diff --git a/src/transformers/trainer.py b/src/transformers/trainer.py
index 1002ceb0cfe..423eaa69fd1 100755
--- a/src/transformers/trainer.py
+++ b/src/transformers/trainer.py
@@ -4822,10 +4822,15 @@ class Trainer:
             wrapper = "DeepSpeed" if self.is_deepspeed_enabled else "FSDP"
             raise ValueError(f"{wrapper} can't be used with `save_only_model` along with `load_best_model_at_end`.")
 
-        # `auto_find_batch_size` isn't yet supported with DeepSpeed/FSDP
-        if (self.is_deepspeed_enabled or self.is_fsdp_enabled) and self.args.auto_find_batch_size:
-            wrapper = "DeepSpeed" if self.is_deepspeed_enabled else "FSDP"
-            raise NotImplementedError(f"`{wrapper}` doesn't support `auto_find_batch_size`.")
+        # `auto_find_batch_size` isn't supported yet with DeepSpeed Zero-3
+        if (
+            self.is_deepspeed_enabled
+            and self.accelerator.state.deepspeed_plugin.zero_stage == 3
+            and self.args.auto_find_batch_size
+        ):
+            raise ValueError(
+                "`auto_find_batch_size` isn't supported yet with DeepSpeed Zero-3. Please consider using Zero-2, Zero-1, or FSDP"
+            )
 
     def propagate_args_to_deepspeed(self, auto_find_batch_size=False):
         """
diff --git a/tests/trainer/test_trainer.py b/tests/trainer/test_trainer.py
index a557e0f80b7..49213f19187 100644
--- a/tests/trainer/test_trainer.py
+++ b/tests/trainer/test_trainer.py
@@ -145,6 +145,21 @@ if is_accelerate_available():
 PATH_SAMPLE_TEXT = f"{get_tests_dir()}/fixtures/sample_text.txt"
 
 
+class MockCudaOOMCallback(TrainerCallback):
+    """
+    Simple callback to simulate CUDA OOM error if
+    the batch size is >= to `batch_size_limit`.
+    """
+
+    def __init__(self, batch_size_limit=16):
+        self.batch_size_limit = batch_size_limit
+
+    def on_step_end(self, args, state, control, **kwargs):
+        # simulate OOM on the first step
+        if state.train_batch_size >= self.batch_size_limit:
+            raise RuntimeError("CUDA out of memory.")
+
+
 class RegressionDataset:
     def __init__(self, a=2, b=3, length=64, seed=42, label_names=None):
         np.random.seed(seed)
@@ -2504,7 +2519,7 @@ class TrainerIntegrationTest(TestCasePlus, TrainerIntegrationCommon):
             run_glue.main()
 
     @require_deepspeed
-    def test_auto_batch_size_with_resume_from_checkpoint_with_deepspeed(self):
+    def test_auto_batch_size_with_deepspeed(self):
         train_dataset = RegressionDataset(length=128)
 
         config = RegressionModelConfig(a=0, b=2)
@@ -2512,33 +2527,27 @@ class TrainerIntegrationTest(TestCasePlus, TrainerIntegrationCommon):
 
         tmp_dir = self.get_auto_remove_tmp_dir()
 
-        class MockCudaOOMCallback(TrainerCallback):
-            def on_step_end(self, args, state, control, **kwargs):
-                # simulate OOM on the first step
-                if state.train_batch_size >= 16:
-                    raise RuntimeError("CUDA out of memory.")
-
-        deepspeed = {
-            "zero_optimization": {
-                "stage": 1,
-            },
-            "train_batch_size": "auto",
-            "train_micro_batch_size_per_gpu": "auto",
-        }
+        for stage in [1, 2]:
+            deepspeed = {
+                "zero_optimization": {
+                    "stage": stage,
+                },
+                "train_batch_size": "auto",
+                "train_micro_batch_size_per_gpu": "auto",
+            }
 
         args = RegressionTrainingArguments(
             tmp_dir,
             do_train=True,
             max_steps=2,
-            save_steps=1,
+            save_strategy="no",
             per_device_train_batch_size=16,
             auto_find_batch_size=True,
             deepspeed=deepspeed,
         )
-        # Note: This can have issues, for now we don't support this functionality
-        # ref: https://github.com/huggingface/transformers/pull/29057
-        with self.assertRaises(NotImplementedError):
-            _ = Trainer(model, args, train_dataset=train_dataset, callbacks=[MockCudaOOMCallback()])
+        trainer = Trainer(model, args, train_dataset=train_dataset, callbacks=[MockCudaOOMCallback()])
+        trainer.train()
+        self.assertEqual(trainer._train_batch_size, 8)
 
     def test_auto_batch_size_with_resume_from_checkpoint(self):
         train_dataset = RegressionDataset(length=128)
@@ -2548,12 +2557,6 @@ class TrainerIntegrationTest(TestCasePlus, TrainerIntegrationCommon):
 
         tmp_dir = self.get_auto_remove_tmp_dir()
 
-        class MockCudaOOMCallback(TrainerCallback):
-            def on_step_end(self, args, state, control, **kwargs):
-                # simulate OOM on the first step
-                if state.train_batch_size >= 16:
-                    raise RuntimeError("CUDA out of memory.")
-
         args = RegressionTrainingArguments(
             tmp_dir,
             do_train=True,