Anyone else having an issue where the after the model is finetuned to make predictions on the dogs vs cats redux data, the predictions are binary? When I generate predictions on dogs/cats data with the vgg model before fine tuning, I get fractional probabilities for each of the 1000 imagenet categories (eg. .23 likelihood of Egyptian cat). However, after finetuning, I never get any predictions with fractional probabilities between 0 and 1, they're always exactly 0 or exactly 1. The reason I ask is because the scoring function on kaggle is more forgiving of incorrect predictions closer to .5, eg for a given example, .55 likelihood of dog, .45 of cat, rather than 1 of dog, 0 of cat.