Hi there! I’ve just watched lesson 1 so that’s my level of background.
I’m trying to train a classifier using the Oxford 102 Flowers dataset, doing pretty much what’s shown in the lecture, but the error rate is too high
This is how I created the databunch:
And these were the results:
I’ve also tried resnet50 and it was the same (0.127)
I don’t think the error rate is too high. You are almost getting 90 percent accuracy with ResNet34 which is really good. If you take a look at this link you will see that you are close to the top 10 by using just fastai’s defaults for hyper-parameters. (and after just a few epochs!)
I suggest using Progressive Resizing (a technique you will learn in lesson 3 I think) which could help the accuracy. The other thing you might want to consider is other sets of hyper parameters (the most important being
hey, thanks! good to know. I’ll keep calm then haha. Good information