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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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Loading checkpoint shards: 0%| | 0/2 [00:00<?, ?it/s] Loading checkpoint shards: 50%|█████ | 1/2 [00:00<00:00, 4.27it/s] Loading checkpoint shards: 100%|██████████| 2/2 [00:00<00:00, 5.14it/s] Loading checkpoint shards: 100%|██████████| 2/2 [00:00<00:00, 4.98it/s]
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
Bucket sizes for /workspace/ai-toolkit/images:
448x576: 13 files
1 buckets made
Caching latents for /workspace/ai-toolkit/images
- Saving latents to disk
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Dataset: /workspace/ai-toolkit/images
- Preprocessing image dimensions
0%| | 0/13 [00:00<?, ?it/s] 100%|██████████| 13/13 [00:00<00:00, 47249.53it/s]
- Found 13 images
Bucket sizes for /workspace/ai-toolkit/images:
640x832: 13 files
1 buckets made
Caching latents for /workspace/ai-toolkit/images
- Saving latents to disk
Caching latents to disk: 0%| | 0/13 [00:00<?, ?it/s] Caching latents to disk: 8%|▊ | 1/13 [00:00<00:02, 5.59it/s] Caching latents to disk: 15%|█▌ | 2/13 [00:00<00:01, 5.91it/s] Caching latents to disk: 23%|██▎ | 3/13 [00:00<00:01, 6.68it/s] Caching latents to disk: 31%|███ | 4/13 [00:00<00:01, 7.35it/s] Caching latents to disk: 38%|███▊ | 5/13 [00:00<00:01, 7.74it/s] Caching latents to disk: 46%|████▌ | 6/13 [00:00<00:00, 7.96it/s] Caching latents to disk: 54%|█████▍ | 7/13 [00:00<00:00, 8.00it/s] Caching latents to disk: 62%|██████▏ | 8/13 [00:01<00:00, 8.19it/s] Caching latents to disk: 69%|██████▉ | 9/13 [00:01<00:00, 8.28it/s] Caching latents to disk: 77%|███████▋ | 10/13 [00:01<00:00, 8.41it/s] Caching latents to disk: 85%|████████▍ | 11/13 [00:01<00:00, 8.20it/s] Caching latents to disk: 92%|█████████▏| 12/13 [00:01<00:00, 8.26it/s] Caching latents to disk: 100%|██████████| 13/13 [00:01<00:00, 8.34it/s] Caching latents to disk: 100%|██████████| 13/13 [00:01<00:00, 7.85it/s]
Dataset: /workspace/ai-toolkit/images
- Preprocessing image dimensions
0%| | 0/13 [00:00<?, ?it/s] 100%|██████████| 13/13 [00:00<00:00, 25940.03it/s]
- Found 13 images
Bucket sizes for /workspace/ai-toolkit/images:
832x1152: 13 files
1 buckets made
Caching latents for /workspace/ai-toolkit/images
- Saving latents to disk
Caching latents to disk: 0%| | 0/13 [00:00<?, ?it/s] Caching latents to disk: 8%|▊ | 1/13 [00:00<00:02, 5.06it/s] Caching latents to disk: 15%|█▌ | 2/13 [00:00<00:02, 5.44it/s] Caching latents to disk: 23%|██▎ | 3/13 [00:00<00:01, 5.60it/s] Caching latents to disk: 31%|███ | 4/13 [00:00<00:01, 5.42it/s] Caching latents to disk: 38%|███▊ | 5/13 [00:00<00:01, 5.55it/s] Caching latents to disk: 46%|████▌ | 6/13 [00:01<00:01, 5.62it/s] Caching latents to disk: 54%|█████▍ | 7/13 [00:01<00:01, 5.67it/s] Caching latents to disk: 62%|██████▏ | 8/13 [00:01<00:00, 5.68it/s] Caching latents to disk: 69%|██████▉ | 9/13 [00:01<00:00, 5.66it/s] Caching latents to disk: 77%|███████▋ | 10/13 [00:01<00:00, 5.49it/s] Caching latents to disk: 85%|████████▍ | 11/13 [00:01<00:00, 5.38it/s] Caching latents to disk: 92%|█████████▏| 12/13 [00:02<00:00, 5.15it/s] Caching latents to disk: 100%|██████████| 13/13 [00:02<00:00, 5.10it/s] Caching latents to disk: 100%|██████████| 13/13 [00:02<00:00, 5.39it/s]
Generating baseline samples before training
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[34:10<3:21:36, 4.82s/it, lr: 1.0e-04 loss: 4.476e-01] my_first_flux_lora_v1: 16%|█▋ | 492/3000 [34:13<3:21:36, 4.82s/it, lr: 1.0e-04 loss: 6.253e-01] my_first_flux_lora_v1: 16%|█▋ | 493/3000 [34:13<2:53:31, 4.15s/it, lr: 1.0e-04 loss: 6.253e-01] my_first_flux_lora_v1: 16%|█▋ | 493/3000 [34:19<2:53:31, 4.15s/it, lr: 1.0e-04 loss: 5.220e-01] my_first_flux_lora_v1: 16%|█▋ | 494/3000 [34:19<3:16:16, 4.70s/it, lr: 1.0e-04 loss: 5.220e-01] my_first_flux_lora_v1: 16%|█▋ | 494/3000 [34:23<3:16:16, 4.70s/it, lr: 1.0e-04 loss: 2.928e-01] my_first_flux_lora_v1: 16%|█▋ | 495/3000 [34:23<3:06:00, 4.46s/it, lr: 1.0e-04 loss: 2.928e-01] my_first_flux_lora_v1: 16%|█▋ | 495/3000 [34:26<3:06:00, 4.46s/it, lr: 1.0e-04 loss: 3.107e-01] my_first_flux_lora_v1: 17%|█▋ | 496/3000 [34:26<2:58:42, 4.28s/it, lr: 1.0e-04 loss: 3.107e-01] my_first_flux_lora_v1: 17%|█▋ | 496/3000 [34:29<2:58:42, 4.28s/it, lr: 1.0e-04 loss: 3.036e-01] my_first_flux_lora_v1: 17%|█▋ | 497/3000 [34:29<2:37:19, 3.77s/it, lr: 1.0e-04 loss: 3.036e-01] my_first_flux_lora_v1: 17%|█▋ | 497/3000 [34:35<2:37:19, 3.77s/it, lr: 1.0e-04 loss: 4.469e-01] my_first_flux_lora_v1: 17%|█▋ | 498/3000 [34:35<3:04:44, 4.43s/it, lr: 1.0e-04 loss: 4.469e-01] my_first_flux_lora_v1: 17%|█▋ | 498/3000 [34:41<3:04:44, 4.43s/it, lr: 1.0e-04 loss: 4.936e-01] my_first_flux_lora_v1: 17%|█▋ | 499/3000 [34:41<3:24:01, 4.89s/it, lr: 1.0e-04 loss: 4.936e-01] my_first_flux_lora_v1: 17%|█▋ | 499/3000 [34:47<3:24:01, 4.89s/it, lr: 1.0e-04 loss: 3.838e-01]
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Generating Images: 90%|█████████ | 9/10 [05:48<00:38, 38.66s/it]
Generating Images: 100%|██████████| 10/10 [06:26<00:00, 38.65s/it]
 my_first_flux_lora_v1: 17%|█▋ | 499/3000 [34:47<3:24:01, 4.89s/it, lr: 1.0e-04 loss: 3.838e-01] my_first_flux_lora_v1: 17%|█▋ | 499/3000 [34:58<3:24:01, 4.89s/it, lr: 1.0e-04 loss: 3.838e-01] my_first_flux_lora_v1: 17%|█▋ | 500/3000 [34:51<3:23:56, 4.89s/it, lr: 1.0e-04 loss: 5.139e-01] my_first_flux_lora_v1: 17%|█▋ | 501/3000 [34:51<2:27:03, 3.53s/it, lr: 1.0e-04 loss: 5.139e-01] my_first_flux_lora_v1: 17%|█▋ | 501/3000 [34:53<2:27:03, 3.53s/it, lr: 1.0e-04 loss: 2.890e-01] my_first_flux_lora_v1: 17%|█▋ | 502/3000 [34:53<2:16:44, 3.28s/it, lr: 1.0e-04 loss: 2.890e-01] my_first_flux_lora_v1: 17%|█▋ | 502/3000 [34:59<2:16:44, 3.28s/it, lr: 1.0e-04 loss: 2.619e-01] my_first_flux_lora_v1: 17%|█▋ | 503/3000 [34:59<2:45:59, 3.99s/it, lr: 1.0e-04 loss: 2.619e-01] my_first_flux_lora_v1: 17%|█▋ | 503/3000 [35:03<2:45:59, 3.99s/it, lr: 1.0e-04 loss: 5.491e-01] my_first_flux_lora_v1: 17%|█▋ | 504/3000 [35:03<2:44:45, 3.96s/it, lr: 1.0e-04 loss: 5.491e-01] my_first_flux_lora_v1: 17%|█▋ | 504/3000 [35:06<2:44:45, 3.96s/it, lr: 1.0e-04 loss: 5.654e-01] my_first_flux_lora_v1: 17%|█▋ | 505/3000 [35:06<2:29:18, 3.59s/it, lr: 1.0e-04 loss: 5.654e-01] my_first_flux_lora_v1: 17%|█▋ | 505/3000 [35:08<2:29:18, 3.59s/it, lr: 1.0e-04 loss: 6.048e-01] my_first_flux_lora_v1: 17%|█▋ | 506/3000 [35:08<2:16:37, 3.29s/it, lr: 1.0e-04 loss: 6.048e-01]Saving at step 500
Saved to output/my_first_flux_lora_v1/optimizer.pt
my_first_flux_lora_v1: 17%|█▋ | 506/3000 [35:13<2:16:37, 3.29s/it, lr: 1.0e-04 loss: 3.626e-01] my_first_flux_lora_v1: 17%|█▋ | 507/3000 [35:13<2:24:01, 3.47s/it, lr: 1.0e-04 loss: 3.626e-01] my_first_flux_lora_v1: 17%|█▋ | 507/3000 [35:19<2:24:01, 3.47s/it, lr: 1.0e-04 loss: 3.987e-01] my_first_flux_lora_v1: 17%|█▋ | 508/3000 [35:19<2:54:13, 4.19s/it, lr: 1.0e-04 loss: 3.987e-01] my_first_flux_lora_v1: 17%|█▋ | 508/3000 [35:23<2:54:13, 4.19s/it, lr: 1.0e-04 loss: 4.219e-01] my_first_flux_lora_v1: 17%|█▋ | 509/3000 [35:23<2:51:57, 4.14s/it, lr: 1.0e-04 loss: 4.219e-01] my_first_flux_lora_v1: 17%|█▋ | 509/3000 [35:25<2:51:57, 4.14s/it, lr: 1.0e-04 loss: 6.116e-01] my_first_flux_lora_v1: 17%|█▋ | 510/3000 [35:25<2:32:04, 3.66s/it, lr: 1.0e-04 loss: 6.116e-01] my_first_flux_lora_v1: 17%|█▋ | 510/3000 [35:31<2:32:04, 3.66s/it, lr: 1.0e-04 loss: 5.401e-01] my_first_flux_lora_v1: 17%|█▋ | 511/3000 [35:31<3:00:21, 4.35s/it, lr: 1.0e-04 loss: 5.401e-01] my_first_flux_lora_v1: 17%|█▋ | 511/3000 [35:34<3:00:21, 4.35s/it, lr: 1.0e-04 loss: 3.505e-01] my_first_flux_lora_v1: 17%|█▋ | 512/3000 [35:34<2:38:01, 3.81s/it, lr: 1.0e-04 loss: 3.505e-01] my_first_flux_lora_v1: 17%|█▋ | 512/3000 [35:38<2:38:01, 3.81s/it, lr: 1.0e-04 loss: 2.874e-01] my_first_flux_lora_v1: 17%|█▋ | 513/3000 [35:38<2:39:50, 3.86s/it, lr: 1.0e-04 loss: 2.874e-01] my_first_flux_lora_v1: 17%|█▋ | 513/3000 [35:40<2:39:50, 3.86s/it, lr: 1.0e-04 loss: 4.320e-01] my_first_flux_lora_v1: 17%|█▋ | 514/3000 [35:40<2:23:18, 3.46s/it, lr: 1.0e-04 loss: 4.320e-01] my_first_flux_lora_v1: 17%|█▋ | 514/3000 [35:43<2:23:18, 3.46s/it, lr: 1.0e-04 loss: 5.364e-01] my_first_flux_lora_v1: 17%|█▋ | 515/3000 [35:43<2:11:41, 3.18s/it, lr: 1.0e-04 loss: 5.364e-01] my_first_flux_lora_v1: 17%|█▋ | 515/3000 [35:47<2:11:41, 3.18s/it, lr: 1.0e-04 loss: 5.349e-01] my_first_flux_lora_v1: 17%|█▋ | 516/3000 [35:47<2:20:23, 3.39s/it, lr: 1.0e-04 loss: 5.349e-01] my_first_flux_lora_v1: 17%|█▋ | 516/3000 [35:49<2:20:23, 3.39s/it, lr: 1.0e-04 loss: 6.199e-01] my_first_flux_lora_v1: 17%|█▋ | 517/3000 [35:49<2:10:46, 3.16s/it, lr: 1.0e-04 loss: 6.199e-01]