# Purpose of validation data NN

Aside from using validation data to tune the hyperparameters is there any other benefit to including validation data to the model?

All I ever read about is it being used to tune hyperparameters and check for overfitting. Is the checking for overfitting separate from tuning the hyperparameters?

Training: Tune the parameters (weights and biases) Validation: Tune hyperparameters Test: Evaluate the model

So, if we are NOT tuning the hyperparameters, the validation set is pointless?

• Is the checking for overfitting separate from tuning the hyperparameters yes. – Mohammad Athar Feb 28 at 17:55
• Does this answer your question? Why use both validation set and test set? – Mohammad Athar Feb 28 at 17:56
• So if I am correct, validation set is ONLY used to set the hyperparameters. IF the hyperparameters have been set empirically, there is no need for it? – Shinobii Feb 28 at 17:59
• Ah never mind, I guess overfitting is really a problem with the length in training time? Thus, the validation set provides a measure to if we have starting fitting too well. I get it now! – Shinobii Feb 28 at 18:03