I am trying to overfit my model on 2 samples. I run the training until training loss is 0 and then I run validation on the same 2 samples. But the validation loss is higher, as can be seen here:
Why is the validation loss not 0 as well and why is it going in the opposite direction ?
Is the output used for validation loss calculation the same as the one for training loss?
I ask this because I wonder whether the model’s behavior is up to the value of model.training.
model.training
Yes it’s exactly the same, and yes I do call model.eval() for validation.
It sounds weird. Could you share a minimal reproducible code?