Skip to main content

​
🎛️ Configuring a Training Job

This guide explains every field on the Train Model panel to help you understand and configure your model training setup.
Training Config UI

​
1. Details

​
2. Base Model

You can currently choose between two base models depending on the project type:
  1. YOLOv11 Object Detection – used with bounding boxes annotations
  2. YOLOv11 Segmentation – used with polygon and SAM-2 generated annotations
Depending on the current project’s type (object detection or segmentation), you will only see the one available model for that project type. Both models the latest generation from Ultralytics, fusing an upgraded backbone and neck for higher accuracy with fewer parameters [Ultralytics Docs].

​
3. Model Variant

Choosing a variant is a trade-off between speed & accuracy.
m is an excellent starting point for most users.

​
4. Customization

​
5. Hyper-parameters

Other YOLO hyper-parameters (batch size, learning rate, momentum, etc.) are managed automatically by the trainer and use Ultralytics’ recommended defaults.

​
6. Launch the Job

Hit Create Model. Your run queues and begins on our GPU fleet. You will be redirected to the models tab, where performance metrics and graphs will be available after the training run is complete.
Prefer code? Head to Notebooks for SDK-based examples.