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I'm training a neural network and the training loss decreases, but the validation loss doesn't, or it decreases much less than what I would expect, based on references or experiments with very similar architectures and data. How can I fix this?

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What should I do when my neural network doesn't learn?

to which this question is inspired, the question is intentionally left general so that other questions about how to reduce the generalization error of a neural network down to a level which has been proved to be attainable, can closed as a duplicate of this one. See also thread on Meta:

Is there a generic question to which we can redirect questions of the type "why does my neural network not generalize well?"

I'm training a neural network and the training loss decreases, but the validation loss doesn't, or it decreases much less than what I would expect, based on references or experiments with very similar architectures and data. How can I fix this?

As for question

What should I do when my neural network doesn't learn?

to which this question is inspired, the question is intentionally left general so that other questions about how to reduce the generalization error of a neural network down to a level which has been proved to be attainable, can be closed as duplicates of this one. 

See also dedicated thread on Meta:

Is there a generic question to which we can redirect questions of the type "why does my neural network not generalize well?"