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Title: GitHub - Hello-One/DeepNER: 天池中药说明书实体识别挑战冠军方案；中文命名实体识别；NER; BERT-CRF & BERT-SPAN & BERT-MRC；Pytorch · GitHub

Open Graph Title: GitHub - Hello-One/DeepNER: 天池中药说明书实体识别挑战冠军方案；中文命名实体识别；NER; BERT-CRF & BERT-SPAN & BERT-MRC；Pytorch

X Title: GitHub - Hello-One/DeepNER: 天池中药说明书实体识别挑战冠军方案；中文命名实体识别；NER; BERT-CRF & BERT-SPAN & BERT-MRC；Pytorch

Description: 天池中药说明书实体识别挑战冠军方案；中文命名实体识别；NER; BERT-CRF & BERT-SPAN & BERT-MRC；Pytorch - Hello-One/DeepNER

Open Graph Description: 天池中药说明书实体识别挑战冠军方案；中文命名实体识别；NER; BERT-CRF & BERT-SPAN & BERT-MRC；Pytorch - Hello-One/DeepNER

X Description: 天池中药说明书实体识别挑战冠军方案；中文命名实体识别；NER; BERT-CRF & BERT-SPAN & BERT-MRC；Pytorch - Hello-One/DeepNER

Opengraph URL: https://github.com/Hello-One/DeepNER

X: @github

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DeepNER	https://github.com/Hello-One/DeepNER
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	https://github.com/Hello-One/DeepNER#chinese-deepner-pytorch
	https://github.com/Hello-One/DeepNER#天池中药说明书实体识别挑战冠军方案开源
	https://github.com/Hello-One/DeepNER#贡献者
https://github.com/z814081807	https://github.com/z814081807
https://github.com/WuHuRestaurant	https://github.com/WuHuRestaurant
https://github.com/zchaizju	https://github.com/zchaizju
	https://github.com/Hello-One/DeepNER#后续官方开放数据集后deepner项目会进行优化升级包含完整的数据处理训练验证测试部署流程提供详细的代码注释模型介绍实验结果提供更普适的基于预训练的中文命名实体识别方案开箱即用欢迎star
	https://github.com/Hello-One/DeepNER#环境
	https://github.com/Hello-One/DeepNER#项目目录说明
	https://github.com/Hello-One/DeepNER#使用说明
	https://github.com/Hello-One/DeepNER#预训练使用说明
https://github.com/dbiir/UER-py/wiki/Modelzoo	https://github.com/dbiir/UER-py/wiki/Modelzoo
https://github.com/ymcui/Chinese-BERT-wwm	https://github.com/ymcui/Chinese-BERT-wwm
https://pan.baidu.com/s/1axdkovbzGaszl8bXIn4sPw	https://pan.baidu.com/s/1axdkovbzGaszl8bXIn4sPw
	https://github.com/Hello-One/DeepNER#数据转换
	https://github.com/Hello-One/DeepNER#训练阶段
	https://github.com/Hello-One/DeepNER#bert-crf模型训练
	https://github.com/Hello-One/DeepNER#bert-span模型训练
	https://github.com/Hello-One/DeepNER#bert-mrc模型训练
	https://github.com/Hello-One/DeepNER#预测复赛-test-文件-上述模型训练完成后
	https://github.com/Hello-One/DeepNER#赛题背景
	https://github.com/Hello-One/DeepNER#任务描述
	https://github.com/Hello-One/DeepNER#数据探索分析
	https://github.com/Hello-One/DeepNER/blob/master/md_files/1.png
	https://github.com/Hello-One/DeepNER/blob/master/md_files/2.png
	https://github.com/Hello-One/DeepNER/blob/master/md_files/3.png
	https://github.com/Hello-One/DeepNER#核心思路
	https://github.com/Hello-One/DeepNER#数据预处理
	https://github.com/Hello-One/DeepNER#baseline-bert-crf
	https://github.com/Hello-One/DeepNER/blob/master/md_files/6.png
	https://github.com/Hello-One/DeepNER/blob/master/md_files/7.png
	https://github.com/Hello-One/DeepNER#优化1对抗训练
	https://github.com/Hello-One/DeepNER#优化2混合精度训练fp16
	https://github.com/Hello-One/DeepNER#优化3多模型融合
	https://github.com/Hello-One/DeepNER/blob/master/md_files/10.png
	https://github.com/Hello-One/DeepNER/blob/master/md_files/11.png
	https://github.com/Hello-One/DeepNER/blob/master/md_files/12.png
	https://github.com/Hello-One/DeepNER#优化4半监督学习
	https://github.com/Hello-One/DeepNER/blob/master/md_files/13.png
	https://github.com/Hello-One/DeepNER#其他无明显提升的尝试方案
	https://github.com/Hello-One/DeepNER#最终线上成绩7290复赛rank-1决赛rank-1
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