Semantics Squad at BLP-2023 Task 2: Sentiment Analysis of Bangla Text with Fine Tuned Transformer Based Models

Krishno Dey, Md. Arid Hasan, Prerona Tarannum, Francis Palma


Abstract
Sentiment analysis (SA) is a crucial task in natural language processing, especially in contexts with a variety of linguistic features, like Bangla. We participated in BLP-2023 Shared Task 2 on SA of Bangla text. We investigated the performance of six transformer-based models for SA in Bangla on the shared task dataset. We fine-tuned these models and conducted a comprehensive performance evaluation. We ranked 20th on the leaderboard of the shared task with a blind submission that used BanglaBERT Small. BanglaBERT outperformed other models with 71.33% accuracy, and the closest model was BanglaBERT Large, with an accuracy of 70.90%. BanglaBERT consistently outperformed others, demonstrating the benefits of models developed using sizable datasets in Bangla.
Anthology ID:
2023.banglalp-1.41
Volume:
Proceedings of the First Workshop on Bangla Language Processing (BLP-2023)
Month:
December
Year:
2023
Address:
Singapore
Editors:
Firoj Alam, Sudipta Kar, Shammur Absar Chowdhury, Farig Sadeque, Ruhul Amin
Venue:
BanglaLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
312–316
Language:
URL:
https://aclanthology.org/2023.banglalp-1.41
DOI:
10.18653/v1/2023.banglalp-1.41
Bibkey:
Cite (ACL):
Krishno Dey, Md. Arid Hasan, Prerona Tarannum, and Francis Palma. 2023. Semantics Squad at BLP-2023 Task 2: Sentiment Analysis of Bangla Text with Fine Tuned Transformer Based Models. In Proceedings of the First Workshop on Bangla Language Processing (BLP-2023), pages 312–316, Singapore. Association for Computational Linguistics.
Cite (Informal):
Semantics Squad at BLP-2023 Task 2: Sentiment Analysis of Bangla Text with Fine Tuned Transformer Based Models (Dey et al., BanglaLP 2023)
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PDF:
https://preview.aclanthology.org/ingest-2024-clasp/2023.banglalp-1.41.pdf