Issue with Custom object detection using tensorflow when Training on a single type of object
How many images are you using to train?  You might need more... let's say  at least 1000 for a single category - depending on how big your MobileNet is (there are different variants).

Are you using a pretrained MobileNet, or are you training it from scratch. If Mac'n Cheese was not a category in the original data used for a pre-trained model, then you might need to train from scratch, or only keep the first few layers of the model frozen, as they learn very general features from images that will liekly be useful for your target class (and many other). If you are unsure, search for transfer learning, to see what is possible.

The nominal value of the loss is quite hard to interpret, so values of 0.3 or 1.0 don't mean a lot without context. You can use them for comparison - so if you change something and loss values then start dropping to 0.005, you know that you are likely onto a good idea.

You can check out this tutorial notebook on MobileNet, which might give you more ideas about how to play with the network