Document that iterable train_dataset requires max_steps in RewardTrainer

Author: albertvillanova

trl/trainer/reward_trainer.py

@@ -273,6 +273,10 @@ class RewardTrainer(_BaseTrainer):
 
             The trainer also supports processed datasets (tokenized) as long as they contain `chosen_ids` and
             `rejected_ids` fields.
+
+            When `train_dataset` is an [`~datasets.IterableDataset`] (e.g. a streaming dataset), `max_steps` must be
+            set in the training arguments, since its length cannot be inferred and the total number of training steps
+            is required to bound the training loop and configure the learning rate scheduler.
         eval_dataset ([`~datasets.Dataset`], [`~datasets.IterableDataset`], [`~datasets.DatasetDict`], [`~datasets.IterableDatasetDict`] or `dict[str, Dataset | IterableDataset]`):
             Dataset to use for evaluation. It must meet the same requirements as `train_dataset`.
         processing_class ([`~transformers.PreTrainedTokenizerBase`], *optional*):