BERT and RoBERTa models fine-tuned on the MNLI dataset, optimized for binary entailment/non-entailment classification. Additionally, their performance is explored in handling figurative language.

Implementing VADER, RoBERTa and TextCNN on a twitter dataset from Kaggle

Code associated with the "Enhanced Cognitive Distortions Detection and Classification through Data Augmentation Techniques" paper

Fine-tuning RoBERTa sentiment analysis model on tweets about the Coachella 2015 music festival lineup

In this project we have tried to do multi-label hate-speech classification in Bengali and Hindi language using fill-mask transformer models.