Why is accuracy absent in training progress plot?
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I do not see training accuracy as illustrated in the docs. My code for training initialization is below and resultant plot attached.
% 6. specify training options
options = trainingOptions('sgdm', ...
BatchNormalizationStatistics = 'moving', ...
ExecutionEnvironment = 'auto', ...
GradientThreshold = 35, ...
InitialLearnRate = 0.0005, ...
LearnRateSchedule = 'piecewise', ...
LearnRateDropFactor = 0.99, ...
LearnRateDropPeriod = 1, ...
MaxEpochs = 20, ...
MiniBatchSize = 4, ...
Momentum = 0.9, ...
OutputNetwork = 'best-validation-loss', ...
Plots = 'training-progress', ...
ResetInputNormalization = false, ...
ValidationData = validationDS, ...
ValidationFrequency = 25, ...
VerboseFrequency = 5);
[trainedModel, info] = trainSOLOV2(trainingDS, preTrainedModel, options, ...
FreezeSubNetwork = "backbone", ExperimentMonitor = experiments.Monitor);
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/1493647/image.png)
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回答 (1 件)
Matt J
2023 年 9 月 26 日
Probably because the examples in the docs are for trainNetwork, not trainSOLOV2.
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