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In this paper, we describe our approach to utilize pre-trained BERT modelswith Convolutional Neural Networks for sub-task A of the Multilingual OffensiveLanguage Identification shared task (OffensEval 2020), which is a part of theSemEval 2020. We show that combining CNN with BERT is better than using BERT onits own, and we emphasize the importance of utilizing pre-trained languagemodels for downstream tasks. Our system, ranked 4th with macro averagedF1-Score of 0.897 in Arabic, 4th with score of 0.843 in Greek, and 3rd withscore of 0.814 in Turkish. Additionally, we present ArabicBERT, a set ofpre-trained transformer language models for Arabic that we share with thecommunity.

KUISAIL at SemEval-2020 Task 12: BERT-CNN for Offensive Speech Identification in Social Media