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crypto_model

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crypto
price-prediction
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crypto_model
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---

license: mit
tags:
  - crypto
  - price-prediction
  - lstm
  - trading
library_name: pytorch
---


# Crypto Price Predictor V8

A high-performance LSTM-based cryptocurrency price prediction model with bias correction.

## Model Details

### Architecture
- **Type**: Bidirectional LSTM
- **Layers**: 2 stacked LSTM layers
- **Hidden Size**: 64 (auto-detected per model)
- **Input Features**: 44 technical indicators
- **Output**: Next hour price prediction

### Supported Cryptocurrencies
BTC, ETH, SOL, BNB, XRP, ADA, DOT, LINK, MATIC, AVAX, FTM, NEAR, ATOM, ARB, OP, LTC, DOGE, UNI, SHIB, PEPE

### Performance
- **Average MAPE**: < 0.05%
- **Average MAE**: < 50 USD (varies by price)
- **Direction Accuracy**: ~65-75%

## Usage

### Quick Start

```python

from bot_predictor import BotPredictor



# Initialize

bot = BotPredictor()



# Get prediction

prediction = bot.predict('BTC')

print(f"Next Hour Price: ${prediction['corrected_price']:.2f}")

print(f"Direction: {prediction['direction']}")

print(f"Confidence: {prediction['confidence']*100:.1f}%")

```

### Installation

```bash

pip install torch torchvision torchaudio

pip install scikit-learn pandas numpy ccxt

```

### Models

All models are in PyTorch format (.pth files). Download all models to use the full suite.

### Bias Correction

Each model includes an automatic bias correction value to account for training/test distribution differences.

File: `bias_corrections_v8.json`

## Technical Indicators (44 total)

- RSI (14, 21)
- MACD + Signal + Histogram
- Bollinger Bands (20, 2)
- ATR (14)
- CCI (20)
- Momentum (10)
- SMA (5, 10, 20, 50)
- EMA (12, 26)
- Volume Ratio
- OHLC-derived features

## Training Details

- **Data**: 1000 hourly candles per symbol
- **Train/Val/Test Split**: 80/10/10
- **Optimizer**: Adam (LR=0.005)
- **Loss**: MSE
- **Batch Size**: 64
- **Epochs**: 150 (with early stopping)
- **Dropout**: 0.3

## Requirements

```

torch>=2.0.0

torchvision

pandas>=1.5.0

numpy>=1.23.0

scikit-learn>=1.2.0

ccxt>=2.0.0

huggingface_hub>=0.16.0

python-dotenv>=1.0.0

```

## License

MIT License

## Citation

```

@software{crypto_predictor_v8,

  title={Crypto Price Predictor V8},

  author={Your Name},

  year={2025},

  url={https://huggingface.co/caizongxun/crypto-price-predictor-v8}

}

```

## Disclaimer

These models are for educational and research purposes only. Do not use for actual trading without thorough validation.

## Support

For issues and questions, please refer to the GitHub repository.