  This paper describes SalamNET, an Arabic offensive language detection system
that has been submitted to SemEval 2020 shared task 12: Multilingual Offensive
Language Identification in Social Media. Our approach focuses on applying
multiple deep learning models and conducting in depth error analysis of results
to provide system implications for future development considerations. To pursue
our goal, a Recurrent Neural Network (RNN), a Gated Recurrent Unit (GRU), and
Long-Short Term Memory (LSTM) models with different design architectures have
been developed and evaluated. The SalamNET, a Bi-directional Gated Recurrent
Unit (Bi-GRU) based model, reports a macro-F1 score of 0.83.
