diff --git a/litellm/tests/test_fine_tuning_api.py b/litellm/tests/test_fine_tuning_api.py
index b7e3c957cc..26f39e8453 100644
--- a/litellm/tests/test_fine_tuning_api.py
+++ b/litellm/tests/test_fine_tuning_api.py
@@ -14,101 +14,117 @@ import litellm
 litellm.num_retries = 0
 import logging
 
+import openai
+
 from litellm import create_fine_tuning_job
 from litellm._logging import verbose_logger
 
 
 def test_create_fine_tune_job():
-    verbose_logger.setLevel(logging.DEBUG)
-    file_name = "openai_batch_completions.jsonl"
-    _current_dir = os.path.dirname(os.path.abspath(__file__))
-    file_path = os.path.join(_current_dir, file_name)
+    try:
+        verbose_logger.setLevel(logging.DEBUG)
+        file_name = "openai_batch_completions.jsonl"
+        _current_dir = os.path.dirname(os.path.abspath(__file__))
+        file_path = os.path.join(_current_dir, file_name)
 
-    file_obj = litellm.create_file(
-        file=open(file_path, "rb"),
-        purpose="fine-tune",
-        custom_llm_provider="openai",
-    )
-    print("Response from creating file=", file_obj)
+        file_obj = litellm.create_file(
+            file=open(file_path, "rb"),
+            purpose="fine-tune",
+            custom_llm_provider="openai",
+        )
+        print("Response from creating file=", file_obj)
 
-    create_fine_tuning_response = litellm.create_fine_tuning_job(
-        model="gpt-3.5-turbo-0125",
-        training_file=file_obj.id,
-    )
+        create_fine_tuning_response = litellm.create_fine_tuning_job(
+            model="gpt-3.5-turbo-0125",
+            training_file=file_obj.id,
+        )
 
-    print("response from litellm.create_fine_tuning_job=", create_fine_tuning_response)
+        print(
+            "response from litellm.create_fine_tuning_job=", create_fine_tuning_response
+        )
 
-    assert create_fine_tuning_response.id is not None
-    assert create_fine_tuning_response.model == "gpt-3.5-turbo-0125"
+        assert create_fine_tuning_response.id is not None
+        assert create_fine_tuning_response.model == "gpt-3.5-turbo-0125"
 
-    # list fine tuning jobs
-    print("listing ft jobs")
-    ft_jobs = litellm.list_fine_tuning_jobs(limit=2)
-    print("response from litellm.list_fine_tuning_jobs=", ft_jobs)
+        # list fine tuning jobs
+        print("listing ft jobs")
+        ft_jobs = litellm.list_fine_tuning_jobs(limit=2)
+        print("response from litellm.list_fine_tuning_jobs=", ft_jobs)
 
-    assert len(list(ft_jobs)) > 0
+        assert len(list(ft_jobs)) > 0
 
-    # delete file
+        # delete file
 
-    litellm.file_delete(
-        file_id=file_obj.id,
-    )
+        litellm.file_delete(
+            file_id=file_obj.id,
+        )
 
-    # cancel ft job
-    response = litellm.cancel_fine_tuning_job(
-        fine_tuning_job_id=create_fine_tuning_response.id,
-    )
+        # cancel ft job
+        response = litellm.cancel_fine_tuning_job(
+            fine_tuning_job_id=create_fine_tuning_response.id,
+        )
 
-    print("response from litellm.cancel_fine_tuning_job=", response)
+        print("response from litellm.cancel_fine_tuning_job=", response)
 
-    assert response.status == "cancelled"
-    assert response.id == create_fine_tuning_response.id
-    pass
+        assert response.status == "cancelled"
+        assert response.id == create_fine_tuning_response.id
+        pass
+    except openai.RateLimitError:
+        pass
+    except Exception as e:
+        pytest.fail(f"Error occurred: {e}")
 
 
 @pytest.mark.asyncio
 async def test_create_fine_tune_jobs_async():
-    verbose_logger.setLevel(logging.DEBUG)
-    file_name = "openai_batch_completions.jsonl"
-    _current_dir = os.path.dirname(os.path.abspath(__file__))
-    file_path = os.path.join(_current_dir, file_name)
+    try:
+        verbose_logger.setLevel(logging.DEBUG)
+        file_name = "openai_batch_completions.jsonl"
+        _current_dir = os.path.dirname(os.path.abspath(__file__))
+        file_path = os.path.join(_current_dir, file_name)
 
-    file_obj = await litellm.acreate_file(
-        file=open(file_path, "rb"),
-        purpose="fine-tune",
-        custom_llm_provider="openai",
-    )
-    print("Response from creating file=", file_obj)
+        file_obj = await litellm.acreate_file(
+            file=open(file_path, "rb"),
+            purpose="fine-tune",
+            custom_llm_provider="openai",
+        )
+        print("Response from creating file=", file_obj)
 
-    create_fine_tuning_response = await litellm.acreate_fine_tuning_job(
-        model="gpt-3.5-turbo-0125",
-        training_file=file_obj.id,
-    )
+        create_fine_tuning_response = await litellm.acreate_fine_tuning_job(
+            model="gpt-3.5-turbo-0125",
+            training_file=file_obj.id,
+        )
 
-    print("response from litellm.create_fine_tuning_job=", create_fine_tuning_response)
+        print(
+            "response from litellm.create_fine_tuning_job=", create_fine_tuning_response
+        )
 
-    assert create_fine_tuning_response.id is not None
-    assert create_fine_tuning_response.model == "gpt-3.5-turbo-0125"
+        assert create_fine_tuning_response.id is not None
+        assert create_fine_tuning_response.model == "gpt-3.5-turbo-0125"
 
-    # list fine tuning jobs
-    print("listing ft jobs")
-    ft_jobs = await litellm.alist_fine_tuning_jobs(limit=2)
-    print("response from litellm.list_fine_tuning_jobs=", ft_jobs)
-    assert len(list(ft_jobs)) > 0
+        # list fine tuning jobs
+        print("listing ft jobs")
+        ft_jobs = await litellm.alist_fine_tuning_jobs(limit=2)
+        print("response from litellm.list_fine_tuning_jobs=", ft_jobs)
+        assert len(list(ft_jobs)) > 0
 
-    # delete file
+        # delete file
 
-    await litellm.afile_delete(
-        file_id=file_obj.id,
-    )
+        await litellm.afile_delete(
+            file_id=file_obj.id,
+        )
 
-    # cancel ft job
-    response = await litellm.acancel_fine_tuning_job(
-        fine_tuning_job_id=create_fine_tuning_response.id,
-    )
+        # cancel ft job
+        response = await litellm.acancel_fine_tuning_job(
+            fine_tuning_job_id=create_fine_tuning_response.id,
+        )
 
-    print("response from litellm.cancel_fine_tuning_job=", response)
+        print("response from litellm.cancel_fine_tuning_job=", response)
 
-    assert response.status == "cancelled"
-    assert response.id == create_fine_tuning_response.id
+        assert response.status == "cancelled"
+        assert response.id == create_fine_tuning_response.id
+    except openai.RateLimitError:
+        pass
+    except Exception as e:
+        pytest.fail(f"Error occurred: {e}")
     pass