hossam87
/

bert-base-arabic-hate-speech

@@ -1,199 +1,125 @@
 ---
 library_name: transformers
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 ---
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 ---
 library_name: transformers
+pipeline_tag: text-classification
+tags:
+- hate-speech
+- arabic
+- classification
+- bert
+- social-media
+- moderation
+language:
+- ar
+license: mit
+datasets:
+- IbrahimAmin/egyptian-arabic-hate-speech
+metrics:
+- accuracy
+- f1
+widget:
+- text: هذا نص عربي للاختبار
+base_model:
+- CAMeL-Lab/bert-base-arabic-camelbert-da-sentiment
 ---
+# Model Card for hossam87/bert-base-arabic-hate-speech
+A fine-tuned BERT model to classify Arabic text into: Neutral, Offensive, Sexism, Religious Discrimination, or Racism.
+---
 ## Model Details
 ### Model Description
+This model is based on `bert-base-multilingual-cased` and fine-tuned on an Arabic social media dataset for hate speech detection.
+It classifies Arabic text into one of five categories: Neutral, Offensive, Sexism, Religious Discrimination, or Racism.
+Intended uses include moderation, analytics, and academic research.
+- **Developed by:** [hossam87](https://huggingface.co/hossam87)
+- **Model type:** Sequence classification (BERT)
+- **Language(s):** Arabic (ar)
+- **License:** MIT
+- **Finetuned from model:** [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased)
+### Model Sources
+- **Repository:** [https://huggingface.co/hossam87/bert-base-arabic-hate-speech](https://huggingface.co/hossam87/bert-base-arabic-hate-speech)
+- **Demo:** [https://huggingface.co/spaces/hossam87/arabic-hate-speech-detector](https://huggingface.co/spaces/hossam87/arabic-hate-speech-detector)
 ## Training Details
 ### Training Data
+The model was fine-tuned on a labeled dataset of Arabic social media posts, manually annotated for the five target categories.
 ### Training Procedure
+- **Precision:** Mixed precision (`fp16`)
+- **Epochs:** 4 (best model at epoch 3)
+- **Batch size:** 32
+- **Learning rate:** 3e-5
+- **Optimizer:** AdamW
+- **Hardware:** 2 x NVIDIA T4 GPUs (Kaggle)
+---
 ## Evaluation
+### Metrics
+| Metric   | Score  |
+|----------|:------:|
+| Accuracy | 0.944  |
+| F1 Macro | 0.946  |
+## Uses
+### Direct Use
+- Content moderation for Arabic social media, forums, and chats.
+- Analytics and research into hate speech patterns in Arabic.
+- Educational and academic projects.
+### Out-of-Scope Use
+- Automated moderation without human oversight in sensitive or legal contexts.
+- Use on languages other than Arabic.
+- General text classification tasks outside hate speech detection.
+## Bias, Risks, and Limitations
+The model may misclassify:
+- Sarcasm, slang, or context-dependent expressions.
+- Formal written Arabic, since trained on social media content.
+- Domain-specific or emerging hate speech not represented in the training data.
+### Recommendations
+Always keep a human-in-the-loop for sensitive moderation tasks. Use responsibly and be transparent about automation.
+## How to Get Started with the Model
+```python
+from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
+model_id = "hossam87/bert-base-arabic-hate-speech"
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForSequenceClassification.from_pretrained(model_id)
+classifier = pipeline("text-classification", model=model, tokenizer=tokenizer)
+text = "هذا نص عربي للاختبار"
+result = classifier(text)
+print(result)
+@misc{hossam87_2025_arabichate,
+  title = {BERT-base Arabic Hate Speech Detector},
+  author = {Hossam87},
+  year = {2025},
+  howpublished = {\url{https://huggingface.co/hossam87/bert-base-arabic-hate-speech}},
+}