BertIntermediate( | |
| (dense): Linear(in_features=128, out_features=512, bias=True) | |
| (intermediate_act_fn): GELUActivation() | |
| ) | |
| (output): BertOutput( | |
| (dense): Linear(in_features=512, out_features=128, bias=True) | |
| (LayerNorm): LayerNorm((128,), eps=1e-12, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| ) | |
| ) | |
| (pooler): BertPooler( | |
| (dense): Linear(in_features=128, out_features=128, bias=True) | |
| (activation): Tanh() | |
| ) | |
| ) | |
| ) | |
| (locked_dropout): LockedDropout(p=0.5) | |
| (linear): Linear(in_features=128, out_features=17, bias=True) | |
| (loss_function): CrossEntropyLoss() | |
| )" | |
| 2023-10-19 20:37:47,501 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 20:37:47,501 MultiCorpus: 7142 train + 698 dev + 2570 test sentences | |
| - NER_HIPE_2022 Corpus: 7142 train + 698 dev + 2570 test sentences - /root/.flair/datasets/ner_hipe_2022/v2.1/newseye/fr/with_doc_seperator | |
| 2023-10-19 20:37:47,501 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 20:37:47,501 Train: 7142 sentences | |
| 2023-10-19 20:37:47,502 (train_with_dev=False, train_with_test=False) | |
| 2023-10-19 20:37:47,502 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 20:37:47,502 Training Params: | |
| 2023-10-19 20:37:47,502 - learning_rate: "5e-05" | |
| 2023-10-19 20:37:47,502 - mini_batch_size: "4" | |
| 2023-10-19 20:37:47,502 - max_epochs: "10" | |
| 2023-10-19 20:37:47,502 - shuffle: "True" | |
| 2023-10-19 20:37:47,502 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 20:37:47,502 Plugins: | |
| 2023-10-19 20:37:47,502 - TensorboardLogger | |
| 2023-10-19 20:37:47,502 - LinearScheduler | warmup_fraction: '0.1' | |
| 2023-10-19 20:37:47,502 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 20:37:47,502 Final evaluation on model from best epoch (best-model.pt) | |
| 2023-10-19 20:37:47,502 - metric: "('micro avg', 'f1-score')" | |
| 2023-10-19 20:37:47,502 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 20:37:47,502 Computation: | |
| 2023-10-19 20:37:47,502 - compute on device: cuda:0 | |
| 2023-10-19 20:37:47,502 - embedding storage: none | |
| 2023-10-19 20:37:47,502 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 20:37:47,502 Model training base path: "hmbench-newseye/fr-dbmdz/bert-tiny-historic-multilingual-cased-bs4-wsFalse-e10-lr5e-05-poolingfirst-layers-1-crfFalse-4" | |
| 2023-10-19 20:37:47,502 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 20:37:47,502 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 20:37:47,502 Logging anything other than scalars to TensorBoard is currently not supported. | |
| 2023-10-19 20:37:50,218 epoch 1 - iter 178/1786 - loss 3.25038440 - time (sec): 2.71 - samples/sec: 9003.73 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-19 20:37:53,334 epoch 1 - iter 356/1786 - loss 2.72723456 - time (sec): 5.83 - samples/sec: 8560.72 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-19 20:37:56,391 epoch 1 - iter 534/1786 - loss 2.13524414 - time (sec): 8.89 - samples/sec: 8481.62 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-19 20:37:59,443 epoch 1 - iter 712/1786 - loss 1.75821465 - time (sec): 11.94 - samples/sec: 8570.20 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-19 20:38:02,460 epoch 1 - iter 890/1786 - loss 1.56053783 - time (sec): 14.96 - samples/sec: 8457.10 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-19 20:38:05,477 epoch 1 - iter 1068/1786 - loss 1.41754035 - time (sec): 17.97 - samples/sec: 8347.51 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-19 20:38:08,514 epoch 1 - iter 1246/1786 - loss 1.30441193 - time (sec): 21.01 - samples/sec: 8250.97 - lr: 0.000035 - momentum: 0.000000 | |
| 2023-10-19 20:38:11,602 epoch 1 - iter 1424/1786 - loss 1.20423029 - time (sec): 24.10 - samples/sec: 8223.35 - lr: 0.000040 - momentum: 0.000000 | |
| 2023-10-19 20:38:14,683 epoch 1 - iter 1602/1786 - loss 1.12451472 - time (sec): 27.18 - samples/sec: 8226.15 - lr: 0.000045 - momentum: 0.000000 | |
| 2023-10-19 20:38:17,750 epoch 1 - iter 1780/1786 - loss 1.05967954 - time (sec): 30.25 - samples/sec: 8210.13 - lr: 0.000050 - momentum: 0.000000 | |
| 2023-10-19 20:38:17,841 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 20:38:17,841 EPOCH 1 done: loss 1.0591 - lr: 0.000050 | |
| 2023-10-19 20:38:19,268 DEV : loss 0.2911563515663147 - f1-score (micro avg) 0.2194 | |
| 2023-10-19 20:38:19,281 saving best model | |
| 2023-10-19 20:38:19,317 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 20:38:22,372 epoch 2 - iter 178/1786 - loss 0.43030123 - time (sec): 3.05 - samples/sec: 8566.85 - lr: 0.000049 - momentum: 0.000000 | |
| 2023-10-19 20:38:25,394 epoch 2 - iter 356/1786 - loss 0.42697674 - time (sec): 6.08 - samples/sec: 8308.39 - lr: 0.000049 - momentum: 0.000000 | |
| 2023-10-19 20:38:28,377 epoch 2 - iter 534/1786 - loss 0.41531955 - time (sec): 9.06 - samples/sec: 8180.29 - lr: 0.000048 - momentum: 0.000000 | |
| 2023-10-19 20:38:31,485 epoch 2 - iter 712/1786 - loss 0.41406429 - time (sec): 12.17 - samples/sec: 8249.87 - lr: 0.000048 - momentum: 0.000000 | |
| 2023-10-19 20:38:34,537 epoch 2 - iter 890/1786 - loss 0.40178088 - time (sec): 15.22 - samples/sec: 8234.11 - lr: 0.000047 - momentum: 0.000000 | |
| 2023-10-19 20:38:37,582 epoch 2 - iter 1068/1786 - loss 0.40129750 - time (sec): 18.26 - samples/sec: 8234.00 - lr: 0.000047 - momentum: 0.000000 | |
| 2023-10-19 20:38:40,571 epoch 2 - iter 1246/1786 - loss 0.39641341 - time (sec): 21.25 - samples/sec: 8194.34 - lr: 0.000046 - momentum: 0.000000 | |
| 2023-10-19 20:38:43,411 epoch 2 - iter 1424/1786 - loss 0.39072789 - time (sec): 24.09 - samples/sec: 8264.27 - lr: 0.000046 - momentum: 0.000000 | |
| 2023-10-19 20:38:46,396 epoch 2 - iter 1602/1786 - loss 0.38909677 - time (sec): 27.08 - samples/sec: 8278.05 - lr: 0.000045 - momentum: 0.000000 | |
| 2023-10-19 20:38:49,429 epoch 2 - iter 1780/1786 - loss 0.38366296 - time (sec): 30.11 - samples/sec: 8243.44 - lr: 0.000044 - momentum: 0.000000 | |
| 2023-10-19 20:38:49,517 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 20:38:49,517 EPOCH 2 done: loss 0.3839 - lr: 0.000044 | |
| 2023-10-19 20:38:52,342 DEV : loss 0.22596031427383423 - f1-score (micro avg) 0.44 | |
| 2023-10-19 20:38:52,357 saving best model | |
| 2023-10-19 20:38:52,401 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 20:38:55,409 epoch 3 - iter 178/1786 - loss 0.31914122 - time (sec): 3.01 - samples/sec: 7689.78 - lr: 0.000044 - momentum: 0.000000 | |
| 2023-10-19 20:38:58,513 epoch 3 - iter 356/1786 - loss 0.31467803 - time (sec): 6.11 - samples/sec: 7874.30 - lr: 0.000043 - momentum: 0.000000 | |
| 2023-10-19 20:39:01,608 epoch 3 - iter 534/1786 - loss 0.31791586 - time (sec): 9.21 - samples/sec: 7952.03 - lr: 0.000043 - momentum: 0.000000 | |
| 2023-10-19 20:39:04,722 epoch 3 - iter 712/1786 - loss 0.32683842 - time (sec): 12.32 - samples/sec: 8044.64 - lr: 0.000042 - momentum: 0.000000 | |
| 2023-10-19 20:39:07,739 epoch 3 - iter 890/1786 - loss 0.32735327 - time (sec): 15.34 - samples/sec: 8054.04 - lr: 0.000042 - momentum: 0.000000 | |
| 2023-10-19 20:39:10,840 epoch 3 - iter 1068/1786 - loss 0.31925669 - time (sec): 18.44 - samples/sec: 8066.25 - lr: 0.000041 - momentum: 0.000000 | |
| 2023-10-19 20:39:14,011 epoch 3 - iter 1246/1786 - loss 0.31637069 - time (sec): 21.61 - samples/sec: 8038.72 - lr: 0.000041 - momentum: 0.000000 | |
| 2023-10-19 20:39:17,146 epoch 3 - iter 1424/1786 - loss 0.31200384 - time (sec): 24.74 - samples/sec: 8043.31 - lr: 0.000040 - momentum: 0.000000 | |
| 2023-10-19 20:39:20,329 epoch 3 - iter 1602/1786 - loss 0.30757124 - time (sec): 27.93 - samples/sec: 8017.97 - lr: 0.000039 - momentum: 0.000000 | |
| 2023-10-19 20:39:23,304 epoch 3 - iter 1780/1786 - loss 0.30421286 - time (sec): 30.90 - samples/sec: 8009.38 - lr: 0.000039 - momentum: 0.000000 | |
| 2023-10-19 20:39:23,420 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 20:39:23,420 EPOCH 3 done: loss 0.3041 - lr: 0.000039 | |
| 2023-10-19 20:39:25,770 DEV : loss 0.20335422456264496 - f1-score (micro avg) 0.4838 | |
| 2023-10-19 20:39:25,784 saving best model | |
| 2023-10-19 20:39:25,818 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 20:39:28,873 epoch 4 - iter 178/1786 - loss 0.28120448 - time (sec): 3.05 - samples/sec: 8065.57 - lr: 0.000038 - momentum: 0.000000 | |
| 2023-10-19 20:39:31,879 epoch 4 - iter 356/1786 - loss 0.28162907 - time (sec): 6.06 - samples/sec: 8160.54 - lr: 0.000038 - momentum: 0.000000 | |
| 2023-10-19 20:39:34,912 epoch 4 - iter 534/1786 - loss 0.26744737 - time (sec): 9.09 - samples/sec: 8154.76 - lr: 0.000037 - momentum: 0.000000 | |
| 2023-10-19 20:39:37,961 epoch 4 - iter 712/1786 - loss 0.26511953 - time (sec): 12.14 - samples/sec: 8148.29 - lr: 0.000037 - momentum: 0.000000 | |
| 2023-10-19 20:39:41,026 epoch 4 - iter 890/1786 - loss 0.26550097 - time (sec): 15.21 - samples/sec: 8141.25 - lr: 0.000036 - momentum: 0.000000 | |
| 2023-10-19 20:39:44,100 epoch 4 - iter 1068/1786 - loss 0.26573746 - time (sec): 18.28 - samples/sec: 8179.43 - lr: 0.000036 - momentum: 0.000000 | |
| 2023-10-19 20:39:47,135 epoch 4 - iter 1246/1786 - loss 0.26849947 - time (sec): 21.32 - samples/sec: 8116.37 - lr: 0.000035 - momentum: 0.000000 | |
| 2023-10-19 20:39:50,221 epoch 4 - iter 1424/1786 - loss 0.26853077 - time (sec): 24.40 - samples/sec: 8134.82 - lr: 0.000034 - momentum: 0.000000 | |
| 2023-10-19 20:39:53,283 epoch 4 - iter 1602/1786 - loss 0.26807341 - time (sec): 27.46 - samples/sec: 8071.04 - lr: 0.000034 - momentum: 0.000000 | |
| 2023-10-19 20:39:56,481 epoch 4 - iter 1780/1786 - loss 0.26526365 - time (sec): 30.66 - samples/sec: 8085.04 - lr: 0.000033 - momentum: 0.000000 | |
| 2023-10-19 20:39:56,581 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 20:39:56,581 EPOCH 4 done: loss 0.2650 - lr: 0.000033 | |
| 2023-10-19 20:39:59,392 DEV : loss 0.1998205929994583 - f1-score (micro avg) 0.4911 | |
| 2023-10-19 20:39:59,406 saving best model | |
| 2023-10-19 20:39:59,441 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 20:40:02,525 epoch 5 - iter 178/1786 - loss 0.22521854 - time (sec): 3.08 - samples/sec: 7905.59 - lr: 0.000033 - momentum: 0.000000 | |
| 2023-10-19 20:40:05,575 epoch 5 - iter 356/1786 - loss 0.23509832 - time (sec): 6.13 - samples/sec: 7930.76 - lr: 0.000032 - momentum: 0.000000 | |
| 2023-10-19 20:40:08,566 epoch 5 - iter 534/1786 - loss 0.23834051 - time (sec): 9.12 - samples/sec: 7997.55 - lr: 0.000032 - momentum: 0.000000 | |
| 2023-10-19 20:40:11,659 epoch 5 - iter 712/1786 - loss 0.23851056 - time (sec): 12.22 - samples/sec: 8049.31 - lr: 0.000031 - momentum: 0.000000 | |
| 2023-10-19 20:40:14,717 epoch 5 - iter 890/1786 - loss 0.24170666 - time (sec): 15.28 - samples/sec: 8111.02 - lr: 0.000031 - momentum: 0.000000 | |
| 2023-10-19 20:40:17,635 epoch 5 - iter 1068/1786 - loss 0.23929066 - time (sec): 18.19 - samples/sec: 8180.01 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-19 20:40:20,743 epoch 5 - iter 1246/1786 - loss 0.24080387 - time (sec): 21.30 - samples/sec: 8140.72 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-19 20:40:23,818 epoch 5 - iter 1424/1786 - loss 0.24269516 - time (sec): 24.38 - samples/sec: 8151.89 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-19 20:40:26,856 epoch 5 - iter 1602/1786 - loss 0.23904279 - time (sec): 27.41 - samples/sec: 8140.69 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-19 20:40:29,905 epoch 5 - iter 1780/1786 - loss 0.23838990 - time (sec): 30.46 - samples/sec: 8138.26 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-19 20:40:30,002 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 20:40:30,002 EPOCH 5 done: loss 0.2383 - lr: 0.000028 | |
| 2023-10-19 20:40:32,346 DEV : loss 0.19193986058235168 - f1-score (micro avg) 0.5141 | |
| 2023-10-19 20:40:32,359 saving best model | |
| 2023-10-19 20:40:32,394 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 20:40:35,541 epoch 6 - iter 178/1786 - loss 0.22022921 - time (sec): 3.15 - samples/sec: 7916.90 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-19 20:40:38,573 epoch 6 - iter 356/1786 - loss 0.22009712 - time (sec): 6.18 - samples/sec: 7793.77 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-19 20:40:41,626 epoch 6 - iter 534/1786 - loss 0.21614358 - time (sec): 9.23 - samples/sec: 7792.40 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-19 20:40:44,653 epoch 6 - iter 712/1786 - loss 0.21370923 - time (sec): 12.26 - samples/sec: 7868.70 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-19 20:40:47,713 epoch 6 - iter 890/1786 - loss 0.21638230 - time (sec): 15.32 - samples/sec: 7875.92 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-19 20:40:50,715 epoch 6 - iter 1068/1786 - loss 0.21880081 - time (sec): 18.32 - samples/sec: 7941.46 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-19 20:40:53,782 epoch 6 - iter 1246/1786 - loss 0.21972606 - time (sec): 21.39 - samples/sec: 7993.42 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-19 20:40:56,910 epoch 6 - iter 1424/1786 - loss 0.22189381 - time (sec): 24.52 - samples/sec: 8039.84 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-19 20:41:00,080 epoch 6 - iter 1602/1786 - loss 0.22127930 - time (sec): 27.69 - samples/sec: 8040.59 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-19 20:41:03,207 epoch 6 - iter 1780/1786 - loss 0.22077708 - time (sec): 30.81 - samples/sec: 8040.50 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-19 20:41:03,326 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 20:41:03,326 EPOCH 6 done: loss 0.2204 - lr: 0.000022 | |
| 2023-10-19 20:41:06,202 DEV : loss 0.18350262939929962 - f1-score (micro avg) 0.536 | |
| 2023-10-19 20:41:06,216 saving best model | |
| 2023-10-19 20:41:06,251 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 20:41:09,203 epoch 7 - iter 178/1786 - loss 0.19164778 - time (sec): 2.95 - samples/sec: 7736.55 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-19 20:41:12,209 epoch 7 - iter 356/1786 - loss 0.20305516 - time (sec): 5.96 - samples/sec: 7908.04 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-19 20:41:15,276 epoch 7 - iter 534/1786 - loss 0.20243257 - time (sec): 9.02 - samples/sec: 8026.84 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-19 20:41:18,401 epoch 7 - iter 712/1786 - loss 0.20043618 - time (sec): 12.15 - samples/sec: 7926.15 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-19 20:41:21,489 epoch 7 - iter 890/1786 - loss 0.19885104 - time (sec): 15.24 - samples/sec: 8005.15 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-19 20:41:24,379 epoch 7 - iter 1068/1786 - loss 0.20114197 - time (sec): 18.13 - samples/sec: 8023.68 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-19 20:41:27,266 epoch 7 - iter 1246/1786 - loss 0.20353714 - time (sec): 21.01 - samples/sec: 8008.93 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-19 20:41:30,473 epoch 7 - iter 1424/1786 - loss 0.20389885 - time (sec): 24.22 - samples/sec: 8134.58 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-19 20:41:33,490 epoch 7 - iter 1602/1786 - loss 0.20418664 - time (sec): 27.24 - samples/sec: 8220.64 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-19 20:41:36,145 epoch 7 - iter 1780/1786 - loss 0.20471845 - time (sec): 29.89 - samples/sec: 8297.20 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-19 20:41:36,243 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 20:41:36,243 EPOCH 7 done: loss 0.2044 - lr: 0.000017 | |
| 2023-10-19 20:41:38,607 DEV : loss 0.18785029649734497 - f1-score (micro avg) 0.5566 | |
| 2023-10-19 20:41:38,621 saving best model | |
| 2023-10-19 20:41:38,656 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 20:41:41,747 epoch 8 - iter 178/1786 - loss 0.17209114 - time (sec): 3.09 - samples/sec: 7635.51 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-19 20:41:44,834 epoch 8 - iter 356/1786 - loss 0.18649148 - time (sec): 6.18 - samples/sec: 8050.90 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-19 20:41:47,770 epoch 8 - iter 534/1786 - loss 0.19257228 - time (sec): 9.11 - samples/sec: 8143.11 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-19 20:41:50,802 epoch 8 - iter 712/1786 - loss 0.18865919 - time (sec): 12.15 - samples/sec: 8159.67 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-19 20:41:53,862 epoch 8 - iter 890/1786 - loss 0.19551212 - time (sec): 15.21 - samples/sec: 8069.21 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-19 20:41:56,869 epoch 8 - iter 1068/1786 - loss 0.19666334 - time (sec): 18.21 - samples/sec: 8097.11 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-19 20:41:59,961 epoch 8 - iter 1246/1786 - loss 0.19544818 - time (sec): 21.30 - samples/sec: 8042.12 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-19 20:42:02,975 epoch 8 - iter 1424/1786 - loss 0.19344021 - time (sec): 24.32 - samples/sec: 8041.95 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-19 20:42:06,103 epoch 8 - iter 1602/1786 - loss 0.19343569 - time (sec): 27.45 - samples/sec: 8117.39 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-19 20:42:09,630 epoch 8 - iter 1780/1786 - loss 0.19218063 - time (sec): 30.97 - samples/sec: 8008.93 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-19 20:42:09,731 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 20:42:09,731 EPOCH 8 done: loss 0.1927 - lr: 0.000011 | |
| 2023-10-19 20:42:12,129 DEV : loss 0.18572503328323364 - f1-score (micro avg) 0.5618 | |
| 2023-10-19 20:42:12,143 saving best model | |
| 2023-10-19 20:42:12,182 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 20:42:15,250 epoch 9 - iter 178/1786 - loss 0.19667861 - time (sec): 3.07 - samples/sec: 7940.55 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-19 20:42:18,298 epoch 9 - iter 356/1786 - loss 0.18488315 - time (sec): 6.12 - samples/sec: 8020.57 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-19 20:42:21,350 epoch 9 - iter 534/1786 - loss 0.18801911 - time (sec): 9.17 - samples/sec: 7986.67 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-19 20:42:24,420 epoch 9 - iter 712/1786 - loss 0.19094468 - time (sec): 12.24 - samples/sec: 8068.42 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-19 20:42:27,582 epoch 9 - iter 890/1786 - loss 0.19203212 - time (sec): 15.40 - samples/sec: 8162.53 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-19 20:42:30,593 epoch 9 - iter 1068/1786 - loss 0.18757669 - time (sec): 18.41 - samples/sec: 8116.35 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-19 20:42:33,700 epoch 9 - iter 1246/1786 - loss 0.18805714 - time (sec): 21.52 - samples/sec: 8113.44 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-19 20:42:36,559 epoch 9 - iter 1424/1786 - loss 0.18712464 - time (sec): 24.38 - samples/sec: 8144.68 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-19 20:42:39,647 epoch 9 - iter 1602/1786 - loss 0.18607916 - time (sec): 27.46 - samples/sec: 8143.69 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-19 20:42:42,752 epoch 9 - iter 1780/1786 - loss 0.18572632 - time (sec): 30.57 - samples/sec: 8108.96 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-19 20:42:42,854 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 20:42:42,854 EPOCH 9 done: loss 0.1856 - lr: 0.000006 | |
| 2023-10-19 20:42:45,252 DEV : loss 0.19007962942123413 - f1-score (micro avg) 0.5685 | |
| 2023-10-19 20:42:45,266 saving best model | |
| 2023-10-19 20:42:45,300 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 20:42:48,484 epoch 10 - iter 178/1786 - loss 0.17314883 - time (sec): 3.18 - samples/sec: 8236.77 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-19 20:42:51,678 epoch 10 - iter 356/1786 - loss 0.17597820 - time (sec): 6.38 - samples/sec: 8122.48 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-19 20:42:54,852 epoch 10 - iter 534/1786 - loss 0.18240659 - time (sec): 9.55 - samples/sec: 8166.07 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-19 20:42:57,846 epoch 10 - iter 712/1786 - loss 0.18381425 - time (sec): 12.54 - samples/sec: 8166.67 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-19 20:43:00,912 epoch 10 - iter 890/1786 - loss 0.18290301 - time (sec): 15.61 - samples/sec: 8151.54 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-19 20:43:04,044 epoch 10 - iter 1068/1786 - loss 0.18308905 - time (sec): 18.74 - samples/sec: 8086.03 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-19 20:43:07,605 epoch 10 - iter 1246/1786 - loss 0.18156946 - time (sec): 22.30 - samples/sec: 7889.83 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-19 20:43:10,669 epoch 10 - iter 1424/1786 - loss 0.18071674 - time (sec): 25.37 - samples/sec: 7877.57 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-19 20:43:13,642 epoch 10 - iter 1602/1786 - loss 0.18145714 - time (sec): 28.34 - samples/sec: 7889.82 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-19 20:43:17,011 epoch 10 - iter 1780/1786 - loss 0.18146549 - time (sec): 31.71 - samples/sec: 7809.46 - lr: 0.000000 - momentum: 0.000000 | |
| 2023-10-19 20:43:17,140 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 20:43:17,140 EPOCH 10 done: loss 0.1815 - lr: 0.000000 | |
| 2023-10-19 20:43:19,536 DEV : loss 0.18993768095970154 - f1-score (micro avg) 0.5632 | |
| 2023-10-19 20:43:19,580 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 20:43:19,580 Loading model from best epoch ... | |
| 2023-10-19 20:43:19,660 SequenceTagger predicts: Dictionary with 17 tags: O, S-PER, B-PER, E-PER, I-PER, S-LOC, B-LOC, E-LOC, I-LOC, S-ORG, B-ORG, E-ORG, I-ORG, S-HumanProd, B-HumanProd, E-HumanProd, I-HumanProd | |
| 2023-10-19 20:43:24,342 | |
| Results: | |
| - F-score (micro) 0.4627 | |
| - F-score (macro) 0.3013 | |
| - Accuracy 0.3107 | |
| By class: | |
| precision recall f1-score support | |
| LOC 0.4447 0.5653 0.4978 1095 | |
| PER 0.4861 0.5346 0.5092 1012 | |
| ORG 0.2215 0.1793 0.1981 357 | |
| HumanProd 0.0000 0.0000 0.0000 33 | |
| micro avg 0.4381 0.4902 0.4627 2497 | |
| macro avg 0.2881 0.3198 0.3013 2497 | |
| weighted avg 0.4237 0.4902 0.4530 2497 | |
| 2023-10-19 20:43:24,342 ---------------------------------------------------------------------------------------------------- | |