基于pytorch和bert,参考NER的网络结构,第一个全连接的输出层输出属性/观点的起始位置(按照BEIS,共有8个类),第二个输出观点+属性的分类(合计有28个类)
python3.6 + pytorch==1.0.1 + pytorch-pretrained-bert==0.6.2
cd code; CUDA_VISIBLE_DEVICES=0 python train_v2.py
- 数据增强
- 多网络融合
This project forked from eliascai/viewpoint-mining
参考NER,基于BERT的电商评论观点挖掘和情感分析
基于pytorch和bert,参考NER的网络结构,第一个全连接的输出层输出属性/观点的起始位置(按照BEIS,共有8个类),第二个输出观点+属性的分类(合计有28个类)
python3.6 + pytorch==1.0.1 + pytorch-pretrained-bert==0.6.2
cd code; CUDA_VISIBLE_DEVICES=0 python train_v2.py
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