I am trying to train a simple model for https://www.kaggle.com/c/alaska2-image-steganalysis and I expect around 0.8 weighted roc metric as a baseline. However, my metric goes to 0.1 already during or after the very first epoch.
I kept the bare minimum for data transforms and still don’t understand what’s happening. Other people successfully trained simple models with same augmentations and architectures.
The bare minimum is:
- vertical\horizontal flips
- no resize
- resnet34 / resnet50 / effnet_b0
- train/valid split is fixed. Now that I noticed classes contain the same picture, so I removed shuffling, but it didn’t change anything.