---
license: cc-by-sa-4.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: korean_disease_ner
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# korean_disease_ner

This model is a fine-tuned version of [klue/bert-base](https://huggingface.co/klue/bert-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0855
- Precision: 0.9424
- Recall: 0.9475
- F1: 0.9449
- Accuracy: 0.9801

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 30
- eval_batch_size: 30
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:------:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0663        | 1.0   | 15954  | 0.0599          | 0.9417    | 0.9246 | 0.9331 | 0.9763   |
| 0.0471        | 2.0   | 31908  | 0.0514          | 0.9408    | 0.9442 | 0.9425 | 0.9795   |
| 0.0384        | 3.0   | 47862  | 0.0511          | 0.9419    | 0.9471 | 0.9445 | 0.9802   |
| 0.0292        | 4.0   | 63816  | 0.0558          | 0.9456    | 0.9449 | 0.9453 | 0.9804   |
| 0.0253        | 5.0   | 79770  | 0.0572          | 0.9421    | 0.9507 | 0.9464 | 0.9807   |
| 0.0225        | 6.0   | 95724  | 0.0649          | 0.9474    | 0.9435 | 0.9454 | 0.9805   |
| 0.0209        | 7.0   | 111678 | 0.0695          | 0.9409    | 0.9504 | 0.9456 | 0.9805   |
| 0.019         | 8.0   | 127632 | 0.0742          | 0.9431    | 0.9469 | 0.9450 | 0.9802   |
| 0.0178        | 9.0   | 143586 | 0.0799          | 0.9425    | 0.9477 | 0.9451 | 0.9802   |
| 0.016         | 10.0  | 159540 | 0.0855          | 0.9424    | 0.9475 | 0.9449 | 0.9801   |


### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2