Merge pull request #2829 from iamrohitanshu/sd3-flux.1

Update 3 files in kohya_gui folder
bmaltais · Sep 17, 2024 · 0ba8ab6 · 0ba8ab6
2 parents e696df2 + b8c4de1
commit 0ba8ab6
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Showing 3 changed files with 6 additions and 6 deletions.
diff --git a/kohya_gui/dreambooth_gui.py b/kohya_gui/dreambooth_gui.py
@@ -763,11 +763,11 @@ def train_model(
             reg_factor = 1
         else:
             log.warning(
-                "Regularisation images are used... Will double the number of steps required..."
+                "Regularization images are used... Will double the number of steps required..."
             )
             reg_factor = 2
 
-        log.info(f"Regulatization factor: {reg_factor}")
+        log.info(f"Regularization factor: {reg_factor}")
 
         if max_train_steps == 0:
             # calculate max_train_steps

diff --git a/kohya_gui/lora_gui.py b/kohya_gui/lora_gui.py
@@ -1052,11 +1052,11 @@ def train_model(
             reg_factor = 1
         else:
             log.warning(
-                "Regularisation images are used... Will double the number of steps required..."
+                "Regularization images are used... Will double the number of steps required..."
             )
             reg_factor = 2
 
-        log.info(f"Regulatization factor: {reg_factor}")
+        log.info(f"Regularization factor: {reg_factor}")
 
         if max_train_steps == 0:
             # calculate max_train_steps

diff --git a/kohya_gui/textual_inversion_gui.py b/kohya_gui/textual_inversion_gui.py
@@ -648,11 +648,11 @@ def train_model(
             reg_factor = 1
         else:
             log.warning(
-                "Regularisation images are used... Will double the number of steps required..."
+                "Regularization images are used... Will double the number of steps required..."
             )
             reg_factor = 2
 
-        log.info(f"Regulatization factor: {reg_factor}")
+        log.info(f"Regularization factor: {reg_factor}")
 
         if max_train_steps == 0:
             # calculate max_train_steps