In reference to the topic title, is there a way to access the parameters and weights during training?
The proposed solutions I’ve seen so far on the forum are the following:
Using the .parameters() method on the model seems to return the parameters set during the initialization of the model, e.g.,
for p in model.parameters():
In addition, checking the individual layer of the model using model.Layer.weight.data has the same behavior.
Both the above methods do not change as the models train.
I would like to see the weights changing as a function of epoch/minibatch.