CinEro XL - PANDORA | LoCon / LoHa

I changed the training mode (now LoHa) and changed the training parameters in Kohya SS to fix the instability of optimizer. Optimizer also changed/ Now I use Prodigy.

Full settings below:

number of images (including repeats) / 各bucketの画像枚数（繰り返し回数を含む）

bucket 0: resolution (768, 512), count: 816

bucket 1: resolution (768, 896), count: 4

bucket 2: resolution (768, 1024), count: 992

bucket 3: resolution (768, 1152), count: 2170

bucket 4: resolution (896, 768), count: 23

bucket 5: resolution (896, 896), count: 71

bucket 6: resolution (896, 1024), count: 98

bucket 7: resolution (896, 1152), count: 40

bucket 8: resolution (1024, 768), count: 1490

bucket 9: resolution (1024, 896), count: 99

bucket 10: resolution (1024, 1024), count: 802

bucket 11: resolution (1152, 768), count: 763

bucket 12: resolution (1280, 768), count: 540

mean ar error (without repeats): 0.025714800356640224

preparing accelerator

loading model for process 0/1

load StableDiffusion checkpoint: /mnt/SD/.ckpt/SDXL/juggernautXL_version2.safetensors

Using rank adaptation algo: loha

Use Dropout value: 0.0

Create LyCORIS Module

Create LyCORIS Module

create LyCORIS for Text Encoder: 264 modules.

Create LyCORIS Module

create LyCORIS for U-Net: 788 modules.

enable LyCORIS for U-Net

prepare optimizer, data loader etc.

Deprecated: use prepare_optimizer_params(text_encoder_lr, unet_lr, learning_rate) instead of prepare_optimizer_params(text_encoder_lr, unet_lr)

use Prodigy optimizer | {}

override steps. steps for 40 epochs is / 指定エポックまでのステップ数: 63280

enable full bf16 training.

running training / 学習開始

num train images * repeats / 学習画像の数×繰り返し回数: 3954

num reg images / 正則化画像の数: 30064

num batches per epoch / 1epochのバッチ数: 7908

num epochs / epoch数: 40

batch size per device / バッチサイズ: 1

gradient accumulation steps / 勾配を合計するステップ数 = 5

total optimization steps / 学習ステップ数: 63280