VictorMylle/Kohya-ss-sd-scripts
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Allow negative learning rate

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This can be used to train away from a group of images you don't want
As this moves the model away from a point instead of towards it, the change in the model is unbounded
So, don't set it too low. -4e-7 seemed to work well.
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Cauldrath
2024-04-18 23:29:01 -04:00
parent 71e2c91330
commit fc374375de
1 changed files with 3 additions and 3 deletions
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6
sdxl_train.py
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@@ -272,7 +272,7 @@ def train(args):
# 学習を準備する：モデルを適切な状態にする # 学習を準備する：モデルを適切な状態にする
if args.gradient_checkpointing: if args.gradient_checkpointing:
unet.enable_gradient_checkpointing() unet.enable_gradient_checkpointing()
train_unet = args.learning_rate > 0 train_unet = args.learning_rate != 0
train_text_encoder1 = False train_text_encoder1 = False
train_text_encoder2 = False train_text_encoder2 = False
@@ -284,8 +284,8 @@ def train(args):
text_encoder2.gradient_checkpointing_enable() text_encoder2.gradient_checkpointing_enable()
lr_te1 = args.learning_rate_te1 if args.learning_rate_te1 is not None else args.learning_rate # 0 means not train lr_te1 = args.learning_rate_te1 if args.learning_rate_te1 is not None else args.learning_rate # 0 means not train
lr_te2 = args.learning_rate_te2 if args.learning_rate_te2 is not None else args.learning_rate # 0 means not train lr_te2 = args.learning_rate_te2 if args.learning_rate_te2 is not None else args.learning_rate # 0 means not train
train_text_encoder1 = lr_te1 > 0 train_text_encoder1 = lr_te1 != 0
train_text_encoder2 = lr_te2 > 0 train_text_encoder2 = lr_te2 != 0
# caching one text encoder output is not supported # caching one text encoder output is not supported
if not train_text_encoder1: if not train_text_encoder1: