Difference in model performance measures of train and test data sets
Your model suffers of a slight overfitting, however it doesn't seem too dramatic.

Performance on train set are always better than test set if random sampled (when you have statistically significant volumes)

Maybe you can reduce the gap of performance by controlling the CP parameter, try setting a higher cp when you prune the tree (like 0.01) or by using the parameter maxdepth that prune according to the length of the tree.