Modelling Sentiment Analysis: LLMs and data augmentation techniques

This paper provides different approaches for a binary sentiment classification on a small training dataset. LLMs that provided state-of-the-art results in sentiment analysis and similar domains are being used, such as BERT, RoBERTa and XLNet. The reader can also find different data augmentation techniques to deal with the small amount of training data provided.