How to Find Your “Just Right” Strategy for Quality, Alignment, and Model Performance.
When it comes to data annotation, more isn’t always better—and less can quietly stall your model.
Too much annotation creates noise.
Too little annotation weakens model performance.
Somewhere in between is the Goldilocks Zone—the sweet spot where your data delivers clarity, confidence, and consistent results. This guide shows you how to find that balance and build an annotation strategy that’s just right for your model’s needs.
Sama provides ML Professionals and AI team Leads with an indispensable solution for Computer Vision data labeling.
