Closed zeek-han closed 4 years ago
There is no 'validation loss' as such, since the train function is not run on the validation set. To implement this function, you will need to:
train_network
function to run with self.eval()
mode.Oh, I think I express improper way thus you misunderstood my purpose... The sample code you give just train on training set, and for every 10 epoch, calculate EER on test set and print it. how could I print LOSS on TEST SET as well as equal error rate for every 10 epoch?
thank you...
I think my answer still remains the same. You will need to run the train function without the weight update every 10 epochs. Currently the script does not compute the validation loss.
Oh, thank you for your answer! I understand it!
When i train with default setting, VEER is calculated for every 10 iteration, and I regard VEER as Validation Equal Error Rate. thus, VEER is derived from test accuracy and it is very important measure. But I need not only VEER but Validation Loss also to pick the best model. How could I print Validation loss?
Thank you...