Using the BirdNet Custom Training Pipeline on AML

Running the Pipeline

Steps in Azure Machine Learning Studio

  1. Log in to AML Studio.
  2. Navigate to the Pipelines section.
  3. Select the BirdNet-Custom-Training-Pipeline.
  4. Set the following parameters:
    • Input Data: Path to the training dataset (BirdNET_training_datasets/Stage1/Training/ in customaudiodata).
    • Output Location: Path where the trained model will be saved (BirdNet_custom_models/Stage1/).
  5. Submit the pipeline for execution.

Monitor Pipeline Execution

  • You can monitor the progress of the pipeline in the Experiments tab. Each step of the training process will be logged and can be viewed in real-time.

Model Storage

  • After the pipeline completes, the trained model will be available in the customaudiodata datastore at the location BirdNet_custom_models/Stage1/.