| 2023-10-18 22:11:46,686 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 22:11:46,687 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=13, bias=True) | |
| (loss_function): CrossEntropyLoss() | |
| )" | |
| 2023-10-18 22:11:46,687 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 22:11:46,687 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 | |
| 2023-10-18 22:11:46,687 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 22:11:46,687 Train: 5777 sentences | |
| 2023-10-18 22:11:46,687 (train_with_dev=False, train_with_test=False) | |
| 2023-10-18 22:11:46,687 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 22:11:46,687 Training Params: | |
| 2023-10-18 22:11:46,687 - learning_rate: "5e-05" | |
| 2023-10-18 22:11:46,687 - mini_batch_size: "8" | |
| 2023-10-18 22:11:46,687 - max_epochs: "10" | |
| 2023-10-18 22:11:46,687 - shuffle: "True" | |
| 2023-10-18 22:11:46,687 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 22:11:46,687 Plugins: | |
| 2023-10-18 22:11:46,687 - TensorboardLogger | |
| 2023-10-18 22:11:46,687 - LinearScheduler | warmup_fraction: '0.1' | |
| 2023-10-18 22:11:46,687 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 22:11:46,687 Final evaluation on model from best epoch (best-model.pt) | |
| 2023-10-18 22:11:46,687 - metric: "('micro avg', 'f1-score')" | |
| 2023-10-18 22:11:46,687 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 22:11:46,688 Computation: | |
| 2023-10-18 22:11:46,688 - compute on device: cuda:0 | |
| 2023-10-18 22:11:46,688 - embedding storage: none | |
| 2023-10-18 22:11:46,688 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 22:11:46,688 Model training base path: "hmbench-icdar/nl-dbmdz/bert-tiny-historic-multilingual-cased-bs8-wsFalse-e10-lr5e-05-poolingfirst-layers-1-crfFalse-1" | |
| 2023-10-18 22:11:46,688 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 22:11:46,688 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 22:11:46,688 Logging anything other than scalars to TensorBoard is currently not supported. | |
| 2023-10-18 22:11:48,521 epoch 1 - iter 72/723 - loss 3.15369193 - time (sec): 1.83 - samples/sec: 9418.43 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-18 22:11:50,353 epoch 1 - iter 144/723 - loss 2.82531096 - time (sec): 3.66 - samples/sec: 9750.79 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-18 22:11:52,174 epoch 1 - iter 216/723 - loss 2.35058830 - time (sec): 5.49 - samples/sec: 9736.98 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-18 22:11:53,972 epoch 1 - iter 288/723 - loss 1.91572462 - time (sec): 7.28 - samples/sec: 9734.87 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-18 22:11:55,779 epoch 1 - iter 360/723 - loss 1.59356684 - time (sec): 9.09 - samples/sec: 9795.92 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-18 22:11:57,603 epoch 1 - iter 432/723 - loss 1.37380455 - time (sec): 10.91 - samples/sec: 9818.38 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-18 22:11:59,430 epoch 1 - iter 504/723 - loss 1.22307055 - time (sec): 12.74 - samples/sec: 9797.58 - lr: 0.000035 - momentum: 0.000000 | |
| 2023-10-18 22:12:01,273 epoch 1 - iter 576/723 - loss 1.11055697 - time (sec): 14.58 - samples/sec: 9758.58 - lr: 0.000040 - momentum: 0.000000 | |
| 2023-10-18 22:12:03,063 epoch 1 - iter 648/723 - loss 1.02493184 - time (sec): 16.38 - samples/sec: 9685.83 - lr: 0.000045 - momentum: 0.000000 | |
| 2023-10-18 22:12:04,793 epoch 1 - iter 720/723 - loss 0.95066192 - time (sec): 18.11 - samples/sec: 9693.53 - lr: 0.000050 - momentum: 0.000000 | |
| 2023-10-18 22:12:04,877 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 22:12:04,877 EPOCH 1 done: loss 0.9486 - lr: 0.000050 | |
| 2023-10-18 22:12:06,089 DEV : loss 0.31063002347946167 - f1-score (micro avg) 0.0 | |
| 2023-10-18 22:12:06,102 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 22:12:07,989 epoch 2 - iter 72/723 - loss 0.23255061 - time (sec): 1.89 - samples/sec: 9861.83 - lr: 0.000049 - momentum: 0.000000 | |
| 2023-10-18 22:12:09,742 epoch 2 - iter 144/723 - loss 0.23804088 - time (sec): 3.64 - samples/sec: 9834.13 - lr: 0.000049 - momentum: 0.000000 | |
| 2023-10-18 22:12:11,573 epoch 2 - iter 216/723 - loss 0.24106924 - time (sec): 5.47 - samples/sec: 9842.86 - lr: 0.000048 - momentum: 0.000000 | |
| 2023-10-18 22:12:13,330 epoch 2 - iter 288/723 - loss 0.23333713 - time (sec): 7.23 - samples/sec: 9913.68 - lr: 0.000048 - momentum: 0.000000 | |
| 2023-10-18 22:12:15,083 epoch 2 - iter 360/723 - loss 0.22213309 - time (sec): 8.98 - samples/sec: 9890.07 - lr: 0.000047 - momentum: 0.000000 | |
| 2023-10-18 22:12:16,869 epoch 2 - iter 432/723 - loss 0.21724811 - time (sec): 10.77 - samples/sec: 9985.45 - lr: 0.000047 - momentum: 0.000000 | |
| 2023-10-18 22:12:18,591 epoch 2 - iter 504/723 - loss 0.21698959 - time (sec): 12.49 - samples/sec: 9901.44 - lr: 0.000046 - momentum: 0.000000 | |
| 2023-10-18 22:12:20,283 epoch 2 - iter 576/723 - loss 0.21535393 - time (sec): 14.18 - samples/sec: 9886.96 - lr: 0.000046 - momentum: 0.000000 | |
| 2023-10-18 22:12:22,061 epoch 2 - iter 648/723 - loss 0.21374976 - time (sec): 15.96 - samples/sec: 9885.22 - lr: 0.000045 - momentum: 0.000000 | |
| 2023-10-18 22:12:23,798 epoch 2 - iter 720/723 - loss 0.20898244 - time (sec): 17.70 - samples/sec: 9933.82 - lr: 0.000044 - momentum: 0.000000 | |
| 2023-10-18 22:12:23,856 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 22:12:23,856 EPOCH 2 done: loss 0.2092 - lr: 0.000044 | |
| 2023-10-18 22:12:25,964 DEV : loss 0.22788439691066742 - f1-score (micro avg) 0.3239 | |
| 2023-10-18 22:12:25,979 saving best model | |
| 2023-10-18 22:12:26,010 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 22:12:27,797 epoch 3 - iter 72/723 - loss 0.19078244 - time (sec): 1.79 - samples/sec: 10043.51 - lr: 0.000044 - momentum: 0.000000 | |
| 2023-10-18 22:12:29,543 epoch 3 - iter 144/723 - loss 0.19123649 - time (sec): 3.53 - samples/sec: 9837.27 - lr: 0.000043 - momentum: 0.000000 | |
| 2023-10-18 22:12:31,289 epoch 3 - iter 216/723 - loss 0.18622492 - time (sec): 5.28 - samples/sec: 9893.55 - lr: 0.000043 - momentum: 0.000000 | |
| 2023-10-18 22:12:33,145 epoch 3 - iter 288/723 - loss 0.17538802 - time (sec): 7.13 - samples/sec: 9922.72 - lr: 0.000042 - momentum: 0.000000 | |
| 2023-10-18 22:12:34,879 epoch 3 - iter 360/723 - loss 0.17611275 - time (sec): 8.87 - samples/sec: 9917.65 - lr: 0.000042 - momentum: 0.000000 | |
| 2023-10-18 22:12:36,750 epoch 3 - iter 432/723 - loss 0.17600510 - time (sec): 10.74 - samples/sec: 9821.66 - lr: 0.000041 - momentum: 0.000000 | |
| 2023-10-18 22:12:38,475 epoch 3 - iter 504/723 - loss 0.17653894 - time (sec): 12.46 - samples/sec: 9798.39 - lr: 0.000041 - momentum: 0.000000 | |
| 2023-10-18 22:12:40,261 epoch 3 - iter 576/723 - loss 0.17866614 - time (sec): 14.25 - samples/sec: 9817.94 - lr: 0.000040 - momentum: 0.000000 | |
| 2023-10-18 22:12:42,033 epoch 3 - iter 648/723 - loss 0.17625735 - time (sec): 16.02 - samples/sec: 9858.26 - lr: 0.000039 - momentum: 0.000000 | |
| 2023-10-18 22:12:43,814 epoch 3 - iter 720/723 - loss 0.17698859 - time (sec): 17.80 - samples/sec: 9872.51 - lr: 0.000039 - momentum: 0.000000 | |
| 2023-10-18 22:12:43,871 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 22:12:43,871 EPOCH 3 done: loss 0.1768 - lr: 0.000039 | |
| 2023-10-18 22:12:45,631 DEV : loss 0.21366006135940552 - f1-score (micro avg) 0.3814 | |
| 2023-10-18 22:12:45,646 saving best model | |
| 2023-10-18 22:12:45,684 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 22:12:47,421 epoch 4 - iter 72/723 - loss 0.15319449 - time (sec): 1.74 - samples/sec: 10153.35 - lr: 0.000038 - momentum: 0.000000 | |
| 2023-10-18 22:12:49,178 epoch 4 - iter 144/723 - loss 0.15219794 - time (sec): 3.49 - samples/sec: 9871.73 - lr: 0.000038 - momentum: 0.000000 | |
| 2023-10-18 22:12:50,904 epoch 4 - iter 216/723 - loss 0.15958723 - time (sec): 5.22 - samples/sec: 10037.56 - lr: 0.000037 - momentum: 0.000000 | |
| 2023-10-18 22:12:52,729 epoch 4 - iter 288/723 - loss 0.15641675 - time (sec): 7.04 - samples/sec: 10141.55 - lr: 0.000037 - momentum: 0.000000 | |
| 2023-10-18 22:12:54,430 epoch 4 - iter 360/723 - loss 0.15539065 - time (sec): 8.74 - samples/sec: 10131.07 - lr: 0.000036 - momentum: 0.000000 | |
| 2023-10-18 22:12:56,173 epoch 4 - iter 432/723 - loss 0.15963557 - time (sec): 10.49 - samples/sec: 10188.50 - lr: 0.000036 - momentum: 0.000000 | |
| 2023-10-18 22:12:58,321 epoch 4 - iter 504/723 - loss 0.15900354 - time (sec): 12.64 - samples/sec: 9892.63 - lr: 0.000035 - momentum: 0.000000 | |
| 2023-10-18 22:13:00,068 epoch 4 - iter 576/723 - loss 0.15775232 - time (sec): 14.38 - samples/sec: 9897.82 - lr: 0.000034 - momentum: 0.000000 | |
| 2023-10-18 22:13:01,795 epoch 4 - iter 648/723 - loss 0.15793963 - time (sec): 16.11 - samples/sec: 9854.22 - lr: 0.000034 - momentum: 0.000000 | |
| 2023-10-18 22:13:03,655 epoch 4 - iter 720/723 - loss 0.16172244 - time (sec): 17.97 - samples/sec: 9776.09 - lr: 0.000033 - momentum: 0.000000 | |
| 2023-10-18 22:13:03,711 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 22:13:03,711 EPOCH 4 done: loss 0.1617 - lr: 0.000033 | |
| 2023-10-18 22:13:05,482 DEV : loss 0.19289655983448029 - f1-score (micro avg) 0.4815 | |
| 2023-10-18 22:13:05,497 saving best model | |
| 2023-10-18 22:13:05,533 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 22:13:07,441 epoch 5 - iter 72/723 - loss 0.16811055 - time (sec): 1.91 - samples/sec: 9536.49 - lr: 0.000033 - momentum: 0.000000 | |
| 2023-10-18 22:13:09,201 epoch 5 - iter 144/723 - loss 0.15925998 - time (sec): 3.67 - samples/sec: 9799.25 - lr: 0.000032 - momentum: 0.000000 | |
| 2023-10-18 22:13:10,943 epoch 5 - iter 216/723 - loss 0.15623823 - time (sec): 5.41 - samples/sec: 9557.30 - lr: 0.000032 - momentum: 0.000000 | |
| 2023-10-18 22:13:12,686 epoch 5 - iter 288/723 - loss 0.15588053 - time (sec): 7.15 - samples/sec: 9547.60 - lr: 0.000031 - momentum: 0.000000 | |
| 2023-10-18 22:13:14,425 epoch 5 - iter 360/723 - loss 0.15281731 - time (sec): 8.89 - samples/sec: 9559.96 - lr: 0.000031 - momentum: 0.000000 | |
| 2023-10-18 22:13:16,265 epoch 5 - iter 432/723 - loss 0.15073615 - time (sec): 10.73 - samples/sec: 9668.65 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-18 22:13:17,926 epoch 5 - iter 504/723 - loss 0.14950718 - time (sec): 12.39 - samples/sec: 9809.91 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-18 22:13:19,596 epoch 5 - iter 576/723 - loss 0.14885470 - time (sec): 14.06 - samples/sec: 9898.68 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-18 22:13:21,379 epoch 5 - iter 648/723 - loss 0.15131920 - time (sec): 15.84 - samples/sec: 9902.45 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-18 22:13:23,193 epoch 5 - iter 720/723 - loss 0.15022435 - time (sec): 17.66 - samples/sec: 9943.96 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-18 22:13:23,253 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 22:13:23,253 EPOCH 5 done: loss 0.1504 - lr: 0.000028 | |
| 2023-10-18 22:13:25,007 DEV : loss 0.1961345225572586 - f1-score (micro avg) 0.4696 | |
| 2023-10-18 22:13:25,022 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 22:13:26,804 epoch 6 - iter 72/723 - loss 0.13617864 - time (sec): 1.78 - samples/sec: 9559.29 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-18 22:13:28,589 epoch 6 - iter 144/723 - loss 0.14005984 - time (sec): 3.57 - samples/sec: 9628.21 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-18 22:13:30,437 epoch 6 - iter 216/723 - loss 0.15059229 - time (sec): 5.42 - samples/sec: 9626.66 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-18 22:13:32,163 epoch 6 - iter 288/723 - loss 0.15216103 - time (sec): 7.14 - samples/sec: 9579.75 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-18 22:13:34,396 epoch 6 - iter 360/723 - loss 0.14557675 - time (sec): 9.37 - samples/sec: 9231.32 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-18 22:13:36,183 epoch 6 - iter 432/723 - loss 0.14252551 - time (sec): 11.16 - samples/sec: 9279.64 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-18 22:13:37,996 epoch 6 - iter 504/723 - loss 0.14416986 - time (sec): 12.97 - samples/sec: 9456.22 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-18 22:13:39,763 epoch 6 - iter 576/723 - loss 0.14274090 - time (sec): 14.74 - samples/sec: 9548.14 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-18 22:13:41,578 epoch 6 - iter 648/723 - loss 0.14378379 - time (sec): 16.56 - samples/sec: 9609.62 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-18 22:13:43,291 epoch 6 - iter 720/723 - loss 0.14185352 - time (sec): 18.27 - samples/sec: 9606.77 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-18 22:13:43,355 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 22:13:43,356 EPOCH 6 done: loss 0.1414 - lr: 0.000022 | |
| 2023-10-18 22:13:45,122 DEV : loss 0.19116047024726868 - f1-score (micro avg) 0.4857 | |
| 2023-10-18 22:13:45,137 saving best model | |
| 2023-10-18 22:13:45,174 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 22:13:46,912 epoch 7 - iter 72/723 - loss 0.13529263 - time (sec): 1.74 - samples/sec: 9722.45 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-18 22:13:48,713 epoch 7 - iter 144/723 - loss 0.13613335 - time (sec): 3.54 - samples/sec: 9958.96 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-18 22:13:50,482 epoch 7 - iter 216/723 - loss 0.13441868 - time (sec): 5.31 - samples/sec: 9917.67 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-18 22:13:52,251 epoch 7 - iter 288/723 - loss 0.13760997 - time (sec): 7.08 - samples/sec: 9848.22 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-18 22:13:53,993 epoch 7 - iter 360/723 - loss 0.13573573 - time (sec): 8.82 - samples/sec: 9819.71 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-18 22:13:55,820 epoch 7 - iter 432/723 - loss 0.13560010 - time (sec): 10.65 - samples/sec: 9890.16 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-18 22:13:57,634 epoch 7 - iter 504/723 - loss 0.13364674 - time (sec): 12.46 - samples/sec: 9840.57 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-18 22:13:59,388 epoch 7 - iter 576/723 - loss 0.13450202 - time (sec): 14.21 - samples/sec: 9772.70 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-18 22:14:01,207 epoch 7 - iter 648/723 - loss 0.13529263 - time (sec): 16.03 - samples/sec: 9801.38 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-18 22:14:03,065 epoch 7 - iter 720/723 - loss 0.13363141 - time (sec): 17.89 - samples/sec: 9814.24 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-18 22:14:03,126 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 22:14:03,127 EPOCH 7 done: loss 0.1334 - lr: 0.000017 | |
| 2023-10-18 22:14:04,891 DEV : loss 0.1891321837902069 - f1-score (micro avg) 0.4815 | |
| 2023-10-18 22:14:04,906 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 22:14:06,635 epoch 8 - iter 72/723 - loss 0.12504995 - time (sec): 1.73 - samples/sec: 9327.36 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-18 22:14:08,831 epoch 8 - iter 144/723 - loss 0.14497774 - time (sec): 3.92 - samples/sec: 8703.68 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-18 22:14:10,623 epoch 8 - iter 216/723 - loss 0.13421076 - time (sec): 5.72 - samples/sec: 9270.31 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-18 22:14:12,411 epoch 8 - iter 288/723 - loss 0.12980263 - time (sec): 7.50 - samples/sec: 9387.38 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-18 22:14:14,168 epoch 8 - iter 360/723 - loss 0.12913939 - time (sec): 9.26 - samples/sec: 9523.64 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-18 22:14:16,043 epoch 8 - iter 432/723 - loss 0.12544526 - time (sec): 11.14 - samples/sec: 9576.42 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-18 22:14:17,799 epoch 8 - iter 504/723 - loss 0.12520676 - time (sec): 12.89 - samples/sec: 9556.09 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-18 22:14:19,682 epoch 8 - iter 576/723 - loss 0.12476139 - time (sec): 14.78 - samples/sec: 9558.26 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-18 22:14:21,488 epoch 8 - iter 648/723 - loss 0.12586790 - time (sec): 16.58 - samples/sec: 9535.81 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-18 22:14:23,247 epoch 8 - iter 720/723 - loss 0.12811874 - time (sec): 18.34 - samples/sec: 9586.01 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-18 22:14:23,303 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 22:14:23,303 EPOCH 8 done: loss 0.1279 - lr: 0.000011 | |
| 2023-10-18 22:14:25,072 DEV : loss 0.18201254308223724 - f1-score (micro avg) 0.5072 | |
| 2023-10-18 22:14:25,087 saving best model | |
| 2023-10-18 22:14:25,123 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 22:14:26,935 epoch 9 - iter 72/723 - loss 0.11411652 - time (sec): 1.81 - samples/sec: 10766.66 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-18 22:14:28,686 epoch 9 - iter 144/723 - loss 0.10939075 - time (sec): 3.56 - samples/sec: 10321.51 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-18 22:14:30,443 epoch 9 - iter 216/723 - loss 0.11384251 - time (sec): 5.32 - samples/sec: 10057.20 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-18 22:14:32,214 epoch 9 - iter 288/723 - loss 0.11951860 - time (sec): 7.09 - samples/sec: 9978.23 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-18 22:14:34,027 epoch 9 - iter 360/723 - loss 0.12179869 - time (sec): 8.90 - samples/sec: 9931.67 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-18 22:14:35,758 epoch 9 - iter 432/723 - loss 0.12431945 - time (sec): 10.63 - samples/sec: 9850.04 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-18 22:14:37,499 epoch 9 - iter 504/723 - loss 0.12584957 - time (sec): 12.38 - samples/sec: 9780.76 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-18 22:14:39,356 epoch 9 - iter 576/723 - loss 0.12515093 - time (sec): 14.23 - samples/sec: 9893.29 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-18 22:14:41,122 epoch 9 - iter 648/723 - loss 0.12556555 - time (sec): 16.00 - samples/sec: 9903.79 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-18 22:14:42,893 epoch 9 - iter 720/723 - loss 0.12475240 - time (sec): 17.77 - samples/sec: 9882.46 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-18 22:14:42,962 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 22:14:42,962 EPOCH 9 done: loss 0.1247 - lr: 0.000006 | |
| 2023-10-18 22:14:45,097 DEV : loss 0.1882598102092743 - f1-score (micro avg) 0.4959 | |
| 2023-10-18 22:14:45,112 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 22:14:46,869 epoch 10 - iter 72/723 - loss 0.10866994 - time (sec): 1.76 - samples/sec: 9731.03 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-18 22:14:48,671 epoch 10 - iter 144/723 - loss 0.12562583 - time (sec): 3.56 - samples/sec: 9529.64 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-18 22:14:50,455 epoch 10 - iter 216/723 - loss 0.12325727 - time (sec): 5.34 - samples/sec: 9768.34 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-18 22:14:52,279 epoch 10 - iter 288/723 - loss 0.12513734 - time (sec): 7.17 - samples/sec: 9689.81 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-18 22:14:54,208 epoch 10 - iter 360/723 - loss 0.13109443 - time (sec): 9.10 - samples/sec: 9713.73 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-18 22:14:55,958 epoch 10 - iter 432/723 - loss 0.12975067 - time (sec): 10.85 - samples/sec: 9720.21 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-18 22:14:57,713 epoch 10 - iter 504/723 - loss 0.12653515 - time (sec): 12.60 - samples/sec: 9811.00 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-18 22:14:59,552 epoch 10 - iter 576/723 - loss 0.12518131 - time (sec): 14.44 - samples/sec: 9762.73 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-18 22:15:01,283 epoch 10 - iter 648/723 - loss 0.12318594 - time (sec): 16.17 - samples/sec: 9754.98 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-18 22:15:03,005 epoch 10 - iter 720/723 - loss 0.12424305 - time (sec): 17.89 - samples/sec: 9814.44 - lr: 0.000000 - momentum: 0.000000 | |
| 2023-10-18 22:15:03,068 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 22:15:03,068 EPOCH 10 done: loss 0.1244 - lr: 0.000000 | |
| 2023-10-18 22:15:04,871 DEV : loss 0.1862431764602661 - f1-score (micro avg) 0.4991 | |
| 2023-10-18 22:15:04,918 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 22:15:04,918 Loading model from best epoch ... | |
| 2023-10-18 22:15:05,001 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 | |
| 2023-10-18 22:15:06,339 | |
| Results: | |
| - F-score (micro) 0.5138 | |
| - F-score (macro) 0.3616 | |
| - Accuracy 0.3566 | |
| By class: | |
| precision recall f1-score support | |
| LOC 0.5583 0.6485 0.6000 458 | |
| PER 0.4975 0.4212 0.4562 482 | |
| ORG 1.0000 0.0145 0.0286 69 | |
| micro avg 0.5324 0.4965 0.5138 1009 | |
| macro avg 0.6853 0.3614 0.3616 1009 | |
| weighted avg 0.5595 0.4965 0.4922 1009 | |
| 2023-10-18 22:15:06,339 ---------------------------------------------------------------------------------------------------- | |