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Text Classification Benchmark

A Benchmark of Text Classification in PyTorch

Motivation

We are trying to build a Benchmark for Text Classification including

Many Text Classification DataSet, including Sentiment/Topic Classfication, popular language(e.g. English and Chinese). Meanwhile, a basic word embedding is provided.

Implment many popular and state-of-art Models, especially in deep neural network.

Have done

We have done some dataset and models

Dataset done

  • IMDB
  • SST
  • Trec

Models done

  • FastText
  • BasicCNN (KimCNN,MultiLayerCNN, Multi-perspective CNN)
  • InceptionCNN
  • LSTM (BILSTM, StackLSTM)
  • LSTM with Attention (Self Attention / Quantum Attention)
  • Hybrids between CNN and RNN (RCNN, C-LSTM)
  • Transformer - Attention is all you need
  • ConS2S
  • Capsule
  • Quantum-inspired NN

Libary

You should have install these librarys

python3
torch
torchtext (optional)

Dataset

Dataset will be automatically configured in current path, or download manually your data in Dataset, step-by step.

including

Glove embeding
Sentiment classfication dataset IMDB

usage

Run in default setting

python main.py

CNN

python main.py --model cnn

LSTM

python main.py --model lstm

Road Map

  • [X] Data preprossing framework
  • [X] Models modules
  • [ ] Loss, Estimator and hyper-paramter tuning.
  • [ ] Test modules
  • [ ] More Dataset
  • [ ] More models

Organisation of the repository

The core of this repository is models and dataset.

  • dataloader/: loading all dataset such as IMDB, SST

  • models/: creating all models such as FastText, LSTM,CNN,Capsule,QuantumCNN ,Multi-Head Attention

  • opts.py: Parameter and config info.

  • utils.py: tools.

  • dataHelper: data helper

Contributor

Welcome your issues and contribution!!!


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