Resolve automatic label name detection when single label provided
Author: ndonthi
Pull request: yes

# What does this PR do?

Users frequently encounter a confusing KeyError when setting label_names=['label'] in TrainingArguments, leading to errors like:
```
KeyError: "The `metric_for_best_model` training argument is set to 'eval_f1', which is not found in the evaluation metrics. The available evaluation metrics are: []."
```

The label_names parameter is designed for advanced multi-label scenarios, but users often mistakenly use label_names=['label'] thinking they need to specify their label column. This breaks the automatic "label" → "labels" conversion that happens during data collation which causes loss calculation to fail silently. 

This PR introduces validation for this edge case and fixes the issue in the Trainer to use automatic label detection. If it's preferred, I can make this change where the automatic label detection happens as well!

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Implements a code fix to #28530  #40217 and [#32373 on huggingface forum](https://discuss.huggingface.co/t/why-do-i-get-no-validation-loss-and-why-are-metrics-not-calculated/32373)


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Comments:
cc @sunmarc

checking in on this! @SunMarc @Rocketknight1 

let me know if there's another preferred solution :)