Linear Regression Predicting Absurdly Large Numbers?

I have a model where I input an image and two labels which are floats. There are 2 outputs, both having linear activation functions. I am using mae loss function if that matters.

When I try to predict images with this model, it gives me absurdly large numbers that like nothing the model was trained on.

Does anyone know why this happens and/or how to fix it?

Thanks!