UL & UM6P at SemEval-2023 Task 10: Semi-Supervised Multi-task Learning for Explainable Detection of Online Sexism

Salima Lamsiyah, Abdelkader El Mahdaouy, Hamza Alami, Ismail Berrada, Christoph Schommer


Abstract
This paper introduces our participating system to the Explainable Detection of Online Sexism (EDOS) SemEval-2023 - Task 10: Explainable Detection of Online Sexism. The EDOS shared task covers three hierarchical sub-tasks for sexism detection, coarse-grained and fine-grained categorization. We have investigated both single-task and multi-task learning based on RoBERTa transformer-based language models. For improving the results, we have performed further pre-training of RoBERTa on the provided unlabeled data. Besides, we have employed a small sample of the unlabeled data for semi-supervised learning using the minimum class-confusion loss. Our system has achieved macro F1 scores of 82.25\%, 67.35\%, and 49.8\% on Tasks A, B, and C, respectively.
Anthology ID:
2023.semeval-1.88
Volume:
Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)
Month:
July
Year:
2023
Address:
Toronto, Canada
Editors:
Atul Kr. Ojha, A. Seza Doğruöz, Giovanni Da San Martino, Harish Tayyar Madabushi, Ritesh Kumar, Elisa Sartori
Venue:
SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
644–650
Language:
URL:
https://aclanthology.org/2023.semeval-1.88
DOI:
10.18653/v1/2023.semeval-1.88
Bibkey:
Cite (ACL):
Salima Lamsiyah, Abdelkader El Mahdaouy, Hamza Alami, Ismail Berrada, and Christoph Schommer. 2023. UL & UM6P at SemEval-2023 Task 10: Semi-Supervised Multi-task Learning for Explainable Detection of Online Sexism. In Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023), pages 644–650, Toronto, Canada. Association for Computational Linguistics.
Cite (Informal):
UL & UM6P at SemEval-2023 Task 10: Semi-Supervised Multi-task Learning for Explainable Detection of Online Sexism (Lamsiyah et al., SemEval 2023)
Copy Citation:
PDF:
https://aclanthology.org/2023.semeval-1.88.pdf