Cats-VS-Dogs

This is my first nice machine learning model, This model gave a 97.85% accuracy in classifying between Cats and Dogs. I made it using a pre-trained base model MobileNet V2 , and after that i added a global average pooling and then a dense layer for categorization between two classes ( cats and dogs) , i used only one dense neuron in last layer even when i had to classify 2 classes because , as we know that in test data there will only be two type of images cats and dogs , so we can just classify dogs and then ones that doesn't qualify the classification are cats. It has been trained on a small dataset to show how a machine learning model can work well even on a small dataset if we use pre-trained models inn architecture.