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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. |