Repository: huggingface/transformers
Pull request: Fix `Seq2SeqTrainingArguments` documentation

# What does this PR do?

https://huggingface.co/docs/transformers/en/main_classes/trainer#transformers.Seq2SeqTrainingArguments

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Changed files:
filename: src/transformers/training_args_seq2seq.py
patch: @@ -28,7 +28,12 @@
 @add_start_docstrings(TrainingArguments.__doc__)
 class Seq2SeqTrainingArguments(TrainingArguments):
     """
-    Args:
+        sortish_sampler (`bool`, *optional*, defaults to `False`):
+            Whether to use a *sortish sampler* or not. Only possible if the underlying datasets are *Seq2SeqDataset*
+            for now but will become generally available in the near future.
+
+            It sorts the inputs according to lengths in order to minimize the padding size, with a bit of randomness
+            for the training set.
         predict_with_generate (`bool`, *optional*, defaults to `False`):
             Whether to use generate to calculate generative metrics (ROUGE, BLEU).
         generation_max_length (`int`, *optional*):
@@ -45,7 +50,7 @@ class Seq2SeqTrainingArguments(TrainingArguments):
             - a path to a *directory* containing a configuration file saved using the
               [`~GenerationConfig.save_pretrained`] method, e.g., `./my_model_directory/`.
             - a [`~generation.GenerationConfig`] object.
-    """
+    """  # fmt: skip  # Prevent Ruff from altering the indentation
 
     sortish_sampler: bool = field(default=False, metadata={"help": "Whether to use SortishSampler or not."})
     predict_with_generate: bool = field(