I have built a CNN-LSTM neural network with 2 inputs and 2 outputs in Keras. I trained the network with model.fit_generator() (and not model.fit()), to load just parts of the training data when needed, because the training data is too large to load at once.
After the training the model was not working. So I checked training data (before and after augmentation). The training data are correct. So I thought the reason why the model does not work must be that I have not found the optimal hyperparameters yet.
But how can I do hyperparameter optimization on a network with multiple inputs and outputs and trained with model.fit_generator()? All I can find online is hyperparameter optimization of networks with a single input and single output and trained with model.fit().
