average performace metric for all validation dataset
Assume the model is train using dataset A and validated against dataset B and dataset C.
I read somewhere either in the documentation or issue being raise in Github (Both of which I am unable to trace back now š š) that the build-in script outputs performance metric of the dataset B and C seperately.
But instead, I would like have the average performance metric for overall validation dataset alongwith for sepeate dataset. May I know which .py function that I can modify to achieve the desire requirement? or is their anything I have to do in the abinet config.
average performace metric for all validation dataset
Assume the model is train using dataset A and validated against dataset B and dataset C.
I read somewhere either in the documentation or issue being raise in Github (Both of which I am unable to trace back now š š) that the build-in script outputs performance metric of the dataset B and C seperately.
But instead, I would like have the average performance metric for overall validation dataset alongwith for sepeate dataset. May I know which
.py
function that I can modify to achieve the desire requirement? or is their anything I have to do in the abinet config.currently my config looks like this below for
Current: After each epoch:
Wish to have: After all the epochs or maybe each epoch: