Every experiment runs under the same -minute clock. This is set by TIME_BUDGET = 300 in prepare.py.
Why does this matter? Without a fixed budget, a training run with layers would take far longer than one with layers. You couldn't tell if a higher score came from a better architecture or just from training longer. The time cap removes that variable. Every experiment gets seconds, so improvements reflect genuine gains in how well the model learns within that window.