Insufficient training samples reduce fine-tuning effectiveness

When training dataset size is inadequate for task complexity, the fine-tuned model fails to capture nuanced semantic relationships. Simple tasks may need only a few hundred samples, while complex domains with specialized terminology require 10,000+ samples.

Start with 1,000-5,000 high-quality samples for narrow domains with good vocabulary overlap. Evaluate performance on validation set. If results plateau, incrementally add more data. Plan for 10,000+ samples for complex domains with specialized terminology.