diff --git a/train_native.py b/train_native.py
index 79418f4d..d8ff94f0 100644
--- a/train_native.py
+++ b/train_native.py
@@ -1258,6 +1258,7 @@ class NativeTrainer:
                 minimum_metadata[key] = metadata[key]
 
         # calculate steps to skip when resuming or starting from a specific step
+        # this is not used for logging and file save. use global_step instead.
         initial_step = 0
         if args.initial_epoch is not None or args.initial_step is not None:
             # if initial_epoch or initial_step is specified, steps_from_state is ignored even when resuming
@@ -1305,6 +1306,7 @@ class NativeTrainer:
                 epoch_to_start = initial_step // math.ceil(len(train_dataloader) / args.gradient_accumulation_steps)
                 initial_step = 0  # do not skip
 
+        # This variable is used for logging and file save: 
         global_step = 0
 
         noise_scheduler = self.get_noise_scheduler(args, accelerator.device)
@@ -1343,7 +1345,8 @@ class NativeTrainer:
             for skip_epoch in range(epoch_to_start):  # skip epochs
                 logger.info(f"skipping epoch {skip_epoch+1} because initial_step (multiplied) is {initial_step}")
                 initial_step -= len(train_dataloader)
-            global_step = initial_step
+            # I have found that the log is screwed up. This should be divided back.
+            global_step = int(initial_step / args.gradient_accumulation_steps)
 
         # log device and dtype for each model
         logger.info(f"unet dtype: {unet_weight_dtype}, device: {unet.device}")