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2023-10-17 08:54:26,109 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 08:54:26,111 Model: "SequenceTagger( |
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(embeddings): TransformerWordEmbeddings( |
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(model): ElectraModel( |
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(embeddings): ElectraEmbeddings( |
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(word_embeddings): Embedding(32001, 768) |
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(position_embeddings): Embedding(512, 768) |
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(token_type_embeddings): Embedding(2, 768) |
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(LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True) |
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(dropout): Dropout(p=0.1, inplace=False) |
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) |
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(encoder): ElectraEncoder( |
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(layer): ModuleList( |
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(0-11): 12 x ElectraLayer( |
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(attention): ElectraAttention( |
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(self): ElectraSelfAttention( |
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(query): Linear(in_features=768, out_features=768, bias=True) |
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(key): Linear(in_features=768, out_features=768, bias=True) |
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(value): Linear(in_features=768, out_features=768, bias=True) |
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(dropout): Dropout(p=0.1, inplace=False) |
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) |
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(output): ElectraSelfOutput( |
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(dense): Linear(in_features=768, out_features=768, bias=True) |
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(LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True) |
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(dropout): Dropout(p=0.1, inplace=False) |
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) |
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) |
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(intermediate): ElectraIntermediate( |
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(dense): Linear(in_features=768, out_features=3072, bias=True) |
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(intermediate_act_fn): GELUActivation() |
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) |
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(output): ElectraOutput( |
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(dense): Linear(in_features=3072, out_features=768, bias=True) |
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(LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True) |
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(dropout): Dropout(p=0.1, inplace=False) |
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) |
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) |
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) |
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) |
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) |
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) |
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(locked_dropout): LockedDropout(p=0.5) |
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(linear): Linear(in_features=768, out_features=13, bias=True) |
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(loss_function): CrossEntropyLoss() |
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)" |
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2023-10-17 08:54:26,111 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 08:54:26,112 MultiCorpus: 6183 train + 680 dev + 2113 test sentences |
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- NER_HIPE_2022 Corpus: 6183 train + 680 dev + 2113 test sentences - /root/.flair/datasets/ner_hipe_2022/v2.1/topres19th/en/with_doc_seperator |
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2023-10-17 08:54:26,112 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 08:54:26,112 Train: 6183 sentences |
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2023-10-17 08:54:26,112 (train_with_dev=False, train_with_test=False) |
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2023-10-17 08:54:26,112 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 08:54:26,112 Training Params: |
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2023-10-17 08:54:26,112 - learning_rate: "3e-05" |
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2023-10-17 08:54:26,112 - mini_batch_size: "4" |
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2023-10-17 08:54:26,112 - max_epochs: "10" |
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2023-10-17 08:54:26,112 - shuffle: "True" |
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2023-10-17 08:54:26,112 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 08:54:26,112 Plugins: |
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2023-10-17 08:54:26,112 - TensorboardLogger |
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2023-10-17 08:54:26,112 - LinearScheduler | warmup_fraction: '0.1' |
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2023-10-17 08:54:26,113 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 08:54:26,113 Final evaluation on model from best epoch (best-model.pt) |
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2023-10-17 08:54:26,113 - metric: "('micro avg', 'f1-score')" |
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2023-10-17 08:54:26,113 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 08:54:26,113 Computation: |
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2023-10-17 08:54:26,113 - compute on device: cuda:0 |
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2023-10-17 08:54:26,113 - embedding storage: none |
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2023-10-17 08:54:26,113 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 08:54:26,113 Model training base path: "hmbench-topres19th/en-hmteams/teams-base-historic-multilingual-discriminator-bs4-wsFalse-e10-lr3e-05-poolingfirst-layers-1-crfFalse-1" |
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2023-10-17 08:54:26,113 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 08:54:26,113 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 08:54:26,113 Logging anything other than scalars to TensorBoard is currently not supported. |
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2023-10-17 08:54:38,761 epoch 1 - iter 154/1546 - loss 2.03813618 - time (sec): 12.65 - samples/sec: 1016.55 - lr: 0.000003 - momentum: 0.000000 |
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2023-10-17 08:54:50,424 epoch 1 - iter 308/1546 - loss 1.16576737 - time (sec): 24.31 - samples/sec: 1031.97 - lr: 0.000006 - momentum: 0.000000 |
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2023-10-17 08:55:01,974 epoch 1 - iter 462/1546 - loss 0.82780908 - time (sec): 35.86 - samples/sec: 1043.52 - lr: 0.000009 - momentum: 0.000000 |
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2023-10-17 08:55:13,456 epoch 1 - iter 616/1546 - loss 0.64844751 - time (sec): 47.34 - samples/sec: 1064.97 - lr: 0.000012 - momentum: 0.000000 |
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2023-10-17 08:55:26,298 epoch 1 - iter 770/1546 - loss 0.54447510 - time (sec): 60.18 - samples/sec: 1040.86 - lr: 0.000015 - momentum: 0.000000 |
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2023-10-17 08:55:38,367 epoch 1 - iter 924/1546 - loss 0.47295779 - time (sec): 72.25 - samples/sec: 1037.01 - lr: 0.000018 - momentum: 0.000000 |
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2023-10-17 08:55:50,285 epoch 1 - iter 1078/1546 - loss 0.43087146 - time (sec): 84.17 - samples/sec: 1030.26 - lr: 0.000021 - momentum: 0.000000 |
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2023-10-17 08:56:01,700 epoch 1 - iter 1232/1546 - loss 0.39626057 - time (sec): 95.59 - samples/sec: 1033.71 - lr: 0.000024 - momentum: 0.000000 |
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2023-10-17 08:56:13,219 epoch 1 - iter 1386/1546 - loss 0.36195701 - time (sec): 107.10 - samples/sec: 1041.77 - lr: 0.000027 - momentum: 0.000000 |
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2023-10-17 08:56:25,365 epoch 1 - iter 1540/1546 - loss 0.33627435 - time (sec): 119.25 - samples/sec: 1039.81 - lr: 0.000030 - momentum: 0.000000 |
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2023-10-17 08:56:25,820 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 08:56:25,821 EPOCH 1 done: loss 0.3357 - lr: 0.000030 |
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2023-10-17 08:56:28,051 DEV : loss 0.06119954213500023 - f1-score (micro avg) 0.7417 |
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2023-10-17 08:56:28,079 saving best model |
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2023-10-17 08:56:28,614 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 08:56:40,142 epoch 2 - iter 154/1546 - loss 0.10453700 - time (sec): 11.53 - samples/sec: 1025.22 - lr: 0.000030 - momentum: 0.000000 |
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2023-10-17 08:56:52,687 epoch 2 - iter 308/1546 - loss 0.08704820 - time (sec): 24.07 - samples/sec: 1003.63 - lr: 0.000029 - momentum: 0.000000 |
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2023-10-17 08:57:05,545 epoch 2 - iter 462/1546 - loss 0.08423983 - time (sec): 36.93 - samples/sec: 1020.87 - lr: 0.000029 - momentum: 0.000000 |
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2023-10-17 08:57:17,766 epoch 2 - iter 616/1546 - loss 0.08543159 - time (sec): 49.15 - samples/sec: 1019.96 - lr: 0.000029 - momentum: 0.000000 |
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2023-10-17 08:57:30,051 epoch 2 - iter 770/1546 - loss 0.08700069 - time (sec): 61.43 - samples/sec: 1021.39 - lr: 0.000028 - momentum: 0.000000 |
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2023-10-17 08:57:42,483 epoch 2 - iter 924/1546 - loss 0.08706791 - time (sec): 73.87 - samples/sec: 1014.33 - lr: 0.000028 - momentum: 0.000000 |
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2023-10-17 08:57:55,337 epoch 2 - iter 1078/1546 - loss 0.08512417 - time (sec): 86.72 - samples/sec: 1008.52 - lr: 0.000028 - momentum: 0.000000 |
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2023-10-17 08:58:07,949 epoch 2 - iter 1232/1546 - loss 0.08386350 - time (sec): 99.33 - samples/sec: 1012.09 - lr: 0.000027 - momentum: 0.000000 |
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2023-10-17 08:58:20,787 epoch 2 - iter 1386/1546 - loss 0.08241631 - time (sec): 112.17 - samples/sec: 1000.28 - lr: 0.000027 - momentum: 0.000000 |
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2023-10-17 08:58:32,838 epoch 2 - iter 1540/1546 - loss 0.08294873 - time (sec): 124.22 - samples/sec: 998.40 - lr: 0.000027 - momentum: 0.000000 |
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2023-10-17 08:58:33,293 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 08:58:33,293 EPOCH 2 done: loss 0.0831 - lr: 0.000027 |
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2023-10-17 08:58:36,749 DEV : loss 0.06554654985666275 - f1-score (micro avg) 0.7308 |
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2023-10-17 08:58:36,779 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 08:58:48,693 epoch 3 - iter 154/1546 - loss 0.05336694 - time (sec): 11.91 - samples/sec: 981.36 - lr: 0.000026 - momentum: 0.000000 |
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2023-10-17 08:59:01,019 epoch 3 - iter 308/1546 - loss 0.05246151 - time (sec): 24.24 - samples/sec: 1024.44 - lr: 0.000026 - momentum: 0.000000 |
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2023-10-17 08:59:13,098 epoch 3 - iter 462/1546 - loss 0.04970324 - time (sec): 36.32 - samples/sec: 1051.46 - lr: 0.000026 - momentum: 0.000000 |
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2023-10-17 08:59:25,184 epoch 3 - iter 616/1546 - loss 0.04604475 - time (sec): 48.40 - samples/sec: 1045.28 - lr: 0.000025 - momentum: 0.000000 |
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2023-10-17 08:59:37,027 epoch 3 - iter 770/1546 - loss 0.04734557 - time (sec): 60.25 - samples/sec: 1036.50 - lr: 0.000025 - momentum: 0.000000 |
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2023-10-17 08:59:48,854 epoch 3 - iter 924/1546 - loss 0.04896834 - time (sec): 72.07 - samples/sec: 1041.64 - lr: 0.000025 - momentum: 0.000000 |
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2023-10-17 09:00:00,733 epoch 3 - iter 1078/1546 - loss 0.05098204 - time (sec): 83.95 - samples/sec: 1038.22 - lr: 0.000024 - momentum: 0.000000 |
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2023-10-17 09:00:13,133 epoch 3 - iter 1232/1546 - loss 0.05011942 - time (sec): 96.35 - samples/sec: 1032.97 - lr: 0.000024 - momentum: 0.000000 |
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2023-10-17 09:00:25,611 epoch 3 - iter 1386/1546 - loss 0.05242302 - time (sec): 108.83 - samples/sec: 1013.79 - lr: 0.000024 - momentum: 0.000000 |
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2023-10-17 09:00:37,699 epoch 3 - iter 1540/1546 - loss 0.05287108 - time (sec): 120.92 - samples/sec: 1024.65 - lr: 0.000023 - momentum: 0.000000 |
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2023-10-17 09:00:38,164 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 09:00:38,164 EPOCH 3 done: loss 0.0528 - lr: 0.000023 |
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2023-10-17 09:00:41,078 DEV : loss 0.06000832840800285 - f1-score (micro avg) 0.8048 |
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2023-10-17 09:00:41,106 saving best model |
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2023-10-17 09:00:42,500 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 09:00:54,331 epoch 4 - iter 154/1546 - loss 0.03629651 - time (sec): 11.83 - samples/sec: 1087.02 - lr: 0.000023 - momentum: 0.000000 |
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2023-10-17 09:01:06,052 epoch 4 - iter 308/1546 - loss 0.03234710 - time (sec): 23.55 - samples/sec: 1041.51 - lr: 0.000023 - momentum: 0.000000 |
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2023-10-17 09:01:18,027 epoch 4 - iter 462/1546 - loss 0.03335157 - time (sec): 35.52 - samples/sec: 1056.04 - lr: 0.000022 - momentum: 0.000000 |
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2023-10-17 09:01:30,170 epoch 4 - iter 616/1546 - loss 0.03256761 - time (sec): 47.67 - samples/sec: 1049.02 - lr: 0.000022 - momentum: 0.000000 |
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2023-10-17 09:01:42,048 epoch 4 - iter 770/1546 - loss 0.03247698 - time (sec): 59.54 - samples/sec: 1048.24 - lr: 0.000022 - momentum: 0.000000 |
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2023-10-17 09:01:53,943 epoch 4 - iter 924/1546 - loss 0.03387399 - time (sec): 71.44 - samples/sec: 1054.17 - lr: 0.000021 - momentum: 0.000000 |
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2023-10-17 09:02:05,990 epoch 4 - iter 1078/1546 - loss 0.03389742 - time (sec): 83.49 - samples/sec: 1054.23 - lr: 0.000021 - momentum: 0.000000 |
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2023-10-17 09:02:17,845 epoch 4 - iter 1232/1546 - loss 0.03395574 - time (sec): 95.34 - samples/sec: 1045.74 - lr: 0.000021 - momentum: 0.000000 |
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2023-10-17 09:02:29,692 epoch 4 - iter 1386/1546 - loss 0.03458275 - time (sec): 107.19 - samples/sec: 1040.29 - lr: 0.000020 - momentum: 0.000000 |
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2023-10-17 09:02:41,652 epoch 4 - iter 1540/1546 - loss 0.03469566 - time (sec): 119.15 - samples/sec: 1040.31 - lr: 0.000020 - momentum: 0.000000 |
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2023-10-17 09:02:42,104 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 09:02:42,104 EPOCH 4 done: loss 0.0350 - lr: 0.000020 |
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2023-10-17 09:02:44,928 DEV : loss 0.08604831993579865 - f1-score (micro avg) 0.7776 |
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2023-10-17 09:02:44,958 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 09:02:57,022 epoch 5 - iter 154/1546 - loss 0.02284007 - time (sec): 12.06 - samples/sec: 983.65 - lr: 0.000020 - momentum: 0.000000 |
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2023-10-17 09:03:09,189 epoch 5 - iter 308/1546 - loss 0.01803104 - time (sec): 24.23 - samples/sec: 1002.50 - lr: 0.000019 - momentum: 0.000000 |
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2023-10-17 09:03:21,262 epoch 5 - iter 462/1546 - loss 0.01912710 - time (sec): 36.30 - samples/sec: 996.31 - lr: 0.000019 - momentum: 0.000000 |
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2023-10-17 09:03:33,353 epoch 5 - iter 616/1546 - loss 0.01989178 - time (sec): 48.39 - samples/sec: 1000.35 - lr: 0.000019 - momentum: 0.000000 |
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2023-10-17 09:03:45,469 epoch 5 - iter 770/1546 - loss 0.02252057 - time (sec): 60.51 - samples/sec: 1014.50 - lr: 0.000018 - momentum: 0.000000 |
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2023-10-17 09:03:57,436 epoch 5 - iter 924/1546 - loss 0.02304384 - time (sec): 72.48 - samples/sec: 1021.05 - lr: 0.000018 - momentum: 0.000000 |
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2023-10-17 09:04:09,542 epoch 5 - iter 1078/1546 - loss 0.02187336 - time (sec): 84.58 - samples/sec: 1022.70 - lr: 0.000018 - momentum: 0.000000 |
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2023-10-17 09:04:21,529 epoch 5 - iter 1232/1546 - loss 0.02255478 - time (sec): 96.57 - samples/sec: 1021.76 - lr: 0.000017 - momentum: 0.000000 |
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2023-10-17 09:04:33,945 epoch 5 - iter 1386/1546 - loss 0.02290087 - time (sec): 108.98 - samples/sec: 1026.82 - lr: 0.000017 - momentum: 0.000000 |
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2023-10-17 09:04:46,517 epoch 5 - iter 1540/1546 - loss 0.02398018 - time (sec): 121.56 - samples/sec: 1018.04 - lr: 0.000017 - momentum: 0.000000 |
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2023-10-17 09:04:47,010 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 09:04:47,010 EPOCH 5 done: loss 0.0242 - lr: 0.000017 |
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2023-10-17 09:04:50,104 DEV : loss 0.09960237890481949 - f1-score (micro avg) 0.7876 |
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2023-10-17 09:04:50,137 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 09:05:02,656 epoch 6 - iter 154/1546 - loss 0.01677459 - time (sec): 12.52 - samples/sec: 1024.75 - lr: 0.000016 - momentum: 0.000000 |
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2023-10-17 09:05:14,857 epoch 6 - iter 308/1546 - loss 0.01372105 - time (sec): 24.72 - samples/sec: 1041.31 - lr: 0.000016 - momentum: 0.000000 |
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2023-10-17 09:05:27,217 epoch 6 - iter 462/1546 - loss 0.01421126 - time (sec): 37.08 - samples/sec: 1025.57 - lr: 0.000016 - momentum: 0.000000 |
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2023-10-17 09:05:39,731 epoch 6 - iter 616/1546 - loss 0.01600038 - time (sec): 49.59 - samples/sec: 1019.56 - lr: 0.000015 - momentum: 0.000000 |
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2023-10-17 09:05:52,141 epoch 6 - iter 770/1546 - loss 0.01705876 - time (sec): 62.00 - samples/sec: 1024.70 - lr: 0.000015 - momentum: 0.000000 |
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2023-10-17 09:06:04,991 epoch 6 - iter 924/1546 - loss 0.01729932 - time (sec): 74.85 - samples/sec: 1003.82 - lr: 0.000015 - momentum: 0.000000 |
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2023-10-17 09:06:17,860 epoch 6 - iter 1078/1546 - loss 0.01687148 - time (sec): 87.72 - samples/sec: 990.68 - lr: 0.000014 - momentum: 0.000000 |
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2023-10-17 09:06:30,814 epoch 6 - iter 1232/1546 - loss 0.01640763 - time (sec): 100.67 - samples/sec: 980.55 - lr: 0.000014 - momentum: 0.000000 |
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2023-10-17 09:06:44,004 epoch 6 - iter 1386/1546 - loss 0.01674242 - time (sec): 113.86 - samples/sec: 978.03 - lr: 0.000014 - momentum: 0.000000 |
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2023-10-17 09:06:57,512 epoch 6 - iter 1540/1546 - loss 0.01702449 - time (sec): 127.37 - samples/sec: 972.60 - lr: 0.000013 - momentum: 0.000000 |
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2023-10-17 09:06:58,036 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 09:06:58,037 EPOCH 6 done: loss 0.0170 - lr: 0.000013 |
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2023-10-17 09:07:00,854 DEV : loss 0.09961654990911484 - f1-score (micro avg) 0.7976 |
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2023-10-17 09:07:00,882 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 09:07:14,298 epoch 7 - iter 154/1546 - loss 0.00495503 - time (sec): 13.41 - samples/sec: 873.42 - lr: 0.000013 - momentum: 0.000000 |
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2023-10-17 09:07:26,536 epoch 7 - iter 308/1546 - loss 0.01087828 - time (sec): 25.65 - samples/sec: 925.23 - lr: 0.000013 - momentum: 0.000000 |
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2023-10-17 09:07:38,433 epoch 7 - iter 462/1546 - loss 0.01334889 - time (sec): 37.55 - samples/sec: 964.89 - lr: 0.000012 - momentum: 0.000000 |
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2023-10-17 09:07:50,256 epoch 7 - iter 616/1546 - loss 0.01321695 - time (sec): 49.37 - samples/sec: 991.28 - lr: 0.000012 - momentum: 0.000000 |
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2023-10-17 09:08:01,813 epoch 7 - iter 770/1546 - loss 0.01313843 - time (sec): 60.93 - samples/sec: 1010.71 - lr: 0.000012 - momentum: 0.000000 |
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2023-10-17 09:08:13,352 epoch 7 - iter 924/1546 - loss 0.01154668 - time (sec): 72.47 - samples/sec: 1020.16 - lr: 0.000011 - momentum: 0.000000 |
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2023-10-17 09:08:24,980 epoch 7 - iter 1078/1546 - loss 0.01103876 - time (sec): 84.10 - samples/sec: 1022.36 - lr: 0.000011 - momentum: 0.000000 |
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2023-10-17 09:08:36,738 epoch 7 - iter 1232/1546 - loss 0.01096499 - time (sec): 95.85 - samples/sec: 1033.68 - lr: 0.000011 - momentum: 0.000000 |
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2023-10-17 09:08:48,467 epoch 7 - iter 1386/1546 - loss 0.01135222 - time (sec): 107.58 - samples/sec: 1039.84 - lr: 0.000010 - momentum: 0.000000 |
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2023-10-17 09:09:01,265 epoch 7 - iter 1540/1546 - loss 0.01229847 - time (sec): 120.38 - samples/sec: 1027.48 - lr: 0.000010 - momentum: 0.000000 |
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2023-10-17 09:09:01,773 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 09:09:01,774 EPOCH 7 done: loss 0.0122 - lr: 0.000010 |
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2023-10-17 09:09:04,924 DEV : loss 0.10686086863279343 - f1-score (micro avg) 0.8068 |
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2023-10-17 09:09:04,958 saving best model |
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2023-10-17 09:09:06,388 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 09:09:18,894 epoch 8 - iter 154/1546 - loss 0.00730795 - time (sec): 12.50 - samples/sec: 990.35 - lr: 0.000010 - momentum: 0.000000 |
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2023-10-17 09:09:31,198 epoch 8 - iter 308/1546 - loss 0.00668288 - time (sec): 24.80 - samples/sec: 1018.51 - lr: 0.000009 - momentum: 0.000000 |
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2023-10-17 09:09:43,852 epoch 8 - iter 462/1546 - loss 0.00776588 - time (sec): 37.46 - samples/sec: 997.70 - lr: 0.000009 - momentum: 0.000000 |
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2023-10-17 09:09:56,384 epoch 8 - iter 616/1546 - loss 0.00746374 - time (sec): 49.99 - samples/sec: 990.02 - lr: 0.000009 - momentum: 0.000000 |
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2023-10-17 09:10:08,876 epoch 8 - iter 770/1546 - loss 0.00675501 - time (sec): 62.48 - samples/sec: 984.51 - lr: 0.000008 - momentum: 0.000000 |
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2023-10-17 09:10:21,661 epoch 8 - iter 924/1546 - loss 0.00715765 - time (sec): 75.27 - samples/sec: 991.92 - lr: 0.000008 - momentum: 0.000000 |
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2023-10-17 09:10:34,171 epoch 8 - iter 1078/1546 - loss 0.00694728 - time (sec): 87.78 - samples/sec: 998.22 - lr: 0.000008 - momentum: 0.000000 |
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2023-10-17 09:10:46,699 epoch 8 - iter 1232/1546 - loss 0.00699978 - time (sec): 100.30 - samples/sec: 991.84 - lr: 0.000007 - momentum: 0.000000 |
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2023-10-17 09:10:58,637 epoch 8 - iter 1386/1546 - loss 0.00720570 - time (sec): 112.24 - samples/sec: 988.67 - lr: 0.000007 - momentum: 0.000000 |
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2023-10-17 09:11:10,512 epoch 8 - iter 1540/1546 - loss 0.00770745 - time (sec): 124.12 - samples/sec: 998.57 - lr: 0.000007 - momentum: 0.000000 |
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2023-10-17 09:11:10,965 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 09:11:10,965 EPOCH 8 done: loss 0.0077 - lr: 0.000007 |
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2023-10-17 09:11:13,892 DEV : loss 0.10704014450311661 - f1-score (micro avg) 0.8 |
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2023-10-17 09:11:13,922 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 09:11:25,981 epoch 9 - iter 154/1546 - loss 0.00378941 - time (sec): 12.05 - samples/sec: 1045.81 - lr: 0.000006 - momentum: 0.000000 |
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2023-10-17 09:11:37,802 epoch 9 - iter 308/1546 - loss 0.00283362 - time (sec): 23.88 - samples/sec: 1027.32 - lr: 0.000006 - momentum: 0.000000 |
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2023-10-17 09:11:50,093 epoch 9 - iter 462/1546 - loss 0.00396993 - time (sec): 36.17 - samples/sec: 1034.15 - lr: 0.000006 - momentum: 0.000000 |
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2023-10-17 09:12:03,236 epoch 9 - iter 616/1546 - loss 0.00400059 - time (sec): 49.31 - samples/sec: 996.36 - lr: 0.000005 - momentum: 0.000000 |
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2023-10-17 09:12:15,466 epoch 9 - iter 770/1546 - loss 0.00385112 - time (sec): 61.54 - samples/sec: 1005.67 - lr: 0.000005 - momentum: 0.000000 |
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2023-10-17 09:12:27,700 epoch 9 - iter 924/1546 - loss 0.00459493 - time (sec): 73.77 - samples/sec: 1003.17 - lr: 0.000005 - momentum: 0.000000 |
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2023-10-17 09:12:39,832 epoch 9 - iter 1078/1546 - loss 0.00412718 - time (sec): 85.91 - samples/sec: 1011.44 - lr: 0.000004 - momentum: 0.000000 |
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2023-10-17 09:12:51,879 epoch 9 - iter 1232/1546 - loss 0.00405342 - time (sec): 97.95 - samples/sec: 1010.84 - lr: 0.000004 - momentum: 0.000000 |
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2023-10-17 09:13:03,846 epoch 9 - iter 1386/1546 - loss 0.00404944 - time (sec): 109.92 - samples/sec: 1021.84 - lr: 0.000004 - momentum: 0.000000 |
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2023-10-17 09:13:15,705 epoch 9 - iter 1540/1546 - loss 0.00452713 - time (sec): 121.78 - samples/sec: 1016.74 - lr: 0.000003 - momentum: 0.000000 |
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2023-10-17 09:13:16,160 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 09:13:16,160 EPOCH 9 done: loss 0.0045 - lr: 0.000003 |
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2023-10-17 09:13:18,878 DEV : loss 0.12154770642518997 - f1-score (micro avg) 0.7983 |
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2023-10-17 09:13:18,904 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 09:13:30,793 epoch 10 - iter 154/1546 - loss 0.00274083 - time (sec): 11.89 - samples/sec: 1053.40 - lr: 0.000003 - momentum: 0.000000 |
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2023-10-17 09:13:42,788 epoch 10 - iter 308/1546 - loss 0.00390665 - time (sec): 23.88 - samples/sec: 1038.05 - lr: 0.000003 - momentum: 0.000000 |
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2023-10-17 09:13:54,809 epoch 10 - iter 462/1546 - loss 0.00330672 - time (sec): 35.90 - samples/sec: 1054.09 - lr: 0.000002 - momentum: 0.000000 |
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2023-10-17 09:14:07,461 epoch 10 - iter 616/1546 - loss 0.00342831 - time (sec): 48.56 - samples/sec: 1035.09 - lr: 0.000002 - momentum: 0.000000 |
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2023-10-17 09:14:20,606 epoch 10 - iter 770/1546 - loss 0.00329853 - time (sec): 61.70 - samples/sec: 1013.00 - lr: 0.000002 - momentum: 0.000000 |
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2023-10-17 09:14:33,362 epoch 10 - iter 924/1546 - loss 0.00299964 - time (sec): 74.46 - samples/sec: 996.99 - lr: 0.000001 - momentum: 0.000000 |
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2023-10-17 09:14:46,754 epoch 10 - iter 1078/1546 - loss 0.00313900 - time (sec): 87.85 - samples/sec: 990.71 - lr: 0.000001 - momentum: 0.000000 |
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2023-10-17 09:14:59,125 epoch 10 - iter 1232/1546 - loss 0.00324827 - time (sec): 100.22 - samples/sec: 986.19 - lr: 0.000001 - momentum: 0.000000 |
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2023-10-17 09:15:12,274 epoch 10 - iter 1386/1546 - loss 0.00311186 - time (sec): 113.37 - samples/sec: 983.00 - lr: 0.000000 - momentum: 0.000000 |
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2023-10-17 09:15:25,848 epoch 10 - iter 1540/1546 - loss 0.00341137 - time (sec): 126.94 - samples/sec: 975.57 - lr: 0.000000 - momentum: 0.000000 |
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2023-10-17 09:15:26,351 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 09:15:26,351 EPOCH 10 done: loss 0.0034 - lr: 0.000000 |
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2023-10-17 09:15:29,674 DEV : loss 0.11997128278017044 - f1-score (micro avg) 0.7886 |
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2023-10-17 09:15:30,263 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 09:15:30,265 Loading model from best epoch ... |
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2023-10-17 09:15:32,732 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 |
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2023-10-17 09:15:40,874 |
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Results: |
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- F-score (micro) 0.8096 |
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- F-score (macro) 0.7186 |
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- Accuracy 0.6984 |
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By class: |
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precision recall f1-score support |
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LOC 0.8731 0.8362 0.8542 946 |
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BUILDING 0.6806 0.5297 0.5957 185 |
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STREET 0.6667 0.7500 0.7059 56 |
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micro avg 0.8365 0.7843 0.8096 1187 |
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macro avg 0.7401 0.7053 0.7186 1187 |
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weighted avg 0.8333 0.7843 0.8069 1187 |
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2023-10-17 09:15:40,875 ---------------------------------------------------------------------------------------------------- |
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