Effacer les filtres
Effacer les filtres

Validation Loss = Nan

14 vues (au cours des 30 derniers jours)
aryan ramesh
aryan ramesh le 6 Fév 2022
Commenté : aryan ramesh le 8 Fév 2022
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);
  1 commentaire
KSSV
KSSV le 7 Fév 2022
Increase the learning rate and see.

Connectez-vous pour commenter.

Réponse acceptée

yanqi liu
yanqi liu le 8 Fév 2022
yes,sir,may be add dropoutLayer、batchNormalizationLayer to the model
  1 commentaire
aryan ramesh
aryan ramesh le 8 Fév 2022
I added the dropoutLayer. Tks

Connectez-vous pour commenter.

Plus de réponses (0)

Catégories

En savoir plus sur Deep Learning Toolbox dans Help Center et File Exchange

Produits


Version

R2021a

Community Treasure Hunt

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

Start Hunting!

Translated by