Social Media platforms have grown their reach worldwide. As an effect of this growth, many vernacular social media platforms have also emerged, focusing more on the diverse languages in the specific regions. Tamil has also emerged as a popular language for use on social media platforms due to the increasing penetration of vernacular media like Sharechat and Moj, which focus more on local Indian languages than English and encourage their users to converse in Indic languages. Abusive language remains a significant challenge in the social media framework and more so when we consider languages like Tamil, which are low-resource languages and have poor performance on multilingual models and lack language-specific models. Based on this shared task, “Abusive Comment detection in Tamil@DravidianLangTech-ACL 2022”, we present an exploration of different techniques used to tackle and increase the accuracy of our models using data augmentation in NLP. We also show the results of these techniques.