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I have slightly modified your algorithm and have adapted it for two classes (k = 12, reduction = 0.5, bottleneck = True). When I train it on Cat and Dog images from CIFAR-10, I only go as high as 82% validation accuracy. Is that what you get as well? Or you get something closer to accuracy for all 10 classes, i.e. > %95?
The text was updated successfully, but these errors were encountered:
I have slightly modified your algorithm and have adapted it for two classes (k = 12, reduction = 0.5, bottleneck = True). When I train it on Cat and Dog images from CIFAR-10, I only go as high as 82% validation accuracy. Is that what you get as well? Or you get something closer to accuracy for all 10 classes, i.e. > %95?
The text was updated successfully, but these errors were encountered: