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50% is quite decent because you have five labels and random guessing model would have achieved only 20% accuracy. So you know your model is learning something.
The other thing you want to check out is whether this is suited to be a regression problem more than classification. For e.g, misclassifying a 5 (ground truth) into a 4 is better than misclassifying ...
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The problem is that you are encoding the pieces of text as vectors and feeding those vectors to the model, but then the first layer of the model is again an embedding layer.
You should only use the embedding once: either you embed the text out of the model (train_embed=encoder(messages)) or you pass integer inputs to the model and them inside the model (X=...
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