Papers › HateBERT: Retraining BERT for Abusive Language Detection in English
HateBERT: Retraining BERT for Abusive Language Detection in English
Tommaso Caselli, Valerio Basile, Jelena Mitrović, Michael Granitzer
In this paper, we introduce HateBERT, a re-trained BERT model for abusive language detection in English. The model was trained on RAL-E, a large-scale dataset of Reddit comments in English from communities banned for being offensive, abusive, or hateful that we have collected and made available to the public. We present the results of a detailed comparison between a general pre-trained language model and the abuse-inclined version obtained by retraining with posts from the banned communities on three English datasets for offensive, abusive language and hate speech detection tasks. In all datasets, HateBERT outperforms the corresponding general BERT model. We also discuss a battery of experiments comparing the portability of the generic pre-trained language model and its corresponding abusive language-inclined counterpart across the datasets, indicating that portability is affected by compatibility of the annotated phenomena.
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Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Hate Speech Detection | AbusEval | HateBERT | Macro F1 | 0.742 | #1 of 2 | Archive leaderboard | report |
| Hate Speech Detection | AbusEval | BERT | Macro F1 | 0.724 | #2 of 2 | Archive leaderboard | report |
| Hate Speech Detection | HatEval | HateBERT | Macro F1 | 0.494 | #1 of 2 | Archive leaderboard | report |
| Hate Speech Detection | HatEval | BERT | Macro F1 | 0.48 | #2 of 2 | Archive leaderboard | report |
| Hate Speech Detection | OffensEval 2019 | HateBERT | Macro F1 | 0.805 | #1 of 2 | Archive leaderboard | report |
| Hate Speech Detection | OffensEval 2019 | BERT | Macro F1 | 0.803 | #2 of 2 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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