I am getting a Assertion `cur_target >= 0 && cur_target < n_classes’ failed error while running learn.fit(lr, 1, cycle_len=1) with a ‘Resnet34’ architecture.
After doing some search it seems number of labels in my training dataset(4251 in my case for Humpback Whale Identification Challenge) is larger than number of output classes in Resnet(which is 1000 I believe) .
Could anyone please suggest how this problem can be approached with fastai library with a pre-trained model.
Any help. Most of the online forums tells its a pytorch error and do suggest a explanation and solution, but how we implement the same in fastai? like for example check this linkcheck this link
Hi,
no I didn’t made any progress on this topic. I used a dicom viewer, and extracted set bone values to 1 and background to 0 with a Hounsfield threshold.
I am thankful for tips, when are progressing in solving!