KLUE-custom-ner / eval.log
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['run_entity.py', '--do_eval', '--eval_test', '--learning_rate=1e-5', '--task_learning_rate=5e-4', '--train_batch_size=32', '--context_window', '0', '--task', 'ko', '--data_dir', 'korean_data/json/', '--model', 'monologg/kobert', '--output_dir', 'sh_aug+klue_dir']
Namespace(bert_model_dir=None, bertadam=False, context_window=0, data_dir='korean_data/json/', dev_data='korean_data/json/dev.json', dev_pred_filename='ent_pred_dev.json', do_eval=True, do_train=False, eval_batch_size=32, eval_per_epoch=1, eval_test=True, learning_rate=1e-05, max_span_length=8, model='monologg/kobert', num_epoch=20, output_dir='sh_aug+klue_dir', print_loss_step=100, seed=0, task='ko', task_learning_rate=0.0005, test_data='korean_data/json/test.json', test_pred_filename='ent_pred_test.json', train_batch_size=32, train_data='korean_data/json/train.json', train_shuffle=False, use_albert=False, warmup_proportion=0.1)
Moving to CUDA...
# GPUs = 1
# Overlap: 0
Extracted 5000 samples from 5000 documents, with 14178 NER labels, 31.704 avg input length, 93 max length
Max Length: 93, max NER: 16
Loading BERT model from sh_aug+klue_dir/
Moving to CUDA...
# GPUs = 1
Loading BERT model from KLUE_dir/
Moving to CUDA...
# GPUs = 1
# Overlap: 0
Extracted 1 samples from 1 documents, with 0 NER labels, 15.000 avg input length, 15 max length
Max Length: 15, max NER: 0
Evaluating...
Accuracy: 0.978261
Cor: 0, Pred TOT: 2, Gold TOT: 0
P: 0.00000, R: 0.00000, F1: 0.00000
Used time: 1.660250
Evaluating...
Accuracy: 0.989130
Cor: 0, Pred TOT: 1, Gold TOT: 0
P: 0.00000, R: 0.00000, F1: 0.00000
Used time: 0.009506
Total pred entities: 2
Output predictions to sh_aug+klue_dir\ent_pred_test.json..
Total pred entities: 1
Output predictions to sh_aug+klue_dir\ent_pred_test.json..
# Overlap: 0
Extracted 1 samples from 1 documents, with 0 NER labels, 14.000 avg input length, 14 max length
Max Length: 14, max NER: 0
Evaluating...
Accuracy: 0.952381
Cor: 0, Pred TOT: 4, Gold TOT: 0
P: 0.00000, R: 0.00000, F1: 0.00000
Used time: 0.145730
Evaluating...
Accuracy: 0.976190
Cor: 0, Pred TOT: 2, Gold TOT: 0
P: 0.00000, R: 0.00000, F1: 0.00000
Used time: 0.203033
Total pred entities: 4
Output predictions to sh_aug+klue_dir\ent_pred_test.json..
Total pred entities: 2
Output predictions to sh_aug+klue_dir\ent_pred_test.json..
# Overlap: 0
Extracted 1 samples from 1 documents, with 0 NER labels, 11.000 avg input length, 11 max length
Max Length: 11, max NER: 0
Evaluating...
Accuracy: 0.950000
Cor: 0, Pred TOT: 3, Gold TOT: 0
P: 0.00000, R: 0.00000, F1: 0.00000
Used time: 0.149735
Evaluating...
Accuracy: 0.950000
Cor: 0, Pred TOT: 3, Gold TOT: 0
P: 0.00000, R: 0.00000, F1: 0.00000
Used time: 0.123036
Total pred entities: 3
Output predictions to sh_aug+klue_dir\ent_pred_test.json..
Total pred entities: 3
Output predictions to sh_aug+klue_dir\ent_pred_test.json..
# Overlap: 0
Extracted 1 samples from 1 documents, with 0 NER labels, 10.000 avg input length, 10 max length
Max Length: 10, max NER: 0
Evaluating...
Accuracy: 0.980769
Cor: 0, Pred TOT: 1, Gold TOT: 0
P: 0.00000, R: 0.00000, F1: 0.00000
Used time: 0.070563
Evaluating...
Accuracy: 0.980769
Cor: 0, Pred TOT: 1, Gold TOT: 0
P: 0.00000, R: 0.00000, F1: 0.00000
Used time: 0.007507
Total pred entities: 1
Output predictions to sh_aug+klue_dir\ent_pred_test.json..
Total pred entities: 1
Output predictions to sh_aug+klue_dir\ent_pred_test.json..
# Overlap: 0
Extracted 1 samples from 1 documents, with 0 NER labels, 13.000 avg input length, 13 max length
Max Length: 13, max NER: 0
Evaluating...
Accuracy: 0.986842
Cor: 0, Pred TOT: 1, Gold TOT: 0
P: 0.00000, R: 0.00000, F1: 0.00000
Used time: 0.011518
Evaluating...
Accuracy: 0.986842
Cor: 0, Pred TOT: 1, Gold TOT: 0
P: 0.00000, R: 0.00000, F1: 0.00000
Used time: 0.010508
Total pred entities: 1
Output predictions to sh_aug+klue_dir\ent_pred_test.json..
Total pred entities: 1
Output predictions to sh_aug+klue_dir\ent_pred_test.json..
# Overlap: 0
Extracted 1 samples from 1 documents, with 0 NER labels, 12.000 avg input length, 12 max length
Max Length: 12, max NER: 0
Evaluating...
Accuracy: 0.955882
Cor: 0, Pred TOT: 3, Gold TOT: 0
P: 0.00000, R: 0.00000, F1: 0.00000
Used time: 0.147390
Evaluating...
Accuracy: 0.955882
Cor: 0, Pred TOT: 3, Gold TOT: 0
P: 0.00000, R: 0.00000, F1: 0.00000
Used time: 0.125365
Total pred entities: 3
Output predictions to sh_aug+klue_dir\ent_pred_test.json..
Total pred entities: 3
Output predictions to sh_aug+klue_dir\ent_pred_test.json..
# Overlap: 0
Extracted 1 samples from 1 documents, with 0 NER labels, 12.000 avg input length, 12 max length
Max Length: 12, max NER: 0
Evaluating...
Accuracy: 0.985294
Cor: 0, Pred TOT: 1, Gold TOT: 0
P: 0.00000, R: 0.00000, F1: 0.00000
Used time: 0.149942
Evaluating...
Accuracy: 0.985294
Cor: 0, Pred TOT: 1, Gold TOT: 0
P: 0.00000, R: 0.00000, F1: 0.00000
Used time: 0.136553
Total pred entities: 1
Output predictions to sh_aug+klue_dir\ent_pred_test.json..
Total pred entities: 1
Output predictions to sh_aug+klue_dir\ent_pred_test.json..
# Overlap: 0
Extracted 1 samples from 1 documents, with 0 NER labels, 11.000 avg input length, 11 max length
Max Length: 11, max NER: 0
Evaluating...
Accuracy: 0.966667
Cor: 0, Pred TOT: 2, Gold TOT: 0
P: 0.00000, R: 0.00000, F1: 0.00000
Used time: 0.144237
Evaluating...
Accuracy: 0.983333
Cor: 0, Pred TOT: 1, Gold TOT: 0
P: 0.00000, R: 0.00000, F1: 0.00000
Used time: 0.133758
Total pred entities: 2
Output predictions to sh_aug+klue_dir\ent_pred_test.json..
Total pred entities: 1
Output predictions to sh_aug+klue_dir\ent_pred_test.json..
# Overlap: 0
Extracted 1 samples from 1 documents, with 0 NER labels, 12.000 avg input length, 12 max length
Max Length: 12, max NER: 0
Evaluating...
Accuracy: 0.955882
Cor: 0, Pred TOT: 3, Gold TOT: 0
P: 0.00000, R: 0.00000, F1: 0.00000
Used time: 0.080669
Evaluating...
Accuracy: 0.970588
Cor: 0, Pred TOT: 2, Gold TOT: 0
P: 0.00000, R: 0.00000, F1: 0.00000
Used time: 0.015511
Total pred entities: 3
Output predictions to sh_aug+klue_dir\ent_pred_test.json..
Total pred entities: 2
Output predictions to sh_aug+klue_dir\ent_pred_test.json..