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Model Card for German Hate Speech Classifier
Model Details
Introduction
This model was developed to explore the potential of German language models in multi-class classification of hate speech in German online journals. It is a fine-tuned version of the GBERT model from (Chan, Schweter, and Möller, 2020).
Dataset
The dataset used for training is a consolidation of three pre-existing German hate speech datasets:
- RP (Assenmacher et al., 2021)
- DeTox (Demus et al., 2022)
- Twitter dataset (Glasenbach, 2022)
The combined dataset underwent cleaning to minimize biases and remove redundant data.
Performance
Our experiments delivered promising results, with the model reliably classifying comments into:
- No Hate Speech
- Other Hate Speech (Threat, Insult, Profanity)
- Political Hate Speech
- Racist Hate Speech
- Sexist Hate Speech
The model achieved a macro F1-score of 0.775. However, to further reduce misclassifications, improvements are essential. Short comments are overproportionally classified as Sexist Hate Speech.
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