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

Article scientifique 2023 Anglais

Résumé

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.

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Lamsiyah, S., Mahdaouy, A., Alami, H., Berrada, I., Schommer, C. (2023). UL & UM6P at SemEval-2023 Task 10: Semi-Supervised Multi-task Learning for Explainable Detection of Online Sexism. https://doi.org/10.18653/v1/2023.semeval-1.88

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Auteur(s)

Salima Lamsiyah Abdelkader El Mahdaouy Hamza Alami Ismaïl Berrada Christoph Schommer

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