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problem: Higher number of epochs lead to worse results? #1879
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I am not from the Autokeras team, but when training ML models, the optimal number of epochs is a difficult problem and there is no final answer. Usually models improve until a local minima and then they can't go further. |
When I fit model with 200 epochs, results are pretty good, 54% instead 50% for random selection. But when I raise epochs to 500, I get much worse success ratio, under 50%. Why is that and what is optimal number of epochs?
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