SSN_MLRG1@DravidianLangTech-ACL2022: Troll Meme Classification in Tamil using Transformer Models

Shruthi Hariprasad, Sarika Esackimuthu, Saritha Madhavan, Rajalakshmi Sivanaiah, Angel S


Abstract
The ACL shared task of DravidianLangTech-2022 for Troll Meme classification is a binary classification task that involves identifying Tamil memes as troll or not-troll. Classification of memes is a challenging task since memes express humour and sarcasm in an implicit way. Team SSN_MLRG1 tested and compared results obtained by using three models namely BERT, ALBERT and XLNET. The XLNet model outperformed the other two models in terms of various performance metrics. The proposed XLNet model obtained the 3rd rank in the shared task with a weighted F1-score of 0.558.
Anthology ID:
2022.dravidianlangtech-1.21
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:
132–137
Language:
URL:
https://aclanthology.org/2022.dravidianlangtech-1.21
DOI:
10.18653/v1/2022.dravidianlangtech-1.21
Bibkey:
Cite (ACL):
Shruthi Hariprasad, Sarika Esackimuthu, Saritha Madhavan, Rajalakshmi Sivanaiah, and Angel S. 2022. SSN_MLRG1@DravidianLangTech-ACL2022: Troll Meme Classification in Tamil using Transformer Models. In Proceedings of the Second Workshop on Speech and Language Technologies for Dravidian Languages, pages 132–137, Dublin, Ireland. Association for Computational Linguistics.
Cite (Informal):
SSN_MLRG1@DravidianLangTech-ACL2022: Troll Meme Classification in Tamil using Transformer Models (Hariprasad et al., DravidianLangTech 2022)
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PDF:
https://preview.aclanthology.org/ingestion-script-update/2022.dravidianlangtech-1.21.pdf