English

Transformer Ensembles for Sexism Detection

Computation and Language 2021-11-01 v1

Abstract

This document presents in detail the work done for the sexism detection task at EXIST2021 workshop. Our methodology is built on ensembles of Transformer-based models which are trained on different background and corpora and fine-tuned on the provided dataset from the EXIST2021 workshop. We report accuracy of 0.767 for the binary classification task (task1), and f1 score 0.766, and for the multi-class task (task2) accuracy 0.623 and f1-score 0.535.

Keywords

Cite

@article{arxiv.2110.15905,
  title  = {Transformer Ensembles for Sexism Detection},
  author = {Lily Davies and Marta Baldracchi and Carlo Alessandro Borella and Konstantinos Perifanos},
  journal= {arXiv preprint arXiv:2110.15905},
  year   = {2021}
}