As far as I know, the cross-validation in Weka (and the other evaluation methods) are only used to estimate the generalisation error. That is, the (implicit) assumption is that you want to use the learned model with data that you didn't give to Weka (also called "validation set"). Hence the model that you get is trained on the entire data.
During the cross-validation, it trains and evaluates a number of different models (10 in your case) to estimate how well the learned model generalises. You don't actually see these models -- they are only used internally. The model that is shown isn't evaluated.