sd15_prodigy_temp

accelerate launch --num_cpu_threads_per_process=2 "./train_network.py" \
  --enable_bucket \
  --min_bucket_reso=256 \
  --max_bucket_reso=2048 \
  --pretrained_model_name_or_path="/workspace/sd_models/v1-5-pruned-emaonly.safetensors" \
  --train_data_dir="/workspace/ksk_sd_15_prodigy/img" \
  --resolution="800,800" \
  --output_dir="/workspace/ksk_sd_15_prodigy/model_03" \
  --logging_dir="/workspace/ksk_sd_15_prodigy/log" \
  --network_alpha="256" \
  --save_model_as=safetensors \
  --network_module=networks.lora \
  --text_encoder_lr=1.0 \
  --unet_lr=1.0 \
  --network_dim=256 \
  --output_name="runpod_prodigy_sd_15_03" \
  --lr_scheduler_num_cycles="30" \
  --no_half_vae \
  --learning_rate="1.0" \
  --lr_scheduler="cosine_with_restarts" \
  --train_batch_size="6" \
  --max_train_steps="21850" \
  --save_every_n_epochs="1" \
  --mixed_precision="bf16" \
  --save_precision="bf16" \
  --seed="1337" \
  --caption_extension=".txt" \
  --cache_latents \
  --cache_latents_to_disk \
  --optimizer_type="Prodigy" \
  --optimizer_args decouple=True weight_decay=0.7 d_coef=2 use_bias_correction=True betas=0.9,0.99 \
  --max_data_loader_n_workers="0" \
  --max_token_length=225 \
  --keep_tokens="2" \
  --bucket_reso_steps=64 \
  --min_snr_gamma=5 \
  --shuffle_caption \
  --xformers \
  --bucket_no_upscale \
  --noise_offset=0.1 \
  --lr_scheduler_type "CosineAnnealingLR" \
  --lr_scheduler_args "T_max=30" \
  --log_with wandb \
  --wandb_api_key="YOUR_WANDB_API_KEY_HERE" \
  --sample_sampler=dpm_2 \
  --sample_prompts="/workspace/ksk_sd_15_prodigy/model_03/sample/prompt.txt" \
  --sample_every_n_epochs="1"