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How to decide the training epochs or early stop condition? #31

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idealwhite opened this issue Mar 11, 2021 · 4 comments
Open

How to decide the training epochs or early stop condition? #31

idealwhite opened this issue Mar 11, 2021 · 4 comments

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@idealwhite
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I really like your paper, thanks for your open source!
It seems that you did not use early stop in the ModelCheckpoint. Could you please tell me how many epochs you trained the VQGAN and transformer? Or do you have suggestions about the training epochs on new datasets?

@idealwhite idealwhite changed the title Thanks for your open source! About training epochs and early stop How to decide the training epochs and early stop condition? Mar 11, 2021
@idealwhite idealwhite changed the title How to decide the training epochs and early stop condition? How to decide the training epochs or early stop condition? Mar 11, 2021
@rromb
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rromb commented Mar 29, 2021

Thanks!
The VQGAN benefits greatly from training it as long as possible (provided the data set is large enough and overfitting is a secondary concern), and tuning in the discriminator rather late. When training on ImageNet, for example, I would recommend 3-5epochs without the adversarial loss (but more is better) and then training for at least another 3-5 epochs with the discriminator turned on (again, more=better).

The stopping condition for the transformer is usually when it starts overfitting in terms of NLL on held-out test data.

@sunshineatnoon
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sunshineatnoon commented Jun 7, 2021

May I ask how long it usually takes to train on the ImageNet and how many GPUs are used?

@gombru
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gombru commented Oct 20, 2022

Any updates on training times? Costs?

@cucdengjunli
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5 participants