What to choose: an overfit model with higher evaluation score or a non-overfit model with lower one?
What library are you using? 
Dropout is used during training to prevent overfitting.

Make sure dropout is not applied for the validation (which is standard for Keras). This could artificially decrease your validation accuracy.

Also, accuracy is a bad metric to evaluate your performance. See this answer to find out why. Try ROC-AUC to evaluate your model performance.