AbstractThis article describes our system for task DravidianLangTech - EACL2021: Meme classification for Tamil. In recent years, we have witnessed the rapid development of the Internet and social media. Compared with traditional TV and radio media platforms, there are not so many restrictions on the use of online social media for individuals and many functions of online social media platforms are free. Based on this feature of social media, it is difficult for people’s posts/comments on social media to be strictly and effectively controlled like TV and radio content. Therefore, the detection of negative information in social media has attracted attention from academic and industrial fields in recent years. The task of classifying memes is also driven by offensive posts/comments prevalent on social media. The data of the meme classification task is the fusion data of text and image information. To identify the content expressed by the meme, we develop a system that combines BiGRU and CNN. It can fuse visual features and text features to achieve the purpose of using multi-modal information from memetic data. In this article, we discuss our methods, models, experiments, and results.