def supervised_hyperparams(lr=1e-3, wd=5e-5, scheduler=True):
    """
    Return a dictionary of hyperparameters for the Supervised algorithm.
    Default parameters are the best ones as found through a hyperparameter search.

    Arguments:
    ----------
    lr: float
        Learning rate.

    wd: float
        Weight decay for the optimizer.

    scheduler: bool
        Will use a OneCycleLR learning rate scheduler if set to True.

    Returns:
    --------
    hyperparams: dict
        Dictionary containing the hyperparameters. Can be passed to the `hyperparams` argument on Supervised.
    """

    hyperparams = {'learning_rate': lr,
                   'weight_decay': wd,
                   'cyclic_scheduler': scheduler
                   }

    return hyperparams