lstm network not giving accurate results

After training the LSTM network I have plotted the confusion matrix, and the data is not classified exactly.

I have trained an LSTM network for fault classification of transmission lines. I have collected the current samples of three phases using Simulink and processed using wavelet transform. The total number of fault cases are 161 for each fault and number of features in each simulation are 104. I have converted the data into cell format. I used the following code to implement LSTM.`inputSize = 104;numHiddenUnits1 = 100;numHiddenUnits2 = 100;numClasses = 10;% layers = [ ...% sequenceInputLayer(inputSize)% lstmLayer(numHiddenUnits1,'OutputMode','sequence')% dropoutLayer(0.2)% lstmLayer(numHiddenUnits2,'OutputMode','last')% dropoutLayer(0.2)% fullyConnectedLayer(numClasses)% softmaxLayer% classificationLayer];

% options = trainingOptions('sgdm', ...%     'MaxEpochs',100, ...%     'Verbose',false, ...%     'Plots','training-progress');net = trainNetwork(XTrain1,YTrain1,layers,options);`