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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: 0.0792 |
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- Precision: 0.9478 |
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- Recall: 0.9553 |
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- F1: 0.9515 |
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- Accuracy: 0.9879 |
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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: 50 |
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- eval_batch_size: 50 |
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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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| 0.1 | 1.0 | 1850 | 0.0461 | 0.9329 | 0.9401 | 0.9365 | 0.9850 | |
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| 0.0346 | 2.0 | 3700 | 0.0433 | 0.9367 | 0.9500 | 0.9433 | 0.9864 | |
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| 0.0211 | 3.0 | 5550 | 0.0482 | 0.9438 | 0.9493 | 0.9465 | 0.9871 | |
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| 0.013 | 4.0 | 7400 | 0.0532 | 0.9449 | 0.9501 | 0.9475 | 0.9869 | |
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| 0.0091 | 5.0 | 9250 | 0.0584 | 0.9430 | 0.9549 | 0.9489 | 0.9872 | |
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| 0.0063 | 6.0 | 11100 | 0.0675 | 0.9497 | 0.9503 | 0.9500 | 0.9874 | |
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| 0.0044 | 7.0 | 12950 | 0.0660 | 0.9467 | 0.9543 | 0.9505 | 0.9876 | |
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| 0.0032 | 8.0 | 14800 | 0.0752 | 0.9429 | 0.9563 | 0.9495 | 0.9873 | |
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| 0.0025 | 9.0 | 16650 | 0.0766 | 0.9463 | 0.9561 | 0.9512 | 0.9878 | |
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| 0.0019 | 10.0 | 18500 | 0.0792 | 0.9478 | 0.9553 | 0.9515 | 0.9879 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.10.0 |
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- Tokenizers 0.13.2 |
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