How to plot performance graph after CNN training

6 次查看（过去 30 天）
Satyabrata Nath
Satyabrata Nath 2017-3-23
回答： Parag 2025-3-7
I am new in deep learning and unable to plot performance graph after training my CNN architecture . My code is as follows :-
opts = trainingOptions('sgdm',
'Momentum', 0.9,
'InitialLearnRate', 0.001,
'LearnRateSchedule', 'piecewise',
'LearnRateDropFactor', 0.1,
'LearnRateDropPeriod', 8,
'L2Regularization', 0.004,
'MaxEpochs', 40,
'MiniBatchSize', 128,
'Verbose', true);
cifar10Net = trainNetwork(trainingImages, trainingLabels, layers, opts);
YTest = classify(cifar10Net, testImages);
accuracy = sum(YTest == testLabels)/numel(testLabels)

请先登录，再回答此问题。

回答（1 个）

Parag
Parag 2025-3-7
Hi, the current code does not include instructions to plot the performance graph (training progress, accuracy, loss, etc.). However, MATLAB automatically displays the training progress plot by default when using the "trainingOptions" function with the "Plots" property set to "training-progress."
Modify the “trainingOptions” to include the “Plots” parameter:
Please refer to MATLAB code for the same
opts = trainingOptions('sgdm', ...
'Momentum', 0.9, ...
'InitialLearnRate', 0.001, ...
'LearnRateSchedule', 'piecewise', ...
'LearnRateDropFactor', 0.1, ...
'LearnRateDropPeriod', 8, ...
'L2Regularization', 0.004, ...
'MaxEpochs', 40, ...
'MiniBatchSize', 128, ...
'Verbose', true, ...
'Plots', 'training-progress'); % Enable performance graph
This will display a real-time training progress plot, including accuracy, loss, and learning rate changes during training.

类别

在 Help Center 和 File Exchange 中查找有关 Recognition, Object Detection, and Semantic Segmentation 的更多信息

标签

Community Treasure Hunt

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

Start Hunting!

Translated by