How to make loose function for validation and training togther for autoencoder

Hi

I am working autoencoder and I am looking to make loose function curve for training and validation together while training the model

I checked this Example of training autoencoder but only show loose curve for training

https://www.mathworks.com/help/deeplearning/ref/trainautoencoder.html

How to make Training and Validation loose curve togther while training the model

Herein my code

dataDir= fullfile('Data/');
exts = {'.jpg','.png','.tif','BMP'};
 
 
imds = imageDatastore(fullfile(dataDir),...
'IncludeSubfolders',true,'FileExtensions','.jpg','LabelSource','foldernames');
countEachLabel(imds);
 
[TrainData, TestData, ValidData] = splitEachLabel(imds, 0.10, 0.20);
size(TrainData);
countEachLabel(TrainData);
numImages = numel(TrainData.Files); 

for i = 1:numImages
    img = readimage(TrainData, i);
    img=rgb2gray(img);
    img3= im2double(img); 
    scale = 0.5;
    img8 = imresize(img3,scale);
    
            
            Train{idx} = (img8);         %#ok<SAGROW>
     
 
end
numImages = numel(ValidData.Files); 
for i = 1:numImages
    img = readimage(ValidData, i);
    img=rgb2gray(img);
    img3= im2double(img); 
    scale = 0.5;
    img8 = imresize(img3,scale);
   
           
            Valid{idx} = (img8);         %#ok<SAGROW>
        
 
end
hiddenSize = 50;
autoenc = trainAutoencoder(Valid,Train,hiddenSize,'MaxEpochs',100,...
'DecoderTransferFunction','purelin','EncoderTransferFunction','satlin','L2WeightRegularization',0.004,'SparsityRegularization',4,'SparsityProportion',0.15);