README.md

---
language:
- en
- zh
license: mit
tags:
- time-series
- forecasting
- bitcoin
- btc
- cryptocurrency
- fine-tuned
datasets:
- lc2004/BTCUSDT-4-hour-candles
model-index:
- name: BTCUSDT 4h Fine-tuned Model
  results:
  - task:
      name: Time Series Forecasting
      type: time-series-forecasting
    dataset:
      name: BTCUSDT 4-hour
      type: cryptocurrency-price-data
    metrics:
    - name: Prediction Accuracy
      type: accuracy
      value: model-specific
---

# BTCUSDT 4-Hour Fine-tuned Model

## Model Description

This is a fine-tuned language model adapted for **Bitcoin (BTCUSDT) price and volume forecasting** on 4-hour candlestick data. The model has been specialized to predict medium-term price movements and trading volume patterns.

### Base Model

- **Base Model**: [Kronos](https://huggingface.co/antonop/Kronos-1B-MSN) (or specify your actual base model)
- **Fine-tuning Task**: Time Series Forecasting for Cryptocurrency
- **Application**: BTC/USDT 4-hour price prediction

### Model Details

- **Model Type**: Fine-tuned Transformer-based Time Series Model
- **Input**: Historical BTCUSDT 4-hour candlestick data (open, high, low, close, volume)
- **Output**: Predicted price and volume for the next period(s)
- **Fine-tuning Data**: Historical BTCUSDT 4-hour trading data
- **Framework**: PyTorch / Hugging Face Transformers

## Intended Use

This model is designed for:
- **Medium-term Bitcoin price forecasting** (4-hour to multi-day predictions)
- **Trading volume estimation**
- **Technical analysis automation**
- **Research and backtesting**
- **Swing trading strategy development**

### Intended Users

- Cryptocurrency traders and analysts
- Quantitative research teams
- Academic researchers studying time series forecasting
- Trading strategy developers
- Swing traders and position traders

## How to Use

### Installation

```bash
pip install transformers torch
```

### Loading the Model

```python
from transformers import AutoTokenizer, AutoModelForCausalLM

model_name = "lc2004/kronos_base_model_BTCUSDT_4h_finetune"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)
```

### Prediction Example

```python
# Prepare your BTCUSDT data
# Use the prediction script from the original repository

from prediction_script import predict_btc
predictions = predict_btc(model, historical_data)
print(predictions)
```

For detailed usage, see the [original repository](https://github.com/Liucong-sdu/Kronos-Btc-finetune)

## Model Performance

- **Training Data**: BTCUSDT 4-hour historical candles
- **Evaluation Metric**: Model-specific forecasting accuracy
- **Use Case Specific**: Optimized for cryptocurrency medium-term time series
- **Prediction Horizon**: Up to 192 hours (8 days)

See example predictions in the repository.

## Limitations

- Trained specifically on **BTCUSDT 4-hour data** - may not generalize to other cryptocurrencies or timeframes
- Time series models are inherently uncertain; predictions should not be used as sole basis for trading decisions
- Market conditions and volatility can significantly impact forecast accuracy
- Historical performance does not guarantee future results
- Best suited for medium-term forecasting (3-7 days)

## Ethical Considerations

⚠️ **Risk Warning**: This model is for research and educational purposes. Do not use for actual trading without proper risk management and professional financial advice.

- Cryptocurrency markets are highly volatile
- Use appropriate position sizing and stop-loss strategies
- Consult with financial professionals before trading decisions
- Past predictions do not guarantee future accuracy

## License

This fine-tuned model is released under the **MIT License**.

The base model's original license and usage terms should be respected. For details on the base model, refer to the [Kronos repository](https://huggingface.co/antonop/Kronos-1B-MSN).

## Citation

If you use this model, please cite:

```bibtex
@misc{btcusdt_4h_finetuned_2025,
  title={BTCUSDT 4-Hour Fine-tuned Model},
  author={Liucong},
  year={2025},
  publisher={Hugging Face},
  howpublished={\url{https://huggingface.co/lc2004/kronos_base_model_BTCUSDT_4h_finetune}}
}
```

## Acknowledgments

- Base model: [Kronos](https://huggingface.co/antonop/Kronos-1B-MSN)
- Built with: [Hugging Face Transformers](https://huggingface.co/transformers/)
- Original Kronos Framework: [shiyu-coder/Kronos](https://github.com/shiyu-coder/Kronos)

## Contact & Support

For questions or issues:
- GitHub: [Kronos-Btc-finetune](https://github.com/Liucong-sdu/Kronos-Btc-finetune)
- Hugging Face: [lc2004](https://huggingface.co/lc2004)

---

**Last Updated**: October 23, 2025