scripts/train_ddpo_pairs_svd.sh
#!/bin/bash
source .venv/bin/activate
which python
python -V

nvidia-smi

export WANDB_MODE="offline"

echo "Started: $(date)"
accelerate launch \
  train_ddpo_svd.py \
  --base_model stabilityai/stable-diffusion-2-base \
  --pretrained_model_name_or_path experiments/svddiff/00008-ad9b-dog6_SVDDiff/checkpoint-1600 \
  --dataset_path data/dog/500-p10k-svddiff/0.json \
  --output_dir experiments/svddiff_ddpo/00001-5с1с-dog6-s500-p10k \
  --beta_dpo 5000 \
  --max_train_steps=1000 \
  --train_batch_size=8 \
  --gradient_accumulation_steps=32 \
  --learning_rate=1e-6 --scale_lr \
  --lr_scheduler="constant_with_warmup" --lr_warmup_steps=200 \
  --checkpointing_steps 100 \
  --dataloader_num_workers=4 \
  --hard_skip_resume \
  --report_to wandb \
  --tracker_project_name persgen \
  --validation_steps 100 \
  --validation_concept "sks dog" \
  --validation_concept_image_dir dreambooth/dataset/dog6 \
  --val_batch_size 64 \
  --svd_scale 1. \
  --logging_dir experiments/svddiff_ddpo/00001-5с1с-dog6-s500-p10k/logs
echo "Finished: $(date)"
