Test it on the Peltarion Platform

A platform to build and deploy deep learning projects.

Even if you’re not an AI superstar.


Run a model

You’ve built a model. Great! Time to train it and see how it performs.

In this section, we will go through all the steps needed to run a model, as well as give you an overview of all the options available for you for training.

Before running a model

Before running your model, make sure that you have:

  • Assigned the desired Feature sets to the Input block and Target block respectively.

  • Selected the desired loss function in the Target block.

  • Verified that you have the right number of output Nodes in the second to last block of your network (corresponding to the number of outputs you want your network to predict).

The Run settings section

Navigate to the Settings tab in the Inspector. This is where you will find the Run settings section, which contains all the parameters you can adjust prior to running your training. Let’s review them briefly:

  • Batch size is the number of examples (i.e., rows of your training set) that are processed in each training iteration and after which your model parameters (i.e., weights) are updated. The batch size is a hyperparameter of your model and can be freely adjusted, but the most common and recommended size are 32, 64, 128, 256 or 512.

Note that the bigger the batch size, the bigger the memory requirements to run your model. You can keep track of the memory requirements of the model by having a look at the Run button in the upper right corner. The memory requirements of your model have to be 5GB or less for you to be able to run it on the platform.
  • One Epoch is when the complete training set has run through the model one time. That means that if you set epochs to 100 the complete training set will be run through the model a 100 times.

  • Data access seed is just a random number. It has no real influence on the training of your model.

  • The Optimizer refers to gradient descent optimizers and it allows you to select your method of choice to optimize the loss with respect to the weights of the network. For a more detailed description of the optimizers available on the platform see our Optimizer article in our Knowledge center.

Change the batch size of your model and see how it affects the memory requirements of running your model.

The Run button

Now that you have set all your preferred Run settings you’re ready to train your model! The only thing left to do is to press the Run button on the upper right corner to start the training process.

5GB model limit

Note that the memory requirements of your model have to be 5GB or less for you to be able to train the model on the platform. If your memory requirements are larger than 5GB the Run button will be disabled (i.e., it will appear greyed out).

If this is the case, you can try reducing the batch size in the Run settings section to reduce the memory requirements or do some additional data preprocessing to reduce the general size of your examples. Once your memory requirements are 5GB or less, the Run button will become active again.