37 lines
1.2 KiB
Bash
Executable File
37 lines
1.2 KiB
Bash
Executable File
export MODEL_NAME="models/Diffusion_Transformer/Wan2.1-Fun-V1.1-1.3B-InP"
|
|
export TRAIN_PROMPT_PATH="MovieGenVideoBench_train.txt"
|
|
# Performing validation simultaneously with training will increase time and GPU memory usage.
|
|
export VALIDATION_PROMPT_PATH="MovieGenVideoBench_val.txt"
|
|
# Set 1 for Wan2.1-Fun-14B-InP
|
|
export BACKPROP_NUM_STEPS=5
|
|
|
|
accelerate launch --mixed_precision="bf16" scripts/wan2.1_fun/train_reward_lora.py \
|
|
--config_path="config/wan2.1/wan_civitai.yaml" \
|
|
--pretrained_model_name_or_path=$MODEL_NAME \
|
|
--rank=32 \
|
|
--network_alpha=16 \
|
|
--train_batch_size=1 \
|
|
--gradient_accumulation_steps=1 \
|
|
--max_train_steps=10000 \
|
|
--checkpointing_steps=100 \
|
|
--learning_rate=1e-05 \
|
|
--seed=42 \
|
|
--output_dir="output_dir" \
|
|
--gradient_checkpointing \
|
|
--vae_gradient_checkpointing \
|
|
--mixed_precision="bf16" \
|
|
--adam_weight_decay=3e-2 \
|
|
--adam_epsilon=1e-10 \
|
|
--max_grad_norm=0.3 \
|
|
--low_vram \
|
|
--prompt_path=$TRAIN_PROMPT_PATH \
|
|
--train_sample_height=256 \
|
|
--train_sample_width=256 \
|
|
--num_inference_steps=30 \
|
|
--video_length=81 \
|
|
--num_decoded_latents=1 \
|
|
--reward_fn="HPSReward" \
|
|
--reward_fn_kwargs='{"version": "v2.1"}' \
|
|
--backprop_strategy="tail" \
|
|
--backprop_num_steps=$BACKPROP_NUM_STEPS \
|
|
--backprop |