SSN_Semeval10 at SemEval-2024 Task 10: Emotion Discovery and Reasoning its Flip in Conversations

This paper presents a transformer-based classifier for recognizing emotions in Hindi-English code-mixed conversations, adhering to the SemEval task constraints. Leveraging BERT-based transformers, we fine-tune pre-trained models (mBERT and indicBERT) on the dataset, incorporating tokenization and attention mechanisms. Our approach achieved competitive performance (weighted F1-score of 0.4), showcasing the effectiveness of BERT in nuanced emotion analysis tasks within code-mixed conversational contexts. This F1-score was ranked 16th among the 39 submissions.