Methodology
===========

Research Design
---------------

Our research follows a systematic approach to fine-tuning language models using LoRA, with a
specific focus on capturing Warren Buffett's investment philosophy and analysis style.


Data Collection
---------------

1. **Source Materials**:
   - Annual letters to Berkshire Hathaway shareholders
   - Transcripts of interviews and speeches
   - Books and articles about Buffett's investment philosophy
   - Public statements and market commentary

2. **Data Processing**:
   - Text cleaning and normalization
   - Content categorization
   - Quality filtering
   - Format standardization


LoRA Implementation
-------------------

1. **Base Model Selection**:
   - Criteria for choosing the foundation model
   - Model architecture considerations
   - Size and computational requirements

2. **LoRA Configuration**:
   - Rank selection
   - Alpha parameter tuning
   - Target modules selection
   - Learning rate optimization


Training Process
----------------

1. **Hyperparameter Selection**:
   - Learning rate scheduling
   - Batch size optimization
   - Training duration
   - Validation approach

2. **Training Infrastructure**:
   - Google Colab (A100 GPU)
   - Python, PyTorch, Hugging Face


Evaluation Framework
--------------------

1. **Quantitative Metrics**:

2. **Qualitative Assessment**: