diff --git a/sdxl_train_control_net_lllite.py b/sdxl_train_control_net_lllite.py
index 0df61e84..8e975252 100644
--- a/sdxl_train_control_net_lllite.py
+++ b/sdxl_train_control_net_lllite.py
@@ -350,8 +350,7 @@ def train(args):
             "lllite_control_net_train" if args.log_tracker_name is None else args.log_tracker_name, init_kwargs=init_kwargs
         )
 
-    loss_list = []
-    loss_total = 0.0
+    loss_recorder = train_util.LossRecorder()
     del train_dataset_group
 
     # function for saving/removing
@@ -500,14 +499,9 @@ def train(args):
                             remove_model(remove_ckpt_name)
 
             current_loss = loss.detach().item()
-            if epoch == 0:
-                loss_list.append(current_loss)
-            else:
-                loss_total -= loss_list[step]
-                loss_list[step] = current_loss
-            loss_total += current_loss
-            avr_loss = loss_total / len(loss_list)
-            logs = {"loss": avr_loss}  # , "lr": lr_scheduler.get_last_lr()[0]}
+            loss_recorder.add(epoch=epoch, step=step, loss=current_loss)
+            avr_loss: float = loss_recorder.moving_average
+            logs = {"avr_loss": avr_loss}  # , "lr": lr_scheduler.get_last_lr()[0]}
             progress_bar.set_postfix(**logs)
 
             if args.logging_dir is not None:
@@ -518,7 +512,7 @@ def train(args):
                 break
 
         if args.logging_dir is not None:
-            logs = {"loss/epoch": loss_total / len(loss_list)}
+            logs = {"loss/epoch": loss_recorder.moving_average}
             accelerator.log(logs, step=epoch + 1)
 
         accelerator.wait_for_everyone()
diff --git a/sdxl_train_control_net_lllite_old.py b/sdxl_train_control_net_lllite_old.py
index 79920a97..066aca59 100644
--- a/sdxl_train_control_net_lllite_old.py
+++ b/sdxl_train_control_net_lllite_old.py
@@ -323,8 +323,7 @@ def train(args):
             "lllite_control_net_train" if args.log_tracker_name is None else args.log_tracker_name, init_kwargs=init_kwargs
         )
 
-    loss_list = []
-    loss_total = 0.0
+    loss_recorder = train_util.LossRecorder()
     del train_dataset_group
 
     # function for saving/removing
@@ -470,14 +469,9 @@ def train(args):
                             remove_model(remove_ckpt_name)
 
             current_loss = loss.detach().item()
-            if epoch == 0:
-                loss_list.append(current_loss)
-            else:
-                loss_total -= loss_list[step]
-                loss_list[step] = current_loss
-            loss_total += current_loss
-            avr_loss = loss_total / len(loss_list)
-            logs = {"loss": avr_loss}  # , "lr": lr_scheduler.get_last_lr()[0]}
+            loss_recorder.add(epoch=epoch, step=step, loss=current_loss)
+            avr_loss: float = loss_recorder.moving_average
+            logs = {"avr_loss": avr_loss}  # , "lr": lr_scheduler.get_last_lr()[0]}
             progress_bar.set_postfix(**logs)
 
             if args.logging_dir is not None:
@@ -488,7 +482,7 @@ def train(args):
                 break
 
         if args.logging_dir is not None:
-            logs = {"loss/epoch": loss_total / len(loss_list)}
+            logs = {"loss/epoch": loss_recorder.moving_average}
             accelerator.log(logs, step=epoch + 1)
 
         accelerator.wait_for_everyone()
diff --git a/train_controlnet.py b/train_controlnet.py
index 5bc8d399..bbd915cb 100644
--- a/train_controlnet.py
+++ b/train_controlnet.py
@@ -337,8 +337,7 @@ def train(args):
             init_kwargs = toml.load(args.log_tracker_config)
         accelerator.init_trackers("controlnet_train" if args.log_tracker_name is None else args.log_tracker_name, init_kwargs=init_kwargs)
 
-    loss_list = []
-    loss_total = 0.0
+    loss_recorder = train_util.LossRecorder()
     del train_dataset_group
 
     # function for saving/removing
@@ -500,14 +499,9 @@ def train(args):
                             remove_model(remove_ckpt_name)
 
             current_loss = loss.detach().item()
-            if epoch == 0:
-                loss_list.append(current_loss)
-            else:
-                loss_total -= loss_list[step]
-                loss_list[step] = current_loss
-            loss_total += current_loss
-            avr_loss = loss_total / len(loss_list)
-            logs = {"loss": avr_loss}  # , "lr": lr_scheduler.get_last_lr()[0]}
+            loss_recorder.add(epoch=epoch, step=step, loss=current_loss)
+            avr_loss: float = loss_recorder.moving_average
+            logs = {"avr_loss": avr_loss}  # , "lr": lr_scheduler.get_last_lr()[0]}
             progress_bar.set_postfix(**logs)
 
             if args.logging_dir is not None:
@@ -518,7 +512,7 @@ def train(args):
                 break
 
         if args.logging_dir is not None:
-            logs = {"loss/epoch": loss_total / len(loss_list)}
+            logs = {"loss/epoch": loss_recorder.moving_average}
             accelerator.log(logs, step=epoch + 1)
 
         accelerator.wait_for_everyone()