Step by Step walk through of model playground experiments.
After creating the splits, the user can now run experiments. By clicking a split, the user is able to create an experiment.
In the experiment, the user is able to specify the name of the
experiment and has the option to use the Hasty template for their model.
On choosing the hasty template, the architectures, its
parameter values, loss metrics, and all other features of a model will
be automatically set for that specific machine learning task. For
example for instance segmentation task, the Basic Instance Segmentor
template would be used.
If the users want to design their own model with the provided
architectures, solvers, optimizers, loss metrics, etc., then that is
also possible by not using the template.
To learn more about the different aspects of the model:
Here, the user can find a detailed explanation of all the model parameters provided by hasty.