When debugging a neural network model, do we expect to get 0 loss on a single batch? For example, running 1000 times optimization on the same single batch input.
If the loss is close to 0, we can conclude the model is able to overfit on that batch.
if the loss is far from 0, e.g. say start at 5.5  and end at 4.7, what does it tell us?
For example:

it needs more training time on a single batch
model is not able to overfit a single batch, its design is not working
model has way too many parameters for a single batch data to tune
any other possible explanations are welcomed~

Thanks!!!