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Expected values of ins_prob and ins_loss in MoCo when training is working #38

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nlml opened this issue Feb 3, 2020 · 1 comment
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@nlml
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nlml commented Feb 3, 2020

Hi there

Thanks a lot for this great repo!

I am trying out MoCo on my own dataset (I also added additional augmentations). Training appears to have converged, but the max value I get for ins_prob is about 13.35, and the lowest value I get for loss is about 0.2422.

I am wondering what metrics you got when training on Imagenet? Am not sure what a "good" score should look like.

Here are screenshots from training progress in tensorboard (ignore the multiple lines at the start of training).

image

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Thanks,
Liam

@ajtejankar
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I think a simple solution would be to use the pre-trained MoCo model and get the loss for Imagenet. That will give you the final loss achieved by the model.

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