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Training plan

Once the model is linked to a dataset, a training object can be created to manage and display the current training plan.

View Training Plan​

To view the current training plan and all its parameters and their values, use the following command:

trainingObject.getTrainingPlan()

Training Plan

It is also possible to adjust the training plan using similar parameters as those found in Tensorflow. However, the training object must be set up properly for this to work. If not, further steps cannot be completed. For a reminder on how to do this, check our Training Guide for Google Colab or Training Guide for Jupyter Notebook.

Set Training Plan​

The training plan parameters are divided into four categories:

  • Training description
  • Dataset Parameters
  • Training Parameters
  • Hyperparameters
  • Augmentation Parameters

To adjust a specific parameter, use the following command:

trainingObject.parameter_name(value)

For the individual training parameters for each framework visit our training plan section.

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