I was experimenting with a kaggle dataset (whale-categorization-playground).
The dataset has a large number of classes (4251) representing whale tail-fin images.
An exercise using fastai V1.0.21 and resnet101 image size 128 got me a model that trained well and reached an accuracy of apprx 0.58 after 40 epochs.
When I increased the image size to 288 (and reduced the batch size for the health of my 4 GB gpu). loaded the model from previous run and trained for 40 epochs overnight. The model refused to learn and accuracy languished at 0.038 ???
Total time: 5:10:14
Any ideas why this could be so ??