Abstract
Our system, submitted to the Nuanced Arabic Dialect Identification (NADI-23), tackles the first sub-task: Closed Country-level dialect identification. In this work, we propose a model that is based on an ensemble of layer-wise fine-tuned BERT-based models. The proposed model ranked fourth out of sixteen submissions, with an F1-macro score of 85.43.- Anthology ID:
- 2023.arabicnlp-1.65
- Volume:
- Proceedings of ArabicNLP 2023
- Month:
- December
- Year:
- 2023
- Address:
- Singapore (Hybrid)
- Editors:
- Hassan Sawaf, Samhaa El-Beltagy, Wajdi Zaghouani, Walid Magdy, Ahmed Abdelali, Nadi Tomeh, Ibrahim Abu Farha, Nizar Habash, Salam Khalifa, Amr Keleg, Hatem Haddad, Imed Zitouni, Khalil Mrini, Rawan Almatham
- Venues:
- ArabicNLP | WS
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 625–630
- Language:
- URL:
- https://aclanthology.org/2023.arabicnlp-1.65
- DOI:
- 10.18653/v1/2023.arabicnlp-1.65
- Cite (ACL):
- Nada Almarwani and Samah Aloufi. 2023. SANA at NADI 2023 shared task: Ensemble of Layer-Wise BERT-based models for Dialectal Arabic Identification. In Proceedings of ArabicNLP 2023, pages 625–630, Singapore (Hybrid). Association for Computational Linguistics.
- Cite (Informal):
- SANA at NADI 2023 shared task: Ensemble of Layer-Wise BERT-based models for Dialectal Arabic Identification (Almarwani & Aloufi, ArabicNLP-WS 2023)
- PDF:
- https://preview.aclanthology.org/emnlp-22-attachments/2023.arabicnlp-1.65.pdf