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The Explainable Detection of Online Sexism task presents the problem ofexplainable sexism detection through fine-grained categorisation of sexistcases with three subtasks. Our team experimented with different ways to combatclass imbalance throughout the tasks using data augmentation and lossalteration techniques. We tackled the challenge by utilising ensembles ofTransformer models trained on different datasets, which are tested to find thebalance between performance and interpretability. This solution ranked us inthe top 40\% of teams for each of the tracks.

AdamR at SemEval-2023 Task 10: Solving the Class Imbalance Problem in Sexism Detection with Ensemble Learning