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2022 SemEval SemEval 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.

🐣 Hot Topic Early Bird - misogyny detection

Authors

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

Topics

Machine Learning > Core Methods > Classification Machine Learning > Core Methods > Embedding Learning Deep Learning > Architectures > Transformers

Keywords

transfer learning text classification word embedding misogyny detection
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