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--- |
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license: cc-by-sa-4.0 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: korean_disease_ner |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# korean_disease_ner |
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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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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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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 |
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- Transformers 4.26.0 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.9.0 |
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- Tokenizers 0.13.2 |
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