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Imagine that your valuation set has just six examples with an accuracy of 66%. Now you tweak your model and your performance goes from 66% to 83%, is this something you can trust? No of course, this is only a change of label for a single example. It could just be noise. The bigger you test set, the less noisy the accuracy measurement will be. Here is a useful rule of thumb. And if youre a statistician, feel free to cover your ears right now. A change that affects 30 examples in your validation set, one way or another, is usually statistically docHub, and typically can be trusted.