📘 A note on training cycles During training, Edge Impulse automatically saves the model with the best loss score. This means you can train a model for as many training cycles as you like and you will always end up with the best possible version.
📘 Hidden benefits You might find that a model trained with data augmentation performs better on your test dataset even if its accuracy during training is similar, so it's always worth checking your models against test data.
📘 Versioning You can use Edge Impulse's Versioning feature to save the state of your Impulse at this point, so that you can restore it if you wish to perform more experimentation. You can find it in the Versioning tab in the left menu.