Wrong number of classes in data.yaml

Description

After labelling all the images in the dataset, when generating a new dataset version and downloading it, the data.yaml created additional non-existing classes.

Steps to reproduce

1. Label your data
2. Create a new dataset version
3. Check the Modify Classses pre-processing step to make sure you have the right classes
4. Generate the dataset version
5. Download the dataset
6. Check the classes in data.yaml

Expected result

You should only get the classes that you labeled

Actual result

The roboflow creates additional non-existing classes (this also alters the class_id of the real classes)

Note: While labeling, there were some classes that were created by mistake, but they were deleted afterwards since they were never used. This somehow was still picked up by the roboflow.

Evidence

You can clearly see I had 2 classes:

When downloading the dataset, its data.yaml config file looked like this:

This remapped my original class_id's of course.
This was my original data.yaml:

Il report non indica file di implementazione né test; inizia riproducendo i passaggi di etichettatura, versionamento del dataset, generazione e download, quindi esamina il data.yaml generato confrontandolo con le classi etichettate e gli ID delle classi originali. Il lavoro è completato quando il file contiene solo classi etichettate e conserva gli ID delle classi attesi.