---
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: 0.0792
- Precision: 0.9478
- Recall: 0.9553
- F1: 0.9515
- Accuracy: 0.9879

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


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.0
- Tokenizers 0.13.2