shiluBERT / README.md
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---
license: apache-2.0
---
## 中文说明
# 多标签分类模型(明/清实录)
本模型基于 [Jihuai/bert-ancient-chinese](https://huggingface.co/Jihuai/bert-ancient-chinese) 预训练权重,可用于对《明实录》和《清实录》中的文本进行多标签分类推理。
## 训练语料
- **来源**:[《朝鲜王朝实录》](https://sillok.history.go.kr/main/main.do)
- **训练样本数**:约30万
- **标签类别数**:194
- **文本语言**:中文繁体(亦支持中文简体)
## 评价指标
| 指标 | 基于 Samples | 基于 Label(Micro) |
| --------------- | :----------: | :-----------------: |
| F1 | 0.7095 | 0.6714 |
| Precision | 0.7692 | 0.7441 |
| Recall | 0.7000 | 0.6116 |
| Hamming Loss | 0.0068 |
> **注**:虽然本模型能大致区分大多数标签,但对于正例极少的标签表现尚不理想。
## 后续工作
相关工作论文coming soon!
## 引用
如需引用,可先引用本页面,仅供学习交流用!
模型链接:<https://huggingface.co/bztxb/shiluBERT>
## 线上使用示例
见HuggingFace Space: [bztxb/InferShilu](https://huggingface.co/spaces/bztxb/InferShilu)
![image/png](https://cdn-uploads.huggingface.co/production/uploads/6687f5437a67e6a352c0195c/QFshR1AKawoLbCxT1p3Qm.png)
## English Version
# Multi-Label Classification Model (The Veritable Records of the Ming/Qing Dynasty)
This model is built on the pretrained weights of [Jihuai/bert-ancient-chinese](https://huggingface.co/Jihuai/bert-ancient-chinese) and is designed for multi-label classification inference on texts from the **Ming Shilu** and **Qing Shilu**.
## Training Corpus
- **Source**: [The Veritable Records of the Joseon Dynasty](https://sillok.history.go.kr/main/main.do)
- **Training size**: about 0.3 million
- **Number of Labels**: 194
- **Text Language**: Traditional Chinese (also supports Simplified Chinese)
## Evaluation Metrics
| Metric | Sample-based | Label-based (Micro) |
| ------------- | :----------: | :-----------------: |
| F1 Score | 0.7095 | 0.6714 |
| Precision | 0.7692 | 0.7441 |
| Recall | 0.7000 | 0.6116 |
| Hamming Loss | 0.0068 | — |
> **Note**: Although this model can broadly distinguish most labels, its performance on classes with very few positive examples remains suboptimal.
## Future Work
Working paper coming soon!
## Citation
If you wish to cite this work, please refer to this page, welcome any feedback.
Model link: <https://huggingface.co/bztxb/shiluBERT>
## How to use
See HuggingFace Space: [bztxb/InferShilu](https://huggingface.co/spaces/bztxb/InferShilu)
![image/png](https://cdn-uploads.huggingface.co/production/uploads/6687f5437a67e6a352c0195c/QFshR1AKawoLbCxT1p3Qm.png)