Hi,@ZEBA
As far as I can guess you should be using trainnet to train the network, which is indeed slightly different from the previous version. However, this doesn't affect your ability to see the final training and validation accuracy, you should check if the "ValidationData" in the "trainingOptions" contains your validation data.
Since R2024a, it is recommended to use trainnet instead of trainNetwork, which is almost compatible with the old version and offers more advantages:
- trainnet supports dlnetwork objects, which support a wider range of network architectures that you can create or import from external platforms. For example, you can create and train neural networks with multiple inputs and multiple outputs.
- trainnet enables you to easily specify loss functions. You can select from built-in loss functions or specify a custom loss function.
- trainnet outputs a dlnetwork object, which is a unified data type that supports network building, prediction, built-in training, visualization, compression, verification, Simulink, code generation, and custom training loops.
- trainnet is typically faster than trainNetwork.
BTW, you can't use the "classify" function on dlnetwork objects, because it only works with older versions of SeriesNetwork or DAGNetwork objects.
-------------------------Off-topic interlude-------------------------------
I am currently looking for a job in the field of CV algorithm development, based in Shenzhen, Guangdong, China. I would be very grateful if anyone is willing to offer me a job or make a recommendation. My preliminary resume can be found at: https://cuixing158.github.io/about/ . Thank you!
Email: cuixingxing150@gmail.com
