Reproducibility Report: Contextualizing Hate Speech Classifiers with Post-hoc Explanation

The presented report evaluates Contextualizing Hate Speech Classifiers with Post-hoc Explanation Kennedy et al. (2020) paper within the scope of ML Reproducibility Challenge 2020. Our work focuses on both aspects constituting the paper: the method itself and the validity of the stated results. In the following sections, we have described the paper, related works, algorithmic frameworks, our experiments and evaluations. Scope of Reproducibility For the GHC (a dataset), the most important difference between BERT WR and BERT SOC is the increase in recall. While, for Stormfront (a dataset), there are similar improvements for in-domain data and the NYT dataset. But, for verifying the claims we also have tried to run the same experiment on a new data-set.