System information

• OS version: Windows 10 Pro 18363
• .NET Version: Core 2.1
• Platform: x64
• ML.NET version: 0.15-preview

Issue

• What did you do?
  I am trying to train an image classifier that makes use of ExponentialLRDecay.
  I would like to see the metrics for training and validation for each epoch.

  var options = new ImageClassificationTrainer.Options()
  {
    LearningRateScheduler = new ExponentialLRDecay(),
    ValidationSetFraction = 0.1f,
    MetricsCallback = (metrics) => Console.WriteLine(metrics  + $"   CrossEntropy: {metrics.Train.CrossEntropy}, LearningRate: {metrics.Train.LearningRate})
  };
  var model = mlContext.MulticlassClassification.Trainers.ImageClassification(options);

  (I added + $" CrossEntropy: {metrics.Train.CrossEntropy}, LearningRate: {metrics.Train.LearningRate}", because the crossentropy and learning rate are not printed by default for the validation set.)

• What happened?

  • The learning rate is not updated for the validation set (seen on every even row in the image).
  • The cross-entropy is not calculated for the validation set (seen on every even row in the image).
  • The learning rate is not updated after the second epoch like the default value of 2 for numEpochsPerDecay in ExponentialLRDecay(), but after the first instead (seen on the third row in the image). After that, the learning rate is correctly updated every 2 epochs. I'm not sure if this is the expected behavior.

  

• What did you expect?

  • I expected a decaying learning rate in the validation step, equal to the one in the training step.
  • I expected the cross-entropy to be calculated in the validation step. The model with the highest Accuracy and lowest CrossEntropy are the best, so if 2 models perform equally well in terms of accuracy, the one with the lowest cross-entropy on the validation set should be picked.
  • Further, I expected the learning rate to start decaying after the 2nd epoch.