Comments (4)
These are the results of logs.
from mae.
Yes, the model is overfitting since cifar10 is a small dataset and we did not perform any data augmentation.
If you wonder why the accuracy is still increasing too, that is because the model is trading accuracy with the cost of perplexity. That is it gets less certain about the right classification, e.g. decrease the probability from 0.9 to 0.6, but get more things right.
from mae.
I see. And where should I extend the dataset by using data augmentations? In the pretrain program or fine-tuning program?
p.s. I'm sorry to ask such questions as this was the first CV program I run.
from mae.
You can add data augmentations when defining the dataset, i.e. changing the transform from here. Something like RandomResizedCrop
should be very helpful. But unfortunately, I do not have the computation resource to verify.
from mae.
Related Issues (20)
- What are the rules for setting the parameters of vit-tiny's decoder? HOT 1
- Fine-tuning and linear evaluation HOT 4
- What are the versions you worked with, keep getting errors HOT 2
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- 最后你得重建图像是怎么来的? HOT 2
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- Ask some questions HOT 8
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- Why do the masks' positions on the visualized images are same? HOT 4
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from mae.