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The cache for model files in Transformers v4.22.0 has been updated. Migrating your old cache. This is a one-time only operation. You can interrupt this and resume the migration later on by calling `transformers.utils.move_cache()`.
Running 1 job
0it [00:00, ?it/s]
0it [00:00, ?it/s]
/usr/local/lib/python3.10/dist-packages/controlnet_aux/mediapipe_face/mediapipe_face_common.py:7: UserWarning: The module 'mediapipe' is not installed. The package will have limited functionality. Please install it using the command: pip install 'mediapipe'
warnings.warn(
/usr/local/lib/python3.10/dist-packages/controlnet_aux/segment_anything/modeling/tiny_vit_sam.py:654: UserWarning: Overwriting tiny_vit_5m_224 in registry with controlnet_aux.segment_anything.modeling.tiny_vit_sam.tiny_vit_5m_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
return register_model(fn_wrapper)
/usr/local/lib/python3.10/dist-packages/controlnet_aux/segment_anything/modeling/tiny_vit_sam.py:654: UserWarning: Overwriting tiny_vit_11m_224 in registry with controlnet_aux.segment_anything.modeling.tiny_vit_sam.tiny_vit_11m_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
return register_model(fn_wrapper)
/usr/local/lib/python3.10/dist-packages/controlnet_aux/segment_anything/modeling/tiny_vit_sam.py:654: UserWarning: Overwriting tiny_vit_21m_224 in registry with controlnet_aux.segment_anything.modeling.tiny_vit_sam.tiny_vit_21m_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
return register_model(fn_wrapper)
/usr/local/lib/python3.10/dist-packages/controlnet_aux/segment_anything/modeling/tiny_vit_sam.py:654: UserWarning: Overwriting tiny_vit_21m_384 in registry with controlnet_aux.segment_anything.modeling.tiny_vit_sam.tiny_vit_21m_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
return register_model(fn_wrapper)
/usr/local/lib/python3.10/dist-packages/controlnet_aux/segment_anything/modeling/tiny_vit_sam.py:654: UserWarning: Overwriting tiny_vit_21m_512 in registry with controlnet_aux.segment_anything.modeling.tiny_vit_sam.tiny_vit_21m_512. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
return register_model(fn_wrapper)
You set `add_prefix_space`. The tokenizer needs to be converted from the slow tokenizers
{
"type": "sd_trainer",
"training_folder": "output",
"device": "cuda:0",
"network": {
"type": "lora",
"linear": 16,
"linear_alpha": 16
},
"save": {
"dtype": "float16",
"save_every": 500,
"max_step_saves_to_keep": 4,
"push_to_hub": false
},
"datasets": [
{
"folder_path": "/workspace/ai-toolkit/images",
"caption_ext": "txt",
"caption_dropout_rate": 0.05,
"shuffle_tokens": false,
"cache_latents_to_disk": true,
"resolution": [
512,
768,
1024
]
}
],
"train": {
"batch_size": 1,
"steps": 3000,
"gradient_accumulation_steps": 1,
"train_unet": true,
"train_text_encoder": false,
"gradient_checkpointing": true,
"noise_scheduler": "flowmatch",
"optimizer": "adamw8bit",
"lr": 0.0001,
"ema_config": {
"use_ema": true,
"ema_decay": 0.99
},
"dtype": "bf16"
},
"model": {
"name_or_path": "black-forest-labs/FLUX.1-dev",
"is_flux": true,
"quantize": true
},
"sample": {
"sampler": "flowmatch",
"sample_every": 500,
"width": 1024,
"height": 1024,
"prompts": [
"woman with red hair, playing chess at the park, bomb going off in the background",
"a woman holding a coffee cup, in a beanie, sitting at a cafe",
"a horse is a DJ at a night club, fish eye lens, smoke machine, lazer lights, holding a martini",
"a man showing off his cool new t shirt at the beach, a shark is jumping out of the water in the background",
"a bear building a log cabin in the snow covered mountains",
"woman playing the guitar, on stage, singing a song, laser lights, punk rocker",
"hipster man with a beard, building a chair, in a wood shop",
"photo of a man, white background, medium shot, modeling clothing, studio lighting, white backdrop",
"a man holding a sign that says, 'this is a sign'",
"a bulldog, in a post apocalyptic world, with a shotgun, in a leather jacket, in a desert, with a motorcycle"
],
"neg": "",
"seed": 42,
"walk_seed": true,
"guidance_scale": 4,
"sample_steps": 20
},
"trigger_word": "c4nt4"
}
Using EMA
#############################################
# Running job: my_first_flux_lora_v1
#############################################
Running 1 process
Loading Flux model
Loading transformer
Quantizing transformer
Loading vae
Loading t5
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Quantizing T5
Loading clip
making pipe
preparing
create LoRA network. base dim (rank): 16, alpha: 16
neuron dropout: p=None, rank dropout: p=None, module dropout: p=None
create LoRA for Text Encoder: 0 modules.
create LoRA for U-Net: 494 modules.
enable LoRA for U-Net
Dataset: /workspace/ai-toolkit/images
- Preprocessing image dimensions
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- Found 13 images
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1 buckets made
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- Found 13 images
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1 buckets made
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Dataset: /workspace/ai-toolkit/images
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- Found 13 images
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1 buckets made
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Saved to output/my_first_flux_lora_v1/optimizer.pt
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my_first_flux_lora_v1: 32%|███▏ | 971/3000 [1:07:29<2:23:26, 4.24s/it, lr: 1.0e-04 loss: 4.163e-01]
my_first_flux_lora_v1: 32%|███▏ | 972/3000 [1:07:29<2:20:24, 4.15s/it, lr: 1.0e-04 loss: 4.163e-01]
my_first_flux_lora_v1: 32%|███▏ | 972/3000 [1:07:33<2:20:24, 4.15s/it, lr: 1.0e-04 loss: 5.283e-01]
my_first_flux_lora_v1: 32%|███▏ | 973/3000 [1:07:33<2:17:41, 4.08s/it, lr: 1.0e-04 loss: 5.283e-01]
my_first_flux_lora_v1: 32%|███▏ | 973/3000 [1:07:39<2:17:41, 4.08s/it, lr: 1.0e-04 loss: 2.650e-01]
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my_first_flux_lora_v1: 32%|███▏ | 974/3000 [1:07:43<2:37:06, 4.65s/it, lr: 1.0e-04 loss: 4.619e-01]
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my_first_flux_lora_v1: 32%|███▎ | 975/3000 [1:07:46<2:29:44, 4.44s/it, lr: 1.0e-04 loss: 3.677e-01]
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my_first_flux_lora_v1: 33%|███▎ | 978/3000 [1:07:54<2:23:35, 4.26s/it, lr: 1.0e-04 loss: 5.319e-01]
my_first_flux_lora_v1: 33%|███▎ | 978/3000 [1:08:01<2:23:35, 4.26s/it, lr: 1.0e-04 loss: 2.713e-01]
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my_first_flux_lora_v1: 33%|███▎ | 979/3000 [1:08:04<2:41:18, 4.79s/it, lr: 1.0e-04 loss: 2.921e-01]
my_first_flux_lora_v1: 33%|███▎ | 980/3000 [1:08:04<2:32:11, 4.52s/it, lr: 1.0e-04 loss: 2.921e-01]
my_first_flux_lora_v1: 33%|███▎ | 980/3000 [1:08:07<2:32:11, 4.52s/it, lr: 1.0e-04 loss: 3.515e-01]
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my_first_flux_lora_v1: 33%|███▎ | 982/3000 [1:08:17<2:32:56, 4.55s/it, lr: 1.0e-04 loss: 5.598e-01]
my_first_flux_lora_v1: 33%|███▎ | 983/3000 [1:08:17<2:26:24, 4.36s/it, lr: 1.0e-04 loss: 5.598e-01]
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my_first_flux_lora_v1: 33%|███▎ | 984/3000 [1:08:19<2:08:03, 3.81s/it, lr: 1.0e-04 loss: 4.900e-01]
my_first_flux_lora_v1: 33%|███▎ | 984/3000 [1:08:25<2:08:03, 3.81s/it, lr: 1.0e-04 loss: 3.245e-01]
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my_first_flux_lora_v1: 33%|███▎ | 985/3000 [1:08:31<2:30:14, 4.47s/it, lr: 1.0e-04 loss: 4.659e-01]
my_first_flux_lora_v1: 33%|███▎ | 986/3000 [1:08:31<2:45:30, 4.93s/it, lr: 1.0e-04 loss: 4.659e-01]
my_first_flux_lora_v1: 33%|███▎ | 986/3000 [1:08:37<2:45:30, 4.93s/it, lr: 1.0e-04 loss: 5.921e-01]
my_first_flux_lora_v1: 33%|███▎ | 987/3000 [1:08:37<2:56:13, 5.25s/it, lr: 1.0e-04 loss: 5.921e-01]
my_first_flux_lora_v1: 33%|███▎ | 987/3000 [1:08:43<2:56:13, 5.25s/it, lr: 1.0e-04 loss: 3.738e-01]
my_first_flux_lora_v1: 33%|███▎ | 988/3000 [1:08:43<3:03:40, 5.48s/it, lr: 1.0e-04 loss: 3.738e-01]
my_first_flux_lora_v1: 33%|███▎ | 988/3000 [1:08:47<3:03:40, 5.48s/it, lr: 1.0e-04 loss: 4.146e-01]
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my_first_flux_lora_v1: 33%|███▎ | 990/3000 [1:08:54<2:23:22, 4.28s/it, lr: 1.0e-04 loss: 3.877e-01]
my_first_flux_lora_v1: 33%|███▎ | 991/3000 [1:08:54<2:19:33, 4.17s/it, lr: 1.0e-04 loss: 3.877e-01]
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my_first_flux_lora_v1: 33%|███▎ | 994/3000 [1:09:07<2:00:24, 3.60s/it, lr: 1.0e-04 loss: 4.154e-01]
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my_first_flux_lora_v1: 33%|███▎ | 995/3000 [1:09:09<1:49:45, 3.28s/it, lr: 1.0e-04 loss: 3.045e-01]
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my_first_flux_lora_v1: 33%|███▎ | 996/3000 [1:09:13<1:42:12, 3.06s/it, lr: 1.0e-04 loss: 5.077e-01]
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my_first_flux_lora_v1: 33%|███▎ | 997/3000 [1:09:16<1:50:35, 3.31s/it, lr: 1.0e-04 loss: 5.339e-01]
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my_first_flux_lora_v1: 33%|███▎ | 998/3000 [1:09:22<1:42:50, 3.08s/it, lr: 1.0e-04 loss: 3.989e-01]
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