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
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
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