diff --git a/TensorFlow/built-in/cv/image_segmentation/UNet2D_ID0008_for_TensorFlow/utils/parse_results.py b/TensorFlow/built-in/cv/image_segmentation/UNet2D_ID0008_for_TensorFlow/utils/parse_results.py
index 34ec762f4c03737240caf9830ce1ef23000ca8c6..a027d5caa5e634db2ae41cfee9fd9e2b00b718d2 100644
--- a/TensorFlow/built-in/cv/image_segmentation/UNet2D_ID0008_for_TensorFlow/utils/parse_results.py
+++ b/TensorFlow/built-in/cv/image_segmentation/UNet2D_ID0008_for_TensorFlow/utils/parse_results.py
@@ -22,7 +22,7 @@ def process_performance_stats(timestamps, batch_size):
     latency_ms = timestamps_ms.mean()
     std = timestamps_ms.std()
     n = np.sqrt(len(timestamps_ms))
-    throughput_imgps = (1000.0 * batch_size / timestamps_ms).mean()
+    throughput_imgps = (10 * 1000.0 * batch_size / timestamps_ms).mean()
 
     stats = [("Throughput Avg", str(throughput_imgps)),
              ('Latency Avg:', str(latency_ms))]
diff --git a/TensorFlow/built-in/cv/image_segmentation/UNet2D_ID0008_for_TensorFlow/utils/setup.py b/TensorFlow/built-in/cv/image_segmentation/UNet2D_ID0008_for_TensorFlow/utils/setup.py
index 753d05c606dc78eb7709d6d6678957ad6d45e290..8292db7d50f0360cf6817cd01c6698ebdcfffc12 100644
--- a/TensorFlow/built-in/cv/image_segmentation/UNet2D_ID0008_for_TensorFlow/utils/setup.py
+++ b/TensorFlow/built-in/cv/image_segmentation/UNet2D_ID0008_for_TensorFlow/utils/setup.py
@@ -87,7 +87,7 @@ def build_estimator(params, model_dir):
         #save_checkpoints_steps=(params.max_steps // hvd.size()) if hvd.rank() == 0 else None,
         save_checkpoints_steps=params.max_steps,
         precision_mode='allow_fp32_to_fp16',
-        iterations_per_loop=1,
+        iterations_per_loop=10,
         hcom_parallel=True,
         keep_checkpoint_max=1)
         # for npu