# Fine-tuned XLM-R Model for swahili Sentiment Analysis

This is a fine-tuned XLM-R model for sentiment analysis in swahili.

## Model Details

- **Model Name**: XLM-R Sentiment Analysis
- **Language**: swahili
- **Fine-tuning Dataset**: DGurgurov/swahili_sa

## Training Details

- **Epochs**: 20
- **Batch Size**: 32 (train), 64 (eval)
- **Optimizer**: AdamW
- **Learning Rate**: 5e-5

## Performance Metrics

- **Accuracy**: 0.73684
- **Macro F1**: 0.42424
- **Micro F1**: 0.73684

## 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_swahili_sentiment")
model = AutoModelForSequenceClassification.from_pretrained("DGurgurov/xlm-r_swahili_sentiment")
```

## License
[MIT]