Abstract
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 sentence-level emotion classification.- Anthology ID:
- 2024.semeval-1.95
- Volume:
- Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024)
- Month:
- June
- Year:
- 2024
- Address:
- Mexico City, Mexico
- Editors:
- Atul Kr. Ojha, A. Seza Doğruöz, Harish Tayyar Madabushi, Giovanni Da San Martino, Sara Rosenthal, Aiala Rosá
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 649–654
- Language:
- URL:
- https://aclanthology.org/2024.semeval-1.95
- DOI:
- 10.18653/v1/2024.semeval-1.95
- Cite (ACL):
- Claudiu Creanga and Liviu P. Dinu. 2024. ISDS-NLP at SemEval-2024 Task 10: Transformer based neural networks for emotion recognition in conversations. In Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024), pages 649–654, Mexico City, Mexico. Association for Computational Linguistics.
- Cite (Informal):
- ISDS-NLP at SemEval-2024 Task 10: Transformer based neural networks for emotion recognition in conversations (Creanga & Dinu, SemEval 2024)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2024.semeval-1.95.pdf