The third phase, and the final step of the training process, is called ‘Refine’. The purpose of this stage is to refine your model and improve labels that are not performing as expected, as well as ensuring you have captured all of the labels and concepts that you are interested in.
Re:infer is designed to be completely transparent to users when it comes to model performance, and very flexible when it comes to improving performance in areas that require it. For any use case, you want to be confident that your model captures an accurate representation of what's in your dataset, and this phase of the training helps ensure that you can be.
This section of the Knowledge Base will cover in detail the steps outlined above, beginning with a detailed explanation of how validation works, and how to understand the different aspects of model performance.