SMASH at AraFinNLP2024: Benchmarking Arabic BERT Models on the Intent Detection

Youssef Al Hariri, Ibrahim Abu Farha


Abstract
The recent growth in Middle Eastern stock markets has intensified the demand for specialized financial Arabic NLP models to serve this sector. This article presents the participation of Team SMASH of The University of Edinburgh in the Multi-dialect Intent Detection task (Subtask 1) of the Arabic Financial NLP (AraFinNLP) Shared Task 2024. The dataset used in the shared task is the ArBanking77 (Jarrar et al., 2023). We tackled this task as a classification problem and utilized several BERT and BART-based models to classify the queries efficiently. Our solution is based on implementing a two-step hierarchical classification model based on MARBERTv2. We fine-tuned the model by using the original queries. Our team, SMASH, was ranked 9th with a macro F1 score of 0.7866, indicating areas for further refinement and potential enhancement of the model’s performance.
Anthology ID:
2024.arabicnlp-1.35
Volume:
Proceedings of The Second Arabic Natural Language Processing Conference
Month:
August
Year:
2024
Address:
Bangkok, Thailand
Editors:
Nizar Habash, Houda Bouamor, Ramy Eskander, Nadi Tomeh, Ibrahim Abu Farha, Ahmed Abdelali, Samia Touileb, Injy Hamed, Yaser Onaizan, Bashar Alhafni, Wissam Antoun, Salam Khalifa, Hatem Haddad, Imed Zitouni, Badr AlKhamissi, Rawan Almatham, Khalil Mrini
Venues:
ArabicNLP | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
403–409
Language:
URL:
https://aclanthology.org/2024.arabicnlp-1.35
DOI:
10.18653/v1/2024.arabicnlp-1.35
Bibkey:
Cite (ACL):
Youssef Al Hariri and Ibrahim Abu Farha. 2024. SMASH at AraFinNLP2024: Benchmarking Arabic BERT Models on the Intent Detection. In Proceedings of The Second Arabic Natural Language Processing Conference, pages 403–409, Bangkok, Thailand. Association for Computational Linguistics.
Cite (Informal):
SMASH at AraFinNLP2024: Benchmarking Arabic BERT Models on the Intent Detection (Al Hariri & Abu Farha, ArabicNLP-WS 2024)
Copy Citation:
PDF:
https://aclanthology.org/2024.arabicnlp-1.35.pdf