As it says in the first paragraph, what you see in the Regression Learner App is the Validated model. In your case, the validated model has been cross-validated 10-fold. The exported model however would be, what is referred to as, the Full model. The Full model is learned using the whole training dataset. The Validated model is trained on part of the dataset in order to give an estimate on how it would perform on unseen data.
If you'd like your exported model's behaviour to match the plots/results in the app, select Resubstitution Validation when creating your session. In this approach, the responses/predictions that you see will match that of the exported model since all the training data is used in this validation approach.
Also to be clear, the k-fold cross validated models do not overfit the data. In fact, cross-validation is performed to better understand how a model would perform on unseen data. The final exported model would trained on all the data available.
