I would like to know is there a way by which I can find the corresponding words for features in every node?

Hey guys, I have been trying to classify text data using decision tree classifier as an experiment. I vectorized the data with countvectorizer and fitted the model. For hyperparameter tuning, I plotted training error and validation error for hyperparams(max_depth and min_samples_split) separately to find the place of overfitting and underfitting and chose the best hyperparams and the model is performing nominally. But I'm trying to find what all words are in each of my internal nodes.

I would like to know is there a way by which I can find the corresponding words for features in every node?