  This research presents our team KEIS@JUST participation at SemEval-2020 Task
12 which represents shared task on multilingual offensive language. We
participated in all the provided languages for all subtasks except sub-task-A
for the English language. Two main approaches have been developed the first is
performed to tackle both languages Arabic and English, a weighted ensemble
consists of Bi-GRU and CNN followed by Gaussian noise and global pooling layer
multiplied by weights to improve the overall performance. The second is
performed for other languages, a transfer learning from BERT beside the
recurrent neural networks such as Bi-LSTM and Bi-GRU followed by a global
average pooling layer. Word embedding and contextual embedding have been used
as features, moreover, data augmentation has been used only for the Arabic
language.
