Using CNN on one class only
Since you are only using one class for training, you can't expect the network to understand what the object is not.
For example, if you want to classify cats you have to pass to the network images that are not in your main class [dogs, cars, boats, random_noise, penguins]. If you try to pass any other image to your current model it will answer with great confidence that it is a cat.
Your validation accuracy will always be 100% if you have no other classes in your dataset.
For a classification problem you need at least two classes, and your train/val/test subsets should have enough images of each class so your metrics become meaningful.