diff --git a/src/transformers/trainer.py b/src/transformers/trainer.py
index e537b3b6357adb..64d5a3fadf4d6d 100755
--- a/src/transformers/trainer.py
+++ b/src/transformers/trainer.py
@@ -1935,7 +1935,9 @@ def _load_from_checkpoint(self, resume_from_checkpoint, model=None):
             else:
                 # We load the model state dict on the CPU to avoid an OOM error.
                 state_dict = torch.load(os.path.join(resume_from_checkpoint, WEIGHTS_NAME), map_location="cpu")
-                load_result = model.load_state_dict(state_dict, strict=False)
+                # workaround for FSDP bug https://github.com/pytorch/pytorch/issues/82963
+                # which takes *args instead of **kwargs
+                load_result = model.load_state_dict(state_dict, False)
                 # release memory
                 del state_dict
                 self._issue_warnings_after_load(load_result)
@@ -1989,7 +1991,9 @@ def _load_best_model(self):
                     # We load the model state dict on the CPU to avoid an OOM error.
                     state_dict = torch.load(best_model_path, map_location="cpu")
                     # If the model is on the GPU, it still works!
-                    load_result = model.load_state_dict(state_dict, strict=False)
+                    # workaround for FSDP bug https://github.com/pytorch/pytorch/issues/82963
+                    # which takes *args instead of **kwargs
+                    load_result = model.load_state_dict(state_dict, False)
                 if not is_sagemaker_mp_enabled():
                     self._issue_warnings_after_load(load_result)
         elif os.path.exists(os.path.join(self.state.best_model_checkpoint, WEIGHTS_INDEX_NAME)):