DeepSeek Trading Assistant
This is a fine-tuned version of DeepSeek-R1-Distill-Qwen-32B
specialized for generating trading strategies and market analysis.
Model Details
Model Description
- Developed by: latchkeyChild
- Model type: Decoder-only language model
- Language(s): English
- License: MIT
- Finetuned from model: deepseek-ai/DeepSeek-R1-Distill-Qwen-32B
Uses
Direct Use
This model is designed to:
- Analyze market conditions using technical indicators
- Generate trading strategies based on market analysis
- Implement risk management rules
- Create Python code for strategy implementation
Training Data
The model is trained on a custom dataset containing:
- Market analysis using technical indicators (RSI, MACD, Moving Averages)
- Trading strategy implementations
- Risk management rules
- Python code examples using QuantConnect framework
Training Procedure
Training Hyperparameters
- Number of epochs: 3
- Batch size: 2
- Learning rate: 1e-5
- Gradient accumulation steps: 8
- Warmup steps: 100
- Training regime: fp16 mixed precision with gradient checkpointing
- Temperature: 0.6 (recommended for DeepSeek-R1 series)
Technical Specifications
Compute Infrastructure
- Required Hardware: 2x NVIDIA A10G GPUs or 1x A100 GPU
- Training Time (estimated): 2-4 hours
Model Card Contact
For questions or issues, please open an issue in the repository.
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