Versioning
Dataset versions allow you to keep track of different snapshots of your dataset for export or model training. This creates a "locked" version of your dataset which you can use to train and tweak variations of your models.
You will need at least 1 approved annotation to lock a dataset version.
When a new version is created, the following attributes will be locked in your current version, and changes after that time will be applied to the next version:
Source data
Label definitions
Label instructions
Label annotations
Label status
In your dataset, navigate to the "Versions" tab.
Click "New Version"
In the modal, click "Create Version" to lock in your current dataset.
If this is your first version, this will lock in Version 1. You will then be able to train a model with Version 1 of your dataset. Additional changes to your dataset will be applied to Version 2, and so on.
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