Training Deep Networks
Learning Rate & Schedules
9 min+85 XPStep 1/11
One dial to rule training
Gradient descent needs a step size — the learning rate — and it's the single most consequential choice in training.
Too high: you leap over the minimum each step and the loss diverges or rattles forever. Too low: you creep downhill and run out of time or compute budget long before you arrive. There's no universally right value — it depends on the loss surface you're standing on.
analogy
Landing a plane: fast descent at altitude, careful corrections near the runway. One fixed speed all the way down ends badly either way.