Error in training data sequence length. How to rectify this?

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sample_data.xlsx

Hi,

I am creating cnn+lstm architecture for prediction. When I am training the model, I am getting error " Error using trainNetwork: Invalid training data. Sequence responses must have the same sequence length as the corresponding predictors."

the code is below. The sample data is attached here.

data = xlsread("sample_data.xlsx", 1);
data_norm = normalize(data(:,1:end));
train_ratio = 0.8;
n_train = round(size(data,1) * train_ratio);
train_data = data(1:n_train,:);
test_data = data(n_train+1:end,:);
numFeatures = size(train_data,2)-1;
XTrain = train_data(:,1:end-1);
YTrain = train_data(:,end);
XTest = test_data(:,1:end-1);
YTest = test_data(:,end);
sequenceLength = 1;
% Reshape the input sequences 
numTrain = floor(size(train_data,1)/sequenceLength);
XTrain = XTrain(1:numTrain*sequenceLength,:);
YTrain = YTrain(1:numTrain*sequenceLength,:);
XTrain = reshape(XTrain, [1, sequenceLength, numFeatures, numTrain]);
YTrain = reshape(YTrain, [1, sequenceLength, 1, numTrain]);
numValidation = floor(size(test_data,1)/sequenceLength);
XTest = XTest(1:numValidation*sequenceLength,:);
YTest = YTest(1:numValidation*sequenceLength,:);
XTest = reshape(XTest, [1, sequenceLength, numFeatures, numValidation]);
YTest = reshape(YTest, [1, sequenceLength, 1, numValidation]);
% the CNN LSTM model
inputSize = [1 size(XTrain,2) size(XTrain,3)];
numHiddenUnits = 64;
numClasses = 1;
layers = [ ...
    sequenceInputLayer(inputSize)
    convolution2dLayer([1 3],16,'Padding','same')
    batchNormalizationLayer
    reluLayer
    convolution2dLayer([1 3],32,'Padding','same')
    batchNormalizationLayer
    reluLayer
    convolution2dLayer([1 3],64,'Padding','same')
    batchNormalizationLayer
    reluLayer
    flattenLayer
    lstmLayer(numHiddenUnits,'OutputMode','sequence')
    fullyConnectedLayer(numClasses)
    regressionLayer];
% Specify the training options
options = trainingOptions('adam', ...
    'MaxEpochs',50, ...
    'MiniBatchSize',32, ...
    'ValidationData',{test_data(:,1:end-1), test_data(:,end)}, ...
    'ValidationFrequency',10, ...
    'Shuffle','every-epoch', ...
    'Plots','training-progress');
% Train the CNN LSTM model
net = trainNetwork(XTrain,YTrain, layers, options);
Error using trainNetwork
Invalid training data. Sequence responses must have the same sequence length as the corresponding predictors.