| 2026-10-29 11:06:45,367 ---------------------------------------------------------------------------------------------------- |
| 2026-10-29 11:06:45,367 Model: "SequenceTagger( |
| (embeddings): StackedEmbeddings( |
| (list_embedding_0): TransformerWordEmbeddings( |
| (model): XLMRobertaModel( |
| (embeddings): XLMRobertaEmbeddings( |
| (word_embeddings): Embedding(250003, 1024, padding_idx=1) |
| (position_embeddings): Embedding(514, 1024, padding_idx=1) |
| (token_type_embeddings): Embedding(1, 1024) |
| (LayerNorm): LayerNorm((1024,), eps=1e-05, elementwise_affine=True, bias=True) |
| (dropout): Dropout(p=0.1, inplace=False) |
| ) |
| (encoder): XLMRobertaEncoder( |
| (layer): ModuleList( |
| (0-23): 24 x XLMRobertaLayer( |
| (attention): XLMRobertaAttention( |
| (self): XLMRobertaSdpaSelfAttention( |
| (query): Linear(in_features=1024, out_features=1024, bias=True) |
| (key): Linear(in_features=1024, out_features=1024, bias=True) |
| (value): Linear(in_features=1024, out_features=1024, bias=True) |
| (dropout): Dropout(p=0.1, inplace=False) |
| ) |
| (output): XLMRobertaSelfOutput( |
| (dense): Linear(in_features=1024, out_features=1024, bias=True) |
| (LayerNorm): LayerNorm((1024,), eps=1e-05, elementwise_affine=True, bias=True) |
| (dropout): Dropout(p=0.1, inplace=False) |
| ) |
| ) |
| (intermediate): XLMRobertaIntermediate( |
| (dense): Linear(in_features=1024, out_features=4096, bias=True) |
| (intermediate_act_fn): GELUActivation() |
| ) |
| (output): XLMRobertaOutput( |
| (dense): Linear(in_features=4096, out_features=1024, bias=True) |
| (LayerNorm): LayerNorm((1024,), eps=1e-05, elementwise_affine=True, bias=True) |
| (dropout): Dropout(p=0.1, inplace=False) |
| ) |
| ) |
| ) |
| ) |
| (pooler): XLMRobertaPooler( |
| (dense): Linear(in_features=1024, out_features=1024, bias=True) |
| (activation): Tanh() |
| ) |
| ) |
| ) |
| (list_embedding_1): FlairEmbeddings( |
| (lm): LanguageModel( |
| (drop): Dropout(p=0.1, inplace=False) |
| (encoder): Embedding(333, 200) |
| (rnn): LSTM(200, 2048, num_layers=2, dropout=0.1) |
| ) |
| ) |
| (list_embedding_2): FlairEmbeddings( |
| (lm): LanguageModel( |
| (drop): Dropout(p=0.1, inplace=False) |
| (encoder): Embedding(333, 200) |
| (rnn): LSTM(200, 2048, num_layers=2, dropout=0.1) |
| ) |
| ) |
| ) |
| (word_dropout): WordDropout(p=0.05) |
| (locked_dropout): LockedDropout(p=0.5) |
| (linear): Linear(in_features=5120, out_features=43, bias=True) |
| (loss_function): ViterbiLoss() |
| (crf): CRF() |
| )" |
| 2026-10-29 11:06:45,367 ---------------------------------------------------------------------------------------------------- |
| 2026-10-29 11:06:45,367 Corpus: 89250 train + 11990 dev + 10511 test sentences |
| 2026-10-29 11:06:45,367 ---------------------------------------------------------------------------------------------------- |
| 2026-10-29 11:06:45,368 Train: 89250 sentences |
| 2026-10-29 11:06:45,368 (train_with_dev=False, train_with_test=False) |
| 2026-10-29 11:06:45,368 ---------------------------------------------------------------------------------------------------- |
| 2026-10-29 11:06:45,368 Training Params: |
| 2026-10-29 11:06:45,368 - learning_rate: "5e-05" |
| 2026-10-29 11:06:45,368 - mini_batch_size: "16" |
| 2026-10-29 11:06:45,368 - max_epochs: "20" |
| 2026-10-29 11:06:45,368 - shuffle: "True" |
| 2026-10-29 11:06:45,368 ---------------------------------------------------------------------------------------------------- |
| 2026-10-29 11:06:45,368 Plugins: |
| 2026-10-29 11:06:45,368 - LinearScheduler | warmup_fraction: '0.1' |
| 2026-10-29 11:06:45,368 ---------------------------------------------------------------------------------------------------- |
| 2026-10-29 11:06:45,368 Final evaluation on model from best epoch (best-model.pt) |
| 2026-10-29 11:06:45,368 - metric: "('micro avg', 'f1-score')" |
| 2026-10-29 11:06:45,368 ---------------------------------------------------------------------------------------------------- |
| 2026-10-29 11:06:45,368 Computation: |
| 2026-10-29 11:06:45,368 - compute on device: cuda |
| 2026-10-29 11:06:45,368 - embedding storage: none |
| 2026-10-29 11:06:45,368 ---------------------------------------------------------------------------------------------------- |
| 2026-10-29 11:06:45,368 Model training base path: "/home/schonhardt/flair-train2/output/flair/model" |
| 2026-10-29 11:06:45,368 ---------------------------------------------------------------------------------------------------- |
| 2026-10-29 11:06:45,368 ---------------------------------------------------------------------------------------------------- |
| 2026-10-29 11:08:07,752 epoch 1 - iter 557/5579 - loss 2.84577215 - time (sec): 82.38 - samples/sec: 2863.77 - lr: 0.000002 - momentum: 0.000000 |
| 2026-10-29 11:09:32,509 epoch 1 - iter 1114/5579 - loss 1.79914958 - time (sec): 167.14 - samples/sec: 2811.96 - lr: 0.000005 - momentum: 0.000000 |
| 2026-10-29 11:10:53,927 epoch 1 - iter 1671/5579 - loss 1.37098927 - time (sec): 248.56 - samples/sec: 2835.03 - lr: 0.000007 - momentum: 0.000000 |
| 2026-10-29 11:12:16,479 epoch 1 - iter 2228/5579 - loss 1.13476833 - time (sec): 331.11 - samples/sec: 2842.07 - lr: 0.000010 - momentum: 0.000000 |
| 2026-10-29 11:13:38,883 epoch 1 - iter 2785/5579 - loss 0.98855375 - time (sec): 413.51 - samples/sec: 2848.05 - lr: 0.000012 - momentum: 0.000000 |
| 2026-10-29 11:15:00,749 epoch 1 - iter 3342/5579 - loss 0.88985307 - time (sec): 495.38 - samples/sec: 2843.46 - lr: 0.000015 - momentum: 0.000000 |
| 2026-10-29 11:16:23,386 epoch 1 - iter 3899/5579 - loss 0.81423309 - time (sec): 578.02 - samples/sec: 2850.43 - lr: 0.000017 - momentum: 0.000000 |
| 2026-10-29 11:17:48,211 epoch 1 - iter 4456/5579 - loss 0.75808393 - time (sec): 662.84 - samples/sec: 2840.23 - lr: 0.000020 - momentum: 0.000000 |
| 2026-10-29 11:19:09,978 epoch 1 - iter 5013/5579 - loss 0.71440223 - time (sec): 744.61 - samples/sec: 2842.12 - lr: 0.000022 - momentum: 0.000000 |
| 2026-10-29 11:20:32,348 epoch 1 - iter 5570/5579 - loss 0.67837716 - time (sec): 826.98 - samples/sec: 2847.92 - lr: 0.000025 - momentum: 0.000000 |
| 2026-10-29 11:20:33,649 ---------------------------------------------------------------------------------------------------- |
| 2026-10-29 11:20:33,649 EPOCH 1 done: loss 0.6779 - lr: 0.000025 |
| 2026-10-29 11:20:33,649 Saving model at current epoch since 'save_model_each_k_epochs=1' was set |
| 2026-10-29 11:22:06,391 DEV : loss 0.07737061381340027 - f1-score (micro avg) 0.8502 |
| 2026-10-29 11:22:06,476 saving best model |
| 2026-10-29 11:22:07,305 ---------------------------------------------------------------------------------------------------- |
| 2026-10-29 11:23:28,671 epoch 2 - iter 557/5579 - loss 0.34944486 - time (sec): 81.36 - samples/sec: 2894.06 - lr: 0.000027 - momentum: 0.000000 |
| 2026-10-29 11:24:49,780 epoch 2 - iter 1114/5579 - loss 0.34752419 - time (sec): 162.47 - samples/sec: 2901.03 - lr: 0.000030 - momentum: 0.000000 |
| 2026-10-29 11:26:10,900 epoch 2 - iter 1671/5579 - loss 0.34777551 - time (sec): 243.59 - samples/sec: 2908.03 - lr: 0.000032 - momentum: 0.000000 |
| 2026-10-29 11:27:32,596 epoch 2 - iter 2228/5579 - loss 0.34799066 - time (sec): 325.29 - samples/sec: 2904.96 - lr: 0.000035 - momentum: 0.000000 |
| 2026-10-29 11:28:54,796 epoch 2 - iter 2785/5579 - loss 0.34527488 - time (sec): 407.49 - samples/sec: 2899.02 - lr: 0.000037 - momentum: 0.000000 |
| 2026-10-29 11:30:18,591 epoch 2 - iter 3342/5579 - loss 0.34511715 - time (sec): 491.28 - samples/sec: 2876.97 - lr: 0.000040 - momentum: 0.000000 |
| 2026-10-29 11:31:39,767 epoch 2 - iter 3899/5579 - loss 0.34312173 - time (sec): 572.46 - samples/sec: 2882.27 - lr: 0.000042 - momentum: 0.000000 |
| 2026-10-29 11:33:01,019 epoch 2 - iter 4456/5579 - loss 0.34282511 - time (sec): 653.71 - samples/sec: 2882.78 - lr: 0.000045 - momentum: 0.000000 |
| 2026-10-29 11:34:22,402 epoch 2 - iter 5013/5579 - loss 0.34195704 - time (sec): 735.10 - samples/sec: 2886.85 - lr: 0.000047 - momentum: 0.000000 |
| 2026-10-29 11:35:44,125 epoch 2 - iter 5570/5579 - loss 0.34110199 - time (sec): 816.82 - samples/sec: 2883.33 - lr: 0.000050 - momentum: 0.000000 |
| 2026-10-29 11:35:45,359 ---------------------------------------------------------------------------------------------------- |
| 2026-10-29 11:35:45,359 EPOCH 2 done: loss 0.3411 - lr: 0.000050 |
| 2026-10-29 11:35:45,359 Saving model at current epoch since 'save_model_each_k_epochs=1' was set |
| 2026-10-29 11:37:17,345 DEV : loss 0.07375720143318176 - f1-score (micro avg) 0.8547 |
| 2026-10-29 11:37:17,432 saving best model |
| 2026-10-29 11:37:18,212 ---------------------------------------------------------------------------------------------------- |
| 2026-10-29 11:38:39,059 epoch 3 - iter 557/5579 - loss 0.32322892 - time (sec): 80.84 - samples/sec: 2912.02 - lr: 0.000050 - momentum: 0.000000 |
| 2026-10-29 11:40:00,496 epoch 3 - iter 1114/5579 - loss 0.32186943 - time (sec): 162.28 - samples/sec: 2906.15 - lr: 0.000049 - momentum: 0.000000 |
| 2026-10-29 11:41:25,001 epoch 3 - iter 1671/5579 - loss 0.31648625 - time (sec): 246.79 - samples/sec: 2870.45 - lr: 0.000049 - momentum: 0.000000 |
| 2026-10-29 11:42:46,815 epoch 3 - iter 2228/5579 - loss 0.31473342 - time (sec): 328.60 - samples/sec: 2880.76 - lr: 0.000049 - momentum: 0.000000 |
| 2026-10-29 11:44:08,109 epoch 3 - iter 2785/5579 - loss 0.31339832 - time (sec): 409.89 - samples/sec: 2883.06 - lr: 0.000049 - momentum: 0.000000 |
| 2026-10-29 11:45:29,276 epoch 3 - iter 3342/5579 - loss 0.31187892 - time (sec): 491.06 - samples/sec: 2885.71 - lr: 0.000048 - momentum: 0.000000 |
| 2026-10-29 11:46:50,352 epoch 3 - iter 3899/5579 - loss 0.30795691 - time (sec): 572.14 - samples/sec: 2882.56 - lr: 0.000048 - momentum: 0.000000 |
| 2026-10-29 11:48:12,445 epoch 3 - iter 4456/5579 - loss 0.30638711 - time (sec): 654.23 - samples/sec: 2883.38 - lr: 0.000048 - momentum: 0.000000 |
| 2026-10-29 11:49:33,483 epoch 3 - iter 5013/5579 - loss 0.30413089 - time (sec): 735.27 - samples/sec: 2885.16 - lr: 0.000048 - momentum: 0.000000 |
| 2026-10-29 11:50:54,535 epoch 3 - iter 5570/5579 - loss 0.30206995 - time (sec): 816.32 - samples/sec: 2884.76 - lr: 0.000047 - momentum: 0.000000 |
| 2026-10-29 11:50:55,830 ---------------------------------------------------------------------------------------------------- |
| 2026-10-29 11:50:55,830 EPOCH 3 done: loss 0.3021 - lr: 0.000047 |
| 2026-10-29 11:50:55,831 Saving model at current epoch since 'save_model_each_k_epochs=1' was set |
| 2026-10-29 11:52:31,409 DEV : loss 0.06683672219514847 - f1-score (micro avg) 0.8472 |
| 2026-10-29 11:52:31,490 ---------------------------------------------------------------------------------------------------- |
| 2026-10-29 11:53:52,069 epoch 4 - iter 557/5579 - loss 0.27362532 - time (sec): 80.58 - samples/sec: 2925.04 - lr: 0.000047 - momentum: 0.000000 |
| 2026-10-29 11:55:13,091 epoch 4 - iter 1114/5579 - loss 0.27507408 - time (sec): 161.60 - samples/sec: 2906.80 - lr: 0.000047 - momentum: 0.000000 |
| 2026-10-29 11:56:34,532 epoch 4 - iter 1671/5579 - loss 0.27488676 - time (sec): 243.04 - samples/sec: 2902.70 - lr: 0.000046 - momentum: 0.000000 |
| 2026-10-29 11:57:56,356 epoch 4 - iter 2228/5579 - loss 0.27204146 - time (sec): 324.86 - samples/sec: 2893.74 - lr: 0.000046 - momentum: 0.000000 |
| 2026-10-29 11:59:17,483 epoch 4 - iter 2785/5579 - loss 0.27009169 - time (sec): 405.99 - samples/sec: 2888.32 - lr: 0.000046 - momentum: 0.000000 |
| 2026-10-29 12:00:37,850 epoch 4 - iter 3342/5579 - loss 0.26788641 - time (sec): 486.36 - samples/sec: 2892.27 - lr: 0.000046 - momentum: 0.000000 |
| 2026-10-29 12:01:58,844 epoch 4 - iter 3899/5579 - loss 0.26577299 - time (sec): 567.35 - samples/sec: 2895.45 - lr: 0.000045 - momentum: 0.000000 |
| 2026-10-29 12:03:20,759 epoch 4 - iter 4456/5579 - loss 0.26425480 - time (sec): 649.27 - samples/sec: 2896.28 - lr: 0.000045 - momentum: 0.000000 |
| 2026-10-29 12:04:44,905 epoch 4 - iter 5013/5579 - loss 0.26336808 - time (sec): 733.41 - samples/sec: 2884.78 - lr: 0.000045 - momentum: 0.000000 |
| 2026-10-29 12:06:06,845 epoch 4 - iter 5570/5579 - loss 0.26182039 - time (sec): 815.35 - samples/sec: 2888.74 - lr: 0.000044 - momentum: 0.000000 |
| 2026-10-29 12:06:07,996 ---------------------------------------------------------------------------------------------------- |
| 2026-10-29 12:06:07,996 EPOCH 4 done: loss 0.2618 - lr: 0.000044 |
| 2026-10-29 12:06:07,996 Saving model at current epoch since 'save_model_each_k_epochs=1' was set |
| 2026-10-29 12:07:39,695 DEV : loss 0.05958981812000275 - f1-score (micro avg) 0.8503 |
| 2026-10-29 12:07:39,777 ---------------------------------------------------------------------------------------------------- |
| 2026-10-29 12:09:00,267 epoch 5 - iter 557/5579 - loss 0.23392708 - time (sec): 80.49 - samples/sec: 2895.46 - lr: 0.000044 - momentum: 0.000000 |
| 2026-10-29 12:10:21,737 epoch 5 - iter 1114/5579 - loss 0.23597266 - time (sec): 161.96 - samples/sec: 2880.79 - lr: 0.000044 - momentum: 0.000000 |
| 2026-10-29 12:11:44,022 epoch 5 - iter 1671/5579 - loss 0.23307977 - time (sec): 244.24 - samples/sec: 2879.86 - lr: 0.000044 - momentum: 0.000000 |
| 2026-10-29 12:13:03,923 epoch 5 - iter 2228/5579 - loss 0.23513003 - time (sec): 324.15 - samples/sec: 2888.09 - lr: 0.000043 - momentum: 0.000000 |
| 2026-10-29 12:14:25,147 epoch 5 - iter 2785/5579 - loss 0.23308136 - time (sec): 405.37 - samples/sec: 2894.20 - lr: 0.000043 - momentum: 0.000000 |
| 2026-10-29 12:15:49,761 epoch 5 - iter 3342/5579 - loss 0.23098197 - time (sec): 489.98 - samples/sec: 2882.68 - lr: 0.000043 - momentum: 0.000000 |
| 2026-10-29 12:17:10,311 epoch 5 - iter 3899/5579 - loss 0.22925154 - time (sec): 570.53 - samples/sec: 2886.10 - lr: 0.000043 - momentum: 0.000000 |
| 2026-10-29 12:18:31,428 epoch 5 - iter 4456/5579 - loss 0.22781743 - time (sec): 651.65 - samples/sec: 2890.03 - lr: 0.000042 - momentum: 0.000000 |
| 2026-10-29 12:19:52,795 epoch 5 - iter 5013/5579 - loss 0.22613009 - time (sec): 733.02 - samples/sec: 2891.14 - lr: 0.000042 - momentum: 0.000000 |
| 2026-10-29 12:21:14,147 epoch 5 - iter 5570/5579 - loss 0.22411286 - time (sec): 814.37 - samples/sec: 2892.02 - lr: 0.000042 - momentum: 0.000000 |
| 2026-10-29 12:21:15,431 ---------------------------------------------------------------------------------------------------- |
| 2026-10-29 12:21:15,431 EPOCH 5 done: loss 0.2241 - lr: 0.000042 |
| 2026-10-29 12:21:15,432 Saving model at current epoch since 'save_model_each_k_epochs=1' was set |
| 2026-10-29 12:22:47,286 DEV : loss 0.05807289853692055 - f1-score (micro avg) 0.8725 |
| 2026-10-29 12:22:47,370 saving best model |
| 2026-10-29 12:22:48,160 ---------------------------------------------------------------------------------------------------- |
| 2026-10-29 12:24:10,148 epoch 6 - iter 557/5579 - loss 0.19851654 - time (sec): 81.99 - samples/sec: 2896.12 - lr: 0.000041 - momentum: 0.000000 |
| 2026-10-29 12:25:31,798 epoch 6 - iter 1114/5579 - loss 0.20174685 - time (sec): 163.64 - samples/sec: 2879.33 - lr: 0.000041 - momentum: 0.000000 |
| 2026-10-29 12:26:55,754 epoch 6 - iter 1671/5579 - loss 0.20059126 - time (sec): 247.59 - samples/sec: 2849.47 - lr: 0.000041 - momentum: 0.000000 |
| 2026-10-29 12:28:17,866 epoch 6 - iter 2228/5579 - loss 0.19910174 - time (sec): 329.70 - samples/sec: 2859.78 - lr: 0.000041 - momentum: 0.000000 |
| 2026-10-29 12:29:38,742 epoch 6 - iter 2785/5579 - loss 0.19778860 - time (sec): 410.58 - samples/sec: 2869.58 - lr: 0.000040 - momentum: 0.000000 |
| 2026-10-29 12:31:00,767 epoch 6 - iter 3342/5579 - loss 0.19604283 - time (sec): 492.61 - samples/sec: 2868.94 - lr: 0.000040 - momentum: 0.000000 |
| 2026-10-29 12:32:22,077 epoch 6 - iter 3899/5579 - loss 0.19471407 - time (sec): 573.91 - samples/sec: 2870.19 - lr: 0.000040 - momentum: 0.000000 |
| 2026-10-29 12:33:42,914 epoch 6 - iter 4456/5579 - loss 0.19325787 - time (sec): 654.75 - samples/sec: 2876.56 - lr: 0.000039 - momentum: 0.000000 |
| 2026-10-29 12:35:03,880 epoch 6 - iter 5013/5579 - loss 0.19180697 - time (sec): 735.72 - samples/sec: 2880.22 - lr: 0.000039 - momentum: 0.000000 |
| 2026-10-29 12:36:25,664 epoch 6 - iter 5570/5579 - loss 0.18991550 - time (sec): 817.50 - samples/sec: 2880.89 - lr: 0.000039 - momentum: 0.000000 |
| 2026-10-29 12:36:26,947 ---------------------------------------------------------------------------------------------------- |
| 2026-10-29 12:36:26,947 EPOCH 6 done: loss 0.1899 - lr: 0.000039 |
| 2026-10-29 12:36:26,947 Saving model at current epoch since 'save_model_each_k_epochs=1' was set |
| 2026-10-29 12:38:03,125 DEV : loss 0.058688338845968246 - f1-score (micro avg) 0.8832 |
| 2026-10-29 12:38:03,208 saving best model |
| 2026-10-29 12:38:04,007 ---------------------------------------------------------------------------------------------------- |
| 2026-10-29 12:39:24,599 epoch 7 - iter 557/5579 - loss 0.17163184 - time (sec): 80.59 - samples/sec: 2931.04 - lr: 0.000039 - momentum: 0.000000 |
| 2026-10-29 12:40:45,669 epoch 7 - iter 1114/5579 - loss 0.16868352 - time (sec): 161.66 - samples/sec: 2915.31 - lr: 0.000038 - momentum: 0.000000 |
| 2026-10-29 12:42:07,647 epoch 7 - iter 1671/5579 - loss 0.16615177 - time (sec): 243.64 - samples/sec: 2905.10 - lr: 0.000038 - momentum: 0.000000 |
| 2026-10-29 12:43:28,245 epoch 7 - iter 2228/5579 - loss 0.16496529 - time (sec): 324.24 - samples/sec: 2902.67 - lr: 0.000038 - momentum: 0.000000 |
| 2026-10-29 12:44:48,898 epoch 7 - iter 2785/5579 - loss 0.16365526 - time (sec): 404.89 - samples/sec: 2908.18 - lr: 0.000038 - momentum: 0.000000 |
| 2026-10-29 12:46:14,427 epoch 7 - iter 3342/5579 - loss 0.16244566 - time (sec): 490.42 - samples/sec: 2876.58 - lr: 0.000037 - momentum: 0.000000 |
| 2026-10-29 12:47:39,438 epoch 7 - iter 3899/5579 - loss 0.16157028 - time (sec): 575.43 - samples/sec: 2861.44 - lr: 0.000037 - momentum: 0.000000 |
| 2026-10-29 12:49:04,626 epoch 7 - iter 4456/5579 - loss 0.16064610 - time (sec): 660.62 - samples/sec: 2850.55 - lr: 0.000037 - momentum: 0.000000 |
| 2026-10-29 12:50:30,108 epoch 7 - iter 5013/5579 - loss 0.15896472 - time (sec): 746.10 - samples/sec: 2839.03 - lr: 0.000036 - momentum: 0.000000 |
| 2026-10-29 12:52:00,193 epoch 7 - iter 5570/5579 - loss 0.15733813 - time (sec): 836.18 - samples/sec: 2816.43 - lr: 0.000036 - momentum: 0.000000 |
| 2026-10-29 12:52:01,600 ---------------------------------------------------------------------------------------------------- |
| 2026-10-29 12:52:01,600 EPOCH 7 done: loss 0.1573 - lr: 0.000036 |
| 2026-10-29 12:52:01,600 Saving model at current epoch since 'save_model_each_k_epochs=1' was set |
| 2026-10-29 12:53:38,943 DEV : loss 0.055343907326459885 - f1-score (micro avg) 0.8841 |
| 2026-10-29 12:53:39,030 saving best model |
| 2026-10-29 12:53:39,906 ---------------------------------------------------------------------------------------------------- |
| 2026-10-29 12:55:05,565 epoch 8 - iter 557/5579 - loss 0.13938168 - time (sec): 85.66 - samples/sec: 2732.64 - lr: 0.000036 - momentum: 0.000000 |
| 2026-10-29 12:56:31,901 epoch 8 - iter 1114/5579 - loss 0.13827679 - time (sec): 171.99 - samples/sec: 2738.51 - lr: 0.000036 - momentum: 0.000000 |
| 2026-10-29 12:57:58,002 epoch 8 - iter 1671/5579 - loss 0.13747612 - time (sec): 258.09 - samples/sec: 2738.94 - lr: 0.000035 - momentum: 0.000000 |
| 2026-10-29 12:59:23,209 epoch 8 - iter 2228/5579 - loss 0.13530167 - time (sec): 343.30 - samples/sec: 2746.17 - lr: 0.000035 - momentum: 0.000000 |
| 2026-10-29 13:00:49,794 epoch 8 - iter 2785/5579 - loss 0.13437980 - time (sec): 429.89 - samples/sec: 2745.93 - lr: 0.000035 - momentum: 0.000000 |
| 2026-10-29 13:02:15,109 epoch 8 - iter 3342/5579 - loss 0.13453104 - time (sec): 515.20 - samples/sec: 2746.24 - lr: 0.000034 - momentum: 0.000000 |
| 2026-10-29 13:03:44,578 epoch 8 - iter 3899/5579 - loss 0.13361116 - time (sec): 604.67 - samples/sec: 2726.63 - lr: 0.000034 - momentum: 0.000000 |
| 2026-10-29 13:05:09,291 epoch 8 - iter 4456/5579 - loss 0.13255525 - time (sec): 689.38 - samples/sec: 2733.20 - lr: 0.000034 - momentum: 0.000000 |
| 2026-10-29 13:06:34,971 epoch 8 - iter 5013/5579 - loss 0.13187366 - time (sec): 775.06 - samples/sec: 2737.92 - lr: 0.000034 - momentum: 0.000000 |
| 2026-10-29 13:07:59,864 epoch 8 - iter 5570/5579 - loss 0.13032230 - time (sec): 859.96 - samples/sec: 2738.86 - lr: 0.000033 - momentum: 0.000000 |
| 2026-10-29 13:08:01,142 ---------------------------------------------------------------------------------------------------- |
| 2026-10-29 13:08:01,142 EPOCH 8 done: loss 0.1303 - lr: 0.000033 |
| 2026-10-29 13:08:01,142 Saving model at current epoch since 'save_model_each_k_epochs=1' was set |
| 2026-10-29 13:09:38,717 DEV : loss 0.05920719727873802 - f1-score (micro avg) 0.8868 |
| 2026-10-29 13:09:38,806 saving best model |
| 2026-10-29 13:09:39,682 ---------------------------------------------------------------------------------------------------- |
| 2026-10-29 13:11:05,722 epoch 9 - iter 557/5579 - loss 0.11658757 - time (sec): 86.04 - samples/sec: 2721.23 - lr: 0.000033 - momentum: 0.000000 |
| 2026-10-29 13:12:30,462 epoch 9 - iter 1114/5579 - loss 0.11649605 - time (sec): 170.78 - samples/sec: 2741.84 - lr: 0.000033 - momentum: 0.000000 |
| 2026-10-29 13:13:58,694 epoch 9 - iter 1671/5579 - loss 0.11538758 - time (sec): 259.01 - samples/sec: 2716.87 - lr: 0.000033 - momentum: 0.000000 |
| 2026-10-29 13:15:24,066 epoch 9 - iter 2228/5579 - loss 0.11394943 - time (sec): 344.38 - samples/sec: 2732.52 - lr: 0.000032 - momentum: 0.000000 |
| 2026-10-29 13:16:49,154 epoch 9 - iter 2785/5579 - loss 0.11354693 - time (sec): 429.47 - samples/sec: 2736.55 - lr: 0.000032 - momentum: 0.000000 |
| 2026-10-29 13:18:15,090 epoch 9 - iter 3342/5579 - loss 0.11288969 - time (sec): 515.41 - samples/sec: 2737.58 - lr: 0.000032 - momentum: 0.000000 |
| 2026-10-29 13:19:41,122 epoch 9 - iter 3899/5579 - loss 0.11220893 - time (sec): 601.44 - samples/sec: 2741.10 - lr: 0.000031 - momentum: 0.000000 |
| 2026-10-29 13:21:06,979 epoch 9 - iter 4456/5579 - loss 0.11162845 - time (sec): 687.30 - samples/sec: 2743.31 - lr: 0.000031 - momentum: 0.000000 |
| 2026-10-29 13:22:33,370 epoch 9 - iter 5013/5579 - loss 0.11052746 - time (sec): 773.69 - samples/sec: 2741.80 - lr: 0.000031 - momentum: 0.000000 |
| 2026-10-29 13:23:59,210 epoch 9 - iter 5570/5579 - loss 0.10938783 - time (sec): 859.53 - samples/sec: 2740.08 - lr: 0.000031 - momentum: 0.000000 |
| 2026-10-29 13:24:00,512 ---------------------------------------------------------------------------------------------------- |
| 2026-10-29 13:24:00,513 EPOCH 9 done: loss 0.1094 - lr: 0.000031 |
| 2026-10-29 13:24:00,513 Saving model at current epoch since 'save_model_each_k_epochs=1' was set |
| 2026-10-29 13:25:42,720 DEV : loss 0.052628327161073685 - f1-score (micro avg) 0.895 |
| 2026-10-29 13:25:42,810 saving best model |
| 2026-10-29 13:25:43,639 ---------------------------------------------------------------------------------------------------- |
| 2026-10-29 13:27:09,146 epoch 10 - iter 557/5579 - loss 0.09525402 - time (sec): 85.50 - samples/sec: 2773.79 - lr: 0.000030 - momentum: 0.000000 |
| 2026-10-29 13:28:34,669 epoch 10 - iter 1114/5579 - loss 0.09342600 - time (sec): 171.03 - samples/sec: 2769.20 - lr: 0.000030 - momentum: 0.000000 |
| 2026-10-29 13:29:59,282 epoch 10 - iter 1671/5579 - loss 0.09354923 - time (sec): 255.64 - samples/sec: 2766.43 - lr: 0.000030 - momentum: 0.000000 |
| 2026-10-29 13:31:24,706 epoch 10 - iter 2228/5579 - loss 0.09303583 - time (sec): 341.07 - samples/sec: 2759.44 - lr: 0.000029 - momentum: 0.000000 |
| 2026-10-29 13:32:50,047 epoch 10 - iter 2785/5579 - loss 0.09356955 - time (sec): 426.41 - samples/sec: 2758.81 - lr: 0.000029 - momentum: 0.000000 |
| 2026-10-29 13:34:14,378 epoch 10 - iter 3342/5579 - loss 0.09328635 - time (sec): 510.74 - samples/sec: 2769.47 - lr: 0.000029 - momentum: 0.000000 |
| 2026-10-29 13:35:39,670 epoch 10 - iter 3899/5579 - loss 0.09261667 - time (sec): 596.03 - samples/sec: 2766.09 - lr: 0.000029 - momentum: 0.000000 |
| 2026-10-29 13:37:05,856 epoch 10 - iter 4456/5579 - loss 0.09197920 - time (sec): 682.22 - samples/sec: 2761.70 - lr: 0.000028 - momentum: 0.000000 |
| 2026-10-29 13:38:31,709 epoch 10 - iter 5013/5579 - loss 0.09157568 - time (sec): 768.07 - samples/sec: 2761.62 - lr: 0.000028 - momentum: 0.000000 |
| 2026-10-29 13:40:00,504 epoch 10 - iter 5570/5579 - loss 0.09086475 - time (sec): 856.86 - samples/sec: 2748.84 - lr: 0.000028 - momentum: 0.000000 |
| 2026-10-29 13:40:01,753 ---------------------------------------------------------------------------------------------------- |
| 2026-10-29 13:40:01,754 EPOCH 10 done: loss 0.0908 - lr: 0.000028 |
| 2026-10-29 13:40:01,754 Saving model at current epoch since 'save_model_each_k_epochs=1' was set |
| 2026-10-29 13:41:40,160 DEV : loss 0.050733957439661026 - f1-score (micro avg) 0.8984 |
| 2026-10-29 13:41:40,253 saving best model |
| 2026-10-29 13:41:41,119 ---------------------------------------------------------------------------------------------------- |
| 2026-10-29 13:43:06,692 epoch 11 - iter 557/5579 - loss 0.08170004 - time (sec): 85.57 - samples/sec: 2737.83 - lr: 0.000028 - momentum: 0.000000 |
| 2026-10-29 13:44:32,759 epoch 11 - iter 1114/5579 - loss 0.08325461 - time (sec): 171.64 - samples/sec: 2759.25 - lr: 0.000027 - momentum: 0.000000 |
| 2026-10-29 13:45:57,787 epoch 11 - iter 1671/5579 - loss 0.08284715 - time (sec): 256.67 - samples/sec: 2761.67 - lr: 0.000027 - momentum: 0.000000 |
| 2026-10-29 13:47:19,091 epoch 11 - iter 2228/5579 - loss 0.08176326 - time (sec): 337.97 - samples/sec: 2796.62 - lr: 0.000027 - momentum: 0.000000 |
| 2026-10-29 13:48:38,930 epoch 11 - iter 2785/5579 - loss 0.08093871 - time (sec): 417.81 - samples/sec: 2817.95 - lr: 0.000026 - momentum: 0.000000 |
| 2026-10-29 13:50:00,762 epoch 11 - iter 3342/5579 - loss 0.08042352 - time (sec): 499.64 - samples/sec: 2827.46 - lr: 0.000026 - momentum: 0.000000 |
| 2026-10-29 13:51:25,743 epoch 11 - iter 3899/5579 - loss 0.07989006 - time (sec): 584.62 - samples/sec: 2817.31 - lr: 0.000026 - momentum: 0.000000 |
| 2026-10-29 13:52:46,246 epoch 11 - iter 4456/5579 - loss 0.07935116 - time (sec): 665.13 - samples/sec: 2828.32 - lr: 0.000026 - momentum: 0.000000 |
| 2026-10-29 13:54:08,020 epoch 11 - iter 5013/5579 - loss 0.07858721 - time (sec): 746.90 - samples/sec: 2835.76 - lr: 0.000025 - momentum: 0.000000 |
| 2026-10-29 13:55:30,021 epoch 11 - iter 5570/5579 - loss 0.07816694 - time (sec): 828.90 - samples/sec: 2841.16 - lr: 0.000025 - momentum: 0.000000 |
| 2026-10-29 13:55:31,269 ---------------------------------------------------------------------------------------------------- |
| 2026-10-29 13:55:31,269 EPOCH 11 done: loss 0.0782 - lr: 0.000025 |
| 2026-10-29 13:55:31,269 Saving model at current epoch since 'save_model_each_k_epochs=1' was set |
| 2026-10-29 13:57:07,666 DEV : loss 0.047053784132003784 - f1-score (micro avg) 0.9005 |
| 2026-10-29 13:57:07,751 saving best model |
| 2026-10-29 13:57:08,593 ---------------------------------------------------------------------------------------------------- |
| 2026-10-29 13:58:30,031 epoch 12 - iter 557/5579 - loss 0.06734793 - time (sec): 81.44 - samples/sec: 2868.76 - lr: 0.000025 - momentum: 0.000000 |
| 2026-10-29 13:59:52,124 epoch 12 - iter 1114/5579 - loss 0.06785637 - time (sec): 163.53 - samples/sec: 2876.28 - lr: 0.000024 - momentum: 0.000000 |
| 2026-10-29 14:01:13,223 epoch 12 - iter 1671/5579 - loss 0.06768999 - time (sec): 244.63 - samples/sec: 2887.35 - lr: 0.000024 - momentum: 0.000000 |
| 2026-10-29 14:02:38,239 epoch 12 - iter 2228/5579 - loss 0.06847354 - time (sec): 329.64 - samples/sec: 2862.70 - lr: 0.000024 - momentum: 0.000000 |
| 2026-10-29 14:04:00,859 epoch 12 - iter 2785/5579 - loss 0.06824984 - time (sec): 412.27 - samples/sec: 2873.52 - lr: 0.000024 - momentum: 0.000000 |
| 2026-10-29 14:05:21,947 epoch 12 - iter 3342/5579 - loss 0.06799071 - time (sec): 493.35 - samples/sec: 2872.69 - lr: 0.000023 - momentum: 0.000000 |
| 2026-10-29 14:06:43,033 epoch 12 - iter 3899/5579 - loss 0.06759135 - time (sec): 574.44 - samples/sec: 2874.39 - lr: 0.000023 - momentum: 0.000000 |
| 2026-10-29 14:08:04,916 epoch 12 - iter 4456/5579 - loss 0.06720636 - time (sec): 656.32 - samples/sec: 2874.71 - lr: 0.000023 - momentum: 0.000000 |
| 2026-10-29 14:09:26,631 epoch 12 - iter 5013/5579 - loss 0.06726618 - time (sec): 738.04 - samples/sec: 2873.41 - lr: 0.000023 - momentum: 0.000000 |
| 2026-10-29 14:10:47,660 epoch 12 - iter 5570/5579 - loss 0.06687179 - time (sec): 819.07 - samples/sec: 2874.95 - lr: 0.000022 - momentum: 0.000000 |
| 2026-10-29 14:10:48,948 ---------------------------------------------------------------------------------------------------- |
| 2026-10-29 14:10:48,949 EPOCH 12 done: loss 0.0669 - lr: 0.000022 |
| 2026-10-29 14:10:48,949 Saving model at current epoch since 'save_model_each_k_epochs=1' was set |
| 2026-10-29 14:12:21,606 DEV : loss 0.05575225502252579 - f1-score (micro avg) 0.9002 |
| 2026-10-29 14:12:21,692 ---------------------------------------------------------------------------------------------------- |
| 2026-10-29 14:13:46,937 epoch 13 - iter 557/5579 - loss 0.05925823 - time (sec): 85.24 - samples/sec: 2758.72 - lr: 0.000022 - momentum: 0.000000 |
| 2026-10-29 14:15:09,106 epoch 13 - iter 1114/5579 - loss 0.05911578 - time (sec): 167.41 - samples/sec: 2820.14 - lr: 0.000022 - momentum: 0.000000 |
| 2026-10-29 14:16:30,141 epoch 13 - iter 1671/5579 - loss 0.06003023 - time (sec): 248.45 - samples/sec: 2852.30 - lr: 0.000021 - momentum: 0.000000 |
| 2026-10-29 14:17:49,928 epoch 13 - iter 2228/5579 - loss 0.06102632 - time (sec): 328.23 - samples/sec: 2868.45 - lr: 0.000021 - momentum: 0.000000 |
| 2026-10-29 14:19:10,633 epoch 13 - iter 2785/5579 - loss 0.06064766 - time (sec): 408.94 - samples/sec: 2874.30 - lr: 0.000021 - momentum: 0.000000 |
| 2026-10-29 14:20:32,318 epoch 13 - iter 3342/5579 - loss 0.06025582 - time (sec): 490.63 - samples/sec: 2879.80 - lr: 0.000021 - momentum: 0.000000 |
| 2026-10-29 14:21:53,760 epoch 13 - iter 3899/5579 - loss 0.05996714 - time (sec): 572.07 - samples/sec: 2880.76 - lr: 0.000020 - momentum: 0.000000 |
| 2026-10-29 14:23:15,362 epoch 13 - iter 4456/5579 - loss 0.05959631 - time (sec): 653.67 - samples/sec: 2887.27 - lr: 0.000020 - momentum: 0.000000 |
| 2026-10-29 14:24:36,970 epoch 13 - iter 5013/5579 - loss 0.05951605 - time (sec): 735.28 - samples/sec: 2885.79 - lr: 0.000020 - momentum: 0.000000 |
| 2026-10-29 14:26:02,158 epoch 13 - iter 5570/5579 - loss 0.05942707 - time (sec): 820.47 - samples/sec: 2870.59 - lr: 0.000019 - momentum: 0.000000 |
| 2026-10-29 14:26:03,380 ---------------------------------------------------------------------------------------------------- |
| 2026-10-29 14:26:03,380 EPOCH 13 done: loss 0.0594 - lr: 0.000019 |
| 2026-10-29 14:26:03,380 Saving model at current epoch since 'save_model_each_k_epochs=1' was set |
| 2026-10-29 14:27:35,776 DEV : loss 0.05230270326137543 - f1-score (micro avg) 0.9039 |
| 2026-10-29 14:27:35,863 saving best model |
| 2026-10-29 14:27:36,665 ---------------------------------------------------------------------------------------------------- |
| 2026-10-29 14:28:58,482 epoch 14 - iter 557/5579 - loss 0.05269678 - time (sec): 81.82 - samples/sec: 2863.20 - lr: 0.000019 - momentum: 0.000000 |
| 2026-10-29 14:30:20,378 epoch 14 - iter 1114/5579 - loss 0.05267670 - time (sec): 163.71 - samples/sec: 2873.88 - lr: 0.000019 - momentum: 0.000000 |
| 2026-10-29 14:31:41,429 epoch 14 - iter 1671/5579 - loss 0.05246863 - time (sec): 244.76 - samples/sec: 2886.21 - lr: 0.000019 - momentum: 0.000000 |
| 2026-10-29 14:33:03,673 epoch 14 - iter 2228/5579 - loss 0.05287643 - time (sec): 327.01 - samples/sec: 2884.97 - lr: 0.000018 - momentum: 0.000000 |
| 2026-10-29 14:34:24,039 epoch 14 - iter 2785/5579 - loss 0.05301162 - time (sec): 407.37 - samples/sec: 2890.24 - lr: 0.000018 - momentum: 0.000000 |
| 2026-10-29 14:35:45,374 epoch 14 - iter 3342/5579 - loss 0.05291394 - time (sec): 488.71 - samples/sec: 2893.06 - lr: 0.000018 - momentum: 0.000000 |
| 2026-10-29 14:37:10,759 epoch 14 - iter 3899/5579 - loss 0.05244442 - time (sec): 574.09 - samples/sec: 2872.31 - lr: 0.000018 - momentum: 0.000000 |
| 2026-10-29 14:38:32,754 epoch 14 - iter 4456/5579 - loss 0.05245332 - time (sec): 656.09 - samples/sec: 2874.36 - lr: 0.000017 - momentum: 0.000000 |
| 2026-10-29 14:39:54,209 epoch 14 - iter 5013/5579 - loss 0.05248046 - time (sec): 737.54 - samples/sec: 2875.63 - lr: 0.000017 - momentum: 0.000000 |
| 2026-10-29 14:41:14,989 epoch 14 - iter 5570/5579 - loss 0.05225152 - time (sec): 818.32 - samples/sec: 2877.69 - lr: 0.000017 - momentum: 0.000000 |
| 2026-10-29 14:41:16,249 ---------------------------------------------------------------------------------------------------- |
| 2026-10-29 14:41:16,249 EPOCH 14 done: loss 0.0522 - lr: 0.000017 |
| 2026-10-29 14:41:16,250 Saving model at current epoch since 'save_model_each_k_epochs=1' was set |
| 2026-10-29 14:42:51,757 DEV : loss 0.061986956745386124 - f1-score (micro avg) 0.9014 |
| 2026-10-29 14:42:51,844 ---------------------------------------------------------------------------------------------------- |
| 2026-10-29 14:44:12,615 epoch 15 - iter 557/5579 - loss 0.05032505 - time (sec): 80.77 - samples/sec: 2921.37 - lr: 0.000016 - momentum: 0.000000 |
| 2026-10-29 14:45:32,995 epoch 15 - iter 1114/5579 - loss 0.04847083 - time (sec): 161.15 - samples/sec: 2912.84 - lr: 0.000016 - momentum: 0.000000 |
| 2026-10-29 14:46:54,591 epoch 15 - iter 1671/5579 - loss 0.04796490 - time (sec): 242.75 - samples/sec: 2904.16 - lr: 0.000016 - momentum: 0.000000 |
| 2026-10-29 14:48:20,621 epoch 15 - iter 2228/5579 - loss 0.04774807 - time (sec): 328.78 - samples/sec: 2861.06 - lr: 0.000016 - momentum: 0.000000 |
| 2026-10-29 14:49:41,881 epoch 15 - iter 2785/5579 - loss 0.04755896 - time (sec): 410.04 - samples/sec: 2863.08 - lr: 0.000015 - momentum: 0.000000 |
| 2026-10-29 14:51:03,232 epoch 15 - iter 3342/5579 - loss 0.04731649 - time (sec): 491.39 - samples/sec: 2874.89 - lr: 0.000015 - momentum: 0.000000 |
| 2026-10-29 14:52:23,956 epoch 15 - iter 3899/5579 - loss 0.04695715 - time (sec): 572.11 - samples/sec: 2880.83 - lr: 0.000015 - momentum: 0.000000 |
| 2026-10-29 14:53:43,892 epoch 15 - iter 4456/5579 - loss 0.04689237 - time (sec): 652.05 - samples/sec: 2888.28 - lr: 0.000014 - momentum: 0.000000 |
| 2026-10-29 14:55:04,588 epoch 15 - iter 5013/5579 - loss 0.04685204 - time (sec): 732.74 - samples/sec: 2893.68 - lr: 0.000014 - momentum: 0.000000 |
| 2026-10-29 14:56:24,948 epoch 15 - iter 5570/5579 - loss 0.04652597 - time (sec): 813.10 - samples/sec: 2896.54 - lr: 0.000014 - momentum: 0.000000 |
| 2026-10-29 14:56:26,167 ---------------------------------------------------------------------------------------------------- |
| 2026-10-29 14:56:26,168 EPOCH 15 done: loss 0.0465 - lr: 0.000014 |
| 2026-10-29 14:56:26,168 Saving model at current epoch since 'save_model_each_k_epochs=1' was set |
| 2026-10-29 14:57:58,727 DEV : loss 0.05928361043334007 - f1-score (micro avg) 0.9062 |
| 2026-10-29 14:57:58,814 saving best model |
| 2026-10-29 14:57:59,618 ---------------------------------------------------------------------------------------------------- |
| 2026-10-29 14:59:24,476 epoch 16 - iter 557/5579 - loss 0.04351964 - time (sec): 84.86 - samples/sec: 2759.07 - lr: 0.000014 - momentum: 0.000000 |
| 2026-10-29 15:00:45,419 epoch 16 - iter 1114/5579 - loss 0.04311430 - time (sec): 165.80 - samples/sec: 2816.63 - lr: 0.000013 - momentum: 0.000000 |
| 2026-10-29 15:02:06,635 epoch 16 - iter 1671/5579 - loss 0.04279316 - time (sec): 247.02 - samples/sec: 2845.66 - lr: 0.000013 - momentum: 0.000000 |
| 2026-10-29 15:03:27,087 epoch 16 - iter 2228/5579 - loss 0.04215418 - time (sec): 327.47 - samples/sec: 2865.44 - lr: 0.000013 - momentum: 0.000000 |
| 2026-10-29 15:04:47,842 epoch 16 - iter 2785/5579 - loss 0.04191772 - time (sec): 408.22 - samples/sec: 2875.63 - lr: 0.000013 - momentum: 0.000000 |
| 2026-10-29 15:06:08,907 epoch 16 - iter 3342/5579 - loss 0.04197374 - time (sec): 489.29 - samples/sec: 2886.65 - lr: 0.000012 - momentum: 0.000000 |
| 2026-10-29 15:07:28,995 epoch 16 - iter 3899/5579 - loss 0.04219253 - time (sec): 569.38 - samples/sec: 2889.82 - lr: 0.000012 - momentum: 0.000000 |
| 2026-10-29 15:08:49,720 epoch 16 - iter 4456/5579 - loss 0.04227352 - time (sec): 650.10 - samples/sec: 2894.45 - lr: 0.000012 - momentum: 0.000000 |
| 2026-10-29 15:10:10,831 epoch 16 - iter 5013/5579 - loss 0.04217651 - time (sec): 731.21 - samples/sec: 2898.23 - lr: 0.000011 - momentum: 0.000000 |
| 2026-10-29 15:11:31,922 epoch 16 - iter 5570/5579 - loss 0.04209559 - time (sec): 812.30 - samples/sec: 2899.26 - lr: 0.000011 - momentum: 0.000000 |
| 2026-10-29 15:11:33,189 ---------------------------------------------------------------------------------------------------- |
| 2026-10-29 15:11:33,189 EPOCH 16 done: loss 0.0421 - lr: 0.000011 |
| 2026-10-29 15:11:33,189 Saving model at current epoch since 'save_model_each_k_epochs=1' was set |
| 2026-10-29 15:13:08,723 DEV : loss 0.06906117498874664 - f1-score (micro avg) 0.9067 |
| 2026-10-29 15:13:08,810 saving best model |
| 2026-10-29 15:13:09,627 ---------------------------------------------------------------------------------------------------- |
| 2026-10-29 15:14:31,370 epoch 17 - iter 557/5579 - loss 0.03866932 - time (sec): 81.74 - samples/sec: 2882.16 - lr: 0.000011 - momentum: 0.000000 |
| 2026-10-29 15:15:52,540 epoch 17 - iter 1114/5579 - loss 0.03892260 - time (sec): 162.91 - samples/sec: 2880.14 - lr: 0.000011 - momentum: 0.000000 |
| 2026-10-29 15:17:14,963 epoch 17 - iter 1671/5579 - loss 0.03888809 - time (sec): 245.33 - samples/sec: 2893.10 - lr: 0.000010 - momentum: 0.000000 |
| 2026-10-29 15:18:36,623 epoch 17 - iter 2228/5579 - loss 0.03906852 - time (sec): 326.99 - samples/sec: 2894.67 - lr: 0.000010 - momentum: 0.000000 |
| 2026-10-29 15:19:57,838 epoch 17 - iter 2785/5579 - loss 0.03906329 - time (sec): 408.21 - samples/sec: 2899.09 - lr: 0.000010 - momentum: 0.000000 |
| 2026-10-29 15:21:18,410 epoch 17 - iter 3342/5579 - loss 0.03877460 - time (sec): 488.78 - samples/sec: 2898.18 - lr: 0.000009 - momentum: 0.000000 |
| 2026-10-29 15:22:39,325 epoch 17 - iter 3899/5579 - loss 0.03902839 - time (sec): 569.70 - samples/sec: 2899.60 - lr: 0.000009 - momentum: 0.000000 |
| 2026-10-29 15:24:04,255 epoch 17 - iter 4456/5579 - loss 0.03904899 - time (sec): 654.63 - samples/sec: 2882.77 - lr: 0.000009 - momentum: 0.000000 |
| 2026-10-29 15:25:25,262 epoch 17 - iter 5013/5579 - loss 0.03875959 - time (sec): 735.63 - samples/sec: 2881.60 - lr: 0.000009 - momentum: 0.000000 |
| 2026-10-29 15:26:46,409 epoch 17 - iter 5570/5579 - loss 0.03857513 - time (sec): 816.78 - samples/sec: 2883.65 - lr: 0.000008 - momentum: 0.000000 |
| 2026-10-29 15:26:47,593 ---------------------------------------------------------------------------------------------------- |
| 2026-10-29 15:26:47,593 EPOCH 17 done: loss 0.0386 - lr: 0.000008 |
| 2026-10-29 15:26:47,593 Saving model at current epoch since 'save_model_each_k_epochs=1' was set |
| 2026-10-29 15:28:20,705 DEV : loss 0.07172158360481262 - f1-score (micro avg) 0.9098 |
| 2026-10-29 15:28:20,792 saving best model |
| 2026-10-29 15:28:21,671 ---------------------------------------------------------------------------------------------------- |
| 2026-10-29 15:29:43,274 epoch 18 - iter 557/5579 - loss 0.03582505 - time (sec): 81.60 - samples/sec: 2877.77 - lr: 0.000008 - momentum: 0.000000 |
| 2026-10-29 15:31:04,615 epoch 18 - iter 1114/5579 - loss 0.03559863 - time (sec): 162.94 - samples/sec: 2892.69 - lr: 0.000008 - momentum: 0.000000 |
| 2026-10-29 15:32:25,533 epoch 18 - iter 1671/5579 - loss 0.03532770 - time (sec): 243.86 - samples/sec: 2887.73 - lr: 0.000008 - momentum: 0.000000 |
| 2026-10-29 15:33:46,315 epoch 18 - iter 2228/5579 - loss 0.03553293 - time (sec): 324.64 - samples/sec: 2898.99 - lr: 0.000007 - momentum: 0.000000 |
| 2026-10-29 15:35:11,554 epoch 18 - iter 2785/5579 - loss 0.03566856 - time (sec): 409.88 - samples/sec: 2867.48 - lr: 0.000007 - momentum: 0.000000 |
| 2026-10-29 15:36:33,620 epoch 18 - iter 3342/5579 - loss 0.03566966 - time (sec): 491.95 - samples/sec: 2867.97 - lr: 0.000007 - momentum: 0.000000 |
| 2026-10-29 15:37:54,738 epoch 18 - iter 3899/5579 - loss 0.03580435 - time (sec): 573.07 - samples/sec: 2874.20 - lr: 0.000006 - momentum: 0.000000 |
| 2026-10-29 15:39:16,464 epoch 18 - iter 4456/5579 - loss 0.03564660 - time (sec): 654.79 - samples/sec: 2876.40 - lr: 0.000006 - momentum: 0.000000 |
| 2026-10-29 15:40:36,904 epoch 18 - iter 5013/5579 - loss 0.03560880 - time (sec): 735.23 - samples/sec: 2884.31 - lr: 0.000006 - momentum: 0.000000 |
| 2026-10-29 15:41:57,083 epoch 18 - iter 5570/5579 - loss 0.03533258 - time (sec): 815.41 - samples/sec: 2888.05 - lr: 0.000006 - momentum: 0.000000 |
| 2026-10-29 15:41:58,347 ---------------------------------------------------------------------------------------------------- |
| 2026-10-29 15:41:58,348 EPOCH 18 done: loss 0.0353 - lr: 0.000006 |
| 2026-10-29 15:41:58,348 Saving model at current epoch since 'save_model_each_k_epochs=1' was set |
| 2026-10-29 15:43:32,736 DEV : loss 0.07542765140533447 - f1-score (micro avg) 0.9106 |
| 2026-10-29 15:43:32,828 saving best model |
| 2026-10-29 15:43:33,634 ---------------------------------------------------------------------------------------------------- |
| 2026-10-29 15:44:55,790 epoch 19 - iter 557/5579 - loss 0.03281103 - time (sec): 82.15 - samples/sec: 2882.15 - lr: 0.000005 - momentum: 0.000000 |
| 2026-10-29 15:46:21,211 epoch 19 - iter 1114/5579 - loss 0.03320277 - time (sec): 167.58 - samples/sec: 2810.23 - lr: 0.000005 - momentum: 0.000000 |
| 2026-10-29 15:47:41,897 epoch 19 - iter 1671/5579 - loss 0.03289690 - time (sec): 248.26 - samples/sec: 2832.23 - lr: 0.000005 - momentum: 0.000000 |
| 2026-10-29 15:49:03,135 epoch 19 - iter 2228/5579 - loss 0.03281427 - time (sec): 329.50 - samples/sec: 2848.96 - lr: 0.000004 - momentum: 0.000000 |
| 2026-10-29 15:50:24,548 epoch 19 - iter 2785/5579 - loss 0.03278373 - time (sec): 410.91 - samples/sec: 2861.88 - lr: 0.000004 - momentum: 0.000000 |
| 2026-10-29 15:51:45,013 epoch 19 - iter 3342/5579 - loss 0.03284259 - time (sec): 491.38 - samples/sec: 2872.91 - lr: 0.000004 - momentum: 0.000000 |
| 2026-10-29 15:53:05,804 epoch 19 - iter 3899/5579 - loss 0.03302192 - time (sec): 572.17 - samples/sec: 2881.18 - lr: 0.000004 - momentum: 0.000000 |
| 2026-10-29 15:54:26,239 epoch 19 - iter 4456/5579 - loss 0.03300898 - time (sec): 652.60 - samples/sec: 2885.45 - lr: 0.000003 - momentum: 0.000000 |
| 2026-10-29 15:55:46,460 epoch 19 - iter 5013/5579 - loss 0.03294982 - time (sec): 732.82 - samples/sec: 2889.25 - lr: 0.000003 - momentum: 0.000000 |
| 2026-10-29 15:57:07,675 epoch 19 - iter 5570/5579 - loss 0.03285316 - time (sec): 814.04 - samples/sec: 2893.43 - lr: 0.000003 - momentum: 0.000000 |
| 2026-10-29 15:57:08,869 ---------------------------------------------------------------------------------------------------- |
| 2026-10-29 15:57:08,869 EPOCH 19 done: loss 0.0328 - lr: 0.000003 |
| 2026-10-29 15:57:08,869 Saving model at current epoch since 'save_model_each_k_epochs=1' was set |
| 2026-10-29 15:58:47,878 DEV : loss 0.08188489079475403 - f1-score (micro avg) 0.9115 |
| 2026-10-29 15:58:47,966 saving best model |
| 2026-10-29 15:58:48,826 ---------------------------------------------------------------------------------------------------- |
| 2026-10-29 16:00:09,613 epoch 20 - iter 557/5579 - loss 0.03045550 - time (sec): 80.79 - samples/sec: 2912.41 - lr: 0.000003 - momentum: 0.000000 |
| 2026-10-29 16:01:30,601 epoch 20 - iter 1114/5579 - loss 0.03059765 - time (sec): 161.77 - samples/sec: 2910.05 - lr: 0.000002 - momentum: 0.000000 |
| 2026-10-29 16:02:51,141 epoch 20 - iter 1671/5579 - loss 0.03052362 - time (sec): 242.31 - samples/sec: 2899.08 - lr: 0.000002 - momentum: 0.000000 |
| 2026-10-29 16:04:12,645 epoch 20 - iter 2228/5579 - loss 0.03089540 - time (sec): 323.82 - samples/sec: 2897.57 - lr: 0.000002 - momentum: 0.000000 |
| 2026-10-29 16:05:34,366 epoch 20 - iter 2785/5579 - loss 0.03114926 - time (sec): 405.54 - samples/sec: 2897.67 - lr: 0.000001 - momentum: 0.000000 |
| 2026-10-29 16:06:55,216 epoch 20 - iter 3342/5579 - loss 0.03134710 - time (sec): 486.39 - samples/sec: 2901.40 - lr: 0.000001 - momentum: 0.000000 |
| 2026-10-29 16:08:16,949 epoch 20 - iter 3899/5579 - loss 0.03132706 - time (sec): 568.12 - samples/sec: 2899.04 - lr: 0.000001 - momentum: 0.000000 |
| 2026-10-29 16:09:41,400 epoch 20 - iter 4456/5579 - loss 0.03115717 - time (sec): 652.57 - samples/sec: 2881.29 - lr: 0.000001 - momentum: 0.000000 |
| 2026-10-29 16:11:03,188 epoch 20 - iter 5013/5579 - loss 0.03132381 - time (sec): 734.36 - samples/sec: 2884.93 - lr: 0.000000 - momentum: 0.000000 |
| 2026-10-29 16:12:24,447 epoch 20 - iter 5570/5579 - loss 0.03116131 - time (sec): 815.62 - samples/sec: 2887.17 - lr: 0.000000 - momentum: 0.000000 |
| 2026-10-29 16:12:25,808 ---------------------------------------------------------------------------------------------------- |
| 2026-10-29 16:12:25,808 EPOCH 20 done: loss 0.0312 - lr: 0.000000 |
| 2026-10-29 16:12:25,808 Saving model at current epoch since 'save_model_each_k_epochs=1' was set |
| 2026-10-29 16:13:58,971 DEV : loss 0.0841129869222641 - f1-score (micro avg) 0.9116 |
| 2026-10-29 16:13:59,059 saving best model |
| 2026-10-29 16:14:00,725 ---------------------------------------------------------------------------------------------------- |
| 2026-10-29 16:14:00,727 Loading model from best epoch ... |
| 2026-10-29 16:14:07,665 SequenceTagger predicts: Dictionary with 43 tags: O, S-CIT_CIV, B-CIT_CIV, E-CIT_CIV, I-CIT_CIV, S-PERSON, B-PERSON, E-PERSON, I-PERSON, S-JURIST, B-JURIST, E-JURIST, I-JURIST, S-CIT_CAN, B-CIT_CAN, E-CIT_CAN, I-CIT_CAN, S-PLACE, B-PLACE, E-PLACE, I-PLACE, S-ORG, B-ORG, E-ORG, I-ORG, S-STATUTE, B-STATUTE, E-STATUTE, I-STATUTE, S-CIT_FEUD, B-CIT_FEUD, E-CIT_FEUD, I-CIT_FEUD, S-DATE, B-DATE, E-DATE, I-DATE, S-CIT_OTHER, B-CIT_OTHER, E-CIT_OTHER, I-CIT_OTHER, <START>, <STOP> |
| 2026-10-29 16:15:21,643 |
| Results: |
| - F-score (micro) 0.9123 |
| - F-score (macro) 0.7439 |
| - Accuracy 0.8419 |
|
|
| By class: |
| precision recall f1-score support |
|
|
| CIT_CIV 0.9502 0.9529 0.9515 4861 |
| PERSON 0.9027 0.9027 0.9027 1871 |
| JURIST 0.9320 0.9288 0.9304 1447 |
| CIT_CAN 0.8810 0.8896 0.8853 915 |
| PLACE 0.6364 0.6434 0.6399 272 |
| ORG 0.7268 0.7472 0.7368 178 |
| STATUTE 0.5794 0.6186 0.5984 118 |
| CIT_FEUD 0.8200 0.8200 0.8200 50 |
| DATE 0.6250 0.7143 0.6667 35 |
| CIT_OTHER 0.3636 0.2667 0.3077 30 |
|
|
| micro avg 0.9109 0.9138 0.9123 9777 |
| macro avg 0.7417 0.7484 0.7439 9777 |
| weighted avg 0.9110 0.9138 0.9124 9777 |
|
|
| 2026-10-29 16:15:21,643 ---------------------------------------------------------------------------------------------------- |
|
|
