diff --git a/train.py b/train.py
index a9a98c4b..98424ed6 100644
--- a/train.py
+++ b/train.py
@@ -170,7 +170,7 @@ def train(cfg,
     t0 = time.time()
     for epoch in range(start_epoch, epochs):
         model.train()
-        print(('\n%8s' + '%10s' * 8) %
+        print(('\n' + '%10s' * 9) %
               ('Epoch', 'gpu_mem', 'GIoU/xy', 'wh', 'obj', 'cls', 'total', 'targets', 'img_size'))
 
         # Update scheduler
@@ -236,7 +236,8 @@ def train(cfg,
             # Print batch results
             mloss = (mloss * i + loss_items) / (i + 1)  # update mean losses
             mem = torch.cuda.memory_cached() / 1E9 if torch.cuda.is_available() else 0  # (GB)
-            s = ('%8s' + '%10.3g' * 8) % ('%g/%g' % (epoch, epochs - 1), mem, *mloss, len(targets), img_size)
+            s = ('%10s' * 2 + '%10.3g' * 7) % (
+                '%g/%g' % (epoch, epochs - 1), '%.3gG' % mem, *mloss, len(targets), img_size)
             pbar.set_description(s)  # print(s)
 
         # Calculate mAP (always test final epoch, skip first 5 if opt.nosave)