Abstract
This paper presents transformer-based models for the “Abusive Comment Detection” shared task at the Second Workshop on Speech and Language Technologies for Dravidian Languages at ACL 2022. Our team participated in both the multi-class classification sub-tasks as a part of this shared task. The dataset for sub-task A was in Tamil text; while B was code-mixed Tamil-English text. Both the datasets contained 8 classes of abusive comments. We trained an XLM-RoBERTa and DeBERTA base model on the training splits for each sub-task. For sub-task A, the XLM-RoBERTa model achieved an accuracy of 0.66 and the DeBERTa model achieved an accuracy of 0.62. For sub-task B, both the models achieved a classification accuracy of 0.72; however, the DeBERTa model performed better in other classification metrics. Our team ranked 2nd in the code-mixed classification sub-task and 8th in Tamil-text sub-task.- Anthology ID:
- 2022.dravidianlangtech-1.15
- Volume:
- Proceedings of the Second Workshop on Speech and Language Technologies for Dravidian Languages
- Month:
- May
- Year:
- 2022
- Address:
- Dublin, Ireland
- Venue:
- DravidianLangTech
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 93–99
- Language:
- URL:
- https://aclanthology.org/2022.dravidianlangtech-1.15
- DOI:
- 10.18653/v1/2022.dravidianlangtech-1.15
- Cite (ACL):
- Gaurang Prasad, Janvi Prasad, and Gunavathi C. 2022. GJG@TamilNLP-ACL2022: Using Transformers for Abusive Comment Classification in Tamil. In Proceedings of the Second Workshop on Speech and Language Technologies for Dravidian Languages, pages 93–99, Dublin, Ireland. Association for Computational Linguistics.
- Cite (Informal):
- GJG@TamilNLP-ACL2022: Using Transformers for Abusive Comment Classification in Tamil (Prasad et al., DravidianLangTech 2022)
- PDF:
- https://preview.aclanthology.org/auto-file-uploads/2022.dravidianlangtech-1.15.pdf