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2022 NAACL NAACL 2022

IITR CodeBusters at SemEval-2022 Task 5: Misogyny Identification using Transformers

Abstract

AbstractThis paper presents our submission to task 5 ( Multimedia Automatic Misogyny Identification) of the SemEval 2022 competition. The purpose of the task is to identify given memes as misogynistic or not and further label the type of misogyny involved. In this paper, we present our approach based on language processing tools. We embed meme texts using GloVe embedding and classify misogyny using BERT model. Our model obtains an F1-score of 66.24% and 63.5% in misogyny classification and misogyny labels, respectively.

🌉 Interdisciplinary Bridge — Deep Learning and Machine Learning
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio

Authors

Gagan Sharma , Gajanan Sunil Gitte , Shlok Goyal , Raksha Sharma

Topics

Machine Learning > Core Methods > Classification Deep Learning > Architectures > Transformers Deep Learning > Techniques > Pretraining

Keywords

text classification word embedding hate speech detection
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