Abstract
Hate speech and toxic comment detection on social media has proven to be an essential issue for content moderation. This paper displays a comparison between different Transformer models for Hate Speech detection such as Hate BERT, a BERT-based model, RoBERTa and BERTweet which is a RoBERTa based model. These Transformer models are tested on Jibes&Delight 2021 reddit dataset using the same training and testing conditions. Multiple approaches are detailed in this paper considering feature extraction and data augmentation. The paper concludes that our RoBERTa st4-aug model trained with data augmentation outperforms simple RoBERTa and HateBERT models.