Learning LoRA, trained on 40 headshots with 100 steps, Minimal resolution: 768x768;Sampler: euler_a <pre><code>Total steps: 4000
Train batch size: 4
Gradient accumulation steps: 1.0
Epoch: 1
Regulatization factor: 1
max_train_steps (4000 / 4 / 1.0 * 1 * 1) = 1000
stop_text_encoder_training = 0
lr_warmup_steps = 0
accelerate launch --num_cpu_threads_per_process=2 "train_network.py" --enable_bucket --pretrained_model_name_or_path="models/Stable-diffusion/lifeLikeDiffusion_lifeLikeDiffusionV20.safetensors" --train_data_dir="training\emily deschanel\lora\img" --resolution=768,768 --output_dir="models/Lora/Celebs/Emily Deschanel" --logging_dir="training\emily deschanel\lora\logs" --network_alpha="128" --save_model_as=safetensors --network_module=lycoris.kohya --network_args "conv_dim=1" "conv_alpha=1" "algo=lora" --text_encoder_lr=5e-05 --unet_lr=0.0001 --network_dim=128 --output_name="emily_deschanel_v2" --lr_scheduler_num_cycles="1" --learning_rate="0.0001" --lr_scheduler="constant" --train_batch_size="4" --max_train_steps="1000" --save_every_n_epochs="1" --mixed_precision="bf16" --save_precision="bf16" --seed="2345" --caption_extension=".txt" --cache_latents --optimizer_type="AdamW" --max_data_loader_n_workers="1" --clip_skip=2 --bucket_reso_steps=64 --xformers --bucket_no_upscale</code></pre>

Files with SHA256: 1cfb8786d26d94fb4a13f65909454b34b7cb7a9d332d5e782dbd249d52d3af95