---
license: apache-2.0
datasets:
- SungJoo/KBMC
language:
- ko
library_name: transformers
tags:
- medical
- NER
---


# Model Card for medical-ner-koelectra

## Model Summary

This model is a fine-tuned version of the [monologg/koelectra-base-v3-discriminator](https://huggingface.co/monologg/koelectra-base-v3-discriminator).

We fine-tuned the model using the KBMC and [Naver X Changwon Univ NER dataset](https://ko-nlp.github.io/Korpora/ko-docs/corpuslist/naver_changwon_ner.html) datasets.

## Model Details

### Model Description

- **Developed by:** Sungjoo Byun (Grace Byun)
- **Language(s) (NLP):** Korean
- **License:** Apache 2.0
- **Finetuned from model:** monologg/koelectra-base-v3-discriminator


## Training Data

The model was trained using the dataset [Naver X Changwon Univ NER dataset](https://ko-nlp.github.io/Korpora/ko-docs/corpuslist/naver_changwon_ner.html) and [Korean Bio-Medical Corpus (KBMC)](https://huggingface.co/datasets/SungJoo/KBMC).

# Model Performance

## Overall Metrics

- **F1 Score:** 0.8886
- **Loss:** 0.2949
- **Precision:** 0.8844
- **Recall:** 0.8928

## Class-wise Performance

| Class       | Precision | Recall | F1-Score | Support |
|-------------|-----------|--------|----------|---------|
| AFW         | 0.6676    | 0.6326 | 0.6496   | 362     |
| ANM         | 0.7476    | 0.7800 | 0.7635   | 600     |
| Body        | 0.9731    | 0.9813 | 0.9772   | 1068    |
| CVL         | 0.8492    | 0.8579 | 0.8536   | 4977    |
| DAT         | 0.9078    | 0.9286 | 0.9181   | 2130    |
| Disease     | 0.9738    | 0.9872 | 0.9805   | 2109    |
| EVT         | 0.7332    | 0.7446 | 0.7389   | 1026    |
| FLD         | 0.6138    | 0.6170 | 0.6154   | 188     |
| LOC         | 0.8721    | 0.8691 | 0.8706   | 1734    |
| MAT         | 0.5385    | 0.5000 | 0.5185   | 14      |
| NUM         | 0.9227    | 0.9305 | 0.9266   | 4660    |
| ORG         | 0.8917    | 0.8866 | 0.8892   | 3307    |
| PER         | 0.8918    | 0.9049 | 0.8983   | 3626    |
| PLT         | 0.2941    | 0.2174 | 0.2500   | 23      |
| TIM         | 0.8644    | 0.9173 | 0.8901   | 278     |
| Treatment   | 0.9468    | 0.9852 | 0.9656   | 271     |

## Averages

| Metric         | Micro Avg | Macro Avg | Weighted Avg |
|----------------|-----------|-----------|--------------|
| Precision      | 0.8844    | 0.7930    | 0.8841       |
| Recall         | 0.8928    | 0.7963    | 0.8928       |
| F1-Score       | 0.8886    | 0.7941    | 0.8884       |


## Citations

Please cite our KBMC paper:

```bibtex
@misc{byun2024korean,
      title={Korean Bio-Medical Corpus (KBMC) for Medical Named Entity Recognition}, 
      author={Sungjoo Byun and Jiseung Hong and Sumin Park and Dongjun Jang and Jean Seo and Minseok Kim and Chaeyoung Oh and Hyopil Shin},
      year={2024},
      eprint={2403.16158},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}
```

## Model Card Contact

For any questions or issues, please contact byunsj@snu.ac.kr.