Hi,
There is no direct way to remove the smoothed training accuracy curve from the graph. If possible, you can upgrade MATLAB and use the "trainnet" function introduced in R2023a. The plots don't provide the smoothed accuracy. Since R2024a, the "trainNetwork" function is not recommended.
Alternately, if it is possible to use custom loops for training the data, you can use the "trainingProgressMonitor" object. It allows for creating animated custom metric plots and record custom metrics during training. Following is an example of using "trainingProgressMonitor":
monitor = trainingProgressMonitor;
addMetrics(monitor, ["TrainingAccuracy", "ValidationAccuracy"]);
% Training loop example
for epoch = 1:numEpochs
% Perform training and validation steps here
% Update custom metrics
recordMetrics(monitor, epoch, ["TrainingAccuracy", trainingAccuracy, "ValidationAccuracy", validationAccuracy]);
end
% Display the training progress monitor
show(monitor);
You can refer the following documentation links to learn about these functions:
- trainnet: https://www.mathworks.com/help/deeplearning/ref/trainnet.html
- trainingProgressMonitor: https://www.mathworks.com/help/deeplearning/ref/deep.trainingprogressmonitor.html
Hope this helps!
