YNUWB at SemEval-2019 Task 6: K-max pooling CNN with average meta-embedding for identifying offensive language
Bin Wang, Xiaobing Zhou, Xuejie Zhang · 2019
This paper describes the system submitted to SemEval 2019 Task 6: OffensEval 2019.The task aims to identify and categorize offensive language in social media, we only participate in Sub-task A, which aims to identify offensive language.In order to address this task, we propose a system based on a K-max pooling convolutional neural network model, and use an argument for averaging as a valid meta-embedding technique to get a metaembedding.Finally, we use a cyclic learning rate policy to improve model performance.Our model achieves a Macro F1-score of 0.802 (ranked 9/103) in the Sub-task A.