<p>Creates a new version of a model and begins training. Models are managed as part of an Amazon Rekognition Custom Labels project. The response from <code>CreateProjectVersion</code> is an Amazon Resource Name (ARN) for the version of the model. </p> <p>Training uses the training and test datasets associated with the project. For more information, see Creating training and test dataset in the <i>Amazon Rekognition Custom Labels Developer Guide</i>. </p> <note> <p>You can train a model in a project that doesn't have associated datasets by specifying manifest files in the <code>TrainingData</code> and <code>TestingData</code> fields. </p> <p>If you open the console after training a model with manifest files, Amazon Rekognition Custom Labels creates the datasets for you using the most recent manifest files. You can no longer train a model version for the project by specifying manifest files. </p> <p>Instead of training with a project without associated datasets, we recommend that you use the manifest files to create training and test datasets for the project.</p> </note> <p>Training takes a while to complete. You can get the current status by calling <a>DescribeProjectVersions</a>. Training completed successfully if the value of the <code>Status</code> field is <code>TRAINING_COMPLETED</code>.</p> <p>If training fails, see Debugging a failed model training in the <i>Amazon Rekognition Custom Labels</i> developer guide. </p> <p>Once training has successfully completed, call <a>DescribeProjectVersions</a> to get the training results and evaluate the model. For more information, see Improving a trained Amazon Rekognition Custom Labels model in the <i>Amazon Rekognition Custom Labels</i> developers guide. </p> <p>After evaluating the model, you start the model by calling <a>StartProjectVersion</a>.</p> <p>This operation requires permissions to perform the <code>rekognition:CreateProjectVersion</code> action.</p>

{
  "success": true,
  "data": {
    "id": "abc123",
    "created_at": "2025-01-01T00:00:00Z"
  }
}

{
  "success": false,
  "error": {
    "code": "VALIDATION_ERROR",
    "message": "Invalid request parameters"
  }
}