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---
license: apache-2.0
---
# Implementation of ACL 2024 findings "Improving Grammatical Error Correction via Contextual Data Augmentation"
[github link](https://github.com/wyxstriker/CDA4GEC)
# Model Weights
We release the model weights of each training stage.
Our model is trained based on the Fairseq framework, details of the weights and links to them are below.
|Name|Data Info|Download Link|
|:--:|--|--|
|Stage1|Pre-training on [C4 synthetic data](https://github.com/google-research-datasets/C4_200M-synthetic-dataset-for-grammatical-error-correction) with 200M scale|[CDA4GEC](https://huggingface.co/DecoderImmortal/CDA4GEC)/tree/main/stage1_checkpoint_best.pt|
|Stage2+|Fine-tuning on the augmented Lang8, NUCLE, FCE and W&I+L datasets|[CDA4GEC](https://huggingface.co/DecoderImmortal/CDA4GEC)/tree/main/stage2_checkpoint_best.pt|
|Stage3+|Continue fine-tuning on the augmented W&I+L dataset|[CDA4GEC](https://huggingface.co/DecoderImmortal/CDA4GEC)/tree/main/stage3_checkpoint_best.pt|
# Synthetic Data
> We only release the synthetic pseudo-data, please follow the official process to apply for the original annotated data.
|DataInfo|Amount|Source|Path|
|:--:|:--:|:--:|:--:|
|stage2+|2M|Lang-8 & NUCLE & FCE & W&I+L|[CDA4GEC](https://huggingface.co/DecoderImmortal/CDA4GEC)/tree/main/pseudo/stage2|
|stage3+|200K|W&I+L|[CDA4GEC](https://huggingface.co/DecoderImmortal/CDA4GEC)/tree/main/pseudo/stage3|
# Citation
If you find this work is useful for your research, please cite our paper:
```
@inproceedings{wang-etal-2024-improving-grammatical,
title = "Improving Grammatical Error Correction via Contextual Data Augmentation",
author = "Wang, Yixuan and
Wang, Baoxin and
Liu, Yijun and
Zhu, Qingfu and
Wu, Dayong and
Che, Wanxiang",
editor = "Ku, Lun-Wei and
Martins, Andre and
Srikumar, Vivek",
booktitle = "Findings of the Association for Computational Linguistics ACL 2024",
month = aug,
year = "2024",
address = "Bangkok, Thailand and virtual meeting",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.findings-acl.647",
pages = "10898--10910",
}
```
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