YNU-HPCC at SemEval-2022 Task 4: Finetuning Pretrained Language Models for Patronizing and Condescending Language Detection
Wenqiang Bai, Jin Wang, Xuejie Zhang · Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022) · 2022
This paper describes a system built for the SemEval-2022 competition.As participants in Task 4: Patronizing and Condescending Language Detection, we implemented the text sentiment classification system for two subtasks in English.Both subtasks involve determining emotions; subtask 1 requires us to determine whether the text belongs to the PCL category (single-label classification), and subtask 2 requires us to determine to which PCL category the text belongs (multi-label classification).Our system is based on the bidirectional encoder representations from transformers (BERT) model.For the single-label classification, our system applies a BertForSequence-Classification model to classify the input text.For the multi-label classification, we use the fine-tuned BERT model to extract the sentiment score of the text and a fully connected layer to classify the text into the PCL categories.Our system achieved relatively good results on the competition's official leaderboard.