DOCS: Clarification on the use of label_names as an argument to TrainingArguments (#40353)

* Update trainer.md

* Update trainer.md

Removed the detail about label_names argument usage from the tip/ warning section

* Update training_args.py

Added the label_names usage clarification in the docstring

* Update trainer.md

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Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

Author: 2 people

src/transformers/training_args.py

@@ -456,6 +456,8 @@ class TrainingArguments:
             Will eventually default to the list of argument names accepted by the model that contain the word "label",
             except if the model used is one of the `XxxForQuestionAnswering` in which case it will also include the
             `["start_positions", "end_positions"]` keys.
+
+            You should only specify `label_names` if you're using custom label names or if your model's `forward` consumes multiple label tensors (e.g., extractive QA).
         load_best_model_at_end (`bool`, *optional*, defaults to `False`):
             Whether or not to load the best model found during training at the end of training. When this option is
             enabled, the best checkpoint will always be saved. See