mmocr/configs/ner/bert_softmax/README.md

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# Chinese Named Entity Recognition using BERT + Softmax
## Introduction
[ALGORITHM]
```bibtex
@article{devlin2018bert,
title={Bert: Pre-training of deep bidirectional transformers for language understanding},
author={Devlin, Jacob and Chang, Ming-Wei and Lee, Kenton and Toutanova, Kristina},
journal={arXiv preprint arXiv:1810.04805},
year={2018}
}
```
## Dataset
### Train Dataset
| trainset | text_num | entity_num |
| :--------: | :----------: | :--------: |
| CLUENER2020 | 10748 | 23338 |
### Test Dataset
| testset | text_num | entity_num |
| :--------: | :----------: | :--------: |
| CLUENER2020 | 1343 | 2982 |
## Results and models
| Method |Pretrain| Precision | Recall | F1-Score | Download |
| :--------------------------------------------------------------------: |:-----------:|:-----------:| :--------:| :-------: | :-------------------------------------: |
| [bert_softmax](/configs/ner/bert_softmax/bert_softmax_cluener_18e.py)| [pretrain](https://download.openmmlab.com/mmocr/ner/bert_softmax/bert_pretrain.pth) |0.7885 | 0.7998 | 0.7941 | [model](https://download.openmmlab.com/mmocr/ner/bert_softmax/bert_softmax_cluener-eea70ea2.pth) \| [log](https://download.openmmlab.com/mmocr/ner/bert_softmax/20210514_172645.log.json) |