Dataset

For pretraining, download MedDialog (here we choose 'processed-zh; version) and put it into ./data/train_data.json

For Entity extraction, see Ali Sky Pool

Run scripts

Pretrained in MedDialog

cd src/
python medlog_pretrain.py

Entity Extration

1. Baseline: run bash src/run.sh
2. Baseline w/ data augmentation
3. Baseline w/ pretraining Model

Reference

@article{chen2020meddiag,
  title={MedDialog: a large-scale medical dialogue dataset},
  author={Chen, Shu and Ju, Zeqian and Dong, Xiangyu and Fang, Hongchao and Wang, Sicheng and Yang, Yue and Zeng, Jiaqi and Zhang, Ruisi and Zhang, Ruoyu and Zhou, Meng and Zhu, Penghui and Xie, Pengtao},
  journal={arXiv preprint arXiv:2004.03329}, 
  year={2020}
}

@inproceedings{wolf-etal-2020-transformers,
    title = "Transformers: State-of-the-Art Natural Language Processing",
    author = "Thomas Wolf and Lysandre Debut and Victor Sanh and Julien Chaumond and Clement Delangue and Anthony Moi and Pierric Cistac and Tim Rault and Rémi Louf and Morgan Funtowicz and Joe Davison and Sam Shleifer and Patrick von Platen and Clara Ma and Yacine Jernite and Julien Plu and Canwen Xu and Teven Le Scao and Sylvain Gugger and Mariama Drame and Quentin Lhoest and Alexander M. Rush",
    booktitle = "Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations",
    month = oct,
    year = "2020",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/2020.emnlp-demos.6",
    pages = "38--45"
}

@inproceedings{jiang-etal-2020-smart,
    title = "{SMART}: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization",
    author = "Jiang, Haoming  and He, Pengcheng  and Chen, Weizhu  and Liu, Xiaodong  and Gao, Jianfeng  and Zhao, Tuo",
    booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics",
    month = jul,
    year = "2020",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    doi = "10.18653/v1/2020.acl-main.197",
    pages = "2177--2190",
}