Invalid training data. The output size (8) of the last layer does not match the number of classes (6).

clc;
close all;
clear all;
%% load network
net=alexnet;
ppl=net.Layers;
net=net.Layers(1:19);
% layers(23)=fullyConnectedLayer(7);
% layers(25)=classificationLayer;
layers=[net
    fullyConnectedLayer(8)
    softmaxLayer()
    classificationLayer()];
    
matlabpath='C:\Users\ayush\MATLAB_CAPSTONE\Dataset1';

data=fullfile(matlabpath,'trainingset');

train=imageDatastore(data,'IncludeSubfolders',true,'FileExtensions','.jpg','LabelSource','foldernames');
[imgtrain,imgtest]=splitEachLabel(train,0.8,'randomized');

count=train.countEachLabel;

%% training
opt=trainingOptions('sgdm','MaxEpochs',2,'InitialLearnRate',0.001,'Plots','training-progress','MiniBatchSize',64);

TrainNet=trainNetwork(train,layers,opt);

%% accuracy
pred=classify(TrainNet,imgtest);
accuracy=mean(pred==imgtest.Labels);


    
    

[AYUSH ANAND SAGAR]

Error using trainNetwork (line 170)

Invalid training data. The output size (8) of the last layer does not match the number of classes (6).

Error in transfer (line 27)

TrainNet=trainNetwork(train,layers,opt);

this is the error thats popping up all the time

Answer 1

[Mohammad Sami]

Your final layer has 8 outputs, however your image data store only has 6 labels / classes. If you expect there to be 8 classes, check you image data store. If there are 6 classes, then change your final layer to have 6 outputs.