Implementation of TextCNN, TextRNN, RCNN, FastText with Pytorch
Pytorch 中文文本分类模型
Python >= 3.5
Pytorch >= 1.1.0
torchtext >= 0.3.1
jieba >= 0.39
Train and test data are organized in the following style
Query, label
In each folder, you could train model in 4 ways:
Random Initialize Word Embedding
python main.py
Use pre-trained Word Embedding (freeze)
python main.py -static=true
Use pre-trained Word Embedding (not freeze)
python main.py -static=true -non-static=true
Use pre-trained Word Embedding (multi-channel : free + not freeze)
python main.py -static=true -non-static=true -multichannel=true