license:cc-by-4.0 size_categories:10K<n<100K format:csv modality:tabular modality:text library:datasets library:pandas library:mlcroissant library:polars doi:10.57967/hf/2463 region:us
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license: cc-by-4.0
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The dataset HateDebias was created to address the problem of detecting and mitigating biases in hate speech detection models, particularly under conditions that simulate real-world scenarios with continuous and varying biases. The goal is to provide a benchmark that evaluates the ability of hate speech detection models to adapt to different types of biases, ensuring they can maintain high performance and fairness even as new biases emerge over time.