cdj0311 / Keras_bert_classification
Bert-classification and bert-dssm implementation with keras.
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基于bert特征的文本分类与dssm语义表示
#0. ready
将bert预训练模型（chinese_L-12_H-768_A-12）放到当前目录下，下载地址：https://storage.googleapis.com/bert_models/2018_11_03/chinese_L-12_H-768_A-12.zip
#1. bert_fc.py
抽取bert句向量特征，接全连接层。 训练命令：python bert_fc.py
#2. bert_lstm.py
抽取bert字向量特征，后面接LSTM/GRU和全连接层。 训练命令：python bert_lstm.py
#3. bert_dssm.py
先将文本转换为bert句向量存在tfrecord中，这一步自行处理即可， 然后从tfrecord中读取数据，数据格式为feed_dict = {"query":[[1,2,3], [4,6,7]], "doc": [[1,2,3], [4,6,7]]}
#4. 基于bert微调DSSM向量
新增bert_dssm_finetune，基于bert微调的DSSM向量，使用https://github.com/CyberZHG/keras-bert 获取CLS向量然后接一层全连接。 data目录下有1000条样本数据，格式为：标题\t内容
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