Add start_time parameter to _maybe_log_save_evaluate method

trl/trainer/online_dpo_trainer.py

@@ -12,6 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import inspect
 import os
 import textwrap
 import warnings
@@ -588,7 +589,8 @@ def training_step(
         return loss.detach() / self.args.gradient_accumulation_steps
 
     # Same as Trainer._maybe_log_save_evaluate but log our metrics
-    def _maybe_log_save_evaluate(self, tr_loss, grad_norm, model, trial, epoch, ignore_keys_for_eval, start_time):
+    # start_time defaults to None to allow compatibility with transformers<=4.46
+    def _maybe_log_save_evaluate(self, tr_loss, grad_norm, model, trial, epoch, ignore_keys_for_eval, start_time=None):
         if self.control.should_log and self.state.global_step > self._globalstep_last_logged:
             logs: Dict[str, float] = {}
 
@@ -612,7 +614,10 @@ def _maybe_log_save_evaluate(self, tr_loss, grad_norm, model, trial, epoch, igno
             self._globalstep_last_logged = self.state.global_step
             self.store_flos()
 
-            self.log(logs, start_time)
+            if "start_time" in inspect.signature(self.log).parameters:  # transformers>=4.47
+                self.log(logs, start_time)
+            else:  # transformers<=4.46
+                self.log(logs)
 
         metrics = None
         if self.control.should_evaluate: