README.md

---
library_name: transformers
tags:
  - trading
  - finance
  - deepseek
  - fine-tuning
---

# 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](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-32B)

## Uses

### Direct Use

This model is designed to:

1. Analyze market conditions using technical indicators
2. Generate trading strategies based on market analysis
3. Implement risk management rules
4. 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.