validation accuracy for cnn showing different than in the plot

9 views (last 30 days)
in the plot it shows validation accuracy curve reached above 75% but the written validation accuraccy is just 66%! Is something wrong??

Accepted Answer

Srivardhan Gadila
Srivardhan Gadila on 29 Dec 2021
When training finishes, the Results shows the finalized validation accuracy and the reason that training is finished. If the 'OutputNetwork' training option is set to 'last-iteration' (which is default), the finalized metrics correspond to the last training iteration. If the 'OutputNetwork' training option is set to 'best-validation-loss', the finalized metrics correspond to the iteration with the lowest validation loss. The iteration from which the final validation metrics are calculated is labeled Final in the plots. And from the plot, it is clear that the validation accuracy dropped after training on the final iteration of the data
Refer to the following pages for more information: Monitor Deep Learning Training Progress, trainingOptions & trainNetwork.
  4 Comments
Srivardhan Gadila
Srivardhan Gadila on 30 Dec 2021
In that case, either you can reduce the value of "MiniBatchSize" and try it or train the network on cpu by setting the "ExecutionEnvironment" to "cpu". Both of these are input arguments of trainingOptions.

Sign in to comment.

More Answers (0)

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!