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This research presents our team KEIS@JUST participation at SemEval-2020 Task12 which represents shared task on multilingual offensive language. Weparticipated in all the provided languages for all subtasks except sub-task-Afor the English language. Two main approaches have been developed the first isperformed to tackle both languages Arabic and English, a weighted ensembleconsists of Bi-GRU and CNN followed by Gaussian noise and global pooling layermultiplied by weights to improve the overall performance. The second isperformed for other languages, a transfer learning from BERT beside therecurrent neural networks such as Bi-LSTM and Bi-GRU followed by a globalaverage pooling layer. Word embedding and contextual embedding have been usedas features, moreover, data augmentation has been used only for the Arabiclanguage.

KEIS@JUST at SemEval-2020 Task 12: Identifying Multilingual Offensive Tweets Using Weighted Ensemble and Fine-Tuned BERT