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--- |
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license: mit |
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tags: |
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- text-classification |
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- hate-speech-detection |
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- xlm-roberta |
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- multilingual |
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language: |
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- ur |
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- multilingual |
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--- |
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# XLM-RoBERTa for Roman Urdu Hate Speech Detection |
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A fine-tuned XLM-RoBERTa model for detecting hate speech and offensive content in Roman Urdu text. |
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## Model Description |
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This model is based on **xlm-roberta-base** and has been fine-tuned on the Hate Speech Roman Urdu (HS-RU-20) dataset for binary classification: |
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- **Label 0**: Safe/Neutral content |
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- **Label 1**: Toxic/Hate/Offensive content |
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## Model Performance |
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- **F1-Score (Weighted)**: 84.15% |
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- **Accuracy**: 83.72% |
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- **Precision**: 84.69% |
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- **Recall**: 83.72% |
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## Usage |
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### Using Transformers Pipeline |
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```python |
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from transformers import pipeline |
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classifier = pipeline( |
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"text-classification", |
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model="WishAshake/XLM-Roberta" |
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) |
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# Classify text |
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result = classifier("your roman urdu text here") |
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print(result) |
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``` |
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### Using AutoModel |
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```python |
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from transformers import AutoTokenizer, AutoModelForSequenceClassification |
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import torch |
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tokenizer = AutoTokenizer.from_pretrained("WishAshake/XLM-Roberta") |
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model = AutoModelForSequenceClassification.from_pretrained("WishAshake/XLM-Roberta") |
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# Tokenize and predict |
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text = "your roman urdu text here" |
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inputs = tokenizer(text, return_tensors="pt", truncation=True, max_length=128) |
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with torch.no_grad(): |
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outputs = model(**inputs) |
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predictions = torch.nn.functional.softmax(outputs.logits, dim=-1) |
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label = "Toxic" if predictions[0][1] > 0.5 else "Safe" |
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confidence = predictions[0][1].item() if predictions[0][1] > 0.5 else predictions[0][0].item() |
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print(f"Label: {label}, Confidence: {confidence:.4f}") |
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``` |
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## Training Details |
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- **Base Model**: xlm-roberta-base |
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- **Training Framework**: Hugging Face Transformers |
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- **Learning Rate**: 2e-5 |
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- **Batch Size**: 16 |
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- **Max Sequence Length**: 128 |
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- **Epochs**: 5 (with early stopping) |
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- **Optimizer**: AdamW |
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- **Mixed Precision**: FP16 (when GPU available) |
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## Dataset |
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The model was trained on the **Hate Speech Roman Urdu (HS-RU-20)** dataset, which contains: |
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- Text samples in Roman Urdu |
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- Binary labels: Safe/Neutral (0) or Toxic/Hate/Offensive (1) |
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## Limitations |
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- The model is trained specifically on Roman Urdu text and may not perform well on other languages or scripts |
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- Performance may vary on different dialects or regional variations of Roman Urdu |
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- The model may have biases present in the training data |
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## Citation |
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If you use this model in your research, please cite: |
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```bibtex |
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@misc{xlm-roberta-roman-urdu-hate-speech, |
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title={XLM-RoBERTa for Roman Urdu Hate Speech Detection}, |
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author={Wisha Zahid}, |
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year={2024}, |
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howpublished={\url{https://huggingface.co/WishAshake/XLM-Roberta}} |
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} |
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``` |
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## License |
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This model is released under the MIT License. |
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## Contact |
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For questions or issues, please open an issue on the [GitHub repository](https://github.com/WishaZahid/Roman-Urdu-Hate-Speech-using-XLM-Roberta). |
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