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

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 finegrained 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.