HITMI&T at SemEval-2022 Task 4: Investigating Task-Adaptive Pretraining And Attention Mechanism On PCL Detection
Zihang Liu, Yancheng He, Feiqing Zhuang, Bing Hao Xu · Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022) · 2022
This paper describes the system for the Semeval-2022 Task4 "Patronizing and Condescending Language Detection".An entity engages in Patronizing and Condescending Language(PCL) when its language use shows a superior attitude towards others or depicts them in a compassionate way.The task contains two parts.The first one is to identify whether the sentence is PCL, and the second one is to categorize PCL.Through experimental verification, the RoBERTa-based model will be used in our system.Respectively, for subtask 1, that is, to judge whether a sentence is PCL, the method of retraining the model with specific task data is adopted, and the method of splicing [CLS] and the keyword representation of the last three layers as the representation of the sentence; for subtask 2, that is, to judge the PCL type of the sentence, in addition to using the same method as task1, the method of selecting a special loss for Multi-label text classification is applied.We give a clear ablation experiment and give the effect of each method on the final result.Our project ranked 11th out of 79 teams participating in subtask 1 and 6th out of 49 teams participating in subtask 2.