Update YOLO training parameters

content/tutorial/segmentation-training.md

@@ -124,14 +124,16 @@ Configure the `YOLO Training | Detect/Segment` worker by clicking on the button
 
 Select **New configuration** on the left column, to create a new configuration. Again, name it after the dataset you are using.
 
-{{ figure(image="tutorial/training/segmentation/train_configuration.png", height=500, caption="Worker configuration") }}
+{{ figure(image="tutorial/training/segmentation/train_configuration.png", height=1000, caption="Worker configuration") }}
 
 The most important parameters are:
 - *Model that will receive the new trained version*: search for the name of [your model](#create-a-model),
-- *Number of epochs[^epoch] to train[^training] the model*: the default value is good enough but you can set it to a larger number if you want to train for a longer period time,
+- *Class names to predict*: add the slugs of the types that the model will predict,
+- *Number of epochs[^epoch] to train[^training] the model*: the default value is good enough but you can set it to a larger number if you want to train for a longer period of time,
 - *Type of object to detect using the segmenter*: 
   - a segmenter will produce masks (polygons),
   - a detector will produce bounding boxes (rectangles).
+- *Batch size for training*: a higher value will make the training faster but will also increase the memory usage.
 
 Click on **Create** then **Save** when you are done filling the fields. Your process is ready to go.