基于TextCNN Pytorch实现的中文文本分类 情感分析，含数据集

## TextCNN Pytorch实现 中文文本分类 ## 论文 [Convolutional Neural Networks for Sentence Classification](https://arxiv.org/abs/1408.5882) ## 参考 * https://github.com/yoonkim/CNN_sentence * https://github.com/dennybritz/cnn-text-classification-tf * https://github.com/Shawn1993/cnn-text-classification-pytorch ## 依赖项 * python3.5 * pytorch==1.0.0 * torchtext==0.3.1 * jieba==0.39 ## 词向量 https://github.com/Embedding/Chinese-Word-Vectors<br> （这里用的是Zhihu_QA 知乎问答训练出来的word Word2vec） ## 用法 ```bash python3 main.py -h ``` ## 训练 ```bash python3 main.py ``` ## 准确率 - [x] CNN-rand 随机初始化Embedding ```bash python main.py ``` > Batch[1800] - loss: 0.009499 acc: 100.0000%(128/128) Evaluation - loss: 0.000026 acc: 94.0000%(6616/7000) early stop by 1000 steps, acc: 94.0000% - [x] CNN-static 使用预训练的静态词向量 ```bash python main.py -static=true ``` > Batch[1900] - loss: 0.011894 acc: 100.0000%(128/128) Evaluation - loss: 0.000018 acc: 95.0000%(6679/7000) early stop by 1000 steps, acc: 95.0000% - [x] CNN-non-static 微调预训练的词向量 ```bash python main.py -static=true -non-static=true ``` > Batch[1500] - loss: 0.008823 acc: 99.0000%(127/128)) Evaluation - loss: 0.000016 acc: 96.0000%(6729/7000) early stop by 1000 steps, acc: 96.0000% - [x] CNN-multichannel 微调加静态 ```bash python main.py -static=true -non-static=true -multichannel=true ``` > Batch[1500] - loss: 0.023020 acc: 98.0000%(126/128)) Evaluation - loss: 0.000016 acc: 96.0000%(6744/7000) early stop by 1000 steps, acc: 96.0000%