BTCUSDT 1-Hour Fine-tuned Model
Model Description
This is a fine-tuned language model adapted for Bitcoin (BTCUSDT) price and volume forecasting on 1-hour candlestick data. The model has been specialized to predict short-term price movements and trading volume patterns.
Base Model
- Base Model: Kronos (or specify your actual base model)
- Fine-tuning Task: Time Series Forecasting for Cryptocurrency
- Application: BTC/USDT hourly price prediction
Model Details
- Model Type: Fine-tuned Transformer-based Time Series Model
- Input: Historical BTCUSDT 1-hour candlestick data (open, high, low, close, volume)
- Output: Predicted price and volume for the next period(s)
- Fine-tuning Data: Historical BTCUSDT 1-hour trading data
- Framework: PyTorch / Hugging Face Transformers
Intended Use
This model is designed for:
- Short-term Bitcoin price forecasting (1-hour predictions)
- Trading volume estimation
- Technical analysis automation
- Research and backtesting
Intended Users
- Cryptocurrency traders and analysts
- Quantitative research teams
- Academic researchers studying time series forecasting
- Trading strategy developers
How to Use
Installation
pip install transformers torch
Loading the Model
from transformers import AutoTokenizer, AutoModelForCausalLM
model_name = "your-huggingface-username/BTCUSDT-1h-finetuned"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)
Prediction Example
# 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
Model Performance
- Training Data: BTCUSDT 1-hour historical candles
- Evaluation Metric: Model-specific forecasting accuracy
- Use Case Specific: Optimized for cryptocurrency time series
Limitations
- Trained specifically on BTCUSDT 1-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
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
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.
Citation
If you use this model, please cite:
@misc{btcusdt_finetuned_2025,
title={BTCUSDT 1-Hour Fine-tuned Model},
author={Your Name},
year={2025},
publisher={Hugging Face},
howpublished={\url{https://huggingface.co/your-username/BTCUSDT-1h-finetuned}}
}
Acknowledgments
- Base model: Kronos
- Built with: Hugging Face Transformers
Contact & Support
For questions or issues:
- GitHub: [your-repository-link]
Last Updated: October 20, 2025
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Dataset used to train lc2004/kronos_base_model_BTCUSDT_1h_finetune
Evaluation results
- Prediction Accuracy on BTCUSDT 1-hourself-reportedmodel-specific
