Abstract
This paper describes the system and the resulted models submitted by our team "IISERB Brains" to SemEval-2022 Task 6 competition. We participated in the three sub-tasks for English language datasets. Our submitted models use BERT-based classifiers along with data augmentation. We ranked 19th out of 43 teams for sub-task A, 8th rank out of 22 teams for sub-task B, and 13th rank out of 16 teams for sub-task C. In this paper, we describe details of our submissions, related evaluation and additional experiments conducted post the termination of the shared task. Our code and used additional resources are present in GitHub for reproducibility. Authors with equal contributions are marked by *.
Cite
CITATION STYLE
Shekhawat, T. S., Kumar, M., Rathore, U., Joshi, A., & Patro, J. (2022). IISERB Brains at SemEval-2022 Task 6: A Deep-learning Framework to Identify Intended Sarcasm in English. In SemEval 2022 - 16th International Workshop on Semantic Evaluation, Proceedings of the Workshop (pp. 938–944). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2022.semeval-1.131
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