# Validation Set

The validation set The validation set is a set of images reserved for validation. The validation set is separate from the training set and test set. Since the validation set is separate, it allows you to evaluate how well the tool performs when using unseen images. The VisionPro Deep Learning application calculates a special metric, the Loss. The Loss is based on the performance of the tool on the validation set. is a set of images reserved for validation Validation refers to a process during the training of a tool that helps to evaluate performance. Validation is like a mock exam that the tool takes during the training phase, separate from the final test. For example, validation helps you to recognize overfitting and avoid wasting time when training a tool. If you recognize that the tool is overfitting, you can stop the training early.. The validation set is separate from the training Training is the process that your tool, which is a neural network, is learning about the features (pixels) based on the labels you made. For example, a tool will learn the defect/normal pixels in each image based on the defect/normal labels you drew. The goal of the tool Training is learning enough to give the correct inspection results of whether an unseen image is defective or not. The key to training is to ensure that you include all possible variations within your training set, and that your images are accurately labeled. Training times vary by the application, tool setup and the GPU in the PC being used to train the network. set and test set. Since the validation set is separate, it allows you to evaluate how well the tool performs when using unseen images. The VisionPro Deep Learning application calculates a special metric, the Loss The Loss refers to validation loss, which is a metric that shows how a tool performs on the validation set. Loss can have a value between 0 and 1. The VisionPro Deep Learning application calculates the Loss based on the errors the tool makes when processing the images in the validation set. During training, you can check the Loss in real-time using the Loss Inspector.. The Loss is based on the performance of the tool on the validation set.

The application creates the validation set for you by default. The application randomly selects the images for the validation set from the training set when you train a tool.

You can control the size of the validation set with the Validation Set Ratio parameter. Adjust the ratio to determine the size of the validation set compared to the size of the training set.

For the best results, you can create your own image sets to use for training, for validation, and for testing. Custom image sets allow you to tailor the data to your specific needs, ensuring better control and more accurate results.

## How to Check the Images in the Validation Set

The images that are in the validation set have an indicator that you can find in the upper right corner of the Image Display Area. In the View Browser, you can filter your images if you enter validated or not validated in the Display search box.

## Validation Results in the Database Overview

If you enable Expert mode, you can include or exclude the results from the validation set in the Database Overview.

- Enter validated into the search box to include the results from the validation set.

- Enter not validated into the search box to exclude the results from the validation set.