Felix&Julia at SemEval-2022 Task 4: Patronizing and Condescending Language Detection

0Citations
Citations of this article
35Readers
Mendeley users who have this article in their library.

Abstract

This paper describes the authors' submission to the SemEval-2022 task 4: Patronizing and Condescending Language (PCL) Detection. The aim of the task is the detection and classification of PCL in an annotated dataset. The authors of this paper worked on two different models with finetuned hyperparameters focusing on number of epochs, training batch size, evaluation batch size, gradient accumulation steps and learning rate. The authors submitted one RoBERTa model and one DistilBERT model. Both systems performed better than the random and RoBERTA baseline given by the task organizers. The RoBERTA model finetuned by the authors performed better in both subtasks than the DistilBERT model.

Cite

CITATION STYLE

APA

Herrmann, F., & Krebs, J. (2022). Felix&Julia at SemEval-2022 Task 4: Patronizing and Condescending Language Detection. In SemEval 2022 - 16th International Workshop on Semantic Evaluation, Proceedings of the Workshop (pp. 357–362). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2022.semeval-1.46

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free