src/transformers/trainer_utils.py/default_hp_space_wandb
def default_hp_space_wandb(trial) -> Dict[str, float]:
    from .integrations import is_wandb_available

    if not is_wandb_available():
        raise ImportError("This function needs wandb installed: `pip install wandb`")

    return {
        "method": "random",
        "metric": {"name": "objective", "goal": "minimize"},
        "parameters": {
            "learning_rate": {"distribution": "uniform", "min": 1e-6, "max": 1e-4},
            "num_train_epochs": {"distribution": "int_uniform", "min": 1, "max": 6},
            "seed": {"distribution": "int_uniform", "min": 1, "max": 40},
            "per_device_train_batch_size": {"values": [4, 8, 16, 32, 64]},
        },
    }