Accuracy on Validation and Test set, Overfit?
If the training set, validation set and the unseen test set (as you put it) have the same score, but lower than you expected then the model has not overfitted.
An overfitted model would have higher scores for the training data at least, and depending on how you optimised the hyper parameters on the validation data but lower for the unseen test set.
The more likely outcome is that your model has underfitted i.e. low but consistent scores across all 3 sets of data.