Prepare Data – Load and preprocess historical cash flow data into a structured format. Tokenization – Convert the financial data into a format the model can process. Fine-Tuning – Train the model using supervised fine-tuning. Evaluation – Validate the model’s performance on unseen financial data. Prediction – Use the fine-tuned model to forecast the next quarter’s cash flow.
"Your dataset should include:"
---Date (Transaction date) ---Category (Revenue, Expense, or Investment) ---Amount (Positive for income, negative for expenses) ---Description (Optional but helpful)
Date Category Amount ($) Description 2024-12-01 Revenue 500 Online sales 2024-12-02 Expense -200 Inventory purchase 2024-12-03 Expense -50 Marketing ads 2024-12-04 Revenue 300 In-store sales
" Summarize revenue, expenses, and net cash flow" " Identify spending patterns and key income sources" "Forecast next month's cash flow using trend analysis"
"STEPS Upload Your Transaction Data (CSV or Excel format). Preprocess & Aggregate the Data into monthly summaries. Tokenize the Data to convert it into a format readable by LLaMA 3. Fine-Tune or Use a Pre-trained Model for time-series forecasting. Generate Predictions for the next two months."