Use self._trial to generate trial_name for Trainer. (huggingface#19874)

* Do not generate trial_name when trail is None

* Use (trial or self._trial) to generate trial_name

* Follow comments

src/transformers/trainer.py

@@ -1652,7 +1652,10 @@ def _inner_training_loop(
         self.callback_handler.optimizer = self.optimizer
         self.callback_handler.lr_scheduler = self.lr_scheduler
         self.callback_handler.train_dataloader = train_dataloader
-        self.state.trial_name = self.hp_name(trial) if self.hp_name is not None else None
+        if self.hp_name is not None and self._trial is not None:
+            # use self._trial because the SigOpt/Optuna hpo only call `_hp_search_setup(trial)` instead of passing trial
+            # parameter to Train when using DDP.
+            self.state.trial_name = self.hp_name(self._trial)
         if trial is not None:
             assignments = trial.assignments if self.hp_search_backend == HPSearchBackend.SIGOPT else trial
             self.state.trial_params = hp_params(assignments)