ortha / experiments /single-concept /linguini /6931_linguini_ortho.yml
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joy, linguini, raya
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# GENERATE TIME: Sat Jun 15 13:29:45 2024
# CMD:
# train_edlora.py -opt single-concept/train_configs/6931_linguini_ortho.yml
name: 6931_linguini_ortho
manual_seed: 6931
mixed_precision: fp16
gradient_accumulation_steps: 1
datasets:
train:
name: LoraDataset
concept_list: single-concept/data_configs/linguini.json
use_caption: true
use_mask: true
instance_transform:
- type: HumanResizeCropFinalV3
size: 512
crop_p: 0.5
- type: ToTensor
- type: Normalize
mean:
- 0.5
std:
- 0.5
- type: ShuffleCaption
keep_token_num: 1
- type: EnhanceText
enhance_type: human
replace_mapping:
<TOK>: <linguini1> <linguini2>
batch_size_per_gpu: 2
dataset_enlarge_ratio: 500
val_vis:
name: PromptDataset
prompts: single-concept/validation_prompts/characters/test_man.txt
num_samples_per_prompt: 8
latent_size:
- 4
- 64
- 64
replace_mapping:
<TOK>: <linguini1> <linguini2>
batch_size_per_gpu: 4
models:
pretrained_path: nitrosocke/mo-di-diffusion
enable_edlora: true
finetune_cfg:
text_embedding:
enable_tuning: true
lr: 0.001
text_encoder:
enable_tuning: true
lora_cfg:
rank: 5
alpha: 1.0
where: CLIPAttention
lr: 1.0e-05
unet:
enable_tuning: true
lora_cfg:
rank: 5
alpha: 1.0
where: Attention
lr: 0.0001
new_concept_token: <linguini1>+<linguini2>
initializer_token: <rand-0.013>+man
noise_offset: 0.01
attn_reg_weight: 0.01
reg_full_identity: false
use_mask_loss: true
gradient_checkpoint: false
enable_xformers: true
path:
pretrain_network: null
train:
optim_g:
type: AdamW
lr: 0.0
weight_decay: 0.01
betas:
- 0.9
- 0.999
unet_kv_drop_rate: 0
scheduler: linear
emb_norm_threshold: 0.55
val:
val_during_save: false
compose_visualize: false
alpha_list:
- 0
- 0.7
- 1.0
sample:
num_inference_steps: 50
guidance_scale: 7.5
logger:
print_freq: 10
save_checkpoint_freq: 10000.0