Same training results for each epoch using LSTM sequence to sequence

Dear all,

I am following the example given in:

https://www.mathworks.com/help/deeplearning/ug/sequence-to-sequence-regression-using-deep-learning.html

using different data but similar in structure to the one in the example.

The problem is when I train the data, the results for each epoch look the same (please see the picture attached).

I use the following setting options for training:

maxEpochs = 20;
miniBatchSize = 20;
options = trainingOptions('adam', ...
    'MaxEpochs',maxEpochs, ...
    'MiniBatchSize',miniBatchSize, ...
    'InitialLearnRate',0.01, ...
    'GradientThreshold',1, ...
    'Shuffle','never', ...
    'Plots','training-progress',...
    'Verbose',0);

I use a single LSTM layer with 128 hidden units working on MATLAB R2022b.

Any advise or idea is really appreciated.

Thanks