anima_train_CivChan.bat

SET VERSION=1
SET DIM=32
SET ALPHA=32
SET LORA_NAME=CivChan_uWu

SET UNET_ONLY=0
SET MAX_EPOCH=10

SET OUTPUT_DIR=E:\AI\Lora\Anima\train
SET DATASET_CONFIG=D:\AI\train_lora\dataset_CivChan.toml

SET LOGGING_DIR=D:\AI\train_lora\log


SET RESUME=1
SET RESUME_EPOCH=4

SET ARGS=


IF %RESUME%==1 (
	setlocal EnableDelayedExpansion
	set "padded=0000000000%RESUME_EPOCH%"
	set "RESUME_EPOCH_FORMATED=!padded:~-6!"
	endlocal
	set ARGS=%ARGS% --resume %OUTPUT_DIR%\%LORA_NAME%-%RESUME_EPOCH_FORMATED%-state
)

IF %UNET_ONLY%==1 (
	echo 1
	SET ARGS=%ARGS% --network_train_unet_only
)


SET FULL_LORA_NAME=%LORA_NAME%_v%VERSION%_n%DIM%-a%ALPHA%



chdir D:\AI\sd-scripts\
call .\venv\Scripts\activate.bat

accelerate.exe launch anima_train_network.py ^
  --dit_path E:\AI\models\Anima-2b\models\anima.safetensors ^
  --vae_path  E:\AI\models\Anima-2b\vae\qwen_image_vae.safetensors ^
  --qwen3_path E:\AI\models\Anima-2b\clip\qwen_3_06b_base.safetensors ^
  --dataset_config %DATASET_CONFIG% ^
  --output_name %FULL_LORA_NAME% ^
  --network_dim %DIM% ^
  --network_alpha %ALPHA% ^
  --clip_skip 2 ^
  --output_dir %OUTPUT_DIR% ^
  --logging_dir %LOGGING_DIR% ^
  --max_train_epochs %MAX_EPOCH% ^
  --log_with="tensorboard" ^
  --network_module networks.lora_anima ^
  --learning_rate 1e-4 ^
  --mixed_precision="bf16"  ^
  --optimizer_type="AdamW8Bit"   ^
  --lr_scheduler="cosine_with_restarts"   ^
  --save_state ^
  --save_state_on_train_end ^
  --save_every_n_epochs=1  ^
  --save_precision="bf16" ^
  --cache_text_encoder_outputs ^
  --cache_latents ^
  --gradient_checkpointing ^
  --train_batch_size=2 ^
  --gradient_accumulation_steps=2 ^
  --blocks_to_swap 10 ^
  --xformers ^
  --seed=42 ^
  %ARGS%

pause