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.
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CITATION STYLE
Hariprasad, S., Esackimuthu, S., Madhavan, S., Sivanaiah, R., & Deborah Suseelan, A. (2022). SSN_MLRG1@DravidianLangTech-ACL2022: Troll Meme Classification in Tamil using Transformer Models. In DravidianLangTech 2022 - 2nd Workshop on Speech and Language Technologies for Dravidian Languages, Proceedings of the Workshop (pp. 132–137). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2022.dravidianlangtech-1.21
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