What is the purpose of using a validation set during model training?

What is the purpose of using a validation set during model training?

Step 1: When training a model, we use a dataset to teach it how to make predictions.
Step 2: We split this dataset into three parts: training set, validation set, and test set.
Step 3: The training set is used to train the model, helping it learn from the data.
Step 4: The validation set is a separate part that we use to check how well the model is doing while it is still being trained.
Step 5: By evaluating the model on the validation set, we can see if it is learning correctly or if it is making mistakes.
Step 6: We can also use the validation set to adjust settings (called hyperparameters) to improve the model's performance.
Step 7: Finally, after training, we use the test set to see how well the model performs on new, unseen data.

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