Buckets:
| license: apache-2.0 | |
| --- | |
| language: en | |
| license: mit | |
| tags: | |
| - hate-speech-detection | |
| - text-classification | |
| - rationale-extraction | |
| datasets: | |
| - your-dataset-name | |
| metrics: | |
| - accuracy | |
| - f1 | |
| model-index: | |
| - name: hate-speech-rationale-model | |
| results: | |
| - task: | |
| type: text-classification | |
| name: Hate Speech Detection | |
| metrics: | |
| - type: accuracy | |
| value: 0.XX # Your test accuracy | |
| - type: f1 | |
| value: 0.XX # Your test F1 | |
| --- | |
| # Hate Speech Detection with Rationale Extraction | |
| This model detects hate speech in text and provides rationale explanations for its predictions. | |
| ## Model Description | |
| - **Architecture**: HateBERT + Rationale BERT + Multi-Scale CNN + Attention | |
| - **Training Data**: [Describe your dataset] | |
| - **Performance**: | |
| - Validation Loss: 0.27 | |
| - Test Accuracy: XX% | |
| - Test F1: XX% | |
| ## Usage | |
| ```python | |
| from huggingface_hub import hf_hub_download | |
| import torch | |
| # Download model | |
| model_path = hf_hub_download( | |
| repo_id="seffyehl/BetterShield", | |
| filename="pytorch_model.pth" | |
| ) | |
| # Load model (see full example in repository) | |
| checkpoint = torch.load(model_path, map_location='cpu') | |
| # ... (rest of loading code) | |
| ``` | |
| ## Training Details | |
| - **Batch Size**: 8 | |
| - **Learning Rate**: 1e-5 | |
| - **Weight Decay**: 0.05 | |
| - **Dropout**: 0.5 | |
| - **Epochs**: Stopped early at epoch X | |
| ## Limitations | |
| [Describe any known limitations] | |
| ## Citation | |
| ```bibtex | |
| @misc{bettershield-2025, | |
| author = Orion, | |
| title = Hate Speech Detection with Rationale Extraction, | |
| year = 2025, | |
| publisher = HuggingFace, | |
| url = https://huggingface.co/seffyehl/BetterShield | |
| } | |
| ``` |
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