As usual, I have three sets of data: Train, Validation and Test. So I use train data for model selection, where I select the model which would perform best on validation data. After selecting the best model, if I use same Train data and Validation data to further tune or improve my model, and then test on Test set, am I doing something fundamentally wrong? Am I introducing any kind of bias or perhaps over-fitting? Is there something fundamental information that perhaps I am skipping?