diff --git a/litellm/fine_tuning/main.py b/litellm/fine_tuning/main.py
index eace2f64a4..7672ad43a9 100644
--- a/litellm/fine_tuning/main.py
+++ b/litellm/fine_tuning/main.py
@@ -19,12 +19,16 @@ import httpx
 import litellm
 from litellm._logging import verbose_logger
 from litellm.llms.azure.fine_tuning.handler import AzureOpenAIFineTuningAPI
-from litellm.llms.openai.fine_tuning.handler import FineTuningJob, OpenAIFineTuningAPI
+from litellm.llms.openai.fine_tuning.handler import OpenAIFineTuningAPI
 from litellm.llms.vertex_ai.fine_tuning.handler import VertexFineTuningAPI
 from litellm.secret_managers.main import get_secret_str
-from litellm.types.llms.openai import FineTuningJobCreate, Hyperparameters
+from litellm.types.llms.openai import (
+    FineTuningJob,
+    FineTuningJobCreate,
+    Hyperparameters,
+)
 from litellm.types.router import *
-from litellm.utils import supports_httpx_timeout
+from litellm.utils import client, supports_httpx_timeout
 
 ####### ENVIRONMENT VARIABLES ###################
 openai_fine_tuning_apis_instance = OpenAIFineTuningAPI()
@@ -33,6 +37,7 @@ vertex_fine_tuning_apis_instance = VertexFineTuningAPI()
 #################################################
 
 
+@client
 async def acreate_fine_tuning_job(
     model: str,
     training_file: str,
@@ -86,6 +91,7 @@ async def acreate_fine_tuning_job(
         raise e
 
 
+@client
 def create_fine_tuning_job(
     model: str,
     training_file: str,
diff --git a/litellm/litellm_core_utils/litellm_logging.py b/litellm/litellm_core_utils/litellm_logging.py
index ee769bb7eb..0736aa2da5 100644
--- a/litellm/litellm_core_utils/litellm_logging.py
+++ b/litellm/litellm_core_utils/litellm_logging.py
@@ -37,6 +37,7 @@ from litellm.litellm_core_utils.redact_messages import (
 from litellm.types.llms.openai import (
     AllMessageValues,
     Batch,
+    FineTuningJob,
     HttpxBinaryResponseContent,
 )
 from litellm.types.rerank import RerankResponse
@@ -760,6 +761,7 @@ class Logging(LiteLLMLoggingBaseClass):
             HttpxBinaryResponseContent,
             RerankResponse,
             Batch,
+            FineTuningJob,
         ],
         cache_hit: Optional[bool] = None,
     ) -> Optional[float]:
@@ -877,6 +879,7 @@ class Logging(LiteLLMLoggingBaseClass):
                     or isinstance(result, HttpxBinaryResponseContent)  # tts
                     or isinstance(result, RerankResponse)
                     or isinstance(result, Batch)
+                    or isinstance(result, FineTuningJob)
                 ):
                     ## RESPONSE COST ##
                     self.model_call_details["response_cost"] = (
diff --git a/litellm/types/llms/openai.py b/litellm/types/llms/openai.py
index e8cda0aae4..b63099f081 100644
--- a/litellm/types/llms/openai.py
+++ b/litellm/types/llms/openai.py
@@ -30,6 +30,7 @@ from openai.types.chat.chat_completion_prediction_content_param import (
     ChatCompletionPredictionContentParam,
 )
 from openai.types.embedding import Embedding as OpenAIEmbedding
+from openai.types.fine_tuning.fine_tuning_job import FineTuningJob
 from pydantic import BaseModel, Field
 from typing_extensions import Dict, Required, TypedDict, override
 
diff --git a/litellm/utils.py b/litellm/utils.py
index e7d7f97ee0..72f5f80933 100644
--- a/litellm/utils.py
+++ b/litellm/utils.py
@@ -1234,6 +1234,7 @@ def _is_async_request(
         or kwargs.get("arerank", False) is True
         or kwargs.get("_arealtime", False) is True
         or kwargs.get("acreate_batch", False) is True
+        or kwargs.get("acreate_fine_tuning_job", False) is True
         or is_pass_through is True
     ):
         return True
diff --git a/tests/batches_tests/test_fine_tuning_api.py b/tests/batches_tests/test_fine_tuning_api.py
index 893849b3b5..cc53f599fa 100644
--- a/tests/batches_tests/test_fine_tuning_api.py
+++ b/tests/batches_tests/test_fine_tuning_api.py
@@ -1,7 +1,7 @@
 import os
 import sys
 import traceback
-
+import json
 import pytest
 
 sys.path.insert(
@@ -14,7 +14,7 @@ import litellm
 litellm.num_retries = 0
 import asyncio
 import logging
-
+from typing import Optional
 import openai
 from test_openai_batches_and_files import load_vertex_ai_credentials
 
@@ -24,10 +24,27 @@ from litellm.llms.vertex_ai.fine_tuning.handler import (
     FineTuningJobCreate,
     VertexFineTuningAPI,
 )
+from litellm.integrations.custom_logger import CustomLogger
+from litellm.types.utils import StandardLoggingPayload
 
 vertex_finetune_api = VertexFineTuningAPI()
 
 
+class TestCustomLogger(CustomLogger):
+    def __init__(self):
+        super().__init__()
+        self.standard_logging_object: Optional[StandardLoggingPayload] = None
+
+    async def async_log_success_event(self, kwargs, response_obj, start_time, end_time):
+        print(
+            "Success event logged with kwargs=",
+            kwargs,
+            "and response_obj=",
+            response_obj,
+        )
+        self.standard_logging_object = kwargs["standard_logging_object"]
+
+
 def test_create_fine_tune_job():
     try:
         verbose_logger.setLevel(logging.DEBUG)
@@ -89,6 +106,8 @@ def test_create_fine_tune_job():
 @pytest.mark.asyncio
 async def test_create_fine_tune_jobs_async():
     try:
+        custom_logger = TestCustomLogger()
+        litellm.callbacks = ["datadog", custom_logger]
         verbose_logger.setLevel(logging.DEBUG)
         file_name = "openai_batch_completions.jsonl"
         _current_dir = os.path.dirname(os.path.abspath(__file__))
@@ -113,6 +132,16 @@ async def test_create_fine_tune_jobs_async():
         assert create_fine_tuning_response.id is not None
         assert create_fine_tuning_response.model == "gpt-3.5-turbo-0125"
 
+        await asyncio.sleep(2)
+        _logged_standard_logging_object = custom_logger.standard_logging_object
+        assert _logged_standard_logging_object is not None
+        print(
+            "custom_logger.standard_logging_object=",
+            json.dumps(_logged_standard_logging_object, indent=4),
+        )
+        assert _logged_standard_logging_object["model"] == "gpt-3.5-turbo-0125"
+        assert _logged_standard_logging_object["id"] == create_fine_tuning_response.id
+
         # list fine tuning jobs
         print("listing ft jobs")
         ft_jobs = await litellm.alist_fine_tuning_jobs(limit=2)