  In this paper, we describe our approach to utilize pre-trained BERT models
with Convolutional Neural Networks for sub-task A of the Multilingual Offensive
Language Identification shared task (OffensEval 2020), which is a part of the
SemEval 2020. We show that combining CNN with BERT is better than using BERT on
its own, and we emphasize the importance of utilizing pre-trained language
models for downstream tasks. Our system, ranked 4th with macro averaged
F1-Score of 0.897 in Arabic, 4th with score of 0.843 in Greek, and 3rd with
score of 0.814 in Turkish. Additionally, we present ArabicBERT, a set of
pre-trained transformer language models for Arabic that we share with the
community.
