Accuracy after selftraining didn't change
Well, that is a bit of a turn down but: your model has limitations.

If the 50.000 data forms a complete set for your problem that means that more data won't be needed or helpful.

What do I mean by complete set is: there are enough samples to form a full rank correlation matrix in your feature space. So from your samples you can get a set that can generate all other samples in your feature space by linear combination.

Also, while your data might represent everything a decision three needs to know for classificating your data in the generated feature space, there may be other feature spaces that benefit from the extra data (such as deeper trees or other models)

You might try helping you decision tree by providing a few normalizations for data and feature engineering