Update README.md

README.md

@@ -5,4 +5,31 @@ language:
 base_model:
 - aubmindlab/bert-base-arabertv02
 pipeline_tag: token-classification
----
+---
+
+# SWEET MADAR CODA Model
+
+## Model Description
+`CAMeL-Lab/text-editing-coda' is a text editing model tailored for grammatical error correction (GEC) in dialectal Arabic (DA).
+The model is based on [AraBERTv02](https://huggingface.co/aubmindlab/bert-base-arabertv02), which we fine-tuned using the MADAR CODA corpus.
+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).
+It achieved SOTA performance on the MADAR CODA dataset. 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}, 
+}
+```
+
+
+