ZJUKLAB at SemEval-2021 Task 4: Negative Augmentation with Language Model for Reading Comprehension of Abstract Meaning
ZJUKLAB at SemEval-2021 Task 4: Negative Augmentation with Language Model for Reading Comprehension of Abstract Meaning
This repository is the official implementation of the ACL 2021 (Semeval Workshop) paper ZJUKLAB at SemEval-2021 Task 4: Negative Augmentation with Language Model for Reading Comprehension of Abstract Meaning which is the 4th rank system of the SemEval 2021 Task4.
Student: Xin Xie, Nanxiang Chen, Xiang Chen and so on
Supervisor: Ningyu Zhang, Huajun Chen.
To install requirements:
-
python >= 3.7
-
torch >= 1.6
-
transformers==3.3.1
pip install -r requirements.txt
To get the NAL answers, we use the models without fine-tuning to get the enhanced dataset.
python ./dataset/preprocess.py
Firstly, pretrain the ALBERT,RoBERTa models to fit the in-domain text.
./scripts/pretrain_model.sh
Secondly, fine-tuning the model with the followed scripts.
./scripts/run_deberta.sh
./scripts/run_albert.sh
./scripts/run_roberta.sh
Finally, we get the best model files and ensemble them with weighted voting (weighted by the acc at dev set).
./scripts/get_answer/save_answer.sh
run the command below to get the result files.
./scripts/get_answer/save_answer.shOur model achieves the following performance on :
If you use or extend our work, please cite the following paper:
@inproceedings{DBLP:conf/semeval/XieCCWZDC21,
author = {Xin Xie and
Xiangnan Chen and
Xiang Chen and
Yong Wang and
Ningyu Zhang and
Shumin Deng and
Huajun Chen},
editor = {Alexis Palmer and
Nathan Schneider and
Natalie Schluter and
Guy Emerson and
Aur{\'{e}}lie Herbelot and
Xiaodan Zhu},
title = {{ZJUKLAB} at SemEval-2021 Task 4: Negative Augmentation with Language
Model for Reading Comprehension of Abstract Meaning},
booktitle = {Proceedings of the 15th International Workshop on Semantic Evaluation,
SemEval@ACL/IJCNLP 2021, Virtual Event / Bangkok, Thailand, August
5-6, 2021},
pages = {810--819},
publisher = {Association for Computational Linguistics},
year = {2021},
url = {https://doi.org/10.18653/v1/2021.semeval-1.108},
doi = {10.18653/v1/2021.semeval-1.108},
timestamp = {Mon, 22 Nov 2021 09:21:39 +0100},
biburl = {https://dblp.org/rec/conf/semeval/XieCCWZDC21.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
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