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keonju
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korean_disease_ner

Token Classification
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bert
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update model card README.md

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@@ -19,11 +19,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [klue/bert-base](https://huggingface.co/klue/bert-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0422
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- - Precision: 0.9558
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- - Recall: 0.9581
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- - F1: 0.9569
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- - Accuracy: 0.9897
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 2e-05
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- - train_batch_size: 16
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- - eval_batch_size: 16
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - num_epochs: 5
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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- |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | 0.0445 | 1.0 | 3025 | 0.0378 | 0.9408 | 0.9585 | 0.9496 | 0.9875 |
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- | 0.0253 | 2.0 | 6050 | 0.0351 | 0.9510 | 0.9564 | 0.9537 | 0.9890 |
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- | 0.0175 | 3.0 | 9075 | 0.0338 | 0.9546 | 0.9571 | 0.9558 | 0.9895 |
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- | 0.0123 | 4.0 | 12100 | 0.0372 | 0.9510 | 0.9640 | 0.9575 | 0.9896 |
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- | 0.0091 | 5.0 | 15125 | 0.0422 | 0.9558 | 0.9581 | 0.9569 | 0.9897 |
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [klue/bert-base](https://huggingface.co/klue/bert-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0855
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+ - Precision: 0.9424
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+ - Recall: 0.9475
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+ - F1: 0.9449
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+ - Accuracy: 0.9801
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 2e-05
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+ - train_batch_size: 30
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+ - eval_batch_size: 30
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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+ - num_epochs: 10
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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+ |:-------------:|:-----:|:------:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 0.0663 | 1.0 | 15954 | 0.0599 | 0.9417 | 0.9246 | 0.9331 | 0.9763 |
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+ | 0.0471 | 2.0 | 31908 | 0.0514 | 0.9408 | 0.9442 | 0.9425 | 0.9795 |
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+ | 0.0384 | 3.0 | 47862 | 0.0511 | 0.9419 | 0.9471 | 0.9445 | 0.9802 |
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+ | 0.0292 | 4.0 | 63816 | 0.0558 | 0.9456 | 0.9449 | 0.9453 | 0.9804 |
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+ | 0.0253 | 5.0 | 79770 | 0.0572 | 0.9421 | 0.9507 | 0.9464 | 0.9807 |
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+ | 0.0225 | 6.0 | 95724 | 0.0649 | 0.9474 | 0.9435 | 0.9454 | 0.9805 |
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+ | 0.0209 | 7.0 | 111678 | 0.0695 | 0.9409 | 0.9504 | 0.9456 | 0.9805 |
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+ | 0.019 | 8.0 | 127632 | 0.0742 | 0.9431 | 0.9469 | 0.9450 | 0.9802 |
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+ | 0.0178 | 9.0 | 143586 | 0.0799 | 0.9425 | 0.9477 | 0.9451 | 0.9802 |
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+ | 0.016 | 10.0 | 159540 | 0.0855 | 0.9424 | 0.9475 | 0.9449 | 0.9801 |
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  ### Framework versions