After converting audio data set from 16 bit to 8 bit I cannot start Deep Learning Model training, every time training stopped stating: training loss is NaN.

Hello Matlab team,

I am using this example to work with my audio data set https://www.mathworks.com/matlabcentral/fileexchange/74611-fault-detection-using-deep-learning-classification#examples_tab.

I am trying to train my network, with lowering BitsPerSample to 8 before it was 16 BitsPerSample. Every time i try to start training model it throw warning (given below) and terminates.

I try it with different sample rate but it gives same error everytime. I tried to change my layer structure, changing InitialLearnRate',0.001 but still i am getting same warning.

Warning: Training stopped at iteration 1 because training loss is NaN. Predictions using the output network might contain NaN values.

Model:

layers = [ ...

sequenceInputLayer(size(trainingFeatures{1},1))

lstmLayer(100,"OutputMode","sequence")

dropoutLayer(0.1)

lstmLayer(100,"OutputMode","last")

fullyConnectedLayer(5)

softmaxLayer

classificationLayer];

miniBatchSize = 30;

validationFrequency = floor(numel(trainingFeatures)/miniBatchSize);

options = trainingOptions("adam", ...

"MaxEpochs",100, ...

"MiniBatchSize",miniBatchSize, ...

"Plots","training-progress", ...

"Verbose",false, ...

"Shuffle","every-epoch", ...

"LearnRateSchedule","piecewise", ...

"LearnRateDropFactor",0.1, ...

"LearnRateDropPeriod",20,...

'InitialLearnRate',0.001,...

'ValidationData',{validationFeatures,adsValidation.Labels}, ...

'ValidationFrequency',validationFrequency);

Regards,

Arslan

[Jeffrey Clark]

@Arslan Munim, did you check that your conversion from 16 to 8 bits didn't result in erroneous audio data?

Also leave message with the author of what you downloaded from the file exchange; see @David Willingham

[Arslan Munim]

Hello @Jeffrey Clark,

Thanks for you reply, Yes I have visualized data set using audio data set and also go through the audio set values its look quite ok to me, I also try converting data from multiple different ways but still i cannot start training always saying Training stopped with:

Warning: Training stopped at iteration 1 because training loss is NaN. Predictions using the output network might contain NaN values.

I didn't really get the second part of your reply, but as far as data set is concerned it is my personal data set.