Train a Model
Train a model using state-of-the-art technology in the Roboflow dashboard.
You can train computer vision models in the Roboflow interface.
Roboflow offers two training options:
Roboflow Train: Our flagship training service, ideal for creating production-ready models.
Roboflow Instant: Train models in a few minutes that are ideal for testing.
When you approve a batch of image annotations, Instant models are automatically trained. These models can be used immediately.
Models trained on Roboflow can be deployed with Inference, our on-device inference server, or in the cloud using our Serverless Hosted API with Workflows, Batch Processing with Workflows, or with your model API endpoint.
Train a Model
To train a computer vision model, first generate a dataset version.
Click the "Custom Train" button to start configuring a training job:

Select a Model Architecture
Next, you need to select a model architecture. This is the machine learning technology used to train your model.
The model architectures you can train depend on the type of project you have set up:
Object Detection: You can train Roboflow 3.0, RF-DETR, YOLOv11, YOLOv12, and YOLO-NAS models.
Classification: ViT and ResNet.
Instance Segmentation: Roboflow 3.0 and YOLO11.
Keypoint Detection: Roboflow 3.0 and YOLO11.
Multimodal: Florence 2, PaliGemma 2, and Qwen-2.5 VL.
Choose an architecture available for your project type, then click "Continue":

Select a Model Size
Next, you need to set a size for your model.
For development and testing, we recommend Fast models. For models intended for production, we recommend Accurate. For production models that do not need to run in real time and where accuracy is essential, choose Extra Large.
Accurate and Extra Large are only available for Object Detection models.

The Fast and Accurate training options are available to all users. Medium, Large, and Extra Large are available only to paid users.
Select a Checkpoint
After selecting a training option, you will be asked whether you want to train from a checkpoint. The tabs below show the configuration options for each model type.
You have three options:
Train from a Previous Checkpoint: Ideal for when you already have a working model that you want to improve.
Train from Public Checkpoint: Ideal for your first model version, or for when a previous training run did not achieve the expected results.
Train from Random Initialization: For advanced users only, this option gives you a blank slate from which to train. Most users see worse results when using this option.
Start the Training Job
Once you have chosen a Checkpoint from which to train, click Start Training.
Your dataset will then be zipped and prepared for training in the Roboflow cloud.
After your dataset has been prepared, you will receive an estimate that shows how long training will take:

The larger the dataset, and the larger the images in your dataset, the longer it will take for your model to train.
We will email you when the training process finished. In most cases, this should be under 24 hours.
Pricing
Training on Roboflow is priced on the length of the train job. You can see more information on our credits page.
If you are a student or researcher and need credits for a project on which you are working, you can apply for additional credits.
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