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validation accuracy for cnn showing different than in the plot

조회 수: 14 (최근 30일)
new_user
new_user 2021년 12월 20일
댓글: Srivardhan Gadila 2021년 12월 30일
in the plot it shows validation accuracy curve reached above 75% but the written validation accuraccy is just 66%! Is something wrong??

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Srivardhan Gadila
Srivardhan Gadila 2021년 12월 29일
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.
  댓글 수: 4
new_user
new_user 2021년 12월 30일
'OutputNetwork', 'best-validation-loss'
When I am adding these two functions then I am getting error messag, GPU out of memory.
But when I am not using these two functions then I can run smoothly.
Srivardhan Gadila
Srivardhan Gadila 2021년 12월 30일
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.

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