Abstract
Emotion Recognition in Conversation (ERC)aims to assign an emotion to a dialogue in aconversation between people. The first subtaskof EDiReF shared task aims to assign an emo-tions to a Hindi-English code mixed conversa-tion. For this, our team proposes a system toidentify the emotion based on fine-tuning largelanguage models on the MaSaC dataset. Forour study we have fine tuned 2 LLMs BERTand Llama 2 to perform sequence classificationto identify the emotion of the text.- Anthology ID:
- 2024.semeval-1.115
- 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:
- 811–815
- Language:
- URL:
- https://aclanthology.org/2024.semeval-1.115
- DOI:
- 10.18653/v1/2024.semeval-1.115
- Cite (ACL):
- Dilip Venkatesh, Pasunti Prasanjith, and Yashvardhan Sharma. 2024. BITS Pilani at SemEval-2024 Task 10: Fine-tuning BERT and Llama 2 for Emotion Recognition in Conversation. In Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024), pages 811–815, Mexico City, Mexico. Association for Computational Linguistics.
- Cite (Informal):
- BITS Pilani at SemEval-2024 Task 10: Fine-tuning BERT and Llama 2 for Emotion Recognition in Conversation (Venkatesh et al., SemEval 2024)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2024.semeval-1.115.pdf