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https://github.com/ProHiryu/bert-chinese-ner

使用预训练语言模型BERT做中文NER
https://github.com/ProHiryu/bert-chinese-ner

bert chinese fine-tune ner tensorflow

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使用预训练语言模型BERT做中文NER

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# bert-chinese-ner

## 前言

使用预训练语言模型BERT做中文NER尝试,fine - tune BERT模型

PS: 移步最新[**albert fine-tune ner**](https://github.com/ProHiryu/albert-chinese-ner)模型

## 代码参考

- [BERT-NER](https://github.com/kyzhouhzau/BERT-NER)
- [BERT-TF](https://github.com/google-research/bert)

## 使用方法

从[BERT-TF](https://github.com/google-research/bert)下载bert源代码,存放在路径下bert文件夹中

从[BERT-Base Chinese](https://storage.googleapis.com/bert_models/2018_11_03/chinese_L-12_H-768_A-12.zip)下载模型,存放在checkpoint文件夹下

使用BIO数据标注模式,使用人民日报经典数据

train:

`python BERT_NER.py --data_dir=data/ --bert_config_file=checkpoint/bert_config.json --init_checkpoint=checkpoint/bert_model.ckpt --vocab_file=vocab.txt --output_dir=./output/result_dir/`

## 结果

经过100个epoch跑出来的结果

```
eval_f = 0.9662649
eval_precision = 0.9668882
eval_recall = 0.9656949
global_step = 135181
loss = 40.160034
```

测试结果第一句:

![](test.png)