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Hi there! Thank you for your work! I have tried to reproduce the reported results (~93% top-1) on CIFAR10 with ResNet18 using MoCoV3, however running the provided script with default parameter only gives about 90% top-1 in the online classifier.
Do you know what I am missing?
Are the reported results with an offline trained linear-probe classifier? What are the hyperparameters needed in that case?
The text was updated successfully, but these errors were encountered:
Hey. I'm pretty sure the results that we have for cifar are just the online eval. The parameters should be the same as in the script (I can check later to confirm) but it can be an issue with library versions. These results are pretty old, so maybe a new pytorch/lightning version changed some stuff.
Hi there! Thank you for your work! I have tried to reproduce the reported results (~93% top-1) on CIFAR10 with ResNet18 using MoCoV3, however running the provided script with default parameter only gives about 90% top-1 in the online classifier.
Do you know what I am missing?
Are the reported results with an offline trained linear-probe classifier? What are the hyperparameters needed in that case?
The text was updated successfully, but these errors were encountered: