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
- 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)
- PDF:
- https://preview.aclanthology.org/dois-2013-emnlp/2023.banglalp-1.45.pdf