Neural Network Architecture - Accuracy issue

I have a structured dataset having features and 570 classes. I have done a lot of experiments with the architecture but accuracy doesn’t increase. I also normalized the dataset before passing it into the model.
Here is the model architecture.

optimizer=‘adam’ also tried SGD(lr=0.01) as well,Y_train,validation_data=(X_test,Y_test_c),epochs=1500,batch_size=512, verbose=2 ,shuffle=True, callbacks=[es])

It’s ambiguous what you’re doing.
Have you tried TabNet?

No, I haven’t. I try to make my own architecture