Validation Loss = Nan
14 次查看(过去 30 天)
显示 更早的评论
Hello, I'm attempting to utilize lstm to categorize data but the validation loss Is Nan.
I reduced the learning rates to 1e-12 but I am still receiving Nan results.
Appreciate any guidance.
Best Regards,
options = trainingOptions("sgdm", ...
"MaxEpochs",400, ...
"InitialLearnRate",0.000000000001, ...
"Shuffle", 'never', ...
"Plots","training-progress",...
"ValidationData",{XValidation,YValidation},...
'ValidationFrequency',1);
%%
layers = [ ...
sequenceInputLayer(1)
bilstmLayer(100,"OutputMode","last")
fullyConnectedLayer(2)
softmaxLayer
classificationLayer];
% displaySequence(tones_cell{1}, label1{1})
net = trainNetwork(XTrain,labelTrain, layers, options )
YPred = classify(net,XTest);
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/886250/image.png)
采纳的回答
更多回答(0 个)
另请参阅
类别
在 Help Center 和 File Exchange 中查找有关 Deep Learning Toolbox 的更多信息
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!