max_steps (`int`, *optional*, defaults to -1):
                If set to a positive number, the total number of training steps to perform. Overrides
                `num_train_epochs`. In case of using a finite iterable dataset the training may stop before reaching
                the set number of steps when all data is exhausted.
            warmup_ratio (`float`, *optional*, defaults to 0.0):
                Ratio of total training steps used for a linear warmup from 0 to `learning_rate`.
            warmup_steps (`int`, *optional*, defaults to 0):
                Number of steps used for a linear warmup from 0 to `learning_rate`. Overrides any effect of
                `warmup_ratio`.

        Example:

        ```py
        >>> from transformers import TrainingArguments

        >>> args = TrainingArguments("working_dir")
        >>> args = args.set_lr_scheduler(name="cosine", warmup_ratio=0.05)
        >>> args.warmup_ratio
        0.05
        ```
        N)