Skip to content

Transferability of Natural Language Inference to Biomedical Question Answering

Notifications You must be signed in to change notification settings

dmis-lab/bioasq8b

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

34 Commits
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Transferability of Natural Language Inference to Biomedical Question Answering

This repository provides a code for our paper, which tries to interpret the transferability of natural language inference to biomedical question answering. We use this code for the BioASQ Challenge Task 8b-Phase B. Please refer to our paper Transferability of Natural Language Inference to Biomedical Question Answering for more details. This project is proceeded by DMIS-Lab.

Data Download

We provide a pre-processed version of the BioASQ Task 8b-Phase B

  • Pubmed Abstract : a pre-processed version of pubmed abstract data used for Task 8b-Phase B.
  • SQuAD Oracle : a pre-processed version of SQuAD oracle dataset.
  • Yes/No type : a pre-processed version of Yes/No type questions in Task 8b-Phase B.
  • Factoid type : a pre-processed version of Factoid type questions in Task 8b-Phase B.
  • List type : a pre-processed version of List type questions in Task 8b-Phase B.

We revised the pre-processed datasets from Pre-trained Language Model for Biomedical Question Answering released by BioASQ-BioBERT.

For details of the original BioASQ datasets, please see An overview of the BIOASQ large-scale biomedical semantic indexing and question answering competition (Tsatsaronis et al. 2015).

Pre-trained Model

We use the BioBERT model as our base model learning. For specific fine-tuning procedure, please see our corresponding folder respectively.

In order to facilitate the reproduction of our results, we provide our learned parameters of our model.

  • BioBERT-MNLI : Sequential transfer learning of our model (BioBERT-MNLI) parameters.
  • BioBERT-MNLI-SQuAD : Sequential transfer learning of our model (BioBERT-MNLI-SQuAD) parameters.
  • BioBERT-MNLI-SQuAD(oracle) : Sequential transfer learning of our model (BioBERT-MNLI-SQuAD(oracle)) parameters.

Requirements

  • GPU (Our setting was a single NVIDIA Titan RTX (24GB) GPU)
  • Python version >= 3.7
  • Tensorflow version >= 1.14.0
  • Pytorch version >= 1.5.1

Contact Information

For help or any issues using our code, please contact Minbyul Jeong or Mujeen Sung (minbyuljeong, mujeensung {at} korea.ac.kr). We welcome for any suggestions to modify our issues.

Bibliography

@misc{jeong2020transferability,
    title={Transferability of Natural Language Inference to Biomedical Question Answering},
    author={Minbyul Jeong and Mujeen Sung and Gangwoo Kim and Donghyeon Kim and Wonjin Yoon and Jaehyo Yoo and Jaewoo Kang},
    year={2020},
    eprint={2007.00217},
    archivePrefix={arXiv},
    primaryClass={cs.CL}
}

About

Transferability of Natural Language Inference to Biomedical Question Answering

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Contributors 4

  •  
  •  
  •  
  •