diff --git a/deepmd/pt/train/training.py b/deepmd/pt/train/training.py
index a073b4868a..c5dbdfd9dd 100644
--- a/deepmd/pt/train/training.py
+++ b/deepmd/pt/train/training.py
@@ -1147,7 +1147,7 @@ def log_loss_valid(_task_key="Default"):
                 log.info(
                     f"The profiling trace has been saved under {self.tensorboard_log_dir}"
                 )
-            if self.profiling:
+            if not self.enable_profiler and self.profiling:
                 prof.export_chrome_trace(self.profiling_file)
                 log.info(
                     f"The profiling trace has been saved to: {self.profiling_file}"
diff --git a/deepmd/utils/argcheck.py b/deepmd/utils/argcheck.py
index e4c15ebd21..e446674db7 100644
--- a/deepmd/utils/argcheck.py
+++ b/deepmd/utils/argcheck.py
@@ -3140,7 +3140,7 @@ def training_args(
     doc_disp_avg = (
         "Display the average loss over the display interval for training sets."
     )
-    doc_profiling = "Export the profiling results to the Chrome JSON file for performance analysis, driven by the legacy TensorFlow profiling API or PyTorch Profiler. The output file will be saved to `profiling_file`."
+    doc_profiling = "Export the profiling results to the Chrome JSON file for performance analysis, driven by the legacy TensorFlow profiling API or PyTorch Profiler. The output file will be saved to `profiling_file`. In the PyTorch backend, when enable_profiler is True, this option is ignored, since the profiling results will be saved to the TensorBoard log."
     doc_profiling_file = "Output file for profiling."
     doc_enable_profiler = "Export the profiling results to the TensorBoard log for performance analysis, driven by TensorFlow Profiler (available in TensorFlow 2.3) or PyTorch Profiler. The log will be saved to `tensorboard_log_dir`."
     doc_tensorboard = "Enable tensorboard"