CLTeam1 at SemEval-2024 Task 10: Large Language Model based ensemble for Emotion Detection in Hinglish

Ankit Vaidya, Aditya Gokhale, Arnav Desai, Ishaan Shukla, Sheetal Sonawane


Abstract
This paper outlines our approach for the ERC subtask of the SemEval 2024 EdiREF Shared Task. In this sub-task, an emotion had to be assigned to an utterance which was the part of a dialogue. The utterance had to be classified into one of the following classes- disgust, contempt, anger, neutral, joy, sadness, fear, surprise. Our proposed system makes use of an ensemble of language specific RoBERTA and BERT models to tackle the problem. A weighted F1-score of 44% was achieved by our system in this task. We conducted comprehensive ablations and suggested directions of future work. Our codebase is available publicly.
Anthology ID:
2024.semeval-1.56
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:
365–369
Language:
URL:
https://aclanthology.org/2024.semeval-1.56
DOI:
10.18653/v1/2024.semeval-1.56
Bibkey:
Cite (ACL):
Ankit Vaidya, Aditya Gokhale, Arnav Desai, Ishaan Shukla, and Sheetal Sonawane. 2024. CLTeam1 at SemEval-2024 Task 10: Large Language Model based ensemble for Emotion Detection in Hinglish. In Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024), pages 365–369, Mexico City, Mexico. Association for Computational Linguistics.
Cite (Informal):
CLTeam1 at SemEval-2024 Task 10: Large Language Model based ensemble for Emotion Detection in Hinglish (Vaidya et al., SemEval 2024)
Copy Citation:
PDF:
https://preview.aclanthology.org/dois-2013-emnlp/2024.semeval-1.56.pdf
Supplementary material:
 2024.semeval-1.56.SupplementaryMaterial.txt