ISDS-NLP at SemEval-2024 Task 10: Transformer based neural networks for emotion recognition in conversations

Claudiu Creanga, Liviu P. Dinu


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:
Bibkey:
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)
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PDF:
https://preview.aclanthology.org/ingestion-checklist/2024.semeval-1.95.pdf
Supplementary material:
 2024.semeval-1.95.SupplementaryMaterial.txt
Supplementary material:
 2024.semeval-1.95.SupplementaryMaterial.zip