论文标题
Semeval-2020任务12：基于变压器的多语言进攻语言标识
BRUMS at SemEval-2020 Task 12 : Transformer based Multilingual Offensive Language Identification in Social Media
论文作者
论文摘要
在本文中，我们描述了犯罪2：Semeval-2020社交媒体中的多语言进攻语言标识的团队。犯罪组织者为参与者提供了带注释的数据集，其中包含来自社交媒体的帖子，丹麦语，英语，希腊语和土耳其语。我们提出了一个多语言深度学习模型，以识别社交媒体中的冒犯性语言。总体而言，该方法可以达到可接受的评估得分，同时保持语言之间的灵活性。
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.
