🏦 AI Hedge Fund Model - Qwen/Qwen2.5-3B-Instruct

Model Description

This is a specialized hedge fund AI model fine-tuned for comprehensive financial analysis and investment decision-making.

Key Features

Memory Optimized: Efficient training for GPU constraints
BCP Score Optimized: Enhanced performance on benchmarks
Hedge Fund Specialized: Tailored for financial analysis

Specializations

Valuation Analysis: DCF modeling, comparable company analysis
Fundamental Analysis: Financial statement analysis, industry research
Sentiment Analysis: Market sentiment and behavioral finance insights
Risk Management: VaR/CVaR modeling, stress testing
Portfolio Optimization: Mean-variance optimization, asset allocation
Stakeholder Communication: Professional reporting and presentations

Technical Details

Base Model: qwen1.5
Task ID: 36
Context Length: 4096
Training Type: LoRA Fine-tuning
GPU Type: NVIDIA A40
Optimization: Memory Efficient + BCP Score Enhanced

Usage

Optimized for hedge fund operations including investment analysis, risk assessment, and portfolio management tasks.

Training Configuration

{
  "per_device_train_batch_size": 1,
  "gradient_accumulation_steps": 2,
  "num_train_epochs": 1,
  "lora_rank": 2,
  "lora_alpha": 4,
  "lora_dropout": 0.1,
  "learning_rate": 5e-07,
  "warmup_ratio": 0.2,
  "eval_steps": 5,
  "save_steps": 5,
  "early_stopping_patience": 2,
  "max_grad_norm": 0.1,
  "weight_decay": 0.03,
  "lr_scheduler_type": "cosine_with_restarts",
  "adam_beta1": 0.9,
  "adam_beta2": 0.95
}

Performance Notes

Optimized for NVIDIA A40 GPU architecture
Memory-efficient training with gradient checkpointing
BCP score optimized with quality-filtered data