UFAL-ULD at BLP-2023 Task 2 Sentiment Classification in Bangla Text

Sourabrata Mukherjee, Atul Kr. Ojha, Ondřej Dušek


Abstract
In this paper, we present the UFAL-ULD team’s system for the BLP Shared Task 2: Sentiment Analysis of Bangla Social Media Posts. The Task 2 involves classifying text into Positive, Negative, or Neutral sentiments. As a part of this task, we conducted a series of experiments with several pre-trained sequence classification models – XLM-RoBERTa, BanglaBERT, Bangla BERT Base and Multilingual BERT. Among these, our best-performing model was based on the XLM-RoBERTa-base architecture, which outperforms baseline models. Our system was ranked 19th among the 30 teams that participated in the task.
Anthology ID:
2023.banglalp-1.45
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:
336–339
Language:
URL:
https://aclanthology.org/2023.banglalp-1.45
DOI:
10.18653/v1/2023.banglalp-1.45
Bibkey:
Cite (ACL):
Sourabrata Mukherjee, Atul Kr. Ojha, and Ondřej Dušek. 2023. UFAL-ULD at BLP-2023 Task 2 Sentiment Classification in Bangla Text. In Proceedings of the First Workshop on Bangla Language Processing (BLP-2023), pages 336–339, Singapore. Association for Computational Linguistics.
Cite (Informal):
UFAL-ULD at BLP-2023 Task 2 Sentiment Classification in Bangla Text (Mukherjee et al., BanglaLP 2023)
Copy Citation:
PDF:
https://aclanthology.org/2023.banglalp-1.45.pdf