Dataset Preparation for Fine-Tuning

Summary

Cleaning, formatting and structuring examples for fine-tuning — dataset quality matters more than dataset size, and this step is where most fine-tuning projects succeed or fail.

• 1Build a small fine-tuning dataset from scratch for a specific task you care about.
• 2Learn to deduplicate, filter low-quality examples, and balance the dataset.
• 3Split into train/validation sets and keep a held-out test set for final evaluation.