That would depend on the training and is should be unrelated to torch.save.
I would recommend to check the training itself and see why your model forgets the previous cases.
Generally I would expect a pre-trained model (e.g. a ResNet trained on ImageNet) to forget the 1000 classes after I sufficiently trained it on my new use case (e.g. a 5 class guitar classifier).
Based on your use case I assume your model has 10 output neurons, while you are ignoring a subset in both steps?