How can I prevent this model to learn more(less) :))) As you can see, GradientBoostingClassifier overfit with more training example.
These are my parameter for the model:

{'learning_rate': 0.1, 'loss': 'deviance', 'max_depth': 6, 'max_features': 0.3, 'min_samples_leaf': 80, 'n_estimators': 300}

What should I to make my model better or stop training at 350?
Well, by making your model better, I suppose you mean enforcing some sort of regularization on it, so that it doesn't overfit. Early stopping, however can be viewed as a regularization method by itself. 

I would suggest sampling the performance of your model more frequently (than the 200 examples you are doing currently) and if you see the validation score is not improving after a few iterations stop the training.

Early stopping can be implemented through the monitor parameter in the GradientBoostingClassifier's .fit() method.