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gec-bart-base
gotutiyan/gec-bart-base
gec-bart-base is a machine learning model from gotutiyan. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as mit.
This is a reproduction of the following paper:
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At a glance
- Library
- transformers
- License
- mit
- Model type
- bart
- Access
- Public
- Created
- Dec 26, 2022
- Updated
- Mar 7, 2026
- SHA
- bb878d72
Model card
From the Hugging Face model README
This is a reproduction of the following paper:
@inproceedings{katsumata-komachi-2020-stronger,
title = "Stronger Baselines for Grammatical Error Correction Using a Pretrained Encoder-Decoder Model",
author = "Katsumata, Satoru and
Komachi, Mamoru",
booktitle = "Proceedings of the 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Language Processing",
month = dec,
year = "2020",
address = "Suzhou, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.aacl-main.83",
pages = "827--832",
}
This model achieves the following results:
| Data | Metric | gotutiyan/gec-bart-base |
|---|---|---|
| CoNLL-2014 | M2 (P/R/F0.5) | 70.0 / 38.5 / 60.2 |
| BEA19-test | ERRANT (P/R/F0.5) | 67.7 / 50.1 / 63.3 |
| JFLEG-test | GLEU | 55.2 |
The details can be found in the GitHub repository.
- Library
- transformers
- Type
- bart
- License
- mit
- Created
- Dec 26, 2022
- Updated
- Mar 7, 2026