README.md

---
license: mit
language:
- ar
base_model:
- aubmindlab/bert-base-arabertv02
pipeline_tag: token-classification
---

# SWEET<sub>NoPnx</sub> ZAEBUC Model

## Model Description
`CAMeL-Lab/text-editing-zaebuc-pnx` is a text editing model tailored for grammatical error correction (GEC) in Modern Standard Arabic (MSA).
The model is based on [AraBERTv02](https://huggingface.co/aubmindlab/bert-base-arabertv02), which we fine-tuned using the [ZAEBUC](https://sites.google.com/view/zaebuc/home) dataset.
This model was introduced in our ACL 2025 paper, [Enhancing Text Editing for Grammatical Error Correction: Arabic as a Case Study](https://arxiv.org/abs/2503.00985), where we refer to it as SWEET (Subword Edit Error Tagger).

The model was fine-tuned to fix non-punctuation (i.e., NoPnx) errors. Details about the training procedure, data preprocessing, and hyperparameters are available in the paper.
The fine-tuning code and associated resources are publicly available on our GitHub repository: https://github.com/CAMeL-Lab/text-editing.



## Citation
```bibtex
@inter{alhafni-habash-2025-enhancing,
      title={Enhancing Text Editing for Grammatical Error Correction: Arabic as a Case Study}, 
      author={Bashar Alhafni and Nizar Habash},
      year={2025},
      eprint={2503.00985},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2503.00985}, 
}
```