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This paper describes our participation in the shared task of hate speechdetection, which is one of the subtasks of the CERIST NLP Challenge 2022. Ourexperiments evaluate the performance of six transformer models and theircombination using 2 ensemble approaches. The best results on the training set,in a five-fold cross validation scenario, were obtained by using the ensembleapproach based on the majority vote. The evaluation of this approach on thetest set resulted in an F1-score of 0.60 and an Accuracy of 0.86.

Transformers and Ensemble methods: A solution for Hate Speech Detection in Arabic languages