Intermediate45 min
Fine-Tuning Basics
Introduction to fine-tuning open source models for your specific use case
Last updated: 2025-01-14
Prerequisites
- Python programming
- Understanding of ML basics
- GPU access
1. Prepare Your Dataset
Format your training data in the correct structure. Use JSON or CSV format with input-output pairs.
2. Configure Training Parameters
Set up learning rate, batch size, and other hyperparameters. Start with learning rate of 2e-5.
3. Start Training
Begin the fine-tuning process and monitor progress using TensorBoard or Weights & Biases.