Record metric values in experiment results table and training plot
records the specified metric value for a trial in the Experiment Manager
results table and training plot.
records the metric values specified by the structure
Track Progress, Display Information and Record Metric Values, and Produce Training Plots
experiments.Monitor object to track the progress of the training,
display information and metric values in the experiment results table, and produce
training plots for custom training experiments.
Before starting the training, specify the names of the information and metric columns of the Experiment Manager results table.
monitor.Info = ["GradientDecayFactor","SquaredGradientDecayFactor"]; monitor.Metrics = ["TrainingLoss","ValidationLoss"];
Specify the horizontal axis label for the training plot. Group the training and validation loss in the same subplot.
monitor.XLabel = "Iteration"; groupSubPlot(monitor,"Loss",["TrainingLoss","ValidationLoss"]);
Update the values of the gradient decay factor and the squared gradient decay factor for the trial in the results table.
updateInfo(monitor, ... GradientDecayFactor=gradientDecayFactor, ... SquaredGradientDecayFactor=squaredGradientDecayFactor);
After each iteration of the custom training loop, record the value of training and validation loss for the trial in the results table and the training plot.
recordMetrics(monitor,iteration, ... TrainingLoss=trainingLoss, ... ValidationLoss=validationLoss);
Update the training progress for the trial based on the fraction of iterations completed.
monitor.Progress = 100 * (iteration/numIterations);
Specify Metric Values by Using Structure
Use a structure to record metric values in the results table and the training plot.
structure.TrainingLoss = trainingLoss; structure.ValidationLoss = validationLoss; recordMetrics(monitor,iteration,structure);
monitor — Experiment monitor
Experiment monitor for the trial, specified as an
experiments.Monitor object. When
you run a custom training experiment, Experiment Manager passes this object as the
second input argument of the training function.
step — Custom training loop step
numeric scalar |
Custom training loop step, such as the iteration or epoch number, specified as a
numeric scalar or
dlarray object. Experiment Manager uses this value as
the x-coordinate in the training plot.
metricName — Metric name
string | character vector
Metric name, specified as a string or character vector. This name must be an element
Metrics property of the
metricValue — Metric value
numeric scalar |
Metric value, specified as a numeric scalar or
Experiment Manager uses this value as the y-coordinate in the
metricStructure — Metric names and values
Both information and metric columns display values in the results table for your experiment. Additionally, the training plot shows a record of the metric values. Use information columns for text and for numerical values that you want to display in the results table but not in the training plot.
groupSubPlotfunction to define your training subplots before calling the function
Introduced in R2021a