I found an answer here: https://www.mathworks.com/matlabcentral/answers/373963-how-do-i-save-the-training-progress-images-generated-in-trainnetwork-when-plots-is-set-to-train
However, this process can cause output errors if you have very large networks (using lots of memory) because you are trying to save a rich in data plot to memory. I found a work around as plotting the last value of training. So, this isn't a nice plot, but at least it give me some metric to evaluate the RMSE value (or accuracy):
function stop=savetrainingplot(info)
stop=false; %prevents this function from ending trainNetwork prematurely
if info.State=='done' %check if all iterations have completed
% if true
%saveas(gcf,'filename.png') % save figure as .png, you can change this
file_name = ['big3_performance_' num2str(floor(now*100000)) '.mat'];
% to_save_fig = findall(groot, 'Type', 'Figure');
% to_save_fig_last = to_save_fig(end);
%saveas(figure(to_save_fig(end)), file_name)
performance = [info.Iteration info.Epoch info.ValidationRMSE];
save(file_name, 'performance', '-v7.3')
end
end
I hope that this helps someone :)
