, Y_train, callbacks=[clr])
        ```
    # Arguments
        base_lr: initial learning rate which is the
            lower boundary in the cycle.
        max_lr: upper boundary in the cycle. Functionally,
            it defines the cycle amplitude (max_lr - base_lr).
            The lr at any cycle is the sum of base_lr
            and some scaling of the amplitude; therefore
            max_lr may not actually be reached depending on
            scaling function.
        step_size: number of training it