Official Code for 'EPiDA: An Easy Plug-in Data Augmentation Framework for High Performance Text Classification'
NAACL 2022 Accepted Paper
Feel free to contact me if you have any problems! zhaomy20@fudan.edu.cn
Suppose you have already get a dataset, you can modify the code in train_sst_epida_eda.py or train_irony_epida_eda.py for quick start.
python3 train_irony_epida_eda.py
The SST dataset can be achieved via SUB2.
The corpus used in major paper can be downloaded by checking the links given in the paper or email.
If you find this project is useful for your research, please cite:
@article{zhao2022epida,
title={EPiDA: An Easy Plug-in Data Augmentation Framework for High Performance Text Classification},
author={Zhao, Minyi and Zhang, Lu and Xu, Yi and Ding, Jiandong and Guan, Jihong and Zhou, Shuigeng},
journal={arXiv preprint arXiv:2204.11205},
year={2022}
}