  In this paper, we describe the team \textit{BRUMS} entry to OffensEval 2:
Multilingual Offensive Language Identification in Social Media in SemEval-2020.
The OffensEval organizers provided participants with annotated datasets
containing posts from social media in Arabic, Danish, English, Greek and
Turkish. We present a multilingual deep learning model to identify offensive
language in social media. Overall, the approach achieves acceptable evaluation
scores, while maintaining flexibility between languages.
