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README.md

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+# Fine-tuned XLM-R Model for hebrew Sentiment Analysis
+
+This is a fine-tuned XLM-R model for sentiment analysis in hebrew.
+
+## Model Details
+
+- **Model Name**: XLM-R Sentiment Analysis
+- **Language**: hebrew
+- **Fine-tuning Dataset**: DGurgurov/hebrew_sa
+
+## Training Details
+
+- **Epochs**: 20
+- **Batch Size**: 32 (train), 64 (eval)
+- **Optimizer**: AdamW
+- **Learning Rate**: 5e-5
+
+## Performance Metrics
+
+- **Accuracy**: 0.92106
+- **Macro F1**: 0.90782
+- **Micro F1**: 0.92106
+
+## Usage
+
+To use this model, you can load it with the Hugging Face Transformers library:
+```python
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+
+tokenizer = AutoTokenizer.from_pretrained("DGurgurov/xlm-r_hebrew_sentiment")
+model = AutoModelForSequenceClassification.from_pretrained("DGurgurov/xlm-r_hebrew_sentiment")
+```
+
+## License
+[MIT]