> you can increase training by a factor of 10 or 100 and there's barely any change. How do you know accuracy didn't increase by a factor of 100 from 0.001% to

> you can increase training by a factor of 10 or 100 and there's barely any change. How do you know accuracy didn't increase by a factor of 100 from 0.001% to 0.1%? Another factor of 100 for both and you're at 10% with "only" 10⁴ as many training FLOPS! If you want to use a nonlinear transformation to show very small and very large inputs in the same graph, surely a similar effort should be made to make changes in accuracy near the limits of 0% and 100% more visible.