NLPopsCIOL@DravidianLangTech 2025: Classification of Abusive Tamil and Malayalam Text Targeting Women Using Pre-trained Models

• Authors: Abdullah Al Nahian, Mst Rafia Islam, Azmine Toushik Wasi, Md Manjurul Ahsan

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Abstract: Hate speech detection in multilingual and code-mixed contexts remains a significant challenge due to linguistic diversity and overlapping syntactic structures. This paper presents a study on the detection of hate speech in Tamil and Malayalam using transformer-based models. Our goal is to address underfitting and develop effective models for hate speech classification. We evaluate several pre-trained models, including MuRIL and XLM-RoBERTa, and show that fine-tuning is crucial for better performance. The test results show a Macro-F1 score of 0.7039 for Tamil and 0.6402 for Malayalam, highlighting the promise of these models with further improvements in fine-tuning. We also discuss data preprocessing techniques, model implementations, and experimental findings.