| 2023-10-18 18:09:46,064 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 18:09:46,064 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=21, bias=True) | |
| (loss_function): CrossEntropyLoss() | |
| )" | |
| 2023-10-18 18:09:46,064 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 18:09:46,064 MultiCorpus: 3575 train + 1235 dev + 1266 test sentences | |
| - NER_HIPE_2022 Corpus: 3575 train + 1235 dev + 1266 test sentences - /root/.flair/datasets/ner_hipe_2022/v2.1/hipe2020/de/with_doc_seperator | |
| 2023-10-18 18:09:46,064 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 18:09:46,065 Train: 3575 sentences | |
| 2023-10-18 18:09:46,065 (train_with_dev=False, train_with_test=False) | |
| 2023-10-18 18:09:46,065 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 18:09:46,065 Training Params: | |
| 2023-10-18 18:09:46,065 - learning_rate: "5e-05" | |
| 2023-10-18 18:09:46,065 - mini_batch_size: "8" | |
| 2023-10-18 18:09:46,065 - max_epochs: "10" | |
| 2023-10-18 18:09:46,065 - shuffle: "True" | |
| 2023-10-18 18:09:46,065 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 18:09:46,065 Plugins: | |
| 2023-10-18 18:09:46,065 - TensorboardLogger | |
| 2023-10-18 18:09:46,065 - LinearScheduler | warmup_fraction: '0.1' | |
| 2023-10-18 18:09:46,065 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 18:09:46,065 Final evaluation on model from best epoch (best-model.pt) | |
| 2023-10-18 18:09:46,065 - metric: "('micro avg', 'f1-score')" | |
| 2023-10-18 18:09:46,065 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 18:09:46,065 Computation: | |
| 2023-10-18 18:09:46,065 - compute on device: cuda:0 | |
| 2023-10-18 18:09:46,065 - embedding storage: none | |
| 2023-10-18 18:09:46,065 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 18:09:46,065 Model training base path: "hmbench-hipe2020/de-dbmdz/bert-tiny-historic-multilingual-cased-bs8-wsFalse-e10-lr5e-05-poolingfirst-layers-1-crfFalse-3" | |
| 2023-10-18 18:09:46,065 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 18:09:46,065 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 18:09:46,065 Logging anything other than scalars to TensorBoard is currently not supported. | |
| 2023-10-18 18:09:47,053 epoch 1 - iter 44/447 - loss 3.48107062 - time (sec): 0.99 - samples/sec: 8149.30 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-18 18:09:48,036 epoch 1 - iter 88/447 - loss 3.27194561 - time (sec): 1.97 - samples/sec: 8188.94 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-18 18:09:49,024 epoch 1 - iter 132/447 - loss 2.95857671 - time (sec): 2.96 - samples/sec: 8487.10 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-18 18:09:50,056 epoch 1 - iter 176/447 - loss 2.57672294 - time (sec): 3.99 - samples/sec: 8501.78 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-18 18:09:51,047 epoch 1 - iter 220/447 - loss 2.24069636 - time (sec): 4.98 - samples/sec: 8528.40 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-18 18:09:52,027 epoch 1 - iter 264/447 - loss 1.99699733 - time (sec): 5.96 - samples/sec: 8479.72 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-18 18:09:52,989 epoch 1 - iter 308/447 - loss 1.80609338 - time (sec): 6.92 - samples/sec: 8448.04 - lr: 0.000034 - momentum: 0.000000 | |
| 2023-10-18 18:09:53,982 epoch 1 - iter 352/447 - loss 1.65672493 - time (sec): 7.92 - samples/sec: 8441.08 - lr: 0.000039 - momentum: 0.000000 | |
| 2023-10-18 18:09:55,020 epoch 1 - iter 396/447 - loss 1.51394066 - time (sec): 8.95 - samples/sec: 8605.93 - lr: 0.000044 - momentum: 0.000000 | |
| 2023-10-18 18:09:56,001 epoch 1 - iter 440/447 - loss 1.42253798 - time (sec): 9.94 - samples/sec: 8579.71 - lr: 0.000049 - momentum: 0.000000 | |
| 2023-10-18 18:09:56,152 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 18:09:56,152 EPOCH 1 done: loss 1.4116 - lr: 0.000049 | |
| 2023-10-18 18:09:58,311 DEV : loss 0.440503865480423 - f1-score (micro avg) 0.0 | |
| 2023-10-18 18:09:58,335 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 18:09:59,384 epoch 2 - iter 44/447 - loss 0.55508516 - time (sec): 1.05 - samples/sec: 8395.32 - lr: 0.000049 - momentum: 0.000000 | |
| 2023-10-18 18:10:00,396 epoch 2 - iter 88/447 - loss 0.52727644 - time (sec): 2.06 - samples/sec: 8360.90 - lr: 0.000049 - momentum: 0.000000 | |
| 2023-10-18 18:10:01,408 epoch 2 - iter 132/447 - loss 0.52183207 - time (sec): 3.07 - samples/sec: 8233.32 - lr: 0.000048 - momentum: 0.000000 | |
| 2023-10-18 18:10:02,425 epoch 2 - iter 176/447 - loss 0.52157574 - time (sec): 4.09 - samples/sec: 8126.32 - lr: 0.000048 - momentum: 0.000000 | |
| 2023-10-18 18:10:03,453 epoch 2 - iter 220/447 - loss 0.51770155 - time (sec): 5.12 - samples/sec: 8137.91 - lr: 0.000047 - momentum: 0.000000 | |
| 2023-10-18 18:10:04,457 epoch 2 - iter 264/447 - loss 0.50585354 - time (sec): 6.12 - samples/sec: 8201.03 - lr: 0.000047 - momentum: 0.000000 | |
| 2023-10-18 18:10:05,438 epoch 2 - iter 308/447 - loss 0.50399864 - time (sec): 7.10 - samples/sec: 8201.77 - lr: 0.000046 - momentum: 0.000000 | |
| 2023-10-18 18:10:06,437 epoch 2 - iter 352/447 - loss 0.49361795 - time (sec): 8.10 - samples/sec: 8250.70 - lr: 0.000046 - momentum: 0.000000 | |
| 2023-10-18 18:10:07,518 epoch 2 - iter 396/447 - loss 0.48893978 - time (sec): 9.18 - samples/sec: 8357.10 - lr: 0.000045 - momentum: 0.000000 | |
| 2023-10-18 18:10:08,526 epoch 2 - iter 440/447 - loss 0.48392438 - time (sec): 10.19 - samples/sec: 8352.26 - lr: 0.000045 - momentum: 0.000000 | |
| 2023-10-18 18:10:08,682 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 18:10:08,683 EPOCH 2 done: loss 0.4823 - lr: 0.000045 | |
| 2023-10-18 18:10:13,841 DEV : loss 0.34371984004974365 - f1-score (micro avg) 0.113 | |
| 2023-10-18 18:10:13,866 saving best model | |
| 2023-10-18 18:10:13,903 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 18:10:15,010 epoch 3 - iter 44/447 - loss 0.43301365 - time (sec): 1.11 - samples/sec: 7369.43 - lr: 0.000044 - momentum: 0.000000 | |
| 2023-10-18 18:10:16,142 epoch 3 - iter 88/447 - loss 0.44758670 - time (sec): 2.24 - samples/sec: 7560.07 - lr: 0.000043 - momentum: 0.000000 | |
| 2023-10-18 18:10:17,243 epoch 3 - iter 132/447 - loss 0.42991796 - time (sec): 3.34 - samples/sec: 7834.85 - lr: 0.000043 - momentum: 0.000000 | |
| 2023-10-18 18:10:18,256 epoch 3 - iter 176/447 - loss 0.43302866 - time (sec): 4.35 - samples/sec: 8004.92 - lr: 0.000042 - momentum: 0.000000 | |
| 2023-10-18 18:10:19,252 epoch 3 - iter 220/447 - loss 0.42209371 - time (sec): 5.35 - samples/sec: 8108.14 - lr: 0.000042 - momentum: 0.000000 | |
| 2023-10-18 18:10:20,220 epoch 3 - iter 264/447 - loss 0.40578864 - time (sec): 6.32 - samples/sec: 8228.82 - lr: 0.000041 - momentum: 0.000000 | |
| 2023-10-18 18:10:21,223 epoch 3 - iter 308/447 - loss 0.40322907 - time (sec): 7.32 - samples/sec: 8256.58 - lr: 0.000041 - momentum: 0.000000 | |
| 2023-10-18 18:10:22,195 epoch 3 - iter 352/447 - loss 0.39866877 - time (sec): 8.29 - samples/sec: 8245.34 - lr: 0.000040 - momentum: 0.000000 | |
| 2023-10-18 18:10:23,204 epoch 3 - iter 396/447 - loss 0.39598782 - time (sec): 9.30 - samples/sec: 8291.45 - lr: 0.000040 - momentum: 0.000000 | |
| 2023-10-18 18:10:24,193 epoch 3 - iter 440/447 - loss 0.39667531 - time (sec): 10.29 - samples/sec: 8277.73 - lr: 0.000039 - momentum: 0.000000 | |
| 2023-10-18 18:10:24,350 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 18:10:24,350 EPOCH 3 done: loss 0.3956 - lr: 0.000039 | |
| 2023-10-18 18:10:29,527 DEV : loss 0.32860174775123596 - f1-score (micro avg) 0.285 | |
| 2023-10-18 18:10:29,551 saving best model | |
| 2023-10-18 18:10:29,586 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 18:10:30,520 epoch 4 - iter 44/447 - loss 0.36943001 - time (sec): 0.93 - samples/sec: 9106.31 - lr: 0.000038 - momentum: 0.000000 | |
| 2023-10-18 18:10:31,531 epoch 4 - iter 88/447 - loss 0.38745357 - time (sec): 1.94 - samples/sec: 8838.65 - lr: 0.000038 - momentum: 0.000000 | |
| 2023-10-18 18:10:32,506 epoch 4 - iter 132/447 - loss 0.38115552 - time (sec): 2.92 - samples/sec: 8839.02 - lr: 0.000037 - momentum: 0.000000 | |
| 2023-10-18 18:10:33,512 epoch 4 - iter 176/447 - loss 0.37121101 - time (sec): 3.93 - samples/sec: 8895.14 - lr: 0.000037 - momentum: 0.000000 | |
| 2023-10-18 18:10:34,550 epoch 4 - iter 220/447 - loss 0.36960639 - time (sec): 4.96 - samples/sec: 8984.03 - lr: 0.000036 - momentum: 0.000000 | |
| 2023-10-18 18:10:35,551 epoch 4 - iter 264/447 - loss 0.36995927 - time (sec): 5.96 - samples/sec: 8809.47 - lr: 0.000036 - momentum: 0.000000 | |
| 2023-10-18 18:10:36,550 epoch 4 - iter 308/447 - loss 0.36353926 - time (sec): 6.96 - samples/sec: 8733.96 - lr: 0.000035 - momentum: 0.000000 | |
| 2023-10-18 18:10:37,569 epoch 4 - iter 352/447 - loss 0.36657074 - time (sec): 7.98 - samples/sec: 8625.94 - lr: 0.000035 - momentum: 0.000000 | |
| 2023-10-18 18:10:38,546 epoch 4 - iter 396/447 - loss 0.36628777 - time (sec): 8.96 - samples/sec: 8561.72 - lr: 0.000034 - momentum: 0.000000 | |
| 2023-10-18 18:10:39,540 epoch 4 - iter 440/447 - loss 0.36059543 - time (sec): 9.95 - samples/sec: 8580.60 - lr: 0.000033 - momentum: 0.000000 | |
| 2023-10-18 18:10:39,696 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 18:10:39,696 EPOCH 4 done: loss 0.3608 - lr: 0.000033 | |
| 2023-10-18 18:10:44,932 DEV : loss 0.320486456155777 - f1-score (micro avg) 0.3043 | |
| 2023-10-18 18:10:44,956 saving best model | |
| 2023-10-18 18:10:44,995 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 18:10:46,000 epoch 5 - iter 44/447 - loss 0.32352808 - time (sec): 1.00 - samples/sec: 8351.93 - lr: 0.000033 - momentum: 0.000000 | |
| 2023-10-18 18:10:47,066 epoch 5 - iter 88/447 - loss 0.32347254 - time (sec): 2.07 - samples/sec: 8722.05 - lr: 0.000032 - momentum: 0.000000 | |
| 2023-10-18 18:10:48,107 epoch 5 - iter 132/447 - loss 0.33387921 - time (sec): 3.11 - samples/sec: 8659.51 - lr: 0.000032 - momentum: 0.000000 | |
| 2023-10-18 18:10:49,084 epoch 5 - iter 176/447 - loss 0.32884812 - time (sec): 4.09 - samples/sec: 8638.09 - lr: 0.000031 - momentum: 0.000000 | |
| 2023-10-18 18:10:50,071 epoch 5 - iter 220/447 - loss 0.33619392 - time (sec): 5.07 - samples/sec: 8511.54 - lr: 0.000031 - momentum: 0.000000 | |
| 2023-10-18 18:10:51,057 epoch 5 - iter 264/447 - loss 0.33428705 - time (sec): 6.06 - samples/sec: 8467.93 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-18 18:10:52,045 epoch 5 - iter 308/447 - loss 0.33761251 - time (sec): 7.05 - samples/sec: 8500.30 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-18 18:10:53,101 epoch 5 - iter 352/447 - loss 0.33546904 - time (sec): 8.10 - samples/sec: 8513.28 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-18 18:10:54,129 epoch 5 - iter 396/447 - loss 0.33425057 - time (sec): 9.13 - samples/sec: 8480.39 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-18 18:10:55,110 epoch 5 - iter 440/447 - loss 0.33363531 - time (sec): 10.11 - samples/sec: 8441.10 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-18 18:10:55,257 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 18:10:55,257 EPOCH 5 done: loss 0.3316 - lr: 0.000028 | |
| 2023-10-18 18:11:00,464 DEV : loss 0.3082502484321594 - f1-score (micro avg) 0.3129 | |
| 2023-10-18 18:11:00,488 saving best model | |
| 2023-10-18 18:11:00,526 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 18:11:01,586 epoch 6 - iter 44/447 - loss 0.27288611 - time (sec): 1.06 - samples/sec: 8701.04 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-18 18:11:02,564 epoch 6 - iter 88/447 - loss 0.30392757 - time (sec): 2.04 - samples/sec: 8602.53 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-18 18:11:03,489 epoch 6 - iter 132/447 - loss 0.32248259 - time (sec): 2.96 - samples/sec: 8719.10 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-18 18:11:04,445 epoch 6 - iter 176/447 - loss 0.32428223 - time (sec): 3.92 - samples/sec: 8749.25 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-18 18:11:05,456 epoch 6 - iter 220/447 - loss 0.32839831 - time (sec): 4.93 - samples/sec: 8750.03 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-18 18:11:06,438 epoch 6 - iter 264/447 - loss 0.32721286 - time (sec): 5.91 - samples/sec: 8725.73 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-18 18:11:07,434 epoch 6 - iter 308/447 - loss 0.31843729 - time (sec): 6.91 - samples/sec: 8635.69 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-18 18:11:08,439 epoch 6 - iter 352/447 - loss 0.31455378 - time (sec): 7.91 - samples/sec: 8592.91 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-18 18:11:09,472 epoch 6 - iter 396/447 - loss 0.30630728 - time (sec): 8.95 - samples/sec: 8597.27 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-18 18:11:10,441 epoch 6 - iter 440/447 - loss 0.30982808 - time (sec): 9.91 - samples/sec: 8575.59 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-18 18:11:10,601 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 18:11:10,601 EPOCH 6 done: loss 0.3103 - lr: 0.000022 | |
| 2023-10-18 18:11:15,515 DEV : loss 0.30133387446403503 - f1-score (micro avg) 0.3376 | |
| 2023-10-18 18:11:15,539 saving best model | |
| 2023-10-18 18:11:15,573 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 18:11:16,597 epoch 7 - iter 44/447 - loss 0.25287805 - time (sec): 1.02 - samples/sec: 7909.44 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-18 18:11:17,643 epoch 7 - iter 88/447 - loss 0.28977731 - time (sec): 2.07 - samples/sec: 8401.57 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-18 18:11:18,644 epoch 7 - iter 132/447 - loss 0.28988167 - time (sec): 3.07 - samples/sec: 8379.93 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-18 18:11:19,673 epoch 7 - iter 176/447 - loss 0.29009755 - time (sec): 4.10 - samples/sec: 8671.40 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-18 18:11:20,674 epoch 7 - iter 220/447 - loss 0.29294307 - time (sec): 5.10 - samples/sec: 8638.88 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-18 18:11:22,035 epoch 7 - iter 264/447 - loss 0.29453891 - time (sec): 6.46 - samples/sec: 8222.76 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-18 18:11:23,013 epoch 7 - iter 308/447 - loss 0.29521798 - time (sec): 7.44 - samples/sec: 8191.12 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-18 18:11:24,050 epoch 7 - iter 352/447 - loss 0.29903791 - time (sec): 8.48 - samples/sec: 8180.70 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-18 18:11:25,047 epoch 7 - iter 396/447 - loss 0.30193005 - time (sec): 9.47 - samples/sec: 8173.12 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-18 18:11:26,053 epoch 7 - iter 440/447 - loss 0.29772260 - time (sec): 10.48 - samples/sec: 8138.11 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-18 18:11:26,218 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 18:11:26,218 EPOCH 7 done: loss 0.2996 - lr: 0.000017 | |
| 2023-10-18 18:11:31,159 DEV : loss 0.2995185852050781 - f1-score (micro avg) 0.3428 | |
| 2023-10-18 18:11:31,184 saving best model | |
| 2023-10-18 18:11:31,223 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 18:11:32,193 epoch 8 - iter 44/447 - loss 0.27978168 - time (sec): 0.97 - samples/sec: 8119.90 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-18 18:11:33,151 epoch 8 - iter 88/447 - loss 0.28824429 - time (sec): 1.93 - samples/sec: 7853.50 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-18 18:11:34,148 epoch 8 - iter 132/447 - loss 0.28662310 - time (sec): 2.92 - samples/sec: 8149.03 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-18 18:11:35,134 epoch 8 - iter 176/447 - loss 0.29888598 - time (sec): 3.91 - samples/sec: 8208.25 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-18 18:11:36,084 epoch 8 - iter 220/447 - loss 0.29137520 - time (sec): 4.86 - samples/sec: 8235.72 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-18 18:11:37,086 epoch 8 - iter 264/447 - loss 0.28874586 - time (sec): 5.86 - samples/sec: 8191.30 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-18 18:11:38,115 epoch 8 - iter 308/447 - loss 0.28559013 - time (sec): 6.89 - samples/sec: 8345.14 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-18 18:11:39,161 epoch 8 - iter 352/447 - loss 0.29125430 - time (sec): 7.94 - samples/sec: 8419.16 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-18 18:11:40,002 epoch 8 - iter 396/447 - loss 0.29049800 - time (sec): 8.78 - samples/sec: 8510.69 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-18 18:11:40,885 epoch 8 - iter 440/447 - loss 0.28778174 - time (sec): 9.66 - samples/sec: 8688.77 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-18 18:11:41,101 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 18:11:41,101 EPOCH 8 done: loss 0.2870 - lr: 0.000011 | |
| 2023-10-18 18:11:46,365 DEV : loss 0.29179754853248596 - f1-score (micro avg) 0.3475 | |
| 2023-10-18 18:11:46,390 saving best model | |
| 2023-10-18 18:11:46,425 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 18:11:47,450 epoch 9 - iter 44/447 - loss 0.30150118 - time (sec): 1.02 - samples/sec: 9520.13 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-18 18:11:48,460 epoch 9 - iter 88/447 - loss 0.30631108 - time (sec): 2.04 - samples/sec: 8952.24 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-18 18:11:49,498 epoch 9 - iter 132/447 - loss 0.29415977 - time (sec): 3.07 - samples/sec: 8877.64 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-18 18:11:50,475 epoch 9 - iter 176/447 - loss 0.29426276 - time (sec): 4.05 - samples/sec: 8537.82 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-18 18:11:51,454 epoch 9 - iter 220/447 - loss 0.27981800 - time (sec): 5.03 - samples/sec: 8555.77 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-18 18:11:52,451 epoch 9 - iter 264/447 - loss 0.28872070 - time (sec): 6.03 - samples/sec: 8511.27 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-18 18:11:53,450 epoch 9 - iter 308/447 - loss 0.28551834 - time (sec): 7.03 - samples/sec: 8505.13 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-18 18:11:54,461 epoch 9 - iter 352/447 - loss 0.28086491 - time (sec): 8.04 - samples/sec: 8503.20 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-18 18:11:55,447 epoch 9 - iter 396/447 - loss 0.27926325 - time (sec): 9.02 - samples/sec: 8513.26 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-18 18:11:56,409 epoch 9 - iter 440/447 - loss 0.27899408 - time (sec): 9.98 - samples/sec: 8476.82 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-18 18:11:56,600 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 18:11:56,600 EPOCH 9 done: loss 0.2788 - lr: 0.000006 | |
| 2023-10-18 18:12:01,866 DEV : loss 0.29360440373420715 - f1-score (micro avg) 0.3437 | |
| 2023-10-18 18:12:01,891 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 18:12:02,845 epoch 10 - iter 44/447 - loss 0.29982169 - time (sec): 0.95 - samples/sec: 9260.58 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-18 18:12:03,842 epoch 10 - iter 88/447 - loss 0.29743769 - time (sec): 1.95 - samples/sec: 8975.17 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-18 18:12:04,837 epoch 10 - iter 132/447 - loss 0.28765785 - time (sec): 2.95 - samples/sec: 8664.41 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-18 18:12:05,825 epoch 10 - iter 176/447 - loss 0.29160770 - time (sec): 3.93 - samples/sec: 8453.40 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-18 18:12:06,779 epoch 10 - iter 220/447 - loss 0.28993886 - time (sec): 4.89 - samples/sec: 8449.64 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-18 18:12:07,819 epoch 10 - iter 264/447 - loss 0.28561611 - time (sec): 5.93 - samples/sec: 8473.17 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-18 18:12:08,861 epoch 10 - iter 308/447 - loss 0.27784141 - time (sec): 6.97 - samples/sec: 8501.64 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-18 18:12:09,891 epoch 10 - iter 352/447 - loss 0.27407641 - time (sec): 8.00 - samples/sec: 8474.39 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-18 18:12:10,888 epoch 10 - iter 396/447 - loss 0.27298519 - time (sec): 9.00 - samples/sec: 8489.94 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-18 18:12:11,937 epoch 10 - iter 440/447 - loss 0.27094189 - time (sec): 10.05 - samples/sec: 8479.74 - lr: 0.000000 - momentum: 0.000000 | |
| 2023-10-18 18:12:12,101 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 18:12:12,101 EPOCH 10 done: loss 0.2713 - lr: 0.000000 | |
| 2023-10-18 18:12:17,372 DEV : loss 0.2932772934436798 - f1-score (micro avg) 0.3486 | |
| 2023-10-18 18:12:17,396 saving best model | |
| 2023-10-18 18:12:17,467 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 18:12:17,467 Loading model from best epoch ... | |
| 2023-10-18 18:12:17,542 SequenceTagger predicts: Dictionary with 21 tags: O, S-loc, B-loc, E-loc, I-loc, S-pers, B-pers, E-pers, I-pers, S-org, B-org, E-org, I-org, S-prod, B-prod, E-prod, I-prod, S-time, B-time, E-time, I-time | |
| 2023-10-18 18:12:19,483 | |
| Results: | |
| - F-score (micro) 0.3408 | |
| - F-score (macro) 0.1668 | |
| - Accuracy 0.216 | |
| By class: | |
| precision recall f1-score support | |
| loc 0.4727 0.5369 0.5027 596 | |
| pers 0.1563 0.1892 0.1712 333 | |
| org 0.0000 0.0000 0.0000 132 | |
| time 0.2308 0.1224 0.1600 49 | |
| prod 0.0000 0.0000 0.0000 66 | |
| micro avg 0.3514 0.3308 0.3408 1176 | |
| macro avg 0.1720 0.1697 0.1668 1176 | |
| weighted avg 0.2934 0.3308 0.3099 1176 | |
| 2023-10-18 18:12:19,483 ---------------------------------------------------------------------------------------------------- | |