ISDS-NLP at SemEval-2024 Task 10: Transformer based neural networks for emotion recognition in conversations
Claudiu Creanga, Liviu P. Dinu · 2024
This paper outlines the approach of the ISDS-NLP team in the SemEval 2024 Task 10: Emotion Discovery and Reasoning its Flip in Conversation (EDiReF).For Subtask 1 we obtained a weighted F1 score of 0.43 and placed 12 in the leaderboard.We investigate two distinct approaches: Masked Language Modeling (MLM) and Causal Language Modeling (CLM).For MLM, we employ pre-trained BERT-like models in a multilingual setting, fine-tuning them with a classifier to predict emotions.Experiments with varying input lengths, classifier architectures, and fine-tuning strategies demonstrate the effectiveness of this approach.Additionally, we utilize Mistral 7B Instruct V0.2, a state-of-the-art model, applying zero-shot and few-shot prompting techniques.Our findings indicate that while Mistral shows promise, MLMs currently outperform them in sentencelevel emotion classification.