cloneofsimo/lora-advanced-training 🔢✓❓🖼️📝 → 🖼️
Performance
701.7sTypical run time
3.0KTotal runs
About
LoRA model trainer, advanced version
Example Output
Output
Performance Metrics
701.71s
Prediction Time
907.74s
Total Time
All Input Parameters
{
"seed": 1337,
"device": "cuda:0",
"scale_lr": true,
"lora_rank": 16,
"lora_scale": 1,
"resolution": 512,
"color_jitter": true,
"lr_scheduler": "constant",
"use_template": "object",
"clip_ti_decay": true,
"instance_data": "https://replicate.delivery/pbxt/IFXAgZ8lKhYoxaYgwqrbYBVoPgeuZJuJVpf78BHlhuqLI58i/me.zip",
"lora_dropout_p": 0.1,
"learning_rate_ti": 0.0005,
"train_batch_size": 1,
"lr_scheduler_lora": "constant",
"perform_inversion": true,
"weight_decay_lora": 0.001,
"learning_rate_text": 0.00001,
"learning_rate_unet": 0.0001,
"max_train_steps_ti": 500,
"placeholder_tokens": "<s1>|<s2>",
"train_text_encoder": true,
"continue_inversion_lr": 0.0001,
"max_train_steps_tuning": 1000,
"gradient_accumulation_steps": 4,
"use_face_segmentation_condition": true
}
Input Parameters
- seed
- A seed for reproducible training
- scale_lr
- Scale the learning rate by the number of GPUs, gradient accumulation steps, and batch size.
- lora_rank
- Rank of the LoRA. Larger it is, more likely to capture fidelity but less likely to be editable. Larger rank will make the end result larger.
- lora_scale
- Scaling parameter at the end of the LoRA layer.
- resolution
- The resolution for input images. All the images in the train/validation dataset will be resized to this resolution.
- color_jitter
- Whether or not to use color jitter at augmentation.
- lr_scheduler
- The scheduler type to use
- use_template
- The template to use for the inversion.
- clip_ti_decay
- Whether or not to perform Bayesian Learning Rule on norm of the CLIP latent.
- instance_data (required)
- A ZIP file containing your training images (JPG, PNG, etc. size not restricted). These images contain your 'subject' that you want the trained model to embed in the output domain for later generating customized scenes beyond the training images. For best results, use images without noise or unrelated objects in the background.
- cached_latents
- Whether or not to cache VAE latent.
- lora_dropout_p
- Dropout for the LoRA layer. Reference LoRA paper for more details.
- lr_warmup_steps
- Number of steps for the warmup in the lr scheduler.
- weight_decay_ti
- The weight decay for the TI.
- learning_rate_ti
- The learning rate for the TI.
- train_batch_size
- Batch size (per device) for the training dataloader.
- lr_scheduler_lora
- The scheduler type to use
- weight_decay_lora
- The weight decay for the LORA loss.
- continue_inversion
- Whether or not to continue inversion.
- initializer_tokens
- The tokens to use for the initializer. If not provided, will randomly initialize from gaussian N(0,0.017^2)
- learning_rate_text
- The learning rate for the text encoder.
- learning_rate_unet
- The learning rate for the unet.
- max_train_steps_ti
- The maximum number of training steps for the TI.
- placeholder_tokens
- The placeholder tokens to use for the initializer. If not provided, will use the first tokens of the data.
- train_text_encoder
- Whether to train the text encoder
- lr_warmup_steps_lora
- Number of steps for the warmup in the lr scheduler.
- continue_inversion_lr
- The learning rate for continuing an inversion.
- gradient_checkpointing
- Whether or not to use gradient checkpointing to save memory at the expense of slower backward pass.
- max_train_steps_tuning
- The maximum number of training steps for the tuning.
- placeholder_token_at_data
- If this value is provided as 'X|Y', it will transform target word X into Y at caption. You are required to provide caption as filename (not regarding extension), and Y has to contain placeholder token below. You are also required to set `None` for `use_template` argument to use this feature.
- gradient_accumulation_steps
- Number of updates steps to accumulate before performing a backward/update pass.
- use_face_segmentation_condition
- Whether or not to use the face segmentation condition.
Output Schema
Output
Example Execution Logs
Using seed: 1337
PTI : Initializer Tokens not given, doing random inits
PTI : Placeholder Tokens ['<s1>', '<s2>']
PTI : Initializer Tokens ['<rand-0.017>', '<rand-0.017>']
Initialized <s1> with random noise (sigma=0.017), empirically -0.000 +- 0.017
Norm : 0.4630
Initialized <s2> with random noise (sigma=0.017), empirically 0.001 +- 0.017
Norm : 0.4595
/root/.pyenv/versions/3.10.9/lib/python3.10/site-packages/diffusers/configuration_utils.py:195: FutureWarning: It is deprecated to pass a pretrained model name or path to `from_config`.If you were trying to load a scheduler, please use <class 'diffusers.schedulers.scheduling_ddpm.DDPMScheduler'>.from_pretrained(...) instead. Otherwise, please make sure to pass a configuration dictionary instead. This functionality will be removed in v1.0.0.
deprecate("config-passed-as-path", "1.0.0", deprecation_message, standard_warn=False)
Mask not found for cog_instance_data/0.mask.png
Warning : this will pre-process all the images in the instance data root.
0%| | 0/7 [00:00<?, ?it/s]INFO: Created TensorFlow Lite XNNPACK delegate for CPU.
71%|███████▏ | 5/7 [00:00<00:00, 48.10it/s]
100%|██████████| 7/7 [00:00<00:00, 58.04it/s]
0%| | 0/500 [00:00<?, ?it/s]
a photo of a <s1><s2>
tensor([[0.4664],
[0.4611]], device='cuda:0')
Current Norm : tensor([0.4531, 0.4489], device='cuda:0')
Steps: 0%| | 0/500 [00:00<?, ?it/s]
Steps: 0%| | 1/500 [00:02<24:50, 2.99s/it]
a photo of a dirty <s1><s2>
Steps: 0%| | 1/500 [00:02<24:50, 2.99s/it, loss=0.000201, lr=0.002]
Steps: 0%| | 2/500 [00:03<12:11, 1.47s/it, loss=0.000201, lr=0.002]
a photo of a dirty <s1><s2>
Steps: 0%| | 2/500 [00:03<12:11, 1.47s/it, loss=0.000732, lr=0.002]
Steps: 1%| | 3/500 [00:03<07:32, 1.10it/s, loss=0.000732, lr=0.002]
a bright photo of the <s1><s2>
Steps: 1%| | 3/500 [00:03<07:32, 1.10it/s, loss=0.0377, lr=0.002]
Steps: 1%| | 4/500 [00:03<05:29, 1.50it/s, loss=0.0377, lr=0.002]
a photo of a clean <s1><s2>
tensor([[0.4567],
[0.4518]], device='cuda:0')
Current Norm : tensor([0.4453, 0.4415], device='cuda:0')
Steps: 1%| | 4/500 [00:03<05:29, 1.50it/s, loss=0.000362, lr=0.002]
Steps: 1%| | 5/500 [00:04<04:16, 1.93it/s, loss=0.000362, lr=0.002]
a photo of the cool <s1><s2>
Steps: 1%| | 5/500 [00:04<04:16, 1.93it/s, loss=0.0665, lr=0.002]
Steps: 1%| | 6/500 [00:04<03:30, 2.34it/s, loss=0.0665, lr=0.002]
a good photo of a <s1><s2>
Steps: 1%| | 6/500 [00:04<03:30, 2.34it/s, loss=0.00297, lr=0.002]
Steps: 1%|▏ | 7/500 [00:04<03:07, 2.63it/s, loss=0.00297, lr=0.002]
a rendition of the <s1><s2>
Steps: 1%|▏ | 7/500 [00:04<03:07, 2.63it/s, loss=0.0443, lr=0.002]
Steps: 2%|▏ | 8/500 [00:04<02:47, 2.94it/s, loss=0.0443, lr=0.002]
a rendition of the <s1><s2>
tensor([[0.4493],
[0.4459]], device='cuda:0')
Current Norm : tensor([0.4395, 0.4367], device='cuda:0')
Steps: 2%|▏ | 8/500 [00:04<02:47, 2.94it/s, loss=0.00504, lr=0.002]
Steps: 2%|▏ | 9/500 [00:05<02:57, 2.76it/s, loss=0.00504, lr=0.002]
a close-up photo of the <s1><s2>
Steps: 2%|▏ | 9/500 [00:05<02:57, 2.76it/s, loss=0.000178, lr=0.002]
Steps: 2%|▏ | 10/500 [00:05<02:54, 2.81it/s, loss=0.000178, lr=0.002]
a photo of the small <s1><s2>
Steps: 2%|▏ | 10/500 [00:05<02:54, 2.81it/s, loss=0.00148, lr=0.002]
Steps: 2%|▏ | 11/500 [00:06<02:45, 2.95it/s, loss=0.00148, lr=0.002]
a photo of my <s1><s2>
Steps: 2%|▏ | 11/500 [00:06<02:45, 2.95it/s, loss=0.065, lr=0.002]
Steps: 2%|▏ | 12/500 [00:06<03:05, 2.63it/s, loss=0.065, lr=0.002]
a good photo of a <s1><s2>
tensor([[0.4438],
[0.4411]], device='cuda:0')
Current Norm : tensor([0.4350, 0.4328], device='cuda:0')
Steps: 2%|▏ | 12/500 [00:06<03:05, 2.63it/s, loss=0.00173, lr=0.002]
Steps: 3%|▎ | 13/500 [00:06<02:50, 2.85it/s, loss=0.00173, lr=0.002]
a dark photo of the <s1><s2>
Steps: 3%|▎ | 13/500 [00:06<02:50, 2.85it/s, loss=0.00652, lr=0.002]
Steps: 3%|▎ | 14/500 [00:07<02:41, 3.01it/s, loss=0.00652, lr=0.002]
the photo of a <s1><s2>
Steps: 3%|▎ | 14/500 [00:07<02:41, 3.01it/s, loss=0.000898, lr=0.002]
Steps: 3%|▎ | 15/500 [00:07<02:52, 2.82it/s, loss=0.000898, lr=0.002]
a photo of the nice <s1><s2>
Steps: 3%|▎ | 15/500 [00:07<02:52, 2.82it/s, loss=0.00124, lr=0.002]
Steps: 3%|▎ | 16/500 [00:07<03:00, 2.68it/s, loss=0.00124, lr=0.002]
a close-up photo of a <s1><s2>
tensor([[0.4386],
[0.4360]], device='cuda:0')
Current Norm : tensor([0.4309, 0.4288], device='cuda:0')
Steps: 3%|▎ | 16/500 [00:07<03:00, 2.68it/s, loss=0.0152, lr=0.002]
Steps: 3%|▎ | 17/500 [00:08<02:46, 2.90it/s, loss=0.0152, lr=0.002]
a dark photo of the <s1><s2>
Steps: 3%|▎ | 17/500 [00:08<02:46, 2.90it/s, loss=0.000531, lr=0.002]
Steps: 4%|▎ | 18/500 [00:08<02:35, 3.11it/s, loss=0.000531, lr=0.002]
a good photo of the <s1><s2>
Steps: 4%|▎ | 18/500 [00:08<02:35, 3.11it/s, loss=0.00043, lr=0.002]
Steps: 4%|▍ | 19/500 [00:08<02:28, 3.24it/s, loss=0.00043, lr=0.002]
a photo of a small <s1><s2>
Steps: 4%|▍ | 19/500 [00:08<02:28, 3.24it/s, loss=0.0199, lr=0.002]
Steps: 4%|▍ | 20/500 [00:08<02:20, 3.41it/s, loss=0.0199, lr=0.002]
a close-up photo of the <s1><s2>
tensor([[0.4347],
[0.4330]], device='cuda:0')
Current Norm : tensor([0.4278, 0.4264], device='cuda:0')
Steps: 4%|▍ | 20/500 [00:08<02:20, 3.41it/s, loss=0.011, lr=0.002]
Steps: 4%|▍ | 21/500 [00:09<02:20, 3.40it/s, loss=0.011, lr=0.002]
a photo of the <s1><s2>
Steps: 4%|▍ | 21/500 [00:09<02:20, 3.40it/s, loss=0.00989, lr=0.002]
Steps: 4%|▍ | 22/500 [00:09<02:14, 3.55it/s, loss=0.00989, lr=0.002]
a rendition of a <s1><s2>
Steps: 4%|▍ | 22/500 [00:09<02:14, 3.55it/s, loss=0.00407, lr=0.002]
Steps: 5%|▍ | 23/500 [00:09<02:31, 3.15it/s, loss=0.00407, lr=0.002]
a photo of my <s1><s2>
Steps: 5%|▍ | 23/500 [00:09<02:31, 3.15it/s, loss=0.00994, lr=0.002]
Steps: 5%|▍ | 24/500 [00:10<02:21, 3.36it/s, loss=0.00994, lr=0.002]
a photo of a <s1><s2>
tensor([[0.4320],
[0.4311]], device='cuda:0')
Current Norm : tensor([0.4256, 0.4249], device='cuda:0')
Steps: 5%|▍ | 24/500 [00:10<02:21, 3.36it/s, loss=0.00795, lr=0.002]
Steps: 5%|▌ | 25/500 [00:10<02:36, 3.03it/s, loss=0.00795, lr=0.002]
a photo of the nice <s1><s2>
Steps: 5%|▌ | 25/500 [00:10<02:36, 3.03it/s, loss=0.00214, lr=0.002]
Steps: 5%|▌ | 26/500 [00:10<02:29, 3.17it/s, loss=0.00214, lr=0.002]
a photo of the clean <s1><s2>
Steps: 5%|▌ | 26/500 [00:10<02:29, 3.17it/s, loss=0.0173, lr=0.002]
Steps: 5%|▌ | 27/500 [00:11<02:27, 3.21it/s, loss=0.0173, lr=0.002]
a photo of a <s1><s2>
Steps: 5%|▌ | 27/500 [00:11<02:27, 3.21it/s, loss=0.000279, lr=0.002]
Steps: 6%|▌ | 28/500 [00:11<02:21, 3.33it/s, loss=0.000279, lr=0.002]
a photo of a small <s1><s2>
tensor([[0.4300],
[0.4298]], device='cuda:0')
Current Norm : tensor([0.4240, 0.4239], device='cuda:0')
Steps: 6%|▌ | 28/500 [00:11<02:21, 3.33it/s, loss=0.00361, lr=0.002]
Steps: 6%|▌ | 29/500 [00:11<02:42, 2.89it/s, loss=0.00361, lr=0.002]
a cropped photo of a <s1><s2>
Steps: 6%|▌ | 29/500 [00:11<02:42, 2.89it/s, loss=0.00475, lr=0.002]
Steps: 6%|▌ | 30/500 [00:12<02:52, 2.72it/s, loss=0.00475, lr=0.002]
a good photo of the <s1><s2>
Steps: 6%|▌ | 30/500 [00:12<02:52, 2.72it/s, loss=0.00284, lr=0.002]
Steps: 6%|▌ | 31/500 [00:12<02:42, 2.89it/s, loss=0.00284, lr=0.002]
a photo of the weird <s1><s2>
Steps: 6%|▌ | 31/500 [00:12<02:42, 2.89it/s, loss=0.00341, lr=0.002]
Steps: 6%|▋ | 32/500 [00:12<02:28, 3.14it/s, loss=0.00341, lr=0.002]
a photo of my <s1><s2>
tensor([[0.4286],
[0.4289]], device='cuda:0')
Current Norm : tensor([0.4229, 0.4231], device='cuda:0')
Steps: 6%|▋ | 32/500 [00:12<02:28, 3.14it/s, loss=0.0215, lr=0.002]
Steps: 7%|▋ | 33/500 [00:13<02:23, 3.26it/s, loss=0.0215, lr=0.002]
a good photo of a <s1><s2>
Steps: 7%|▋ | 33/500 [00:13<02:23, 3.26it/s, loss=0.00195, lr=0.002]
Steps: 7%|▋ | 34/500 [00:13<02:15, 3.43it/s, loss=0.00195, lr=0.002]
a photo of the cool <s1><s2>
Steps: 7%|▋ | 34/500 [00:13<02:15, 3.43it/s, loss=0.0122, lr=0.002]
Steps: 7%|▋ | 35/500 [00:13<02:14, 3.45it/s, loss=0.0122, lr=0.002]
a photo of the clean <s1><s2>
Steps: 7%|▋ | 35/500 [00:13<02:14, 3.45it/s, loss=0.00298, lr=0.002]
Steps: 7%|▋ | 36/500 [00:13<02:10, 3.56it/s, loss=0.00298, lr=0.002]
a photo of my <s1><s2>
tensor([[0.4275],
[0.4282]], device='cuda:0')
Current Norm : tensor([0.4220, 0.4226], device='cuda:0')
Steps: 7%|▋ | 36/500 [00:13<02:10, 3.56it/s, loss=0.0036, lr=0.002]
Steps: 7%|▋ | 37/500 [00:14<02:13, 3.48it/s, loss=0.0036, lr=0.002]
a photo of a nice <s1><s2>
Steps: 7%|▋ | 37/500 [00:14<02:13, 3.48it/s, loss=0.0507, lr=0.002]
Steps: 8%|▊ | 38/500 [00:14<02:14, 3.44it/s, loss=0.0507, lr=0.002]
a cropped photo of a <s1><s2>
Steps: 8%|▊ | 38/500 [00:14<02:14, 3.44it/s, loss=0.018, lr=0.002]
Steps: 8%|▊ | 39/500 [00:14<02:11, 3.52it/s, loss=0.018, lr=0.002]
a photo of one <s1><s2>
Steps: 8%|▊ | 39/500 [00:14<02:11, 3.52it/s, loss=0.000697, lr=0.002]
Steps: 8%|▊ | 40/500 [00:15<02:25, 3.16it/s, loss=0.000697, lr=0.002]
a photo of the <s1><s2>
tensor([[0.4266],
[0.4275]], device='cuda:0')
Current Norm : tensor([0.4213, 0.4220], device='cuda:0')
Steps: 8%|▊ | 40/500 [00:15<02:25, 3.16it/s, loss=0.000108, lr=0.002]
Steps: 8%|▊ | 41/500 [00:15<02:15, 3.38it/s, loss=0.000108, lr=0.002]
a photo of a small <s1><s2>
Steps: 8%|▊ | 41/500 [00:15<02:15, 3.38it/s, loss=0.0312, lr=0.002]
Steps: 8%|▊ | 42/500 [00:15<02:28, 3.08it/s, loss=0.0312, lr=0.002]
a rendering of a <s1><s2>
Steps: 8%|▊ | 42/500 [00:15<02:28, 3.08it/s, loss=0.00149, lr=0.002]
Steps: 9%|▊ | 43/500 [00:16<02:35, 2.93it/s, loss=0.00149, lr=0.002]
a bright photo of the <s1><s2>
Steps: 9%|▊ | 43/500 [00:16<02:35, 2.93it/s, loss=0.00488, lr=0.002]
Steps: 9%|▉ | 44/500 [00:16<02:24, 3.16it/s, loss=0.00488, lr=0.002]
a photo of a cool <s1><s2>
tensor([[0.4260],
[0.4269]], device='cuda:0')
Current Norm : tensor([0.4208, 0.4215], device='cuda:0')
Steps: 9%|▉ | 44/500 [00:16<02:24, 3.16it/s, loss=0.000548, lr=0.002]
Steps: 9%|▉ | 45/500 [00:16<02:15, 3.37it/s, loss=0.000548, lr=0.002]
a photo of my <s1><s2>
Steps: 9%|▉ | 45/500 [00:16<02:15, 3.37it/s, loss=0.00175, lr=0.002]
Steps: 9%|▉ | 46/500 [00:16<02:08, 3.54it/s, loss=0.00175, lr=0.002]
a photo of the <s1><s2>
Steps: 9%|▉ | 46/500 [00:16<02:08, 3.54it/s, loss=0.002, lr=0.002]
Steps: 9%|▉ | 47/500 [00:17<02:26, 3.09it/s, loss=0.002, lr=0.002]
a photo of a cool <s1><s2>
Steps: 9%|▉ | 47/500 [00:17<02:26, 3.09it/s, loss=0.00262, lr=0.002]
Steps: 10%|▉ | 48/500 [00:17<02:20, 3.23it/s, loss=0.00262, lr=0.002]
a cropped photo of a <s1><s2>
tensor([[0.4255],
[0.4262]], device='cuda:0')
Current Norm : tensor([0.4204, 0.4210], device='cuda:0')
Steps: 10%|▉ | 48/500 [00:17<02:20, 3.23it/s, loss=0.0013, lr=0.002]
Steps: 10%|▉ | 49/500 [00:17<02:12, 3.40it/s, loss=0.0013, lr=0.002]
a rendition of the <s1><s2>
Steps: 10%|▉ | 49/500 [00:17<02:12, 3.40it/s, loss=0.0399, lr=0.002]
Steps: 10%|█ | 50/500 [00:18<02:05, 3.57it/s, loss=0.0399, lr=0.002]
a photo of a <s1><s2>
Steps: 10%|█ | 50/500 [00:18<02:05, 3.57it/s, loss=0.00032, lr=0.002]
Steps: 10%|█ | 51/500 [00:18<02:05, 3.58it/s, loss=0.00032, lr=0.002]
a dark photo of the <s1><s2>
Steps: 10%|█ | 51/500 [00:18<02:05, 3.58it/s, loss=0.0014, lr=0.002]
Steps: 10%|█ | 52/500 [00:18<02:01, 3.70it/s, loss=0.0014, lr=0.002]
a close-up photo of a <s1><s2>
tensor([[0.4253],
[0.4257]], device='cuda:0')
Current Norm : tensor([0.4202, 0.4205], device='cuda:0')
Steps: 10%|█ | 52/500 [00:18<02:01, 3.70it/s, loss=0.00244, lr=0.002]
Steps: 11%|█ | 53/500 [00:19<02:16, 3.27it/s, loss=0.00244, lr=0.002]
a photo of a dirty <s1><s2>
Steps: 11%|█ | 53/500 [00:19<02:16, 3.27it/s, loss=0.00279, lr=0.002]
Steps: 11%|█ | 54/500 [00:19<02:08, 3.47it/s, loss=0.00279, lr=0.002]
a close-up photo of a <s1><s2>
Steps: 11%|█ | 54/500 [00:19<02:08, 3.47it/s, loss=0.00102, lr=0.002]
Steps: 11%|█ | 55/500 [00:19<02:05, 3.55it/s, loss=0.00102, lr=0.002]
a photo of the cool <s1><s2>
Steps: 11%|█ | 55/500 [00:19<02:05, 3.55it/s, loss=0.0129, lr=0.002]
Steps: 11%|█ | 56/500 [00:20<02:23, 3.09it/s, loss=0.0129, lr=0.002]
a close-up photo of a <s1><s2>
tensor([[0.4240],
[0.4242]], device='cuda:0')
Current Norm : tensor([0.4192, 0.4193], device='cuda:0')
Steps: 11%|█ | 56/500 [00:20<02:23, 3.09it/s, loss=0.00633, lr=0.002]
Steps: 11%|█▏ | 57/500 [00:20<02:15, 3.28it/s, loss=0.00633, lr=0.002]
a photo of the clean <s1><s2>
Steps: 11%|█▏ | 57/500 [00:20<02:15, 3.28it/s, loss=0.00333, lr=0.002]
Steps: 12%|█▏ | 58/500 [00:20<02:09, 3.40it/s, loss=0.00333, lr=0.002]
a photo of the small <s1><s2>
Steps: 12%|█▏ | 58/500 [00:20<02:09, 3.40it/s, loss=0.000857, lr=0.002]
Steps: 12%|█▏ | 59/500 [00:20<02:07, 3.45it/s, loss=0.000857, lr=0.002]
a photo of a clean <s1><s2>
Steps: 12%|█▏ | 59/500 [00:20<02:07, 3.45it/s, loss=0.00769, lr=0.002]
Steps: 12%|█▏ | 60/500 [00:21<02:24, 3.05it/s, loss=0.00769, lr=0.002]
a photo of my <s1><s2>
tensor([[0.4232],
[0.4233]], device='cuda:0')
Current Norm : tensor([0.4186, 0.4186], device='cuda:0')
Steps: 12%|█▏ | 60/500 [00:21<02:24, 3.05it/s, loss=0.00254, lr=0.002]
Steps: 12%|█▏ | 61/500 [00:21<02:15, 3.25it/s, loss=0.00254, lr=0.002]
a cropped photo of the <s1><s2>
Steps: 12%|█▏ | 61/500 [00:21<02:15, 3.25it/s, loss=0.000715, lr=0.002]
Steps: 12%|█▏ | 62/500 [00:21<02:08, 3.41it/s, loss=0.000715, lr=0.002]
a photo of a small <s1><s2>
Steps: 12%|█▏ | 62/500 [00:21<02:08, 3.41it/s, loss=0.00769, lr=0.002]
Steps: 13%|█▎ | 63/500 [00:22<02:21, 3.10it/s, loss=0.00769, lr=0.002]
a dark photo of the <s1><s2>
Steps: 13%|█▎ | 63/500 [00:22<02:21, 3.10it/s, loss=0.00656, lr=0.002]
Steps: 13%|█▎ | 64/500 [00:22<02:18, 3.16it/s, loss=0.00656, lr=0.002]
a photo of the weird <s1><s2>
tensor([[0.4227],
[0.4227]], device='cuda:0')
Current Norm : tensor([0.4182, 0.4181], device='cuda:0')
Steps: 13%|█▎ | 64/500 [00:22<02:18, 3.16it/s, loss=0.00016, lr=0.002]
Steps: 13%|█▎ | 65/500 [00:22<02:32, 2.85it/s, loss=0.00016, lr=0.002]
a photo of a small <s1><s2>
Steps: 13%|█▎ | 65/500 [00:22<02:32, 2.85it/s, loss=0.00543, lr=0.002]
Steps: 13%|█▎ | 66/500 [00:23<02:18, 3.13it/s, loss=0.00543, lr=0.002]
a cropped photo of a <s1><s2>
Steps: 13%|█▎ | 66/500 [00:23<02:18, 3.13it/s, loss=0.000229, lr=0.002]
Steps: 13%|█▎ | 67/500 [00:23<02:09, 3.33it/s, loss=0.000229, lr=0.002]
a photo of the weird <s1><s2>
Steps: 13%|█▎ | 67/500 [00:23<02:09, 3.33it/s, loss=0.00374, lr=0.002]
Steps: 14%|█▎ | 68/500 [00:23<02:05, 3.44it/s, loss=0.00374, lr=0.002]
a photo of a nice <s1><s2>
tensor([[0.4222],
[0.4221]], device='cuda:0')
Current Norm : tensor([0.4178, 0.4177], device='cuda:0')
Steps: 14%|█▎ | 68/500 [00:23<02:05, 3.44it/s, loss=0.0512, lr=0.002]
Steps: 14%|█▍ | 69/500 [00:23<02:01, 3.54it/s, loss=0.0512, lr=0.002]
a close-up photo of the <s1><s2>
Steps: 14%|█▍ | 69/500 [00:23<02:01, 3.54it/s, loss=0.00241, lr=0.002]
Steps: 14%|█▍ | 70/500 [00:24<02:18, 3.12it/s, loss=0.00241, lr=0.002]
a photo of the nice <s1><s2>
Steps: 14%|█▍ | 70/500 [00:24<02:18, 3.12it/s, loss=0.000527, lr=0.002]
Steps: 14%|█▍ | 71/500 [00:24<02:11, 3.27it/s, loss=0.000527, lr=0.002]
a dark photo of the <s1><s2>
Steps: 14%|█▍ | 71/500 [00:24<02:11, 3.27it/s, loss=0.000677, lr=0.002]
Steps: 14%|█▍ | 72/500 [00:24<02:03, 3.45it/s, loss=0.000677, lr=0.002]
a rendition of the <s1><s2>
tensor([[0.4219],
[0.4217]], device='cuda:0')
Current Norm : tensor([0.4175, 0.4174], device='cuda:0')
Steps: 14%|█▍ | 72/500 [00:24<02:03, 3.45it/s, loss=0.00671, lr=0.002]
Steps: 15%|█▍ | 73/500 [00:25<02:00, 3.56it/s, loss=0.00671, lr=0.002]
a photo of a dirty <s1><s2>
Steps: 15%|█▍ | 73/500 [00:25<02:00, 3.56it/s, loss=0.00828, lr=0.002]
Steps: 15%|█▍ | 74/500 [00:25<02:15, 3.15it/s, loss=0.00828, lr=0.002]
a photo of a small <s1><s2>
Steps: 15%|█▍ | 74/500 [00:25<02:15, 3.15it/s, loss=0.0013, lr=0.002]
Steps: 15%|█▌ | 75/500 [00:25<02:06, 3.37it/s, loss=0.0013, lr=0.002]
a photo of a dirty <s1><s2>
Steps: 15%|█▌ | 75/500 [00:25<02:06, 3.37it/s, loss=0.00365, lr=0.002]
Steps: 15%|█▌ | 76/500 [00:26<02:04, 3.40it/s, loss=0.00365, lr=0.002]
a photo of the <s1><s2>
tensor([[0.4217],
[0.4212]], device='cuda:0')
Current Norm : tensor([0.4174, 0.4170], device='cuda:0')
Steps: 15%|█▌ | 76/500 [00:26<02:04, 3.40it/s, loss=0.00397, lr=0.002]
Steps: 15%|█▌ | 77/500 [00:26<02:21, 2.98it/s, loss=0.00397, lr=0.002]
a photo of the weird <s1><s2>
Steps: 15%|█▌ | 77/500 [00:26<02:21, 2.98it/s, loss=0.000793, lr=0.002]
Steps: 16%|█▌ | 78/500 [00:26<02:26, 2.88it/s, loss=0.000793, lr=0.002]
a good photo of a <s1><s2>
Steps: 16%|█▌ | 78/500 [00:26<02:26, 2.88it/s, loss=0.00784, lr=0.002]
Steps: 16%|█▌ | 79/500 [00:27<02:36, 2.69it/s, loss=0.00784, lr=0.002]
a photo of the <s1><s2>
Steps: 16%|█▌ | 79/500 [00:27<02:36, 2.69it/s, loss=0.00536, lr=0.002]
Steps: 16%|█▌ | 80/500 [00:27<02:22, 2.94it/s, loss=0.00536, lr=0.002]
a photo of the large <s1><s2>
tensor([[0.4215],
[0.4207]], device='cuda:0')
Current Norm : tensor([0.4172, 0.4166], device='cuda:0')
Steps: 16%|█▌ | 80/500 [00:27<02:22, 2.94it/s, loss=0.00415, lr=0.002]
Steps: 16%|█▌ | 81/500 [00:27<02:11, 3.18it/s, loss=0.00415, lr=0.002]
a close-up photo of the <s1><s2>
Steps: 16%|█▌ | 81/500 [00:27<02:11, 3.18it/s, loss=0.00186, lr=0.002]
Steps: 16%|█▋ | 82/500 [00:28<02:07, 3.27it/s, loss=0.00186, lr=0.002]
a close-up photo of the <s1><s2>
Steps: 16%|█▋ | 82/500 [00:28<02:07, 3.27it/s, loss=0.017, lr=0.002]
Steps: 17%|█▋ | 83/500 [00:28<02:01, 3.43it/s, loss=0.017, lr=0.002]
a photo of one <s1><s2>
Steps: 17%|█▋ | 83/500 [00:28<02:01, 3.43it/s, loss=0.000429, lr=0.002]
Steps: 17%|█▋ | 84/500 [00:28<01:58, 3.52it/s, loss=0.000429, lr=0.002]
the photo of a <s1><s2>
tensor([[0.4213],
[0.4201]], device='cuda:0')
Current Norm : tensor([0.4170, 0.4161], device='cuda:0')
Steps: 17%|█▋ | 84/500 [00:28<01:58, 3.52it/s, loss=0.00338, lr=0.002]
Steps: 17%|█▋ | 85/500 [00:29<02:16, 3.04it/s, loss=0.00338, lr=0.002]
a bright photo of the <s1><s2>
Steps: 17%|█▋ | 85/500 [00:29<02:16, 3.04it/s, loss=0.00212, lr=0.002]
Steps: 17%|█▋ | 86/500 [00:29<02:06, 3.27it/s, loss=0.00212, lr=0.002]
a photo of the cool <s1><s2>
Steps: 17%|█▋ | 86/500 [00:29<02:06, 3.27it/s, loss=0.00274, lr=0.002]
Steps: 17%|█▋ | 87/500 [00:29<01:58, 3.48it/s, loss=0.00274, lr=0.002]
a cropped photo of the <s1><s2>
Steps: 17%|█▋ | 87/500 [00:29<01:58, 3.48it/s, loss=0.000433, lr=0.002]
Steps: 18%|█▊ | 88/500 [00:29<01:58, 3.48it/s, loss=0.000433, lr=0.002]
a cropped photo of a <s1><s2>
tensor([[0.4209],
[0.4196]], device='cuda:0')
Current Norm : tensor([0.4167, 0.4157], device='cuda:0')
Steps: 18%|█▊ | 88/500 [00:29<01:58, 3.48it/s, loss=0.000618, lr=0.002]
Steps: 18%|█▊ | 89/500 [00:30<01:55, 3.56it/s, loss=0.000618, lr=0.002]
a photo of a dirty <s1><s2>
Steps: 18%|█▊ | 89/500 [00:30<01:55, 3.56it/s, loss=0.0117, lr=0.002]
Steps: 18%|█▊ | 90/500 [00:30<01:53, 3.63it/s, loss=0.0117, lr=0.002]
a photo of a clean <s1><s2>
Steps: 18%|█▊ | 90/500 [00:30<01:53, 3.63it/s, loss=0.000428, lr=0.002]
Steps: 18%|█▊ | 91/500 [00:30<02:05, 3.25it/s, loss=0.000428, lr=0.002]
a rendering of a <s1><s2>
Steps: 18%|█▊ | 91/500 [00:30<02:05, 3.25it/s, loss=0.000106, lr=0.002]
Steps: 18%|█▊ | 92/500 [00:31<02:04, 3.27it/s, loss=0.000106, lr=0.002]
a photo of a nice <s1><s2>
tensor([[0.4206],
[0.4193]], device='cuda:0')
Current Norm : tensor([0.4165, 0.4155], device='cuda:0')
Steps: 18%|█▊ | 92/500 [00:31<02:04, 3.27it/s, loss=0.0017, lr=0.002]
Steps: 19%|█▊ | 93/500 [00:31<02:00, 3.39it/s, loss=0.0017, lr=0.002]
a photo of the nice <s1><s2>
Steps: 19%|█▊ | 93/500 [00:31<02:00, 3.39it/s, loss=0.0286, lr=0.002]
Steps: 19%|█▉ | 94/500 [00:31<02:13, 3.05it/s, loss=0.0286, lr=0.002]
a photo of the clean <s1><s2>
Steps: 19%|█▉ | 94/500 [00:31<02:13, 3.05it/s, loss=0.0107, lr=0.002]
Steps: 19%|█▉ | 95/500 [00:32<02:26, 2.77it/s, loss=0.0107, lr=0.002]
a photo of one <s1><s2>
Steps: 19%|█▉ | 95/500 [00:32<02:26, 2.77it/s, loss=0.00884, lr=0.002]
Steps: 19%|█▉ | 96/500 [00:32<02:13, 3.02it/s, loss=0.00884, lr=0.002]
a bright photo of the <s1><s2>
tensor([[0.4204],
[0.4192]], device='cuda:0')
Current Norm : tensor([0.4163, 0.4153], device='cuda:0')
Steps: 19%|█▉ | 96/500 [00:32<02:13, 3.02it/s, loss=0.0113, lr=0.002]
Steps: 19%|█▉ | 97/500 [00:32<02:04, 3.23it/s, loss=0.0113, lr=0.002]
a photo of the large <s1><s2>
Steps: 19%|█▉ | 97/500 [00:32<02:04, 3.23it/s, loss=0.000302, lr=0.002]
Steps: 20%|█▉ | 98/500 [00:32<01:58, 3.38it/s, loss=0.000302, lr=0.002]
a cropped photo of the <s1><s2>
Steps: 20%|█▉ | 98/500 [00:32<01:58, 3.38it/s, loss=0.0378, lr=0.002]
Steps: 20%|█▉ | 99/500 [00:33<01:52, 3.56it/s, loss=0.0378, lr=0.002]
a cropped photo of a <s1><s2>
Steps: 20%|█▉ | 99/500 [00:33<01:52, 3.56it/s, loss=0.0469, lr=0.002]
Steps: 20%|██ | 100/500 [00:33<01:51, 3.58it/s, loss=0.0469, lr=0.002]
a cropped photo of a <s1><s2>
tensor([[0.4202],
[0.4190]], device='cuda:0')
Current Norm : tensor([0.4161, 0.4152], device='cuda:0')
Steps: 20%|██ | 100/500 [00:33<01:51, 3.58it/s, loss=0.0724, lr=0.002]
Steps: 20%|██ | 101/500 [00:33<01:51, 3.57it/s, loss=0.0724, lr=0.002]
a photo of a <s1><s2>
Steps: 20%|██ | 101/500 [00:33<01:51, 3.57it/s, loss=0.00152, lr=0.002]
Steps: 20%|██ | 102/500 [00:34<01:49, 3.63it/s, loss=0.00152, lr=0.002]
a photo of the small <s1><s2>
Steps: 20%|██ | 102/500 [00:34<01:49, 3.63it/s, loss=0.00435, lr=0.002]
Steps: 21%|██ | 103/500 [00:34<01:46, 3.73it/s, loss=0.00435, lr=0.002]
a good photo of the <s1><s2>
Steps: 21%|██ | 103/500 [00:34<01:46, 3.73it/s, loss=0.000261, lr=0.002]
Steps: 21%|██ | 104/500 [00:34<02:00, 3.28it/s, loss=0.000261, lr=0.002]
a photo of the small <s1><s2>
tensor([[0.4200],
[0.4187]], device='cuda:0')
Current Norm : tensor([0.4160, 0.4150], device='cuda:0')
Steps: 21%|██ | 104/500 [00:34<02:00, 3.28it/s, loss=0.00487, lr=0.002]
Steps: 21%|██ | 105/500 [00:35<02:15, 2.93it/s, loss=0.00487, lr=0.002]
a photo of a nice <s1><s2>
Steps: 21%|██ | 105/500 [00:35<02:15, 2.93it/s, loss=0.00294, lr=0.002]
Steps: 21%|██ | 106/500 [00:35<02:05, 3.14it/s, loss=0.00294, lr=0.002]
a photo of a cool <s1><s2>
Steps: 21%|██ | 106/500 [00:35<02:05, 3.14it/s, loss=0.00347, lr=0.002]
Steps: 21%|██▏ | 107/500 [00:35<02:16, 2.88it/s, loss=0.00347, lr=0.002]
a close-up photo of a <s1><s2>
Steps: 21%|██▏ | 107/500 [00:35<02:16, 2.88it/s, loss=0.00733, lr=0.002]
Steps: 22%|██▏ | 108/500 [00:36<02:06, 3.10it/s, loss=0.00733, lr=0.002]
a photo of the weird <s1><s2>
tensor([[0.4195],
[0.4184]], device='cuda:0')
Current Norm : tensor([0.4156, 0.4147], device='cuda:0')
Steps: 22%|██▏ | 108/500 [00:36<02:06, 3.10it/s, loss=0.000872, lr=0.002]
Steps: 22%|██▏ | 109/500 [00:36<02:02, 3.20it/s, loss=0.000872, lr=0.002]
a photo of the large <s1><s2>
Steps: 22%|██▏ | 109/500 [00:36<02:02, 3.20it/s, loss=0.0213, lr=0.002]
Steps: 22%|██▏ | 110/500 [00:36<02:12, 2.95it/s, loss=0.0213, lr=0.002]
a cropped photo of a <s1><s2>
Steps: 22%|██▏ | 110/500 [00:36<02:12, 2.95it/s, loss=0.0106, lr=0.002]
Steps: 22%|██▏ | 111/500 [00:37<02:06, 3.08it/s, loss=0.0106, lr=0.002]
a photo of a nice <s1><s2>
Steps: 22%|██▏ | 111/500 [00:37<02:06, 3.08it/s, loss=0.00931, lr=0.002]
Steps: 22%|██▏ | 112/500 [00:37<02:01, 3.20it/s, loss=0.00931, lr=0.002]
a photo of the nice <s1><s2>
tensor([[0.4193],
[0.4181]], device='cuda:0')
Current Norm : tensor([0.4154, 0.4145], device='cuda:0')
Steps: 22%|██▏ | 112/500 [00:37<02:01, 3.20it/s, loss=0.000504, lr=0.002]
Steps: 23%|██▎ | 113/500 [00:37<01:56, 3.34it/s, loss=0.000504, lr=0.002]
a dark photo of the <s1><s2>
Steps: 23%|██▎ | 113/500 [00:37<01:56, 3.34it/s, loss=0.0702, lr=0.002]
Steps: 23%|██▎ | 114/500 [00:37<01:54, 3.38it/s, loss=0.0702, lr=0.002]
a photo of a clean <s1><s2>
Steps: 23%|██▎ | 114/500 [00:37<01:54, 3.38it/s, loss=0.0148, lr=0.002]
Steps: 23%|██▎ | 115/500 [00:38<01:51, 3.46it/s, loss=0.0148, lr=0.002]
a close-up photo of a <s1><s2>
Steps: 23%|██▎ | 115/500 [00:38<01:51, 3.46it/s, loss=0.0113, lr=0.002]
Steps: 23%|██▎ | 116/500 [00:38<02:09, 2.96it/s, loss=0.0113, lr=0.002]
a rendition of a <s1><s2>
tensor([[0.4190],
[0.4178]], device='cuda:0')
Current Norm : tensor([0.4152, 0.4142], device='cuda:0')
Steps: 23%|██▎ | 116/500 [00:38<02:09, 2.96it/s, loss=0.00264, lr=0.002]
Steps: 23%|██▎ | 117/500 [00:38<01:59, 3.19it/s, loss=0.00264, lr=0.002]
a photo of the weird <s1><s2>
Steps: 23%|██▎ | 117/500 [00:38<01:59, 3.19it/s, loss=0.000295, lr=0.002]
Steps: 24%|██▎ | 118/500 [00:39<02:10, 2.94it/s, loss=0.000295, lr=0.002]
a photo of a small <s1><s2>
Steps: 24%|██▎ | 118/500 [00:39<02:10, 2.94it/s, loss=0.000116, lr=0.002]
Steps: 24%|██▍ | 119/500 [00:39<01:59, 3.20it/s, loss=0.000116, lr=0.002]
a photo of the large <s1><s2>
Steps: 24%|██▍ | 119/500 [00:39<01:59, 3.20it/s, loss=0.0289, lr=0.002]
Steps: 24%|██▍ | 120/500 [00:39<01:51, 3.40it/s, loss=0.0289, lr=0.002]
a photo of the clean <s1><s2>
tensor([[0.4187],
[0.4175]], device='cuda:0')
Current Norm : tensor([0.4150, 0.4140], device='cuda:0')
Steps: 24%|██▍ | 120/500 [00:39<01:51, 3.40it/s, loss=0.142, lr=0.002]
Steps: 24%|██▍ | 121/500 [00:40<01:49, 3.46it/s, loss=0.142, lr=0.002]
a rendition of the <s1><s2>
Steps: 24%|██▍ | 121/500 [00:40<01:49, 3.46it/s, loss=0.0397, lr=0.002]
Steps: 24%|██▍ | 122/500 [00:40<01:44, 3.62it/s, loss=0.0397, lr=0.002]
a good photo of the <s1><s2>
Steps: 24%|██▍ | 122/500 [00:40<01:44, 3.62it/s, loss=0.0406, lr=0.002]
Steps: 25%|██▍ | 123/500 [00:40<01:46, 3.53it/s, loss=0.0406, lr=0.002]
a cropped photo of a <s1><s2>
Steps: 25%|██▍ | 123/500 [00:40<01:46, 3.53it/s, loss=0.00687, lr=0.002]
Steps: 25%|██▍ | 124/500 [00:41<02:03, 3.05it/s, loss=0.00687, lr=0.002]
a dark photo of the <s1><s2>
tensor([[0.4180],
[0.4170]], device='cuda:0')
Current Norm : tensor([0.4144, 0.4136], device='cuda:0')
Steps: 25%|██▍ | 124/500 [00:41<02:03, 3.05it/s, loss=0.00264, lr=0.002]
Steps: 25%|██▌ | 125/500 [00:41<02:10, 2.87it/s, loss=0.00264, lr=0.002]
a cropped photo of the <s1><s2>
Steps: 25%|██▌ | 125/500 [00:41<02:10, 2.87it/s, loss=0.00165, lr=0.002]
Steps: 25%|██▌ | 126/500 [00:41<02:00, 3.11it/s, loss=0.00165, lr=0.002]
a rendition of a <s1><s2>
Steps: 25%|██▌ | 126/500 [00:41<02:00, 3.11it/s, loss=0.000393, lr=0.002]
Steps: 25%|██▌ | 127/500 [00:42<02:11, 2.83it/s, loss=0.000393, lr=0.002]
a photo of the small <s1><s2>
Steps: 25%|██▌ | 127/500 [00:42<02:11, 2.83it/s, loss=0.00493, lr=0.002]
Steps: 26%|██▌ | 128/500 [00:42<02:04, 3.00it/s, loss=0.00493, lr=0.002]
a photo of the nice <s1><s2>
tensor([[0.4176],
[0.4167]], device='cuda:0')
Current Norm : tensor([0.4141, 0.4133], device='cuda:0')
Steps: 26%|██▌ | 128/500 [00:42<02:04, 3.00it/s, loss=0.00182, lr=0.002]
Steps: 26%|██▌ | 129/500 [00:42<01:55, 3.21it/s, loss=0.00182, lr=0.002]
a photo of a dirty <s1><s2>
Steps: 26%|██▌ | 129/500 [00:42<01:55, 3.21it/s, loss=0.00474, lr=0.002]
Steps: 26%|██▌ | 130/500 [00:42<01:48, 3.42it/s, loss=0.00474, lr=0.002]
a photo of the weird <s1><s2>
Steps: 26%|██▌ | 130/500 [00:42<01:48, 3.42it/s, loss=0.00189, lr=0.002]
Steps: 26%|██▌ | 131/500 [00:43<02:03, 2.98it/s, loss=0.00189, lr=0.002]
a cropped photo of a <s1><s2>
Steps: 26%|██▌ | 131/500 [00:43<02:03, 2.98it/s, loss=0.0111, lr=0.002]
Steps: 26%|██▋ | 132/500 [00:43<01:55, 3.19it/s, loss=0.0111, lr=0.002]
a photo of the large <s1><s2>
tensor([[0.4175],
[0.4164]], device='cuda:0')
Current Norm : tensor([0.4140, 0.4131], device='cuda:0')
Steps: 26%|██▋ | 132/500 [00:43<01:55, 3.19it/s, loss=0.0121, lr=0.002]
Steps: 27%|██▋ | 133/500 [00:43<01:50, 3.33it/s, loss=0.0121, lr=0.002]
a photo of a nice <s1><s2>
Steps: 27%|██▋ | 133/500 [00:43<01:50, 3.33it/s, loss=0.00485, lr=0.002]
Steps: 27%|██▋ | 134/500 [00:44<02:04, 2.94it/s, loss=0.00485, lr=0.002]
the photo of a <s1><s2>
Steps: 27%|██▋ | 134/500 [00:44<02:04, 2.94it/s, loss=0.00112, lr=0.002]
Steps: 27%|██▋ | 135/500 [00:44<02:00, 3.03it/s, loss=0.00112, lr=0.002]
a photo of a dirty <s1><s2>
Steps: 27%|██▋ | 135/500 [00:44<02:00, 3.03it/s, loss=0.00341, lr=0.002]
Steps: 27%|██▋ | 136/500 [00:45<02:10, 2.79it/s, loss=0.00341, lr=0.002]
a close-up photo of the <s1><s2>
tensor([[0.4176],
[0.4162]], device='cuda:0')
Current Norm : tensor([0.4141, 0.4129], device='cuda:0')
Steps: 27%|██▋ | 136/500 [00:45<02:10, 2.79it/s, loss=0.0062, lr=0.002]
Steps: 27%|██▋ | 137/500 [00:45<02:00, 3.01it/s, loss=0.0062, lr=0.002]
the photo of a <s1><s2>
Steps: 27%|██▋ | 137/500 [00:45<02:00, 3.01it/s, loss=0.00215, lr=0.002]
Steps: 28%|██▊ | 138/500 [00:45<01:51, 3.24it/s, loss=0.00215, lr=0.002]
a photo of a <s1><s2>
Steps: 28%|██▊ | 138/500 [00:45<01:51, 3.24it/s, loss=0.00843, lr=0.002]
Steps: 28%|██▊ | 139/500 [00:45<01:45, 3.43it/s, loss=0.00843, lr=0.002]
a cropped photo of the <s1><s2>
Steps: 28%|██▊ | 139/500 [00:45<01:45, 3.43it/s, loss=0.00101, lr=0.002]
Steps: 28%|██▊ | 140/500 [00:46<01:42, 3.51it/s, loss=0.00101, lr=0.002]
a photo of a nice <s1><s2>
tensor([[0.4176],
[0.4160]], device='cuda:0')
Current Norm : tensor([0.4141, 0.4128], device='cuda:0')
Steps: 28%|██▊ | 140/500 [00:46<01:42, 3.51it/s, loss=0.0133, lr=0.002]
Steps: 28%|██▊ | 141/500 [00:46<01:56, 3.07it/s, loss=0.0133, lr=0.002]
a photo of a small <s1><s2>
Steps: 28%|██▊ | 141/500 [00:46<01:56, 3.07it/s, loss=0.00602, lr=0.002]
Steps: 28%|██▊ | 142/500 [00:46<01:48, 3.30it/s, loss=0.00602, lr=0.002]
a photo of the nice <s1><s2>
Steps: 28%|██▊ | 142/500 [00:46<01:48, 3.30it/s, loss=0.0278, lr=0.002]
Steps: 29%|██▊ | 143/500 [00:47<01:59, 2.99it/s, loss=0.0278, lr=0.002]
a photo of a small <s1><s2>
Steps: 29%|██▊ | 143/500 [00:47<01:59, 2.99it/s, loss=0.000815, lr=0.002]
Steps: 29%|██▉ | 144/500 [00:47<01:50, 3.22it/s, loss=0.000815, lr=0.002]
a photo of the large <s1><s2>
tensor([[0.4176],
[0.4157]], device='cuda:0')
Current Norm : tensor([0.4141, 0.4126], device='cuda:0')
Steps: 29%|██▉ | 144/500 [00:47<01:50, 3.22it/s, loss=0.0248, lr=0.002]
Steps: 29%|██▉ | 145/500 [00:47<01:47, 3.31it/s, loss=0.0248, lr=0.002]
a photo of the nice <s1><s2>
Steps: 29%|██▉ | 145/500 [00:47<01:47, 3.31it/s, loss=0.00912, lr=0.002]
Steps: 29%|██▉ | 146/500 [00:47<01:41, 3.50it/s, loss=0.00912, lr=0.002]
a photo of the clean <s1><s2>
Steps: 29%|██▉ | 146/500 [00:47<01:41, 3.50it/s, loss=0.0298, lr=0.002]
Steps: 29%|██▉ | 147/500 [00:48<01:36, 3.65it/s, loss=0.0298, lr=0.002]
a close-up photo of a <s1><s2>
Steps: 29%|██▉ | 147/500 [00:48<01:36, 3.65it/s, loss=0.0542, lr=0.002]
Steps: 30%|██▉ | 148/500 [00:48<01:48, 3.26it/s, loss=0.0542, lr=0.002]
a photo of the clean <s1><s2>
tensor([[0.4174],
[0.4154]], device='cuda:0')
Current Norm : tensor([0.4139, 0.4123], device='cuda:0')
Steps: 30%|██▉ | 148/500 [00:48<01:48, 3.26it/s, loss=0.000515, lr=0.002]
Steps: 30%|██▉ | 149/500 [00:48<01:42, 3.42it/s, loss=0.000515, lr=0.002]
a photo of the <s1><s2>
Steps: 30%|██▉ | 149/500 [00:48<01:42, 3.42it/s, loss=0.00376, lr=0.002]
Steps: 30%|███ | 150/500 [00:49<01:40, 3.50it/s, loss=0.00376, lr=0.002]
a photo of the nice <s1><s2>
Steps: 30%|███ | 150/500 [00:49<01:40, 3.50it/s, loss=0.0059, lr=0.002]
Steps: 30%|███ | 151/500 [00:49<01:36, 3.63it/s, loss=0.0059, lr=0.002]
a photo of the weird <s1><s2>
Steps: 30%|███ | 151/500 [00:49<01:36, 3.63it/s, loss=0.0217, lr=0.002]
Steps: 30%|███ | 152/500 [00:49<01:38, 3.55it/s, loss=0.0217, lr=0.002]
a photo of the <s1><s2>
tensor([[0.4168],
[0.4151]], device='cuda:0')
Current Norm : tensor([0.4135, 0.4121], device='cuda:0')
Steps: 30%|███ | 152/500 [00:49<01:38, 3.55it/s, loss=0.00187, lr=0.002]
Steps: 31%|███ | 153/500 [00:50<01:54, 3.03it/s, loss=0.00187, lr=0.002]
a photo of the weird <s1><s2>
Steps: 31%|███ | 153/500 [00:50<01:54, 3.03it/s, loss=0.000129, lr=0.002]
Steps: 31%|███ | 154/500 [00:50<01:47, 3.23it/s, loss=0.000129, lr=0.002]
a photo of a nice <s1><s2>
Steps: 31%|███ | 154/500 [00:50<01:47, 3.23it/s, loss=0.0274, lr=0.002]
Steps: 31%|███ | 155/500 [00:50<01:42, 3.37it/s, loss=0.0274, lr=0.002]
a photo of the small <s1><s2>
Steps: 31%|███ | 155/500 [00:50<01:42, 3.37it/s, loss=0.0249, lr=0.002]
Steps: 31%|███ | 156/500 [00:50<01:36, 3.55it/s, loss=0.0249, lr=0.002]
a cropped photo of a <s1><s2>
tensor([[0.4166],
[0.4150]], device='cuda:0')
Current Norm : tensor([0.4133, 0.4120], device='cuda:0')
Steps: 31%|███ | 156/500 [00:50<01:36, 3.55it/s, loss=0.0214, lr=0.002]
Steps: 31%|███▏ | 157/500 [00:51<01:34, 3.63it/s, loss=0.0214, lr=0.002]
a cropped photo of the <s1><s2>
Steps: 31%|███▏ | 157/500 [00:51<01:34, 3.63it/s, loss=0.000945, lr=0.002]
Steps: 32%|███▏ | 158/500 [00:51<01:31, 3.72it/s, loss=0.000945, lr=0.002]
a photo of one <s1><s2>
Steps: 32%|███▏ | 158/500 [00:51<01:31, 3.72it/s, loss=0.00133, lr=0.002]
Steps: 32%|███▏ | 159/500 [00:51<01:33, 3.64it/s, loss=0.00133, lr=0.002]
a rendition of a <s1><s2>
Steps: 32%|███▏ | 159/500 [00:51<01:33, 3.64it/s, loss=0.00302, lr=0.002]
Steps: 32%|███▏ | 160/500 [00:52<01:48, 3.12it/s, loss=0.00302, lr=0.002]
a rendition of the <s1><s2>
tensor([[0.4164],
[0.4152]], device='cuda:0')
Current Norm : tensor([0.4131, 0.4122], device='cuda:0')
Steps: 32%|███▏ | 160/500 [00:52<01:48, 3.12it/s, loss=0.00605, lr=0.002]
Steps: 32%|███▏ | 161/500 [00:52<01:57, 2.87it/s, loss=0.00605, lr=0.002]
a photo of a clean <s1><s2>
Steps: 32%|███▏ | 161/500 [00:52<01:57, 2.87it/s, loss=0.00175, lr=0.002]
Steps: 32%|███▏ | 162/500 [00:52<01:52, 3.00it/s, loss=0.00175, lr=0.002]
a photo of a nice <s1><s2>
Steps: 32%|███▏ | 162/500 [00:52<01:52, 3.00it/s, loss=0.000449, lr=0.002]
Steps: 33%|███▎ | 163/500 [00:53<01:45, 3.20it/s, loss=0.000449, lr=0.002]
a photo of a nice <s1><s2>
Steps: 33%|███▎ | 163/500 [00:53<01:45, 3.20it/s, loss=0.00273, lr=0.002]
Steps: 33%|███▎ | 164/500 [00:53<01:38, 3.43it/s, loss=0.00273, lr=0.002]
a photo of a cool <s1><s2>
tensor([[0.4162],
[0.4154]], device='cuda:0')
Current Norm : tensor([0.4130, 0.4123], device='cuda:0')
Steps: 33%|███▎ | 164/500 [00:53<01:38, 3.43it/s, loss=0.104, lr=0.002]
Steps: 33%|███▎ | 165/500 [00:53<01:34, 3.54it/s, loss=0.104, lr=0.002]
a photo of the clean <s1><s2>
Steps: 33%|███▎ | 165/500 [00:53<01:34, 3.54it/s, loss=0.0254, lr=0.002]
Steps: 33%|███▎ | 166/500 [00:53<01:32, 3.61it/s, loss=0.0254, lr=0.002]
a photo of the <s1><s2>
Steps: 33%|███▎ | 166/500 [00:53<01:32, 3.61it/s, loss=0.00313, lr=0.002]
Steps: 33%|███▎ | 167/500 [00:54<01:44, 3.19it/s, loss=0.00313, lr=0.002]
a bright photo of the <s1><s2>
Steps: 33%|███▎ | 167/500 [00:54<01:44, 3.19it/s, loss=0.00685, lr=0.002]
Steps: 34%|███▎ | 168/500 [00:54<01:50, 2.99it/s, loss=0.00685, lr=0.002]
a close-up photo of a <s1><s2>
tensor([[0.4160],
[0.4156]], device='cuda:0')
Current Norm : tensor([0.4128, 0.4125], device='cuda:0')
Steps: 34%|███▎ | 168/500 [00:54<01:50, 2.99it/s, loss=5.82e-5, lr=0.002]
Steps: 34%|███▍ | 169/500 [00:54<01:45, 3.14it/s, loss=5.82e-5, lr=0.002]
a photo of a cool <s1><s2>
Steps: 34%|███▍ | 169/500 [00:54<01:45, 3.14it/s, loss=0.00185, lr=0.002]
Steps: 34%|███▍ | 170/500 [00:55<01:54, 2.89it/s, loss=0.00185, lr=0.002]
a photo of the clean <s1><s2>
Steps: 34%|███▍ | 170/500 [00:55<01:54, 2.89it/s, loss=0.00742, lr=0.002]
Steps: 34%|███▍ | 171/500 [00:55<01:57, 2.81it/s, loss=0.00742, lr=0.002]
a rendering of a <s1><s2>
Steps: 34%|███▍ | 171/500 [00:55<01:57, 2.81it/s, loss=0.0131, lr=0.002]
Steps: 34%|███▍ | 172/500 [00:55<01:48, 3.03it/s, loss=0.0131, lr=0.002]
a photo of a nice <s1><s2>
tensor([[0.4158],
[0.4157]], device='cuda:0')
Current Norm : tensor([0.4126, 0.4126], device='cuda:0')
Steps: 34%|███▍ | 172/500 [00:55<01:48, 3.03it/s, loss=0.0152, lr=0.002]
Steps: 35%|███▍ | 173/500 [00:56<01:46, 3.07it/s, loss=0.0152, lr=0.002]
a rendition of the <s1><s2>
Steps: 35%|███▍ | 173/500 [00:56<01:46, 3.07it/s, loss=0.0129, lr=0.002]
Steps: 35%|███▍ | 174/500 [00:56<01:38, 3.30it/s, loss=0.0129, lr=0.002]
a photo of the <s1><s2>
Steps: 35%|███▍ | 174/500 [00:56<01:38, 3.30it/s, loss=0.0154, lr=0.002]
Steps: 35%|███▌ | 175/500 [00:56<01:34, 3.43it/s, loss=0.0154, lr=0.002]
a good photo of a <s1><s2>
Steps: 35%|███▌ | 175/500 [00:56<01:34, 3.43it/s, loss=0.0347, lr=0.002]
Steps: 35%|███▌ | 176/500 [00:57<01:48, 2.99it/s, loss=0.0347, lr=0.002]
a cropped photo of the <s1><s2>
tensor([[0.4155],
[0.4158]], device='cuda:0')
Current Norm : tensor([0.4124, 0.4127], device='cuda:0')
Steps: 35%|███▌ | 176/500 [00:57<01:48, 2.99it/s, loss=0.00439, lr=0.002]
Steps: 35%|███▌ | 177/500 [00:57<01:48, 2.97it/s, loss=0.00439, lr=0.002]
a photo of the large <s1><s2>
Steps: 35%|███▌ | 177/500 [00:57<01:48, 2.97it/s, loss=0.00845, lr=0.002]
Steps: 36%|███▌ | 178/500 [00:57<01:42, 3.15it/s, loss=0.00845, lr=0.002]
a photo of the small <s1><s2>
Steps: 36%|███▌ | 178/500 [00:57<01:42, 3.15it/s, loss=0.00099, lr=0.002]
Steps: 36%|███▌ | 179/500 [00:58<01:36, 3.33it/s, loss=0.00099, lr=0.002]
a photo of the <s1><s2>
Steps: 36%|███▌ | 179/500 [00:58<01:36, 3.33it/s, loss=0.00269, lr=0.002]
Steps: 36%|███▌ | 180/500 [00:58<01:45, 3.04it/s, loss=0.00269, lr=0.002]
a photo of a nice <s1><s2>
tensor([[0.4152],
[0.4160]], device='cuda:0')
Current Norm : tensor([0.4121, 0.4128], device='cuda:0')
Steps: 36%|███▌ | 180/500 [00:58<01:45, 3.04it/s, loss=0.0104, lr=0.002]
Steps: 36%|███▌ | 181/500 [00:58<01:38, 3.25it/s, loss=0.0104, lr=0.002]
a good photo of a <s1><s2>
Steps: 36%|███▌ | 181/500 [00:58<01:38, 3.25it/s, loss=0.0474, lr=0.002]
Steps: 36%|███▋ | 182/500 [00:59<01:34, 3.37it/s, loss=0.0474, lr=0.002]
a photo of the small <s1><s2>
Steps: 36%|███▋ | 182/500 [00:59<01:34, 3.37it/s, loss=0.022, lr=0.002]
Steps: 37%|███▋ | 183/500 [00:59<01:30, 3.52it/s, loss=0.022, lr=0.002]
a photo of a <s1><s2>
Steps: 37%|███▋ | 183/500 [00:59<01:30, 3.52it/s, loss=0.00619, lr=0.002]
Steps: 37%|███▋ | 184/500 [00:59<01:26, 3.65it/s, loss=0.00619, lr=0.002]
a photo of a nice <s1><s2>
tensor([[0.4149],
[0.4163]], device='cuda:0')
Current Norm : tensor([0.4119, 0.4130], device='cuda:0')
Steps: 37%|███▋ | 184/500 [00:59<01:26, 3.65it/s, loss=0.0129, lr=0.002]
Steps: 37%|███▋ | 185/500 [00:59<01:27, 3.61it/s, loss=0.0129, lr=0.002]
the photo of a <s1><s2>
Steps: 37%|███▋ | 185/500 [00:59<01:27, 3.61it/s, loss=0.0196, lr=0.002]
Steps: 37%|███▋ | 186/500 [01:00<01:24, 3.71it/s, loss=0.0196, lr=0.002]
a bright photo of the <s1><s2>
Steps: 37%|███▋ | 186/500 [01:00<01:24, 3.71it/s, loss=0.0557, lr=0.002]
Steps: 37%|███▋ | 187/500 [01:00<01:38, 3.17it/s, loss=0.0557, lr=0.002]
a rendition of the <s1><s2>
Steps: 37%|███▋ | 187/500 [01:00<01:38, 3.17it/s, loss=0.00724, lr=0.002]
Steps: 38%|███▊ | 188/500 [01:00<01:32, 3.37it/s, loss=0.00724, lr=0.002]
a photo of the <s1><s2>
tensor([[0.4145],
[0.4167]], device='cuda:0')
Current Norm : tensor([0.4116, 0.4134], device='cuda:0')
Steps: 38%|███▊ | 188/500 [01:00<01:32, 3.37it/s, loss=0.0549, lr=0.002]
Steps: 38%|███▊ | 189/500 [01:01<01:40, 3.09it/s, loss=0.0549, lr=0.002]
a photo of the cool <s1><s2>
Steps: 38%|███▊ | 189/500 [01:01<01:40, 3.09it/s, loss=0.00217, lr=0.002]
Steps: 38%|███▊ | 190/500 [01:01<01:33, 3.32it/s, loss=0.00217, lr=0.002]
a close-up photo of a <s1><s2>
Steps: 38%|███▊ | 190/500 [01:01<01:33, 3.32it/s, loss=0.0175, lr=0.002]
Steps: 38%|███▊ | 191/500 [01:01<01:39, 3.09it/s, loss=0.0175, lr=0.002]
a photo of the nice <s1><s2>
Steps: 38%|███▊ | 191/500 [01:01<01:39, 3.09it/s, loss=0.000155, lr=0.002]
Steps: 38%|███▊ | 192/500 [01:02<01:33, 3.29it/s, loss=0.000155, lr=0.002]
a photo of a <s1><s2>
tensor([[0.4142],
[0.4171]], device='cuda:0')
Current Norm : tensor([0.4114, 0.4137], device='cuda:0')
Steps: 38%|███▊ | 192/500 [01:02<01:33, 3.29it/s, loss=0.0728, lr=0.002]
Steps: 39%|███▊ | 193/500 [01:02<01:31, 3.36it/s, loss=0.0728, lr=0.002]
a rendition of the <s1><s2>
Steps: 39%|███▊ | 193/500 [01:02<01:31, 3.36it/s, loss=0.00176, lr=0.002]
Steps: 39%|███▉ | 194/500 [01:02<01:27, 3.51it/s, loss=0.00176, lr=0.002]
a photo of a <s1><s2>
Steps: 39%|███▉ | 194/500 [01:02<01:27, 3.51it/s, loss=0.00214, lr=0.002]
Steps: 39%|███▉ | 195/500 [01:02<01:36, 3.16it/s, loss=0.00214, lr=0.002]
a photo of a nice <s1><s2>
Steps: 39%|███▉ | 195/500 [01:02<01:36, 3.16it/s, loss=0.00334, lr=0.002]
Steps: 39%|███▉ | 196/500 [01:03<01:30, 3.38it/s, loss=0.00334, lr=0.002]
a photo of a dirty <s1><s2>
tensor([[0.4139],
[0.4179]], device='cuda:0')
Current Norm : tensor([0.4111, 0.4143], device='cuda:0')
Steps: 39%|███▉ | 196/500 [01:03<01:30, 3.38it/s, loss=0.0016, lr=0.002]
Steps: 39%|███▉ | 197/500 [01:03<01:28, 3.41it/s, loss=0.0016, lr=0.002]
a cropped photo of a <s1><s2>
Steps: 39%|███▉ | 197/500 [01:03<01:28, 3.41it/s, loss=0.00117, lr=0.002]
Steps: 40%|███▉ | 198/500 [01:03<01:23, 3.61it/s, loss=0.00117, lr=0.002]
the photo of a <s1><s2>
Steps: 40%|███▉ | 198/500 [01:03<01:23, 3.61it/s, loss=0.0306, lr=0.002]
Steps: 40%|███▉ | 199/500 [01:03<01:21, 3.70it/s, loss=0.0306, lr=0.002]
a good photo of a <s1><s2>
Steps: 40%|███▉ | 199/500 [01:03<01:21, 3.70it/s, loss=0.000478, lr=0.002]
Steps: 40%|████ | 200/500 [01:04<01:30, 3.31it/s, loss=0.000478, lr=0.002]
a photo of the small <s1><s2>
tensor([[0.4136],
[0.4186]], device='cuda:0')
Current Norm : tensor([0.4109, 0.4149], device='cuda:0')
Steps: 40%|████ | 200/500 [01:04<01:30, 3.31it/s, loss=0.00925, lr=0.002]
Steps: 40%|████ | 201/500 [01:04<01:25, 3.48it/s, loss=0.00925, lr=0.002]
the photo of a <s1><s2>
Steps: 40%|████ | 201/500 [01:04<01:25, 3.48it/s, loss=0.0664, lr=0.002]
Steps: 40%|████ | 202/500 [01:04<01:21, 3.65it/s, loss=0.0664, lr=0.002]
a rendition of a <s1><s2>
Steps: 40%|████ | 202/500 [01:04<01:21, 3.65it/s, loss=0.0105, lr=0.002]
Steps: 41%|████ | 203/500 [01:05<01:32, 3.23it/s, loss=0.0105, lr=0.002]
a photo of my <s1><s2>
Steps: 41%|████ | 203/500 [01:05<01:32, 3.23it/s, loss=0.000469, lr=0.002]
Steps: 41%|████ | 204/500 [01:05<01:29, 3.30it/s, loss=0.000469, lr=0.002]
a photo of my <s1><s2>
tensor([[0.4133],
[0.4195]], device='cuda:0')
Current Norm : tensor([0.4106, 0.4156], device='cuda:0')
Steps: 41%|████ | 204/500 [01:05<01:29, 3.30it/s, loss=0.000467, lr=0.002]
Steps: 41%|████ | 205/500 [01:05<01:25, 3.44it/s, loss=0.000467, lr=0.002]
a photo of a small <s1><s2>
Steps: 41%|████ | 205/500 [01:05<01:25, 3.44it/s, loss=0.024, lr=0.002]
Steps: 41%|████ | 206/500 [01:06<01:34, 3.11it/s, loss=0.024, lr=0.002]
a photo of a small <s1><s2>
Steps: 41%|████ | 206/500 [01:06<01:34, 3.11it/s, loss=0.0018, lr=0.002]
Steps: 41%|████▏ | 207/500 [01:06<01:27, 3.37it/s, loss=0.0018, lr=0.002]
a rendition of a <s1><s2>
Steps: 41%|████▏ | 207/500 [01:06<01:27, 3.37it/s, loss=0.000363, lr=0.002]
Steps: 42%|████▏ | 208/500 [01:06<01:22, 3.54it/s, loss=0.000363, lr=0.002]
a photo of a small <s1><s2>
tensor([[0.4130],
[0.4201]], device='cuda:0')
Current Norm : tensor([0.4104, 0.4161], device='cuda:0')
Steps: 42%|████▏ | 208/500 [01:06<01:22, 3.54it/s, loss=0.0199, lr=0.002]
Steps: 42%|████▏ | 209/500 [01:06<01:19, 3.65it/s, loss=0.0199, lr=0.002]
a bright photo of the <s1><s2>
Steps: 42%|████▏ | 209/500 [01:06<01:19, 3.65it/s, loss=0.00127, lr=0.002]
Steps: 42%|████▏ | 210/500 [01:07<01:28, 3.29it/s, loss=0.00127, lr=0.002]
a photo of the nice <s1><s2>
Steps: 42%|████▏ | 210/500 [01:07<01:28, 3.29it/s, loss=0.00241, lr=0.002]
Steps: 42%|████▏ | 211/500 [01:07<01:23, 3.46it/s, loss=0.00241, lr=0.002]
a photo of the clean <s1><s2>
Steps: 42%|████▏ | 211/500 [01:07<01:23, 3.46it/s, loss=0.00201, lr=0.002]
Steps: 42%|████▏ | 212/500 [01:07<01:31, 3.13it/s, loss=0.00201, lr=0.002]
a photo of the <s1><s2>
tensor([[0.4128],
[0.4207]], device='cuda:0')
Current Norm : tensor([0.4103, 0.4166], device='cuda:0')
Steps: 42%|████▏ | 212/500 [01:07<01:31, 3.13it/s, loss=0.00227, lr=0.002]
Steps: 43%|████▎ | 213/500 [01:08<01:25, 3.35it/s, loss=0.00227, lr=0.002]
a cropped photo of the <s1><s2>
Steps: 43%|████▎ | 213/500 [01:08<01:25, 3.35it/s, loss=0.0487, lr=0.002]
Steps: 43%|████▎ | 214/500 [01:08<01:31, 3.12it/s, loss=0.0487, lr=0.002]
a photo of a nice <s1><s2>
Steps: 43%|████▎ | 214/500 [01:08<01:31, 3.12it/s, loss=0.000143, lr=0.002]
Steps: 43%|████▎ | 215/500 [01:08<01:25, 3.35it/s, loss=0.000143, lr=0.002]
a close-up photo of the <s1><s2>
Steps: 43%|████▎ | 215/500 [01:08<01:25, 3.35it/s, loss=0.000309, lr=0.002]
Steps: 43%|████▎ | 216/500 [01:09<01:20, 3.53it/s, loss=0.000309, lr=0.002]
a rendition of a <s1><s2>
tensor([[0.4126],
[0.4212]], device='cuda:0')
Current Norm : tensor([0.4101, 0.4170], device='cuda:0')
Steps: 43%|████▎ | 216/500 [01:09<01:20, 3.53it/s, loss=0.0049, lr=0.002]
Steps: 43%|████▎ | 217/500 [01:09<01:20, 3.53it/s, loss=0.0049, lr=0.002]
a photo of the nice <s1><s2>
Steps: 43%|████▎ | 217/500 [01:09<01:20, 3.53it/s, loss=0.00286, lr=0.002]
Steps: 44%|████▎ | 218/500 [01:09<01:16, 3.66it/s, loss=0.00286, lr=0.002]
the photo of a <s1><s2>
Steps: 44%|████▎ | 218/500 [01:09<01:16, 3.66it/s, loss=0.000149, lr=0.002]
Steps: 44%|████▍ | 219/500 [01:09<01:13, 3.80it/s, loss=0.000149, lr=0.002]
a photo of my <s1><s2>
Steps: 44%|████▍ | 219/500 [01:09<01:13, 3.80it/s, loss=0.0516, lr=0.002]
Steps: 44%|████▍ | 220/500 [01:10<01:12, 3.87it/s, loss=0.0516, lr=0.002]
a photo of the clean <s1><s2>
tensor([[0.4122],
[0.4217]], device='cuda:0')
Current Norm : tensor([0.4098, 0.4173], device='cuda:0')
Steps: 44%|████▍ | 220/500 [01:10<01:12, 3.87it/s, loss=0.0941, lr=0.002]
Steps: 44%|████▍ | 221/500 [01:10<01:14, 3.75it/s, loss=0.0941, lr=0.002]
a close-up photo of a <s1><s2>
Steps: 44%|████▍ | 221/500 [01:10<01:14, 3.75it/s, loss=0.009, lr=0.002]
Steps: 44%|████▍ | 222/500 [01:10<01:24, 3.28it/s, loss=0.009, lr=0.002]
a photo of a small <s1><s2>
Steps: 44%|████▍ | 222/500 [01:10<01:24, 3.28it/s, loss=0.00726, lr=0.002]
Steps: 45%|████▍ | 223/500 [01:10<01:19, 3.48it/s, loss=0.00726, lr=0.002]
a good photo of the <s1><s2>
Steps: 45%|████▍ | 223/500 [01:10<01:19, 3.48it/s, loss=0.00278, lr=0.002]
Steps: 45%|████▍ | 224/500 [01:11<01:26, 3.20it/s, loss=0.00278, lr=0.002]
the photo of a <s1><s2>
tensor([[0.4118],
[0.4219]], device='cuda:0')
Current Norm : tensor([0.4094, 0.4175], device='cuda:0')
Steps: 45%|████▍ | 224/500 [01:11<01:26, 3.20it/s, loss=0.000234, lr=0.002]
Steps: 45%|████▌ | 225/500 [01:11<01:21, 3.39it/s, loss=0.000234, lr=0.002]
a photo of the large <s1><s2>
Steps: 45%|████▌ | 225/500 [01:11<01:21, 3.39it/s, loss=0.0981, lr=0.002]
Steps: 45%|████▌ | 226/500 [01:12<01:30, 3.03it/s, loss=0.0981, lr=0.002]
a photo of the cool <s1><s2>
Steps: 45%|████▌ | 226/500 [01:12<01:30, 3.03it/s, loss=0.0016, lr=0.002]
Steps: 45%|████▌ | 227/500 [01:12<01:23, 3.29it/s, loss=0.0016, lr=0.002]
a photo of one <s1><s2>
Steps: 45%|████▌ | 227/500 [01:12<01:23, 3.29it/s, loss=0.0207, lr=0.002]
Steps: 46%|████▌ | 228/500 [01:12<01:18, 3.48it/s, loss=0.0207, lr=0.002]
a dark photo of the <s1><s2>
tensor([[0.4113],
[0.4222]], device='cuda:0')
Current Norm : tensor([0.4091, 0.4177], device='cuda:0')
Steps: 46%|████▌ | 228/500 [01:12<01:18, 3.48it/s, loss=0.000244, lr=0.002]
Steps: 46%|████▌ | 229/500 [01:12<01:17, 3.50it/s, loss=0.000244, lr=0.002]
a rendering of a <s1><s2>
Steps: 46%|████▌ | 229/500 [01:12<01:17, 3.50it/s, loss=0.0141, lr=0.002]
Steps: 46%|████▌ | 230/500 [01:13<01:14, 3.63it/s, loss=0.0141, lr=0.002]
a photo of the clean <s1><s2>
Steps: 46%|████▌ | 230/500 [01:13<01:14, 3.63it/s, loss=0.0289, lr=0.002]
Steps: 46%|████▌ | 231/500 [01:13<01:21, 3.29it/s, loss=0.0289, lr=0.002]
a photo of the nice <s1><s2>
Steps: 46%|████▌ | 231/500 [01:13<01:21, 3.29it/s, loss=8.23e-5, lr=0.002]
Steps: 46%|████▋ | 232/500 [01:13<01:16, 3.49it/s, loss=8.23e-5, lr=0.002]
a bright photo of the <s1><s2>
tensor([[0.4109],
[0.4223]], device='cuda:0')
Current Norm : tensor([0.4087, 0.4178], device='cuda:0')
Steps: 46%|████▋ | 232/500 [01:13<01:16, 3.49it/s, loss=0.0013, lr=0.002]
Steps: 47%|████▋ | 233/500 [01:14<01:26, 3.10it/s, loss=0.0013, lr=0.002]
a photo of a <s1><s2>
Steps: 47%|████▋ | 233/500 [01:14<01:26, 3.10it/s, loss=0.00504, lr=0.002]
Steps: 47%|████▋ | 234/500 [01:14<01:34, 2.82it/s, loss=0.00504, lr=0.002]
a close-up photo of a <s1><s2>
Steps: 47%|████▋ | 234/500 [01:14<01:34, 2.82it/s, loss=0.00429, lr=0.002]
Steps: 47%|████▋ | 235/500 [01:14<01:29, 2.97it/s, loss=0.00429, lr=0.002]
a photo of the large <s1><s2>
Steps: 47%|████▋ | 235/500 [01:14<01:29, 2.97it/s, loss=0.00422, lr=0.002]
Steps: 47%|████▋ | 236/500 [01:15<01:22, 3.18it/s, loss=0.00422, lr=0.002]
a cropped photo of the <s1><s2>
tensor([[0.4105],
[0.4224]], device='cuda:0')
Current Norm : tensor([0.4084, 0.4180], device='cuda:0')
Steps: 47%|████▋ | 236/500 [01:15<01:22, 3.18it/s, loss=0.00756, lr=0.002]
Steps: 47%|████▋ | 237/500 [01:15<01:20, 3.27it/s, loss=0.00756, lr=0.002]
a photo of the clean <s1><s2>
Steps: 47%|████▋ | 237/500 [01:15<01:20, 3.27it/s, loss=0.00273, lr=0.002]
Steps: 48%|████▊ | 238/500 [01:15<01:16, 3.40it/s, loss=0.00273, lr=0.002]
a close-up photo of a <s1><s2>
Steps: 48%|████▊ | 238/500 [01:15<01:16, 3.40it/s, loss=0.00283, lr=0.002]
Steps: 48%|████▊ | 239/500 [01:15<01:16, 3.43it/s, loss=0.00283, lr=0.002]
a close-up photo of a <s1><s2>
Steps: 48%|████▊ | 239/500 [01:15<01:16, 3.43it/s, loss=0.0263, lr=0.002]
Steps: 48%|████▊ | 240/500 [01:16<01:23, 3.10it/s, loss=0.0263, lr=0.002]
a rendering of a <s1><s2>
tensor([[0.4101],
[0.4226]], device='cuda:0')
Current Norm : tensor([0.4081, 0.4180], device='cuda:0')
Steps: 48%|████▊ | 240/500 [01:16<01:23, 3.10it/s, loss=0.000781, lr=0.002]
Steps: 48%|████▊ | 241/500 [01:16<01:19, 3.25it/s, loss=0.000781, lr=0.002]
the photo of a <s1><s2>
Steps: 48%|████▊ | 241/500 [01:16<01:19, 3.25it/s, loss=0.033, lr=0.002]
Steps: 48%|████▊ | 242/500 [01:16<01:14, 3.44it/s, loss=0.033, lr=0.002]
a photo of the clean <s1><s2>
Steps: 48%|████▊ | 242/500 [01:16<01:14, 3.44it/s, loss=0.00583, lr=0.002]
Steps: 49%|████▊ | 243/500 [01:17<01:12, 3.55it/s, loss=0.00583, lr=0.002]
a photo of the <s1><s2>
Steps: 49%|████▊ | 243/500 [01:17<01:12, 3.55it/s, loss=0.0192, lr=0.002]
Steps: 49%|████▉ | 244/500 [01:17<01:24, 3.01it/s, loss=0.0192, lr=0.002]
a photo of the <s1><s2>
tensor([[0.4099],
[0.4228]], device='cuda:0')
Current Norm : tensor([0.4079, 0.4183], device='cuda:0')
Steps: 49%|████▉ | 244/500 [01:17<01:24, 3.01it/s, loss=0.000695, lr=0.002]
Steps: 49%|████▉ | 245/500 [01:17<01:22, 3.07it/s, loss=0.000695, lr=0.002]
a photo of a nice <s1><s2>
Steps: 49%|████▉ | 245/500 [01:17<01:22, 3.07it/s, loss=0.000637, lr=0.002]
Steps: 49%|████▉ | 246/500 [01:18<01:17, 3.28it/s, loss=0.000637, lr=0.002]
a good photo of a <s1><s2>
Steps: 49%|████▉ | 246/500 [01:18<01:17, 3.28it/s, loss=0.000824, lr=0.002]
Steps: 49%|████▉ | 247/500 [01:18<01:25, 2.97it/s, loss=0.000824, lr=0.002]
a photo of a clean <s1><s2>
Steps: 49%|████▉ | 247/500 [01:18<01:25, 2.97it/s, loss=0.000446, lr=0.002]
Steps: 50%|████▉ | 248/500 [01:18<01:21, 3.08it/s, loss=0.000446, lr=0.002]
a photo of the small <s1><s2>
tensor([[0.4097],
[0.4230]], device='cuda:0')
Current Norm : tensor([0.4078, 0.4184], device='cuda:0')
Steps: 50%|████▉ | 248/500 [01:18<01:21, 3.08it/s, loss=0.00172, lr=0.002]
Steps: 50%|████▉ | 249/500 [01:19<01:29, 2.79it/s, loss=0.00172, lr=0.002]
a photo of the cool <s1><s2>
Steps: 50%|████▉ | 249/500 [01:19<01:29, 2.79it/s, loss=0.000349, lr=0.002]
Steps: 50%|█████ | 250/500 [01:19<01:22, 3.04it/s, loss=0.000349, lr=0.002]
the photo of a <s1><s2>
Steps: 50%|█████ | 250/500 [01:19<01:22, 3.04it/s, loss=0.00635, lr=0.002]
Steps: 50%|█████ | 251/500 [01:19<01:16, 3.25it/s, loss=0.00635, lr=0.002]
a photo of a <s1><s2>
Steps: 50%|█████ | 251/500 [01:19<01:16, 3.25it/s, loss=0.00309, lr=0.002]
Steps: 50%|█████ | 252/500 [01:20<01:12, 3.42it/s, loss=0.00309, lr=0.002]
a photo of the large <s1><s2>
tensor([[0.4095],
[0.4230]], device='cuda:0')
Current Norm : tensor([0.4076, 0.4184], device='cuda:0')
Steps: 50%|█████ | 252/500 [01:20<01:12, 3.42it/s, loss=0.00955, lr=0.002]
Steps: 51%|█████ | 253/500 [01:20<01:10, 3.51it/s, loss=0.00955, lr=0.002]
a close-up photo of the <s1><s2>
Steps: 51%|█████ | 253/500 [01:20<01:10, 3.51it/s, loss=0.0794, lr=0.002]
Steps: 51%|█████ | 254/500 [01:20<01:10, 3.51it/s, loss=0.0794, lr=0.002]
a close-up photo of a <s1><s2>
Steps: 51%|█████ | 254/500 [01:20<01:10, 3.51it/s, loss=0.00516, lr=0.002]
Steps: 51%|█████ | 255/500 [01:20<01:18, 3.13it/s, loss=0.00516, lr=0.002]
a good photo of the <s1><s2>
Steps: 51%|█████ | 255/500 [01:20<01:18, 3.13it/s, loss=0.000313, lr=0.002]
Steps: 51%|█████ | 256/500 [01:21<01:13, 3.31it/s, loss=0.000313, lr=0.002]
a photo of a <s1><s2>
tensor([[0.4093],
[0.4228]], device='cuda:0')
Current Norm : tensor([0.4074, 0.4183], device='cuda:0')
Steps: 51%|█████ | 256/500 [01:21<01:13, 3.31it/s, loss=0.0139, lr=0.002]
Steps: 51%|█████▏ | 257/500 [01:21<01:23, 2.92it/s, loss=0.0139, lr=0.002]
a close-up photo of a <s1><s2>
Steps: 51%|█████▏ | 257/500 [01:21<01:23, 2.92it/s, loss=0.00152, lr=0.002]
Steps: 52%|█████▏ | 258/500 [01:21<01:17, 3.11it/s, loss=0.00152, lr=0.002]
a cropped photo of the <s1><s2>
Steps: 52%|█████▏ | 258/500 [01:21<01:17, 3.11it/s, loss=0.00165, lr=0.002]
Steps: 52%|█████▏ | 259/500 [01:22<01:13, 3.28it/s, loss=0.00165, lr=0.002]
a bright photo of the <s1><s2>
Steps: 52%|█████▏ | 259/500 [01:22<01:13, 3.28it/s, loss=0.00235, lr=0.002]
Steps: 52%|█████▏ | 260/500 [01:22<01:10, 3.40it/s, loss=0.00235, lr=0.002]
a photo of a clean <s1><s2>
tensor([[0.4092],
[0.4226]], device='cuda:0')
Current Norm : tensor([0.4073, 0.4180], device='cuda:0')
Steps: 52%|█████▏ | 260/500 [01:22<01:10, 3.40it/s, loss=0.0602, lr=0.002]
Steps: 52%|█████▏ | 261/500 [01:22<01:23, 2.87it/s, loss=0.0602, lr=0.002]
a close-up photo of a <s1><s2>
Steps: 52%|█████▏ | 261/500 [01:22<01:23, 2.87it/s, loss=0.00551, lr=0.002]
Steps: 52%|█████▏ | 262/500 [01:23<01:31, 2.61it/s, loss=0.00551, lr=0.002]
a bright photo of the <s1><s2>
Steps: 52%|█████▏ | 262/500 [01:23<01:31, 2.61it/s, loss=0.00472, lr=0.002]
Steps: 53%|█████▎ | 263/500 [01:23<01:22, 2.87it/s, loss=0.00472, lr=0.002]
a close-up photo of the <s1><s2>
Steps: 53%|█████▎ | 263/500 [01:23<01:22, 2.87it/s, loss=0.000771, lr=0.002]
Steps: 53%|█████▎ | 264/500 [01:23<01:15, 3.11it/s, loss=0.000771, lr=0.002]
a good photo of the <s1><s2>
tensor([[0.4091],
[0.4224]], device='cuda:0')
Current Norm : tensor([0.4073, 0.4179], device='cuda:0')
Steps: 53%|█████▎ | 264/500 [01:23<01:15, 3.11it/s, loss=0.00174, lr=0.002]
Steps: 53%|█████▎ | 265/500 [01:24<01:14, 3.16it/s, loss=0.00174, lr=0.002]
a photo of the cool <s1><s2>
Steps: 53%|█████▎ | 265/500 [01:24<01:14, 3.16it/s, loss=0.00403, lr=0.002]
Steps: 53%|█████▎ | 266/500 [01:24<01:09, 3.36it/s, loss=0.00403, lr=0.002]
a close-up photo of a <s1><s2>
Steps: 53%|█████▎ | 266/500 [01:24<01:09, 3.36it/s, loss=0.00155, lr=0.002]
Steps: 53%|█████▎ | 267/500 [01:24<01:06, 3.51it/s, loss=0.00155, lr=0.002]
a photo of the small <s1><s2>
Steps: 53%|█████▎ | 267/500 [01:24<01:06, 3.51it/s, loss=0.0192, lr=0.002]
Steps: 54%|█████▎ | 268/500 [01:25<01:06, 3.51it/s, loss=0.0192, lr=0.002]
a photo of one <s1><s2>
tensor([[0.4091],
[0.4222]], device='cuda:0')
Current Norm : tensor([0.4073, 0.4178], device='cuda:0')
Steps: 54%|█████▎ | 268/500 [01:25<01:06, 3.51it/s, loss=0.000823, lr=0.002]
Steps: 54%|█████▍ | 269/500 [01:25<01:16, 3.03it/s, loss=0.000823, lr=0.002]
a photo of a small <s1><s2>
Steps: 54%|█████▍ | 269/500 [01:25<01:16, 3.03it/s, loss=0.00844, lr=0.002]
Steps: 54%|█████▍ | 270/500 [01:25<01:10, 3.26it/s, loss=0.00844, lr=0.002]
a photo of a small <s1><s2>
Steps: 54%|█████▍ | 270/500 [01:25<01:10, 3.26it/s, loss=0.0732, lr=0.002]
Steps: 54%|█████▍ | 271/500 [01:26<01:20, 2.86it/s, loss=0.0732, lr=0.002]
the photo of a <s1><s2>
Steps: 54%|█████▍ | 271/500 [01:26<01:20, 2.86it/s, loss=0.0023, lr=0.002]
Steps: 54%|█████▍ | 272/500 [01:26<01:13, 3.12it/s, loss=0.0023, lr=0.002]
a rendition of a <s1><s2>
tensor([[0.4090],
[0.4219]], device='cuda:0')
Current Norm : tensor([0.4072, 0.4175], device='cuda:0')
Steps: 54%|█████▍ | 272/500 [01:26<01:13, 3.12it/s, loss=0.0172, lr=0.002]
Steps: 55%|█████▍ | 273/500 [01:26<01:08, 3.32it/s, loss=0.0172, lr=0.002]
the photo of a <s1><s2>
Steps: 55%|█████▍ | 273/500 [01:26<01:08, 3.32it/s, loss=0.0111, lr=0.002]
Steps: 55%|█████▍ | 274/500 [01:26<01:05, 3.44it/s, loss=0.0111, lr=0.002]
a close-up photo of a <s1><s2>
Steps: 55%|█████▍ | 274/500 [01:26<01:05, 3.44it/s, loss=0.00722, lr=0.002]
Steps: 55%|█████▌ | 275/500 [01:27<01:03, 3.56it/s, loss=0.00722, lr=0.002]
the photo of a <s1><s2>
Steps: 55%|█████▌ | 275/500 [01:27<01:03, 3.56it/s, loss=0.00764, lr=0.002]
Steps: 55%|█████▌ | 276/500 [01:27<01:00, 3.69it/s, loss=0.00764, lr=0.002]
a cropped photo of the <s1><s2>
tensor([[0.4090],
[0.4214]], device='cuda:0')
Current Norm : tensor([0.4072, 0.4171], device='cuda:0')
Steps: 55%|█████▌ | 276/500 [01:27<01:00, 3.69it/s, loss=0.000535, lr=0.002]
Steps: 55%|█████▌ | 277/500 [01:27<01:09, 3.20it/s, loss=0.000535, lr=0.002]
a rendition of a <s1><s2>
Steps: 55%|█████▌ | 277/500 [01:27<01:09, 3.20it/s, loss=0.00321, lr=0.002]
Steps: 56%|█████▌ | 278/500 [01:28<01:06, 3.35it/s, loss=0.00321, lr=0.002]
a good photo of a <s1><s2>
Steps: 56%|█████▌ | 278/500 [01:28<01:06, 3.35it/s, loss=0.00316, lr=0.002]
Steps: 56%|█████▌ | 279/500 [01:28<01:06, 3.34it/s, loss=0.00316, lr=0.002]
the photo of a <s1><s2>
Steps: 56%|█████▌ | 279/500 [01:28<01:06, 3.34it/s, loss=0.00192, lr=0.002]
Steps: 56%|█████▌ | 280/500 [01:28<01:16, 2.88it/s, loss=0.00192, lr=0.002]
a photo of a clean <s1><s2>
tensor([[0.4090],
[0.4209]], device='cuda:0')
Current Norm : tensor([0.4072, 0.4167], device='cuda:0')
Steps: 56%|█████▌ | 280/500 [01:28<01:16, 2.88it/s, loss=9.6e-5, lr=0.002]
Steps: 56%|█████▌ | 281/500 [01:29<01:11, 3.06it/s, loss=9.6e-5, lr=0.002]
a photo of a dirty <s1><s2>
Steps: 56%|█████▌ | 281/500 [01:29<01:11, 3.06it/s, loss=0.00752, lr=0.002]
Steps: 56%|█████▋ | 282/500 [01:29<01:06, 3.27it/s, loss=0.00752, lr=0.002]
a good photo of a <s1><s2>
Steps: 56%|█████▋ | 282/500 [01:29<01:06, 3.27it/s, loss=0.00161, lr=0.002]
Steps: 57%|█████▋ | 283/500 [01:29<01:03, 3.42it/s, loss=0.00161, lr=0.002]
a rendition of the <s1><s2>
Steps: 57%|█████▋ | 283/500 [01:29<01:03, 3.42it/s, loss=0.0142, lr=0.002]
Steps: 57%|█████▋ | 284/500 [01:30<01:08, 3.14it/s, loss=0.0142, lr=0.002]
a photo of my <s1><s2>
tensor([[0.4090],
[0.4204]], device='cuda:0')
Current Norm : tensor([0.4072, 0.4163], device='cuda:0')
Steps: 57%|█████▋ | 284/500 [01:30<01:08, 3.14it/s, loss=6.19e-5, lr=0.002]
Steps: 57%|█████▋ | 285/500 [01:30<01:07, 3.19it/s, loss=6.19e-5, lr=0.002]
a rendition of the <s1><s2>
Steps: 57%|█████▋ | 285/500 [01:30<01:07, 3.19it/s, loss=0.00561, lr=0.002]
Steps: 57%|█████▋ | 286/500 [01:30<01:02, 3.43it/s, loss=0.00561, lr=0.002]
a photo of the clean <s1><s2>
Steps: 57%|█████▋ | 286/500 [01:30<01:02, 3.43it/s, loss=0.0392, lr=0.002]
Steps: 57%|█████▋ | 287/500 [01:31<01:08, 3.09it/s, loss=0.0392, lr=0.002]
a photo of the <s1><s2>
Steps: 57%|█████▋ | 287/500 [01:31<01:08, 3.09it/s, loss=0.00119, lr=0.002]
Steps: 58%|█████▊ | 288/500 [01:31<01:04, 3.29it/s, loss=0.00119, lr=0.002]
a rendering of a <s1><s2>
tensor([[0.4089],
[0.4198]], device='cuda:0')
Current Norm : tensor([0.4071, 0.4158], device='cuda:0')
Steps: 58%|█████▊ | 288/500 [01:31<01:04, 3.29it/s, loss=0.00417, lr=0.002]
Steps: 58%|█████▊ | 289/500 [01:31<01:03, 3.30it/s, loss=0.00417, lr=0.002]
a photo of the nice <s1><s2>
Steps: 58%|█████▊ | 289/500 [01:31<01:03, 3.30it/s, loss=0.000165, lr=0.002]
Steps: 58%|█████▊ | 290/500 [01:31<01:11, 2.94it/s, loss=0.000165, lr=0.002]
a photo of one <s1><s2>
Steps: 58%|█████▊ | 290/500 [01:31<01:11, 2.94it/s, loss=0.00129, lr=0.002]
Steps: 58%|█████▊ | 291/500 [01:32<01:05, 3.17it/s, loss=0.00129, lr=0.002]
a photo of one <s1><s2>
Steps: 58%|█████▊ | 291/500 [01:32<01:05, 3.17it/s, loss=0.0111, lr=0.002]
Steps: 58%|█████▊ | 292/500 [01:32<01:11, 2.89it/s, loss=0.0111, lr=0.002]
a photo of a clean <s1><s2>
tensor([[0.4089],
[0.4194]], device='cuda:0')
Current Norm : tensor([0.4071, 0.4155], device='cuda:0')
Steps: 58%|█████▊ | 292/500 [01:32<01:11, 2.89it/s, loss=0.00184, lr=0.002]
Steps: 59%|█████▊ | 293/500 [01:32<01:07, 3.07it/s, loss=0.00184, lr=0.002]
a photo of the weird <s1><s2>
Steps: 59%|█████▊ | 293/500 [01:32<01:07, 3.07it/s, loss=0.00349, lr=0.002]
Steps: 59%|█████▉ | 294/500 [01:33<01:01, 3.33it/s, loss=0.00349, lr=0.002]
a photo of the small <s1><s2>
Steps: 59%|█████▉ | 294/500 [01:33<01:01, 3.33it/s, loss=0.0499, lr=0.002]
Steps: 59%|█████▉ | 295/500 [01:33<01:08, 3.01it/s, loss=0.0499, lr=0.002]
a photo of one <s1><s2>
Steps: 59%|█████▉ | 295/500 [01:33<01:08, 3.01it/s, loss=0.00109, lr=0.002]
Steps: 59%|█████▉ | 296/500 [01:34<01:12, 2.81it/s, loss=0.00109, lr=0.002]
a photo of the clean <s1><s2>
tensor([[0.4088],
[0.4189]], device='cuda:0')
Current Norm : tensor([0.4070, 0.4151], device='cuda:0')
Steps: 59%|█████▉ | 296/500 [01:34<01:12, 2.81it/s, loss=0.00157, lr=0.002]
Steps: 59%|█████▉ | 297/500 [01:34<01:06, 3.05it/s, loss=0.00157, lr=0.002]
a cropped photo of the <s1><s2>
Steps: 59%|█████▉ | 297/500 [01:34<01:06, 3.05it/s, loss=0.000537, lr=0.002]
Steps: 60%|█████▉ | 298/500 [01:34<01:01, 3.29it/s, loss=0.000537, lr=0.002]
a rendition of the <s1><s2>
Steps: 60%|█████▉ | 298/500 [01:34<01:01, 3.29it/s, loss=0.000194, lr=0.002]
Steps: 60%|█████▉ | 299/500 [01:34<01:01, 3.27it/s, loss=0.000194, lr=0.002]
a photo of a clean <s1><s2>
Steps: 60%|█████▉ | 299/500 [01:34<01:01, 3.27it/s, loss=0.000989, lr=0.002]
Steps: 60%|██████ | 300/500 [01:35<00:57, 3.47it/s, loss=0.000989, lr=0.002]
a rendering of a <s1><s2>
tensor([[0.4086],
[0.4186]], device='cuda:0')
Current Norm : tensor([0.4069, 0.4148], device='cuda:0')
Steps: 60%|██████ | 300/500 [01:35<00:57, 3.47it/s, loss=0.0205, lr=0.002]
Steps: 60%|██████ | 301/500 [01:35<00:55, 3.56it/s, loss=0.0205, lr=0.002]
a cropped photo of a <s1><s2>
Steps: 60%|██████ | 301/500 [01:35<00:55, 3.56it/s, loss=0.0118, lr=0.002]
Steps: 60%|██████ | 302/500 [01:35<01:03, 3.12it/s, loss=0.0118, lr=0.002]
a photo of the small <s1><s2>
Steps: 60%|██████ | 302/500 [01:35<01:03, 3.12it/s, loss=0.00229, lr=0.002]
Steps: 61%|██████ | 303/500 [01:36<01:09, 2.84it/s, loss=0.00229, lr=0.002]
a good photo of the <s1><s2>
Steps: 61%|██████ | 303/500 [01:36<01:09, 2.84it/s, loss=8.45e-5, lr=0.002]
Steps: 61%|██████ | 304/500 [01:36<01:03, 3.08it/s, loss=8.45e-5, lr=0.002]
a photo of my <s1><s2>
tensor([[0.4085],
[0.4183]], device='cuda:0')
Current Norm : tensor([0.4068, 0.4146], device='cuda:0')
Steps: 61%|██████ | 304/500 [01:36<01:03, 3.08it/s, loss=0.0218, lr=0.002]
Steps: 61%|██████ | 305/500 [01:36<00:59, 3.30it/s, loss=0.0218, lr=0.002]
a good photo of the <s1><s2>
Steps: 61%|██████ | 305/500 [01:36<00:59, 3.30it/s, loss=0.000278, lr=0.002]
Steps: 61%|██████ | 306/500 [01:36<00:55, 3.48it/s, loss=0.000278, lr=0.002]
a photo of a clean <s1><s2>
Steps: 61%|██████ | 306/500 [01:36<00:55, 3.48it/s, loss=0.0216, lr=0.002]
Steps: 61%|██████▏ | 307/500 [01:37<00:53, 3.58it/s, loss=0.0216, lr=0.002]
a photo of a nice <s1><s2>
Steps: 61%|██████▏ | 307/500 [01:37<00:53, 3.58it/s, loss=0.0571, lr=0.002]
Steps: 62%|██████▏ | 308/500 [01:37<00:54, 3.51it/s, loss=0.0571, lr=0.002]
a photo of a small <s1><s2>
tensor([[0.4084],
[0.4179]], device='cuda:0')
Current Norm : tensor([0.4067, 0.4143], device='cuda:0')
Steps: 62%|██████▏ | 308/500 [01:37<00:54, 3.51it/s, loss=0.00128, lr=0.002]
Steps: 62%|██████▏ | 309/500 [01:37<01:01, 3.09it/s, loss=0.00128, lr=0.002]
a photo of a nice <s1><s2>
Steps: 62%|██████▏ | 309/500 [01:37<01:01, 3.09it/s, loss=0.000692, lr=0.002]
Steps: 62%|██████▏ | 310/500 [01:38<01:05, 2.88it/s, loss=0.000692, lr=0.002]
the photo of a <s1><s2>
Steps: 62%|██████▏ | 310/500 [01:38<01:05, 2.88it/s, loss=0.00332, lr=0.002]
Steps: 62%|██████▏ | 311/500 [01:38<01:01, 3.06it/s, loss=0.00332, lr=0.002]
a photo of the large <s1><s2>
Steps: 62%|██████▏ | 311/500 [01:38<01:01, 3.06it/s, loss=0.00511, lr=0.002]
Steps: 62%|██████▏ | 312/500 [01:38<00:57, 3.28it/s, loss=0.00511, lr=0.002]
a rendering of a <s1><s2>
tensor([[0.4082],
[0.4177]], device='cuda:0')
Current Norm : tensor([0.4065, 0.4141], device='cuda:0')
Steps: 62%|██████▏ | 312/500 [01:38<00:57, 3.28it/s, loss=0.00182, lr=0.002]
Steps: 63%|██████▎ | 313/500 [01:39<00:54, 3.43it/s, loss=0.00182, lr=0.002]
a rendition of a <s1><s2>
Steps: 63%|██████▎ | 313/500 [01:39<00:54, 3.43it/s, loss=0.00231, lr=0.002]
Steps: 63%|██████▎ | 314/500 [01:39<00:51, 3.62it/s, loss=0.00231, lr=0.002]
a rendition of a <s1><s2>
Steps: 63%|██████▎ | 314/500 [01:39<00:51, 3.62it/s, loss=0.0285, lr=0.002]
Steps: 63%|██████▎ | 315/500 [01:39<00:49, 3.73it/s, loss=0.0285, lr=0.002]
a photo of the clean <s1><s2>
Steps: 63%|██████▎ | 315/500 [01:39<00:49, 3.73it/s, loss=0.00596, lr=0.002]
Steps: 63%|██████▎ | 316/500 [01:40<00:57, 3.20it/s, loss=0.00596, lr=0.002]
a bright photo of the <s1><s2>
tensor([[0.4080],
[0.4176]], device='cuda:0')
Current Norm : tensor([0.4064, 0.4141], device='cuda:0')
Steps: 63%|██████▎ | 316/500 [01:40<00:57, 3.20it/s, loss=0.00627, lr=0.002]
Steps: 63%|██████▎ | 317/500 [01:40<00:54, 3.38it/s, loss=0.00627, lr=0.002]
a close-up photo of a <s1><s2>
Steps: 63%|██████▎ | 317/500 [01:40<00:54, 3.38it/s, loss=0.00346, lr=0.002]
Steps: 64%|██████▎ | 318/500 [01:40<00:51, 3.51it/s, loss=0.00346, lr=0.002]
a photo of a dirty <s1><s2>
Steps: 64%|██████▎ | 318/500 [01:40<00:51, 3.51it/s, loss=0.000953, lr=0.002]
Steps: 64%|██████▍ | 319/500 [01:40<01:00, 3.00it/s, loss=0.000953, lr=0.002]
a photo of the weird <s1><s2>
Steps: 64%|██████▍ | 319/500 [01:40<01:00, 3.00it/s, loss=0.000627, lr=0.002]
Steps: 64%|██████▍ | 320/500 [01:41<00:56, 3.20it/s, loss=0.000627, lr=0.002]
a photo of a clean <s1><s2>
tensor([[0.4079],
[0.4176]], device='cuda:0')
Current Norm : tensor([0.4063, 0.4141], device='cuda:0')
Steps: 64%|██████▍ | 320/500 [01:41<00:56, 3.20it/s, loss=0.0016, lr=0.002]
Steps: 64%|██████▍ | 321/500 [01:41<00:52, 3.38it/s, loss=0.0016, lr=0.002]
a photo of a cool <s1><s2>
Steps: 64%|██████▍ | 321/500 [01:41<00:52, 3.38it/s, loss=0.00399, lr=0.002]
Steps: 64%|██████▍ | 322/500 [01:41<00:52, 3.42it/s, loss=0.00399, lr=0.002]
a photo of a nice <s1><s2>
Steps: 64%|██████▍ | 322/500 [01:41<00:52, 3.42it/s, loss=0.000543, lr=0.002]
Steps: 65%|██████▍ | 323/500 [01:42<00:58, 3.02it/s, loss=0.000543, lr=0.002]
a close-up photo of a <s1><s2>
Steps: 65%|██████▍ | 323/500 [01:42<00:58, 3.02it/s, loss=0.00301, lr=0.002]
Steps: 65%|██████▍ | 324/500 [01:42<00:55, 3.17it/s, loss=0.00301, lr=0.002]
a close-up photo of a <s1><s2>
tensor([[0.4078],
[0.4176]], device='cuda:0')
Current Norm : tensor([0.4062, 0.4141], device='cuda:0')
Steps: 65%|██████▍ | 324/500 [01:42<00:55, 3.17it/s, loss=0.00776, lr=0.002]
Steps: 65%|██████▌ | 325/500 [01:42<01:00, 2.90it/s, loss=0.00776, lr=0.002]
a photo of a nice <s1><s2>
Steps: 65%|██████▌ | 325/500 [01:42<01:00, 2.90it/s, loss=0.00301, lr=0.002]
Steps: 65%|██████▌ | 326/500 [01:43<00:55, 3.13it/s, loss=0.00301, lr=0.002]
a close-up photo of the <s1><s2>
Steps: 65%|██████▌ | 326/500 [01:43<00:55, 3.13it/s, loss=0.00102, lr=0.002]
Steps: 65%|██████▌ | 327/500 [01:43<00:52, 3.32it/s, loss=0.00102, lr=0.002]
a cropped photo of the <s1><s2>
Steps: 65%|██████▌ | 327/500 [01:43<00:52, 3.32it/s, loss=0.000432, lr=0.002]
Steps: 66%|██████▌ | 328/500 [01:43<00:49, 3.49it/s, loss=0.000432, lr=0.002]
a close-up photo of the <s1><s2>
tensor([[0.4076],
[0.4175]], device='cuda:0')
Current Norm : tensor([0.4061, 0.4140], device='cuda:0')
Steps: 66%|██████▌ | 328/500 [01:43<00:49, 3.49it/s, loss=0.000583, lr=0.002]
Steps: 66%|██████▌ | 329/500 [01:43<00:49, 3.43it/s, loss=0.000583, lr=0.002]
a close-up photo of the <s1><s2>
Steps: 66%|██████▌ | 329/500 [01:43<00:49, 3.43it/s, loss=0.000281, lr=0.002]
Steps: 66%|██████▌ | 330/500 [01:44<00:48, 3.50it/s, loss=0.000281, lr=0.002]
a photo of a nice <s1><s2>
Steps: 66%|██████▌ | 330/500 [01:44<00:48, 3.50it/s, loss=0.00528, lr=0.002]
Steps: 66%|██████▌ | 331/500 [01:44<00:46, 3.65it/s, loss=0.00528, lr=0.002]
a photo of a nice <s1><s2>
Steps: 66%|██████▌ | 331/500 [01:44<00:46, 3.65it/s, loss=0.0451, lr=0.002]
Steps: 66%|██████▋ | 332/500 [01:44<00:55, 3.04it/s, loss=0.0451, lr=0.002]
a cropped photo of a <s1><s2>
tensor([[0.4074],
[0.4174]], device='cuda:0')
Current Norm : tensor([0.4059, 0.4139], device='cuda:0')
Steps: 66%|██████▋ | 332/500 [01:44<00:55, 3.04it/s, loss=0.000493, lr=0.002]
Steps: 67%|██████▋ | 333/500 [01:45<00:51, 3.22it/s, loss=0.000493, lr=0.002]
a photo of one <s1><s2>
Steps: 67%|██████▋ | 333/500 [01:45<00:51, 3.22it/s, loss=0.00374, lr=0.002]
Steps: 67%|██████▋ | 334/500 [01:45<00:49, 3.33it/s, loss=0.00374, lr=0.002]
a photo of my <s1><s2>
Steps: 67%|██████▋ | 334/500 [01:45<00:49, 3.33it/s, loss=0.00137, lr=0.002]
Steps: 67%|██████▋ | 335/500 [01:45<00:49, 3.35it/s, loss=0.00137, lr=0.002]
a rendering of a <s1><s2>
Steps: 67%|██████▋ | 335/500 [01:45<00:49, 3.35it/s, loss=0.0027, lr=0.002]
Steps: 67%|██████▋ | 336/500 [01:46<00:53, 3.06it/s, loss=0.0027, lr=0.002]
a photo of one <s1><s2>
tensor([[0.4074],
[0.4173]], device='cuda:0')
Current Norm : tensor([0.4059, 0.4138], device='cuda:0')
Steps: 67%|██████▋ | 336/500 [01:46<00:53, 3.06it/s, loss=0.000258, lr=0.002]
Steps: 67%|██████▋ | 337/500 [01:46<00:50, 3.22it/s, loss=0.000258, lr=0.002]
a photo of a small <s1><s2>
Steps: 67%|██████▋ | 337/500 [01:46<00:50, 3.22it/s, loss=0.0351, lr=0.002]
Steps: 68%|██████▊ | 338/500 [01:46<00:56, 2.89it/s, loss=0.0351, lr=0.002]
a photo of a clean <s1><s2>
Steps: 68%|██████▊ | 338/500 [01:46<00:56, 2.89it/s, loss=0.00653, lr=0.002]
Steps: 68%|██████▊ | 339/500 [01:47<00:59, 2.71it/s, loss=0.00653, lr=0.002]
a rendition of a <s1><s2>
Steps: 68%|██████▊ | 339/500 [01:47<00:59, 2.71it/s, loss=0.000804, lr=0.002]
Steps: 68%|██████▊ | 340/500 [01:47<00:52, 3.03it/s, loss=0.000804, lr=0.002]
a good photo of the <s1><s2>
tensor([[0.4072],
[0.4171]], device='cuda:0')
Current Norm : tensor([0.4057, 0.4137], device='cuda:0')
Steps: 68%|██████▊ | 340/500 [01:47<00:52, 3.03it/s, loss=0.0193, lr=0.002]
Steps: 68%|██████▊ | 341/500 [01:47<00:50, 3.14it/s, loss=0.0193, lr=0.002]
a photo of the large <s1><s2>
Steps: 68%|██████▊ | 341/500 [01:47<00:50, 3.14it/s, loss=0.000479, lr=0.002]
Steps: 68%|██████▊ | 342/500 [01:48<00:48, 3.26it/s, loss=0.000479, lr=0.002]
a close-up photo of a <s1><s2>
Steps: 68%|██████▊ | 342/500 [01:48<00:48, 3.26it/s, loss=0.0216, lr=0.002]
Steps: 69%|██████▊ | 343/500 [01:48<00:45, 3.45it/s, loss=0.0216, lr=0.002]
a photo of a nice <s1><s2>
Steps: 69%|██████▊ | 343/500 [01:48<00:45, 3.45it/s, loss=0.00175, lr=0.002]
Steps: 69%|██████▉ | 344/500 [01:48<00:45, 3.40it/s, loss=0.00175, lr=0.002]
a photo of the nice <s1><s2>
tensor([[0.4070],
[0.4169]], device='cuda:0')
Current Norm : tensor([0.4056, 0.4135], device='cuda:0')
Steps: 69%|██████▉ | 344/500 [01:48<00:45, 3.40it/s, loss=0.00301, lr=0.002]
Steps: 69%|██████▉ | 345/500 [01:48<00:44, 3.52it/s, loss=0.00301, lr=0.002]
a cropped photo of a <s1><s2>
Steps: 69%|██████▉ | 345/500 [01:48<00:44, 3.52it/s, loss=0.00423, lr=0.002]
Steps: 69%|██████▉ | 346/500 [01:49<00:48, 3.16it/s, loss=0.00423, lr=0.002]
a photo of a <s1><s2>
Steps: 69%|██████▉ | 346/500 [01:49<00:48, 3.16it/s, loss=0.00203, lr=0.002]
Steps: 69%|██████▉ | 347/500 [01:49<00:52, 2.91it/s, loss=0.00203, lr=0.002]
a photo of a clean <s1><s2>
Steps: 69%|██████▉ | 347/500 [01:49<00:52, 2.91it/s, loss=6.97e-5, lr=0.002]
Steps: 70%|██████▉ | 348/500 [01:49<00:48, 3.13it/s, loss=6.97e-5, lr=0.002]
a photo of one <s1><s2>
tensor([[0.4068],
[0.4168]], device='cuda:0')
Current Norm : tensor([0.4055, 0.4134], device='cuda:0')
Steps: 70%|██████▉ | 348/500 [01:49<00:48, 3.13it/s, loss=0.00816, lr=0.002]
Steps: 70%|██████▉ | 349/500 [01:50<00:46, 3.23it/s, loss=0.00816, lr=0.002]
a dark photo of the <s1><s2>
Steps: 70%|██████▉ | 349/500 [01:50<00:46, 3.23it/s, loss=0.00456, lr=0.002]
Steps: 70%|███████ | 350/500 [01:50<00:44, 3.40it/s, loss=0.00456, lr=0.002]
a cropped photo of the <s1><s2>
Steps: 70%|███████ | 350/500 [01:50<00:44, 3.40it/s, loss=0.0143, lr=0.002]
Steps: 70%|███████ | 351/500 [01:50<00:45, 3.26it/s, loss=0.0143, lr=0.002]
a rendition of the <s1><s2>
Steps: 70%|███████ | 351/500 [01:50<00:45, 3.26it/s, loss=0.00219, lr=0.002]
Steps: 70%|███████ | 352/500 [01:51<00:43, 3.42it/s, loss=0.00219, lr=0.002]
a rendition of the <s1><s2>
tensor([[0.4066],
[0.4167]], device='cuda:0')
Current Norm : tensor([0.4053, 0.4134], device='cuda:0')
Steps: 70%|███████ | 352/500 [01:51<00:43, 3.42it/s, loss=0.0016, lr=0.002]
Steps: 71%|███████ | 353/500 [01:51<00:48, 3.05it/s, loss=0.0016, lr=0.002]
a photo of a <s1><s2>
Steps: 71%|███████ | 353/500 [01:51<00:48, 3.05it/s, loss=0.0017, lr=0.002]
Steps: 71%|███████ | 354/500 [01:51<00:44, 3.25it/s, loss=0.0017, lr=0.002]
a photo of a <s1><s2>
Steps: 71%|███████ | 354/500 [01:51<00:44, 3.25it/s, loss=0.00208, lr=0.002]
Steps: 71%|███████ | 355/500 [01:52<00:42, 3.40it/s, loss=0.00208, lr=0.002]
a photo of a small <s1><s2>
Steps: 71%|███████ | 355/500 [01:52<00:42, 3.40it/s, loss=0.0226, lr=0.002]
Steps: 71%|███████ | 356/500 [01:52<00:40, 3.57it/s, loss=0.0226, lr=0.002]
a rendition of the <s1><s2>
tensor([[0.4061],
[0.4166]], device='cuda:0')
Current Norm : tensor([0.4049, 0.4133], device='cuda:0')
Steps: 71%|███████ | 356/500 [01:52<00:40, 3.57it/s, loss=0.0256, lr=0.002]
Steps: 71%|███████▏ | 357/500 [01:52<00:47, 3.04it/s, loss=0.0256, lr=0.002]
a rendering of a <s1><s2>
Steps: 71%|███████▏ | 357/500 [01:52<00:47, 3.04it/s, loss=0.0046, lr=0.002]
Steps: 72%|███████▏ | 358/500 [01:53<00:50, 2.80it/s, loss=0.0046, lr=0.002]
a photo of a dirty <s1><s2>
Steps: 72%|███████▏ | 358/500 [01:53<00:50, 2.80it/s, loss=0.000236, lr=0.002]
Steps: 72%|███████▏ | 359/500 [01:53<00:45, 3.08it/s, loss=0.000236, lr=0.002]
a photo of the clean <s1><s2>
Steps: 72%|███████▏ | 359/500 [01:53<00:45, 3.08it/s, loss=0.0477, lr=0.002]
Steps: 72%|███████▏ | 360/500 [01:53<00:42, 3.26it/s, loss=0.0477, lr=0.002]
a photo of my <s1><s2>
tensor([[0.4058],
[0.4167]], device='cuda:0')
Current Norm : tensor([0.4047, 0.4134], device='cuda:0')
Steps: 72%|███████▏ | 360/500 [01:53<00:42, 3.26it/s, loss=0.000432, lr=0.002]
Steps: 72%|███████▏ | 361/500 [01:53<00:40, 3.43it/s, loss=0.000432, lr=0.002]
a rendition of the <s1><s2>
Steps: 72%|███████▏ | 361/500 [01:53<00:40, 3.43it/s, loss=0.0165, lr=0.002]
Steps: 72%|███████▏ | 362/500 [01:54<00:44, 3.12it/s, loss=0.0165, lr=0.002]
a rendering of a <s1><s2>
Steps: 72%|███████▏ | 362/500 [01:54<00:44, 3.12it/s, loss=0.000304, lr=0.002]
Steps: 73%|███████▎ | 363/500 [01:54<00:41, 3.27it/s, loss=0.000304, lr=0.002]
a good photo of a <s1><s2>
Steps: 73%|███████▎ | 363/500 [01:54<00:41, 3.27it/s, loss=0.00245, lr=0.002]
Steps: 73%|███████▎ | 364/500 [01:54<00:40, 3.36it/s, loss=0.00245, lr=0.002]
a photo of the large <s1><s2>
tensor([[0.4056],
[0.4169]], device='cuda:0')
Current Norm : tensor([0.4045, 0.4135], device='cuda:0')
Steps: 73%|███████▎ | 364/500 [01:54<00:40, 3.36it/s, loss=0.000128, lr=0.002]
Steps: 73%|███████▎ | 365/500 [01:55<00:41, 3.25it/s, loss=0.000128, lr=0.002]
a photo of the large <s1><s2>
Steps: 73%|███████▎ | 365/500 [01:55<00:41, 3.25it/s, loss=0.00679, lr=0.002]
Steps: 73%|███████▎ | 366/500 [01:55<00:44, 2.98it/s, loss=0.00679, lr=0.002]
a close-up photo of the <s1><s2>
Steps: 73%|███████▎ | 366/500 [01:55<00:44, 2.98it/s, loss=0.00325, lr=0.002]
Steps: 73%|███████▎ | 367/500 [01:55<00:41, 3.17it/s, loss=0.00325, lr=0.002]
a bright photo of the <s1><s2>
Steps: 73%|███████▎ | 367/500 [01:55<00:41, 3.17it/s, loss=0.000236, lr=0.002]
Steps: 74%|███████▎ | 368/500 [01:56<00:38, 3.40it/s, loss=0.000236, lr=0.002]
a photo of a <s1><s2>
tensor([[0.4055],
[0.4172]], device='cuda:0')
Current Norm : tensor([0.4044, 0.4138], device='cuda:0')
Steps: 74%|███████▎ | 368/500 [01:56<00:38, 3.40it/s, loss=0.0098, lr=0.002]
Steps: 74%|███████▍ | 369/500 [01:56<00:38, 3.44it/s, loss=0.0098, lr=0.002]
a bright photo of the <s1><s2>
Steps: 74%|███████▍ | 369/500 [01:56<00:38, 3.44it/s, loss=0.00368, lr=0.002]
Steps: 74%|███████▍ | 370/500 [01:56<00:41, 3.15it/s, loss=0.00368, lr=0.002]
a photo of a dirty <s1><s2>
Steps: 74%|███████▍ | 370/500 [01:56<00:41, 3.15it/s, loss=0.00132, lr=0.002]
Steps: 74%|███████▍ | 371/500 [01:57<00:38, 3.33it/s, loss=0.00132, lr=0.002]
a good photo of a <s1><s2>
Steps: 74%|███████▍ | 371/500 [01:57<00:38, 3.33it/s, loss=0.0449, lr=0.002]
Steps: 74%|███████▍ | 372/500 [01:57<00:36, 3.47it/s, loss=0.0449, lr=0.002]
a photo of a cool <s1><s2>
tensor([[0.4054],
[0.4175]], device='cuda:0')
Current Norm : tensor([0.4043, 0.4140], device='cuda:0')
Steps: 74%|███████▍ | 372/500 [01:57<00:36, 3.47it/s, loss=0.000366, lr=0.002]
Steps: 75%|███████▍ | 373/500 [01:57<00:37, 3.40it/s, loss=0.000366, lr=0.002]
a good photo of the <s1><s2>
Steps: 75%|███████▍ | 373/500 [01:57<00:37, 3.40it/s, loss=0.00709, lr=0.002]
Steps: 75%|███████▍ | 374/500 [01:58<00:42, 2.99it/s, loss=0.00709, lr=0.002]
a photo of the cool <s1><s2>
Steps: 75%|███████▍ | 374/500 [01:58<00:42, 2.99it/s, loss=0.00246, lr=0.002]
Steps: 75%|███████▌ | 375/500 [01:58<00:45, 2.75it/s, loss=0.00246, lr=0.002]
a rendering of a <s1><s2>
Steps: 75%|███████▌ | 375/500 [01:58<00:45, 2.75it/s, loss=0.0151, lr=0.002]
Steps: 75%|███████▌ | 376/500 [01:58<00:41, 3.01it/s, loss=0.0151, lr=0.002]
a photo of the weird <s1><s2>
tensor([[0.4055],
[0.4177]], device='cuda:0')
Current Norm : tensor([0.4044, 0.4142], device='cuda:0')
Steps: 75%|███████▌ | 376/500 [01:58<00:41, 3.01it/s, loss=0.00427, lr=0.002]
Steps: 75%|███████▌ | 377/500 [01:59<00:38, 3.20it/s, loss=0.00427, lr=0.002]
a photo of a nice <s1><s2>
Steps: 75%|███████▌ | 377/500 [01:59<00:38, 3.20it/s, loss=0.000826, lr=0.002]
Steps: 76%|███████▌ | 378/500 [01:59<00:35, 3.41it/s, loss=0.000826, lr=0.002]
a cropped photo of the <s1><s2>
Steps: 76%|███████▌ | 378/500 [01:59<00:35, 3.41it/s, loss=0.00124, lr=0.002]
Steps: 76%|███████▌ | 379/500 [01:59<00:34, 3.55it/s, loss=0.00124, lr=0.002]
a photo of the small <s1><s2>
Steps: 76%|███████▌ | 379/500 [01:59<00:34, 3.55it/s, loss=0.0174, lr=0.002]
Steps: 76%|███████▌ | 380/500 [01:59<00:37, 3.23it/s, loss=0.0174, lr=0.002]
a rendering of a <s1><s2>
tensor([[0.4051],
[0.4178]], device='cuda:0')
Current Norm : tensor([0.4041, 0.4143], device='cuda:0')
Steps: 76%|███████▌ | 380/500 [01:59<00:37, 3.23it/s, loss=0.000934, lr=0.002]
Steps: 76%|███████▌ | 381/500 [02:00<00:35, 3.36it/s, loss=0.000934, lr=0.002]
a close-up photo of a <s1><s2>
Steps: 76%|███████▌ | 381/500 [02:00<00:35, 3.36it/s, loss=0.0217, lr=0.002]
Steps: 76%|███████▋ | 382/500 [02:00<00:33, 3.48it/s, loss=0.0217, lr=0.002]
a photo of the nice <s1><s2>
Steps: 76%|███████▋ | 382/500 [02:00<00:33, 3.48it/s, loss=0.00576, lr=0.002]
Steps: 77%|███████▋ | 383/500 [02:00<00:37, 3.08it/s, loss=0.00576, lr=0.002]
a cropped photo of the <s1><s2>
Steps: 77%|███████▋ | 383/500 [02:00<00:37, 3.08it/s, loss=0.00097, lr=0.002]
Steps: 77%|███████▋ | 384/500 [02:01<00:36, 3.15it/s, loss=0.00097, lr=0.002]
a photo of one <s1><s2>
tensor([[0.4049],
[0.4182]], device='cuda:0')
Current Norm : tensor([0.4039, 0.4146], device='cuda:0')
Steps: 77%|███████▋ | 384/500 [02:01<00:36, 3.15it/s, loss=0.00606, lr=0.002]
Steps: 77%|███████▋ | 385/500 [02:01<00:34, 3.35it/s, loss=0.00606, lr=0.002]
a photo of a nice <s1><s2>
Steps: 77%|███████▋ | 385/500 [02:01<00:34, 3.35it/s, loss=0.1, lr=0.002]
Steps: 77%|███████▋ | 386/500 [02:01<00:32, 3.50it/s, loss=0.1, lr=0.002]
a rendition of a <s1><s2>
Steps: 77%|███████▋ | 386/500 [02:01<00:32, 3.50it/s, loss=0.001, lr=0.002]
Steps: 77%|███████▋ | 387/500 [02:01<00:31, 3.59it/s, loss=0.001, lr=0.002]
a photo of a <s1><s2>
Steps: 77%|███████▋ | 387/500 [02:01<00:31, 3.59it/s, loss=0.0502, lr=0.002]
Steps: 78%|███████▊ | 388/500 [02:02<00:30, 3.66it/s, loss=0.0502, lr=0.002]
a photo of a <s1><s2>
tensor([[0.4048],
[0.4187]], device='cuda:0')
Current Norm : tensor([0.4039, 0.4149], device='cuda:0')
Steps: 78%|███████▊ | 388/500 [02:02<00:30, 3.66it/s, loss=0.000544, lr=0.002]
Steps: 78%|███████▊ | 389/500 [02:02<00:34, 3.20it/s, loss=0.000544, lr=0.002]
a dark photo of the <s1><s2>
Steps: 78%|███████▊ | 389/500 [02:02<00:34, 3.20it/s, loss=0.00028, lr=0.002]
Steps: 78%|███████▊ | 390/500 [02:02<00:32, 3.40it/s, loss=0.00028, lr=0.002]
a photo of the <s1><s2>
Steps: 78%|███████▊ | 390/500 [02:02<00:32, 3.40it/s, loss=0.00026, lr=0.002]
Steps: 78%|███████▊ | 391/500 [02:03<00:31, 3.42it/s, loss=0.00026, lr=0.002]
a close-up photo of the <s1><s2>
Steps: 78%|███████▊ | 391/500 [02:03<00:31, 3.42it/s, loss=0.00749, lr=0.002]
Steps: 78%|███████▊ | 392/500 [02:03<00:35, 3.07it/s, loss=0.00749, lr=0.002]
a rendition of a <s1><s2>
tensor([[0.4048],
[0.4192]], device='cuda:0')
Current Norm : tensor([0.4038, 0.4153], device='cuda:0')
Steps: 78%|███████▊ | 392/500 [02:03<00:35, 3.07it/s, loss=0.000102, lr=0.002]
Steps: 79%|███████▊ | 393/500 [02:03<00:33, 3.21it/s, loss=0.000102, lr=0.002]
a photo of the large <s1><s2>
Steps: 79%|███████▊ | 393/500 [02:03<00:33, 3.21it/s, loss=0.0169, lr=0.002]
Steps: 79%|███████▉ | 394/500 [02:04<00:31, 3.36it/s, loss=0.0169, lr=0.002]
a bright photo of the <s1><s2>
Steps: 79%|███████▉ | 394/500 [02:04<00:31, 3.36it/s, loss=0.0099, lr=0.002]
Steps: 79%|███████▉ | 395/500 [02:04<00:30, 3.50it/s, loss=0.0099, lr=0.002]
a photo of the large <s1><s2>
Steps: 79%|███████▉ | 395/500 [02:04<00:30, 3.50it/s, loss=0.0231, lr=0.002]
Steps: 79%|███████▉ | 396/500 [02:04<00:32, 3.17it/s, loss=0.0231, lr=0.002]
a photo of the clean <s1><s2>
tensor([[0.4047],
[0.4195]], device='cuda:0')
Current Norm : tensor([0.4038, 0.4156], device='cuda:0')
Steps: 79%|███████▉ | 396/500 [02:04<00:32, 3.17it/s, loss=0.00311, lr=0.002]
Steps: 79%|███████▉ | 397/500 [02:05<00:35, 2.93it/s, loss=0.00311, lr=0.002]
a photo of a cool <s1><s2>
Steps: 79%|███████▉ | 397/500 [02:05<00:35, 2.93it/s, loss=0.00203, lr=0.002]
Steps: 80%|███████▉ | 398/500 [02:05<00:33, 3.09it/s, loss=0.00203, lr=0.002]
a photo of the cool <s1><s2>
Steps: 80%|███████▉ | 398/500 [02:05<00:33, 3.09it/s, loss=0.00674, lr=0.002]
Steps: 80%|███████▉ | 399/500 [02:05<00:30, 3.27it/s, loss=0.00674, lr=0.002]
a cropped photo of the <s1><s2>
Steps: 80%|███████▉ | 399/500 [02:05<00:30, 3.27it/s, loss=0.0243, lr=0.002]
Steps: 80%|████████ | 400/500 [02:05<00:29, 3.39it/s, loss=0.0243, lr=0.002]
a photo of a small <s1><s2>
tensor([[0.4048],
[0.4197]], device='cuda:0')
Current Norm : tensor([0.4039, 0.4157], device='cuda:0')
Steps: 80%|████████ | 400/500 [02:05<00:29, 3.39it/s, loss=0.00191, lr=0.002]
Steps: 80%|████████ | 401/500 [02:06<00:28, 3.45it/s, loss=0.00191, lr=0.002]
a photo of the nice <s1><s2>
Steps: 80%|████████ | 401/500 [02:06<00:28, 3.45it/s, loss=0.00297, lr=0.002]
Steps: 80%|████████ | 402/500 [02:06<00:31, 3.12it/s, loss=0.00297, lr=0.002]
a photo of one <s1><s2>
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Steps: 81%|████████ | 403/500 [02:06<00:29, 3.34it/s, loss=0.00573, lr=0.002]
a rendering of a <s1><s2>
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Steps: 81%|████████ | 404/500 [02:07<00:27, 3.47it/s, loss=0.00609, lr=0.002]
a photo of the <s1><s2>
tensor([[0.4050],
[0.4199]], device='cuda:0')
Current Norm : tensor([0.4040, 0.4159], device='cuda:0')
Steps: 81%|████████ | 404/500 [02:07<00:27, 3.47it/s, loss=0.00128, lr=0.002]
Steps: 81%|████████ | 405/500 [02:07<00:27, 3.47it/s, loss=0.00128, lr=0.002]
a rendering of a <s1><s2>
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Steps: 81%|████████ | 406/500 [02:07<00:29, 3.16it/s, loss=0.000457, lr=0.002]
a photo of my <s1><s2>
Steps: 81%|████████ | 406/500 [02:07<00:29, 3.16it/s, loss=0.00127, lr=0.002]
Steps: 81%|████████▏ | 407/500 [02:08<00:27, 3.34it/s, loss=0.00127, lr=0.002]
a good photo of a <s1><s2>
Steps: 81%|████████▏ | 407/500 [02:08<00:27, 3.34it/s, loss=0.00103, lr=0.002]
Steps: 82%|████████▏ | 408/500 [02:08<00:26, 3.53it/s, loss=0.00103, lr=0.002]
a photo of a small <s1><s2>
tensor([[0.4052],
[0.4202]], device='cuda:0')
Current Norm : tensor([0.4042, 0.4162], device='cuda:0')
Steps: 82%|████████▏ | 408/500 [02:08<00:26, 3.53it/s, loss=0.0124, lr=0.002]
Steps: 82%|████████▏ | 409/500 [02:08<00:29, 3.13it/s, loss=0.0124, lr=0.002]
a good photo of a <s1><s2>
Steps: 82%|████████▏ | 409/500 [02:08<00:29, 3.13it/s, loss=0.000434, lr=0.002]
Steps: 82%|████████▏ | 410/500 [02:08<00:28, 3.18it/s, loss=0.000434, lr=0.002]
a photo of the weird <s1><s2>
Steps: 82%|████████▏ | 410/500 [02:08<00:28, 3.18it/s, loss=0.00527, lr=0.002]
Steps: 82%|████████▏ | 411/500 [02:09<00:26, 3.41it/s, loss=0.00527, lr=0.002]
a cropped photo of the <s1><s2>
Steps: 82%|████████▏ | 411/500 [02:09<00:26, 3.41it/s, loss=0.0125, lr=0.002]
Steps: 82%|████████▏ | 412/500 [02:09<00:24, 3.55it/s, loss=0.0125, lr=0.002]
a photo of a cool <s1><s2>
tensor([[0.4055],
[0.4207]], device='cuda:0')
Current Norm : tensor([0.4044, 0.4166], device='cuda:0')
Steps: 82%|████████▏ | 412/500 [02:09<00:24, 3.55it/s, loss=0.000284, lr=0.002]
Steps: 83%|████████▎ | 413/500 [02:09<00:27, 3.20it/s, loss=0.000284, lr=0.002]
a photo of a nice <s1><s2>
Steps: 83%|████████▎ | 413/500 [02:09<00:27, 3.20it/s, loss=0.00788, lr=0.002]
Steps: 83%|████████▎ | 414/500 [02:10<00:28, 3.00it/s, loss=0.00788, lr=0.002]
a close-up photo of a <s1><s2>
Steps: 83%|████████▎ | 414/500 [02:10<00:28, 3.00it/s, loss=0.000378, lr=0.002]
Steps: 83%|████████▎ | 415/500 [02:10<00:26, 3.26it/s, loss=0.000378, lr=0.002]
a photo of a nice <s1><s2>
Steps: 83%|████████▎ | 415/500 [02:10<00:26, 3.26it/s, loss=0.000508, lr=0.002]
Steps: 83%|████████▎ | 416/500 [02:10<00:25, 3.26it/s, loss=0.000508, lr=0.002]
a photo of a small <s1><s2>
tensor([[0.4056],
[0.4212]], device='cuda:0')
Current Norm : tensor([0.4045, 0.4170], device='cuda:0')
Steps: 83%|████████▎ | 416/500 [02:10<00:25, 3.26it/s, loss=0.00534, lr=0.002]
Steps: 83%|████████▎ | 417/500 [02:11<00:24, 3.39it/s, loss=0.00534, lr=0.002]
a photo of a small <s1><s2>
Steps: 83%|████████▎ | 417/500 [02:11<00:24, 3.39it/s, loss=0.0287, lr=0.002]
Steps: 84%|████████▎ | 418/500 [02:11<00:23, 3.50it/s, loss=0.0287, lr=0.002]
a good photo of the <s1><s2>
Steps: 84%|████████▎ | 418/500 [02:11<00:23, 3.50it/s, loss=0.000909, lr=0.002]
Steps: 84%|████████▍ | 419/500 [02:11<00:26, 3.07it/s, loss=0.000909, lr=0.002]
a close-up photo of a <s1><s2>
Steps: 84%|████████▍ | 419/500 [02:11<00:26, 3.07it/s, loss=0.0042, lr=0.002]
Steps: 84%|████████▍ | 420/500 [02:12<00:24, 3.27it/s, loss=0.0042, lr=0.002]
a photo of a nice <s1><s2>
tensor([[0.4057],
[0.4215]], device='cuda:0')
Current Norm : tensor([0.4046, 0.4172], device='cuda:0')
Steps: 84%|████████▍ | 420/500 [02:12<00:24, 3.27it/s, loss=0.236, lr=0.002]
Steps: 84%|████████▍ | 421/500 [02:12<00:26, 2.93it/s, loss=0.236, lr=0.002]
a rendering of a <s1><s2>
Steps: 84%|████████▍ | 421/500 [02:12<00:26, 2.93it/s, loss=0.00945, lr=0.002]
Steps: 84%|████████▍ | 422/500 [02:12<00:25, 3.09it/s, loss=0.00945, lr=0.002]
a close-up photo of the <s1><s2>
Steps: 84%|████████▍ | 422/500 [02:12<00:25, 3.09it/s, loss=0.000273, lr=0.002]
Steps: 85%|████████▍ | 423/500 [02:13<00:24, 3.18it/s, loss=0.000273, lr=0.002]
a good photo of the <s1><s2>
Steps: 85%|████████▍ | 423/500 [02:13<00:24, 3.18it/s, loss=0.0115, lr=0.002]
Steps: 85%|████████▍ | 424/500 [02:13<00:25, 2.95it/s, loss=0.0115, lr=0.002]
a dark photo of the <s1><s2>
tensor([[0.4058],
[0.4217]], device='cuda:0')
Current Norm : tensor([0.4046, 0.4173], device='cuda:0')
Steps: 85%|████████▍ | 424/500 [02:13<00:25, 2.95it/s, loss=0.00332, lr=0.002]
Steps: 85%|████████▌ | 425/500 [02:13<00:24, 3.11it/s, loss=0.00332, lr=0.002]
a photo of the small <s1><s2>
Steps: 85%|████████▌ | 425/500 [02:13<00:24, 3.11it/s, loss=0.0154, lr=0.002]
Steps: 85%|████████▌ | 426/500 [02:13<00:22, 3.33it/s, loss=0.0154, lr=0.002]
a photo of the large <s1><s2>
Steps: 85%|████████▌ | 426/500 [02:13<00:22, 3.33it/s, loss=0.00687, lr=0.002]
Steps: 85%|████████▌ | 427/500 [02:14<00:21, 3.44it/s, loss=0.00687, lr=0.002]
a photo of a nice <s1><s2>
Steps: 85%|████████▌ | 427/500 [02:14<00:21, 3.44it/s, loss=0.00678, lr=0.002]
Steps: 86%|████████▌ | 428/500 [02:14<00:22, 3.16it/s, loss=0.00678, lr=0.002]
a photo of the clean <s1><s2>
tensor([[0.4058],
[0.4216]], device='cuda:0')
Current Norm : tensor([0.4046, 0.4173], device='cuda:0')
Steps: 86%|████████▌ | 428/500 [02:14<00:22, 3.16it/s, loss=0.000409, lr=0.002]
Steps: 86%|████████▌ | 429/500 [02:14<00:21, 3.35it/s, loss=0.000409, lr=0.002]
a photo of the cool <s1><s2>
Steps: 86%|████████▌ | 429/500 [02:14<00:21, 3.35it/s, loss=0.015, lr=0.002]
Steps: 86%|████████▌ | 430/500 [02:15<00:19, 3.51it/s, loss=0.015, lr=0.002]
a photo of a clean <s1><s2>
Steps: 86%|████████▌ | 430/500 [02:15<00:19, 3.51it/s, loss=0.000181, lr=0.002]
Steps: 86%|████████▌ | 431/500 [02:15<00:19, 3.46it/s, loss=0.000181, lr=0.002]
a cropped photo of the <s1><s2>
Steps: 86%|████████▌ | 431/500 [02:15<00:19, 3.46it/s, loss=0.00528, lr=0.002]
Steps: 86%|████████▋ | 432/500 [02:15<00:18, 3.62it/s, loss=0.00528, lr=0.002]
a photo of one <s1><s2>
tensor([[0.4057],
[0.4215]], device='cuda:0')
Current Norm : tensor([0.4046, 0.4172], device='cuda:0')
Steps: 86%|████████▋ | 432/500 [02:15<00:18, 3.62it/s, loss=0.042, lr=0.002]
Steps: 87%|████████▋ | 433/500 [02:15<00:18, 3.65it/s, loss=0.042, lr=0.002]
a cropped photo of the <s1><s2>
Steps: 87%|████████▋ | 433/500 [02:15<00:18, 3.65it/s, loss=0.00523, lr=0.002]
Steps: 87%|████████▋ | 434/500 [02:16<00:20, 3.18it/s, loss=0.00523, lr=0.002]
a good photo of the <s1><s2>
Steps: 87%|████████▋ | 434/500 [02:16<00:20, 3.18it/s, loss=0.0014, lr=0.002]
Steps: 87%|████████▋ | 435/500 [02:16<00:20, 3.25it/s, loss=0.0014, lr=0.002]
a close-up photo of the <s1><s2>
Steps: 87%|████████▋ | 435/500 [02:16<00:20, 3.25it/s, loss=0.00769, lr=0.002]
Steps: 87%|████████▋ | 436/500 [02:16<00:18, 3.38it/s, loss=0.00769, lr=0.002]
a cropped photo of the <s1><s2>
tensor([[0.4057],
[0.4215]], device='cuda:0')
Current Norm : tensor([0.4046, 0.4172], device='cuda:0')
Steps: 87%|████████▋ | 436/500 [02:16<00:18, 3.38it/s, loss=0.00411, lr=0.002]
Steps: 87%|████████▋ | 437/500 [02:17<00:18, 3.47it/s, loss=0.00411, lr=0.002]
the photo of a <s1><s2>
Steps: 87%|████████▋ | 437/500 [02:17<00:18, 3.47it/s, loss=0.000765, lr=0.002]
Steps: 88%|████████▊ | 438/500 [02:17<00:20, 3.02it/s, loss=0.000765, lr=0.002]
a photo of a small <s1><s2>
Steps: 88%|████████▊ | 438/500 [02:17<00:20, 3.02it/s, loss=0.000131, lr=0.002]
Steps: 88%|████████▊ | 439/500 [02:17<00:18, 3.23it/s, loss=0.000131, lr=0.002]
a photo of a nice <s1><s2>
Steps: 88%|████████▊ | 439/500 [02:17<00:18, 3.23it/s, loss=0.0151, lr=0.002]
Steps: 88%|████████▊ | 440/500 [02:18<00:17, 3.37it/s, loss=0.0151, lr=0.002]
a photo of the weird <s1><s2>
tensor([[0.4057],
[0.4213]], device='cuda:0')
Current Norm : tensor([0.4046, 0.4170], device='cuda:0')
Steps: 88%|████████▊ | 440/500 [02:18<00:17, 3.37it/s, loss=0.0165, lr=0.002]
Steps: 88%|████████▊ | 441/500 [02:18<00:19, 2.99it/s, loss=0.0165, lr=0.002]
a photo of my <s1><s2>
Steps: 88%|████████▊ | 441/500 [02:18<00:19, 2.99it/s, loss=0.000117, lr=0.002]
Steps: 88%|████████▊ | 442/500 [02:18<00:18, 3.21it/s, loss=0.000117, lr=0.002]
a rendering of a <s1><s2>
Steps: 88%|████████▊ | 442/500 [02:18<00:18, 3.21it/s, loss=0.0148, lr=0.002]
Steps: 89%|████████▊ | 443/500 [02:19<00:16, 3.37it/s, loss=0.0148, lr=0.002]
a rendition of a <s1><s2>
Steps: 89%|████████▊ | 443/500 [02:19<00:16, 3.37it/s, loss=0.00175, lr=0.002]
Steps: 89%|████████▉ | 444/500 [02:19<00:18, 3.08it/s, loss=0.00175, lr=0.002]
a photo of a clean <s1><s2>
tensor([[0.4056],
[0.4213]], device='cuda:0')
Current Norm : tensor([0.4044, 0.4170], device='cuda:0')
Steps: 89%|████████▉ | 444/500 [02:19<00:18, 3.08it/s, loss=0.000158, lr=0.002]
Steps: 89%|████████▉ | 445/500 [02:19<00:17, 3.22it/s, loss=0.000158, lr=0.002]
the photo of a <s1><s2>
Steps: 89%|████████▉ | 445/500 [02:19<00:17, 3.22it/s, loss=0.0253, lr=0.002]
Steps: 89%|████████▉ | 446/500 [02:20<00:16, 3.26it/s, loss=0.0253, lr=0.002]
a photo of a <s1><s2>
Steps: 89%|████████▉ | 446/500 [02:20<00:16, 3.26it/s, loss=0.00205, lr=0.002]
Steps: 89%|████████▉ | 447/500 [02:20<00:15, 3.38it/s, loss=0.00205, lr=0.002]
a photo of the small <s1><s2>
Steps: 89%|████████▉ | 447/500 [02:20<00:15, 3.38it/s, loss=0.062, lr=0.002]
Steps: 90%|████████▉ | 448/500 [02:20<00:17, 2.95it/s, loss=0.062, lr=0.002]
a photo of the large <s1><s2>
tensor([[0.4054],
[0.4213]], device='cuda:0')
Current Norm : tensor([0.4044, 0.4170], device='cuda:0')
Steps: 90%|████████▉ | 448/500 [02:20<00:17, 2.95it/s, loss=0.00169, lr=0.002]
Steps: 90%|████████▉ | 449/500 [02:20<00:16, 3.13it/s, loss=0.00169, lr=0.002]
a photo of one <s1><s2>
Steps: 90%|████████▉ | 449/500 [02:20<00:16, 3.13it/s, loss=0.0322, lr=0.002]
Steps: 90%|█████████ | 450/500 [02:21<00:15, 3.27it/s, loss=0.0322, lr=0.002]
a dark photo of the <s1><s2>
Steps: 90%|█████████ | 450/500 [02:21<00:15, 3.27it/s, loss=0.00691, lr=0.002]
Steps: 90%|█████████ | 451/500 [02:21<00:16, 2.90it/s, loss=0.00691, lr=0.002]
a photo of the <s1><s2>
Steps: 90%|█████████ | 451/500 [02:21<00:16, 2.90it/s, loss=0.000433, lr=0.002]
Steps: 90%|█████████ | 452/500 [02:22<00:17, 2.75it/s, loss=0.000433, lr=0.002]
a photo of the nice <s1><s2>
tensor([[0.4054],
[0.4212]], device='cuda:0')
Current Norm : tensor([0.4043, 0.4170], device='cuda:0')
Steps: 90%|█████████ | 452/500 [02:22<00:17, 2.75it/s, loss=0.00901, lr=0.002]
Steps: 91%|█████████ | 453/500 [02:22<00:15, 3.03it/s, loss=0.00901, lr=0.002]
a bright photo of the <s1><s2>
Steps: 91%|█████████ | 453/500 [02:22<00:15, 3.03it/s, loss=0.0388, lr=0.002]
Steps: 91%|█████████ | 454/500 [02:22<00:14, 3.27it/s, loss=0.0388, lr=0.002]
a rendition of a <s1><s2>
Steps: 91%|█████████ | 454/500 [02:22<00:14, 3.27it/s, loss=0.0913, lr=0.002]
Steps: 91%|█████████ | 455/500 [02:22<00:12, 3.48it/s, loss=0.0913, lr=0.002]
a cropped photo of the <s1><s2>
Steps: 91%|█████████ | 455/500 [02:22<00:12, 3.48it/s, loss=0.0244, lr=0.002]
Steps: 91%|█████████ | 456/500 [02:23<00:14, 3.05it/s, loss=0.0244, lr=0.002]
a photo of the <s1><s2>
tensor([[0.4054],
[0.4211]], device='cuda:0')
Current Norm : tensor([0.4043, 0.4169], device='cuda:0')
Steps: 91%|█████████ | 456/500 [02:23<00:14, 3.05it/s, loss=0.0045, lr=0.002]
Steps: 91%|█████████▏| 457/500 [02:23<00:13, 3.24it/s, loss=0.0045, lr=0.002]
a rendering of a <s1><s2>
Steps: 91%|█████████▏| 457/500 [02:23<00:13, 3.24it/s, loss=0.00231, lr=0.002]
Steps: 92%|█████████▏| 458/500 [02:23<00:12, 3.45it/s, loss=0.00231, lr=0.002]
a photo of a dirty <s1><s2>
Steps: 92%|█████████▏| 458/500 [02:23<00:12, 3.45it/s, loss=0.0285, lr=0.002]
Steps: 92%|█████████▏| 459/500 [02:24<00:11, 3.57it/s, loss=0.0285, lr=0.002]
a cropped photo of a <s1><s2>
Steps: 92%|█████████▏| 459/500 [02:24<00:11, 3.57it/s, loss=0.00767, lr=0.002]
Steps: 92%|█████████▏| 460/500 [02:24<00:12, 3.18it/s, loss=0.00767, lr=0.002]
a close-up photo of the <s1><s2>
tensor([[0.4056],
[0.4210]], device='cuda:0')
Current Norm : tensor([0.4044, 0.4168], device='cuda:0')
Steps: 92%|█████████▏| 460/500 [02:24<00:12, 3.18it/s, loss=0.00317, lr=0.002]
Steps: 92%|█████████▏| 461/500 [02:24<00:12, 3.17it/s, loss=0.00317, lr=0.002]
a photo of the nice <s1><s2>
Steps: 92%|█████████▏| 461/500 [02:24<00:12, 3.17it/s, loss=0.000814, lr=0.002]
Steps: 92%|█████████▏| 462/500 [02:25<00:11, 3.34it/s, loss=0.000814, lr=0.002]
a close-up photo of the <s1><s2>
Steps: 92%|█████████▏| 462/500 [02:25<00:11, 3.34it/s, loss=0.0019, lr=0.002]
Steps: 93%|█████████▎| 463/500 [02:25<00:10, 3.44it/s, loss=0.0019, lr=0.002]
the photo of a <s1><s2>
Steps: 93%|█████████▎| 463/500 [02:25<00:10, 3.44it/s, loss=0.0399, lr=0.002]
Steps: 93%|█████████▎| 464/500 [02:25<00:11, 3.15it/s, loss=0.0399, lr=0.002]
a photo of the small <s1><s2>
tensor([[0.4058],
[0.4210]], device='cuda:0')
Current Norm : tensor([0.4047, 0.4168], device='cuda:0')
Steps: 93%|█████████▎| 464/500 [02:25<00:11, 3.15it/s, loss=0.00133, lr=0.002]
Steps: 93%|█████████▎| 465/500 [02:25<00:10, 3.32it/s, loss=0.00133, lr=0.002]
a dark photo of the <s1><s2>
Steps: 93%|█████████▎| 465/500 [02:25<00:10, 3.32it/s, loss=0.00363, lr=0.002]
Steps: 93%|█████████▎| 466/500 [02:26<00:09, 3.45it/s, loss=0.00363, lr=0.002]
a photo of the nice <s1><s2>
Steps: 93%|█████████▎| 466/500 [02:26<00:09, 3.45it/s, loss=0.00189, lr=0.002]
Steps: 93%|█████████▎| 467/500 [02:26<00:09, 3.58it/s, loss=0.00189, lr=0.002]
a photo of the small <s1><s2>
Steps: 93%|█████████▎| 467/500 [02:26<00:09, 3.58it/s, loss=0.0287, lr=0.002]
Steps: 94%|█████████▎| 468/500 [02:26<00:10, 3.16it/s, loss=0.0287, lr=0.002]
a photo of the nice <s1><s2>
tensor([[0.4059],
[0.4208]], device='cuda:0')
Current Norm : tensor([0.4047, 0.4167], device='cuda:0')
Steps: 94%|█████████▎| 468/500 [02:26<00:10, 3.16it/s, loss=0.00126, lr=0.002]
Steps: 94%|█████████▍| 469/500 [02:27<00:09, 3.20it/s, loss=0.00126, lr=0.002]
a rendition of a <s1><s2>
Steps: 94%|█████████▍| 469/500 [02:27<00:09, 3.20it/s, loss=0.0092, lr=0.002]
Steps: 94%|█████████▍| 470/500 [02:27<00:10, 2.90it/s, loss=0.0092, lr=0.002]
a close-up photo of the <s1><s2>
Steps: 94%|█████████▍| 470/500 [02:27<00:10, 2.90it/s, loss=0.000876, lr=0.002]
Steps: 94%|█████████▍| 471/500 [02:27<00:09, 3.14it/s, loss=0.000876, lr=0.002]
a rendition of the <s1><s2>
Steps: 94%|█████████▍| 471/500 [02:27<00:09, 3.14it/s, loss=0.000824, lr=0.002]
Steps: 94%|█████████▍| 472/500 [02:28<00:08, 3.24it/s, loss=0.000824, lr=0.002]
a photo of a dirty <s1><s2>
tensor([[0.4059],
[0.4207]], device='cuda:0')
Current Norm : tensor([0.4047, 0.4165], device='cuda:0')
Steps: 94%|█████████▍| 472/500 [02:28<00:08, 3.24it/s, loss=0.00901, lr=0.002]
Steps: 95%|█████████▍| 473/500 [02:28<00:07, 3.42it/s, loss=0.00901, lr=0.002]
a photo of my <s1><s2>
Steps: 95%|█████████▍| 473/500 [02:28<00:07, 3.42it/s, loss=0.0135, lr=0.002]
Steps: 95%|█████████▍| 474/500 [02:28<00:08, 3.11it/s, loss=0.0135, lr=0.002]
a photo of the weird <s1><s2>
Steps: 95%|█████████▍| 474/500 [02:28<00:08, 3.11it/s, loss=0.00836, lr=0.002]
Steps: 95%|█████████▌| 475/500 [02:29<00:07, 3.29it/s, loss=0.00836, lr=0.002]
a photo of a nice <s1><s2>
Steps: 95%|█████████▌| 475/500 [02:29<00:07, 3.29it/s, loss=0.00163, lr=0.002]
Steps: 95%|█████████▌| 476/500 [02:29<00:06, 3.44it/s, loss=0.00163, lr=0.002]
a photo of the weird <s1><s2>
tensor([[0.4059],
[0.4205]], device='cuda:0')
Current Norm : tensor([0.4047, 0.4164], device='cuda:0')
Steps: 95%|█████████▌| 476/500 [02:29<00:06, 3.44it/s, loss=0.00151, lr=0.002]
Steps: 95%|█████████▌| 477/500 [02:29<00:07, 3.07it/s, loss=0.00151, lr=0.002]
a photo of a nice <s1><s2>
Steps: 95%|█████████▌| 477/500 [02:29<00:07, 3.07it/s, loss=9.83e-5, lr=0.002]
Steps: 96%|█████████▌| 478/500 [02:29<00:06, 3.28it/s, loss=9.83e-5, lr=0.002]
a photo of the clean <s1><s2>
Steps: 96%|█████████▌| 478/500 [02:29<00:06, 3.28it/s, loss=0.0446, lr=0.002]
Steps: 96%|█████████▌| 479/500 [02:30<00:06, 3.44it/s, loss=0.0446, lr=0.002]
a photo of the <s1><s2>
Steps: 96%|█████████▌| 479/500 [02:30<00:06, 3.44it/s, loss=0.0121, lr=0.002]
Steps: 96%|█████████▌| 480/500 [02:30<00:05, 3.56it/s, loss=0.0121, lr=0.002]
a cropped photo of the <s1><s2>
tensor([[0.4058],
[0.4202]], device='cuda:0')
Current Norm : tensor([0.4046, 0.4161], device='cuda:0')
Steps: 96%|█████████▌| 480/500 [02:30<00:05, 3.56it/s, loss=0.000609, lr=0.002]
Steps: 96%|█████████▌| 481/500 [02:30<00:05, 3.44it/s, loss=0.000609, lr=0.002]
the photo of a <s1><s2>
Steps: 96%|█████████▌| 481/500 [02:30<00:05, 3.44it/s, loss=0.00116, lr=0.002]
Steps: 96%|█████████▋| 482/500 [02:31<00:05, 3.56it/s, loss=0.00116, lr=0.002]
a photo of the clean <s1><s2>
Steps: 96%|█████████▋| 482/500 [02:31<00:05, 3.56it/s, loss=0.00129, lr=0.002]
Steps: 97%|█████████▋| 483/500 [02:31<00:05, 3.12it/s, loss=0.00129, lr=0.002]
a photo of the nice <s1><s2>
Steps: 97%|█████████▋| 483/500 [02:31<00:05, 3.12it/s, loss=0.000587, lr=0.002]
Steps: 97%|█████████▋| 484/500 [02:31<00:04, 3.30it/s, loss=0.000587, lr=0.002]
a photo of a small <s1><s2>
tensor([[0.4057],
[0.4199]], device='cuda:0')
Current Norm : tensor([0.4046, 0.4159], device='cuda:0')
Steps: 97%|█████████▋| 484/500 [02:31<00:04, 3.30it/s, loss=0.0274, lr=0.002]
Steps: 97%|█████████▋| 485/500 [02:31<00:04, 3.45it/s, loss=0.0274, lr=0.002]
a photo of a clean <s1><s2>
Steps: 97%|█████████▋| 485/500 [02:31<00:04, 3.45it/s, loss=0.00014, lr=0.002]
Steps: 97%|█████████▋| 486/500 [02:32<00:04, 3.47it/s, loss=0.00014, lr=0.002]
a photo of the cool <s1><s2>
Steps: 97%|█████████▋| 486/500 [02:32<00:04, 3.47it/s, loss=0.00086, lr=0.002]
Steps: 97%|█████████▋| 487/500 [02:32<00:03, 3.64it/s, loss=0.00086, lr=0.002]
a photo of my <s1><s2>
Steps: 97%|█████████▋| 487/500 [02:32<00:03, 3.64it/s, loss=0.000407, lr=0.002]
Steps: 98%|█████████▊| 488/500 [02:32<00:03, 3.06it/s, loss=0.000407, lr=0.002]
a rendering of a <s1><s2>
tensor([[0.4057],
[0.4196]], device='cuda:0')
Current Norm : tensor([0.4046, 0.4157], device='cuda:0')
Steps: 98%|█████████▊| 488/500 [02:32<00:03, 3.06it/s, loss=0.000273, lr=0.002]
Steps: 98%|█████████▊| 489/500 [02:33<00:03, 3.23it/s, loss=0.000273, lr=0.002]
a photo of a nice <s1><s2>
Steps: 98%|█████████▊| 489/500 [02:33<00:03, 3.23it/s, loss=0.0553, lr=0.002]
Steps: 98%|█████████▊| 490/500 [02:33<00:03, 2.99it/s, loss=0.0553, lr=0.002]
a photo of my <s1><s2>
Steps: 98%|█████████▊| 490/500 [02:33<00:03, 2.99it/s, loss=0.00172, lr=0.002]
Steps: 98%|█████████▊| 491/500 [02:33<00:02, 3.16it/s, loss=0.00172, lr=0.002]
a photo of a small <s1><s2>
Steps: 98%|█████████▊| 491/500 [02:33<00:02, 3.16it/s, loss=0.0108, lr=0.002]
Steps: 98%|█████████▊| 492/500 [02:34<00:02, 3.36it/s, loss=0.0108, lr=0.002]
a photo of my <s1><s2>
tensor([[0.4058],
[0.4193]], device='cuda:0')
Current Norm : tensor([0.4047, 0.4155], device='cuda:0')
Steps: 98%|█████████▊| 492/500 [02:34<00:02, 3.36it/s, loss=0.000218, lr=0.002]
Steps: 99%|█████████▊| 493/500 [02:34<00:02, 3.47it/s, loss=0.000218, lr=0.002]
a close-up photo of a <s1><s2>
Steps: 99%|█████████▊| 493/500 [02:34<00:02, 3.47it/s, loss=0.0466, lr=0.002]
Steps: 99%|█████████▉| 494/500 [02:34<00:01, 3.46it/s, loss=0.0466, lr=0.002]
a good photo of a <s1><s2>
Steps: 99%|█████████▉| 494/500 [02:34<00:01, 3.46it/s, loss=0.00361, lr=0.002]
Steps: 99%|█████████▉| 495/500 [02:34<00:01, 3.57it/s, loss=0.00361, lr=0.002]
a photo of a small <s1><s2>
Steps: 99%|█████████▉| 495/500 [02:34<00:01, 3.57it/s, loss=0.000233, lr=0.002]
Steps: 99%|█████████▉| 496/500 [02:35<00:01, 3.10it/s, loss=0.000233, lr=0.002]
a close-up photo of a <s1><s2>
tensor([[0.4061],
[0.4191]], device='cuda:0')
Current Norm : tensor([0.4048, 0.4153], device='cuda:0')
Steps: 99%|█████████▉| 496/500 [02:35<00:01, 3.10it/s, loss=0.0089, lr=0.002]
Steps: 99%|█████████▉| 497/500 [02:35<00:01, 2.90it/s, loss=0.0089, lr=0.002]
a photo of a dirty <s1><s2>
Steps: 99%|█████████▉| 497/500 [02:35<00:01, 2.90it/s, loss=0.00101, lr=0.002]
Steps: 100%|█████████▉| 498/500 [02:36<00:00, 3.12it/s, loss=0.00101, lr=0.002]
a close-up photo of a <s1><s2>
Steps: 100%|█████████▉| 498/500 [02:36<00:00, 3.12it/s, loss=0.00198, lr=0.002]
Steps: 100%|█████████▉| 499/500 [02:36<00:00, 2.94it/s, loss=0.00198, lr=0.002]
a photo of a small <s1><s2>
Steps: 100%|█████████▉| 499/500 [02:36<00:00, 2.94it/s, loss=0.000176, lr=0.002]
Steps: 100%|██████████| 500/500 [02:36<00:00, 3.18it/s, loss=0.000176, lr=0.002]
Steps: 100%|██████████| 500/500 [02:36<00:00, 3.18it/s, loss=0.000608, lr=0.002]
Steps: 100%|██████████| 500/500 [02:36<00:00, 3.19it/s, loss=0.000608, lr=0.002]
PTI : has 288 lora
PTI : Before training:
0%| | 0/1000 [00:00<?, ?it/s]
a photo of a <s1><s2>
Steps: 0%| | 0/1000 [00:00<?, ?it/s]
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a good photo of the <s1><s2>
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a bright photo of the <s1><s2>
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Steps: 0%| | 3/1000 [00:01<09:46, 1.70it/s, loss=0.00564, lr=0.0004]
a photo of the <s1><s2>
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a photo of the weird <s1><s2>
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a rendering of a <s1><s2>
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a photo of the <s1><s2>
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a photo of the nice <s1><s2>
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a photo of a small <s1><s2>
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a photo of one <s1><s2>
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a photo of a small <s1><s2>
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a good photo of a <s1><s2>
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Steps: 1%| | 12/1000 [00:06<08:57, 1.84it/s, loss=0.0099, lr=0.0004]
a photo of the large <s1><s2>
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Steps: 1%|▏ | 13/1000 [00:06<08:33, 1.92it/s, loss=0.0164, lr=0.0004]
a photo of a <s1><s2>
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a good photo of a <s1><s2>
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a photo of a <s1><s2>
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Steps: 2%|▏ | 16/1000 [00:08<09:06, 1.80it/s, loss=0.00617, lr=0.0004]
a photo of the weird <s1><s2>
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a photo of the <s1><s2>
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Steps: 2%|▏ | 18/1000 [00:09<08:39, 1.89it/s, loss=0.0153, lr=0.0004]
a cropped photo of the <s1><s2>
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a photo of a clean <s1><s2>
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Steps: 2%|▏ | 20/1000 [00:10<08:58, 1.82it/s, loss=0.0649, lr=0.0004]
a photo of a nice <s1><s2>
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Steps: 2%|▏ | 21/1000 [00:11<08:38, 1.89it/s, loss=0.0248, lr=0.0004]
a photo of the weird <s1><s2>
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a photo of the nice <s1><s2>
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Steps: 2%|▏ | 23/1000 [00:12<08:59, 1.81it/s, loss=0.0114, lr=0.0004]
a photo of a nice <s1><s2>
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Steps: 2%|▏ | 24/1000 [00:12<08:33, 1.90it/s, loss=0.00292, lr=0.0004]
a photo of a small <s1><s2>
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Steps: 2%|▎ | 25/1000 [00:13<09:12, 1.76it/s, loss=0.0108, lr=0.0004]
a rendition of the <s1><s2>
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a photo of a cool <s1><s2>
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Steps: 3%|▎ | 27/1000 [00:14<08:14, 1.97it/s, loss=0.00347, lr=0.0004]
a photo of a clean <s1><s2>
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Steps: 3%|▎ | 28/1000 [00:14<08:11, 1.98it/s, loss=0.086, lr=0.0004]
a rendition of the <s1><s2>
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Steps: 3%|▎ | 29/1000 [00:15<09:08, 1.77it/s, loss=0.0693, lr=0.0004]
a photo of a <s1><s2>
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a close-up photo of the <s1><s2>
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a close-up photo of the <s1><s2>
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a good photo of a <s1><s2>
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Steps: 3%|▎ | 33/1000 [00:17<07:59, 2.02it/s, loss=0.0129, lr=0.0004]
a photo of the clean <s1><s2>
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Steps: 3%|▎ | 34/1000 [00:17<07:43, 2.08it/s, loss=0.0135, lr=0.0004]
a photo of a small <s1><s2>
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Steps: 4%|▎ | 35/1000 [00:18<08:20, 1.93it/s, loss=0.0429, lr=0.0004]
a cropped photo of the <s1><s2>
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Steps: 4%|▎ | 36/1000 [00:19<08:09, 1.97it/s, loss=0.0114, lr=0.0004]
the photo of a <s1><s2>
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Steps: 4%|▎ | 37/1000 [00:19<08:25, 1.90it/s, loss=0.00923, lr=0.0004]
a good photo of the <s1><s2>
Steps: 4%|▎ | 37/1000 [00:19<08:25, 1.90it/s, loss=0.0014, lr=0.0004]
Steps: 4%|▍ | 38/1000 [00:20<08:53, 1.80it/s, loss=0.0014, lr=0.0004]
a bright photo of the <s1><s2>
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Steps: 4%|▍ | 39/1000 [00:20<08:27, 1.89it/s, loss=0.0108, lr=0.0004]
a photo of a dirty <s1><s2>
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Steps: 4%|▍ | 40/1000 [00:21<08:16, 1.93it/s, loss=0.029, lr=0.0004]
a cropped photo of the <s1><s2>
Steps: 4%|▍ | 40/1000 [00:21<08:16, 1.93it/s, loss=0.0184, lr=0.0004]
Steps: 4%|▍ | 41/1000 [00:21<08:24, 1.90it/s, loss=0.0184, lr=0.0004]
a cropped photo of a <s1><s2>
Steps: 4%|▍ | 41/1000 [00:21<08:24, 1.90it/s, loss=0.0593, lr=0.0004]
Steps: 4%|▍ | 42/1000 [00:22<08:11, 1.95it/s, loss=0.0593, lr=0.0004]
a photo of a clean <s1><s2>
Steps: 4%|▍ | 42/1000 [00:22<08:11, 1.95it/s, loss=0.192, lr=0.0004]
Steps: 4%|▍ | 43/1000 [00:22<07:56, 2.01it/s, loss=0.192, lr=0.0004]
a photo of a small <s1><s2>
Steps: 4%|▍ | 43/1000 [00:22<07:56, 2.01it/s, loss=0.0242, lr=0.0004]
Steps: 4%|▍ | 44/1000 [00:23<08:37, 1.85it/s, loss=0.0242, lr=0.0004]
a photo of the nice <s1><s2>
Steps: 4%|▍ | 44/1000 [00:23<08:37, 1.85it/s, loss=0.00639, lr=0.0004]
Steps: 4%|▍ | 45/1000 [00:23<08:12, 1.94it/s, loss=0.00639, lr=0.0004]
a photo of one <s1><s2>
Steps: 4%|▍ | 45/1000 [00:23<08:12, 1.94it/s, loss=0.0899, lr=0.0004]
Steps: 5%|▍ | 46/1000 [00:24<08:09, 1.95it/s, loss=0.0899, lr=0.0004]
a rendition of the <s1><s2>
Steps: 5%|▍ | 46/1000 [00:24<08:09, 1.95it/s, loss=0.00219, lr=0.0004]
Steps: 5%|▍ | 47/1000 [00:24<07:54, 2.01it/s, loss=0.00219, lr=0.0004]
a photo of the <s1><s2>
Steps: 5%|▍ | 47/1000 [00:24<07:54, 2.01it/s, loss=0.00525, lr=0.0004]
Steps: 5%|▍ | 48/1000 [00:25<08:44, 1.82it/s, loss=0.00525, lr=0.0004]
a photo of my <s1><s2>
Steps: 5%|▍ | 48/1000 [00:25<08:44, 1.82it/s, loss=0.0145, lr=0.0004]
Steps: 5%|▍ | 49/1000 [00:25<08:25, 1.88it/s, loss=0.0145, lr=0.0004]
a photo of a <s1><s2>
Steps: 5%|▍ | 49/1000 [00:25<08:25, 1.88it/s, loss=0.0618, lr=0.0004]
Steps: 5%|▌ | 50/1000 [00:26<08:54, 1.78it/s, loss=0.0618, lr=0.0004]
a photo of the <s1><s2>
Steps: 5%|▌ | 50/1000 [00:26<08:54, 1.78it/s, loss=0.0212, lr=0.0004]
Steps: 5%|▌ | 51/1000 [00:27<08:42, 1.82it/s, loss=0.0212, lr=0.0004]
a close-up photo of a <s1><s2>
Steps: 5%|▌ | 51/1000 [00:27<08:42, 1.82it/s, loss=0.00471, lr=0.0004]
Steps: 5%|▌ | 52/1000 [00:27<08:29, 1.86it/s, loss=0.00471, lr=0.0004]
a photo of a cool <s1><s2>
Steps: 5%|▌ | 52/1000 [00:27<08:29, 1.86it/s, loss=0.0117, lr=0.0004]
Steps: 5%|▌ | 53/1000 [00:28<08:08, 1.94it/s, loss=0.0117, lr=0.0004]
a photo of a <s1><s2>
Steps: 5%|▌ | 53/1000 [00:28<08:08, 1.94it/s, loss=0.0102, lr=0.0004]
Steps: 5%|▌ | 54/1000 [00:28<07:59, 1.97it/s, loss=0.0102, lr=0.0004]
a bright photo of the <s1><s2>
Steps: 5%|▌ | 54/1000 [00:28<07:59, 1.97it/s, loss=0.0361, lr=0.0004]
Steps: 6%|▌ | 55/1000 [00:28<07:44, 2.03it/s, loss=0.0361, lr=0.0004]
a photo of a dirty <s1><s2>
Steps: 6%|▌ | 55/1000 [00:28<07:44, 2.03it/s, loss=0.00915, lr=0.0004]
Steps: 6%|▌ | 56/1000 [00:29<08:30, 1.85it/s, loss=0.00915, lr=0.0004]
a photo of a dirty <s1><s2>
Steps: 6%|▌ | 56/1000 [00:29<08:30, 1.85it/s, loss=0.00705, lr=0.0004]
Steps: 6%|▌ | 57/1000 [00:30<08:20, 1.88it/s, loss=0.00705, lr=0.0004]
a bright photo of the <s1><s2>
Steps: 6%|▌ | 57/1000 [00:30<08:20, 1.88it/s, loss=0.00867, lr=0.0004]
Steps: 6%|▌ | 58/1000 [00:30<08:10, 1.92it/s, loss=0.00867, lr=0.0004]
a good photo of a <s1><s2>
Steps: 6%|▌ | 58/1000 [00:30<08:10, 1.92it/s, loss=0.334, lr=0.0004]
Steps: 6%|▌ | 59/1000 [00:31<08:02, 1.95it/s, loss=0.334, lr=0.0004]
a photo of a small <s1><s2>
Steps: 6%|▌ | 59/1000 [00:31<08:02, 1.95it/s, loss=0.0265, lr=0.0004]
Steps: 6%|▌ | 60/1000 [00:31<07:44, 2.03it/s, loss=0.0265, lr=0.0004]
a cropped photo of the <s1><s2>
Steps: 6%|▌ | 60/1000 [00:31<07:44, 2.03it/s, loss=0.0471, lr=0.0004]
Steps: 6%|▌ | 61/1000 [00:32<08:29, 1.84it/s, loss=0.0471, lr=0.0004]
a photo of the cool <s1><s2>
Steps: 6%|▌ | 61/1000 [00:32<08:29, 1.84it/s, loss=0.0511, lr=0.0004]
Steps: 6%|▌ | 62/1000 [00:32<08:27, 1.85it/s, loss=0.0511, lr=0.0004]
a photo of a dirty <s1><s2>
Steps: 6%|▌ | 62/1000 [00:32<08:27, 1.85it/s, loss=0.0167, lr=0.0004]
Steps: 6%|▋ | 63/1000 [00:33<09:02, 1.73it/s, loss=0.0167, lr=0.0004]
a rendition of a <s1><s2>
Steps: 6%|▋ | 63/1000 [00:33<09:02, 1.73it/s, loss=0.0248, lr=0.0004]
Steps: 6%|▋ | 64/1000 [00:33<08:27, 1.84it/s, loss=0.0248, lr=0.0004]
a rendition of the <s1><s2>
Steps: 6%|▋ | 64/1000 [00:33<08:27, 1.84it/s, loss=0.0725, lr=0.0004]
Steps: 6%|▋ | 65/1000 [00:34<07:56, 1.96it/s, loss=0.0725, lr=0.0004]
a photo of a cool <s1><s2>
Steps: 6%|▋ | 65/1000 [00:34<07:56, 1.96it/s, loss=0.0709, lr=0.0004]
Steps: 7%|▋ | 66/1000 [00:34<07:51, 1.98it/s, loss=0.0709, lr=0.0004]
a photo of the large <s1><s2>
Steps: 7%|▋ | 66/1000 [00:34<07:51, 1.98it/s, loss=0.00569, lr=0.0004]
Steps: 7%|▋ | 67/1000 [00:35<08:29, 1.83it/s, loss=0.00569, lr=0.0004]
a close-up photo of the <s1><s2>
Steps: 7%|▋ | 67/1000 [00:35<08:29, 1.83it/s, loss=0.0135, lr=0.0004]
Steps: 7%|▋ | 68/1000 [00:35<08:21, 1.86it/s, loss=0.0135, lr=0.0004]
a photo of a small <s1><s2>
Steps: 7%|▋ | 68/1000 [00:35<08:21, 1.86it/s, loss=0.0323, lr=0.0004]
Steps: 7%|▋ | 69/1000 [00:36<08:00, 1.94it/s, loss=0.0323, lr=0.0004]
a cropped photo of a <s1><s2>
Steps: 7%|▋ | 69/1000 [00:36<08:00, 1.94it/s, loss=0.104, lr=0.0004]
Steps: 7%|▋ | 70/1000 [00:37<08:28, 1.83it/s, loss=0.104, lr=0.0004]
the photo of a <s1><s2>
Steps: 7%|▋ | 70/1000 [00:37<08:28, 1.83it/s, loss=0.029, lr=0.0004]
Steps: 7%|▋ | 71/1000 [00:37<08:51, 1.75it/s, loss=0.029, lr=0.0004]
a photo of the clean <s1><s2>
Steps: 7%|▋ | 71/1000 [00:37<08:51, 1.75it/s, loss=0.00426, lr=0.0004]
Steps: 7%|▋ | 72/1000 [00:38<09:05, 1.70it/s, loss=0.00426, lr=0.0004]
a rendering of a <s1><s2>
Steps: 7%|▋ | 72/1000 [00:38<09:05, 1.70it/s, loss=0.0262, lr=0.0004]
Steps: 7%|▋ | 73/1000 [00:38<08:27, 1.83it/s, loss=0.0262, lr=0.0004]
a photo of a small <s1><s2>
Steps: 7%|▋ | 73/1000 [00:38<08:27, 1.83it/s, loss=0.136, lr=0.0004]
Steps: 7%|▋ | 74/1000 [00:39<08:15, 1.87it/s, loss=0.136, lr=0.0004]
a photo of a small <s1><s2>
Steps: 7%|▋ | 74/1000 [00:39<08:15, 1.87it/s, loss=0.0137, lr=0.0004]
Steps: 8%|▊ | 75/1000 [00:39<07:54, 1.95it/s, loss=0.0137, lr=0.0004]
a close-up photo of the <s1><s2>
Steps: 8%|▊ | 75/1000 [00:39<07:54, 1.95it/s, loss=0.0686, lr=0.0004]
Steps: 8%|▊ | 76/1000 [00:40<07:45, 1.98it/s, loss=0.0686, lr=0.0004]
the photo of a <s1><s2>
Steps: 8%|▊ | 76/1000 [00:40<07:45, 1.98it/s, loss=0.00566, lr=0.0004]
Steps: 8%|▊ | 77/1000 [00:40<07:31, 2.04it/s, loss=0.00566, lr=0.0004]
a good photo of a <s1><s2>
Steps: 8%|▊ | 77/1000 [00:40<07:31, 2.04it/s, loss=0.308, lr=0.0004]
Steps: 8%|▊ | 78/1000 [00:41<07:25, 2.07it/s, loss=0.308, lr=0.0004]
a cropped photo of a <s1><s2>
Steps: 8%|▊ | 78/1000 [00:41<07:25, 2.07it/s, loss=0.0281, lr=0.0004]
Steps: 8%|▊ | 79/1000 [00:41<07:25, 2.07it/s, loss=0.0281, lr=0.0004]
a rendition of a <s1><s2>
Steps: 8%|▊ | 79/1000 [00:41<07:25, 2.07it/s, loss=0.00753, lr=0.0004]
Steps: 8%|▊ | 80/1000 [00:42<08:04, 1.90it/s, loss=0.00753, lr=0.0004]
a photo of the clean <s1><s2>
Steps: 8%|▊ | 80/1000 [00:42<08:04, 1.90it/s, loss=0.0104, lr=0.0004]
Steps: 8%|▊ | 81/1000 [00:42<08:49, 1.74it/s, loss=0.0104, lr=0.0004]
a rendering of a <s1><s2>
Steps: 8%|▊ | 81/1000 [00:42<08:49, 1.74it/s, loss=0.0205, lr=0.0004]
Steps: 8%|▊ | 82/1000 [00:43<08:21, 1.83it/s, loss=0.0205, lr=0.0004]
a close-up photo of a <s1><s2>
Steps: 8%|▊ | 82/1000 [00:43<08:21, 1.83it/s, loss=0.00649, lr=0.0004]
Steps: 8%|▊ | 83/1000 [00:43<08:06, 1.88it/s, loss=0.00649, lr=0.0004]
a photo of a <s1><s2>
Steps: 8%|▊ | 83/1000 [00:43<08:06, 1.88it/s, loss=0.012, lr=0.0004]
Steps: 8%|▊ | 84/1000 [00:44<07:48, 1.96it/s, loss=0.012, lr=0.0004]
a photo of a small <s1><s2>
Steps: 8%|▊ | 84/1000 [00:44<07:48, 1.96it/s, loss=0.0324, lr=0.0004]
Steps: 8%|▊ | 85/1000 [00:44<07:46, 1.96it/s, loss=0.0324, lr=0.0004]
a close-up photo of the <s1><s2>
Steps: 8%|▊ | 85/1000 [00:44<07:46, 1.96it/s, loss=0.245, lr=0.0004]
Steps: 9%|▊ | 86/1000 [00:45<08:11, 1.86it/s, loss=0.245, lr=0.0004]
a photo of a nice <s1><s2>
Steps: 9%|▊ | 86/1000 [00:45<08:11, 1.86it/s, loss=0.0105, lr=0.0004]
Steps: 9%|▊ | 87/1000 [00:45<07:58, 1.91it/s, loss=0.0105, lr=0.0004]
a photo of my <s1><s2>
Steps: 9%|▊ | 87/1000 [00:45<07:58, 1.91it/s, loss=0.00964, lr=0.0004]
Steps: 9%|▉ | 88/1000 [00:46<07:47, 1.95it/s, loss=0.00964, lr=0.0004]
a cropped photo of a <s1><s2>
Steps: 9%|▉ | 88/1000 [00:46<07:47, 1.95it/s, loss=0.00499, lr=0.0004]
Steps: 9%|▉ | 89/1000 [00:46<07:54, 1.92it/s, loss=0.00499, lr=0.0004]
a photo of the clean <s1><s2>
Steps: 9%|▉ | 89/1000 [00:46<07:54, 1.92it/s, loss=0.0439, lr=0.0004]
Steps: 9%|▉ | 90/1000 [00:47<07:39, 1.98it/s, loss=0.0439, lr=0.0004]
a photo of a nice <s1><s2>
Steps: 9%|▉ | 90/1000 [00:47<07:39, 1.98it/s, loss=0.0131, lr=0.0004]
Steps: 9%|▉ | 91/1000 [00:48<08:26, 1.79it/s, loss=0.0131, lr=0.0004]
a photo of a clean <s1><s2>
Steps: 9%|▉ | 91/1000 [00:48<08:26, 1.79it/s, loss=0.00324, lr=0.0004]
Steps: 9%|▉ | 92/1000 [00:48<08:09, 1.86it/s, loss=0.00324, lr=0.0004]
a photo of my <s1><s2>
Steps: 9%|▉ | 92/1000 [00:48<08:09, 1.86it/s, loss=0.058, lr=0.0004]
Steps: 9%|▉ | 93/1000 [00:49<07:50, 1.93it/s, loss=0.058, lr=0.0004]
a photo of the nice <s1><s2>
Steps: 9%|▉ | 93/1000 [00:49<07:50, 1.93it/s, loss=0.0096, lr=0.0004]
Steps: 9%|▉ | 94/1000 [00:49<07:40, 1.97it/s, loss=0.0096, lr=0.0004]
a photo of a cool <s1><s2>
Steps: 9%|▉ | 94/1000 [00:49<07:40, 1.97it/s, loss=0.0277, lr=0.0004]
Steps: 10%|▉ | 95/1000 [00:50<07:41, 1.96it/s, loss=0.0277, lr=0.0004]
a rendition of the <s1><s2>
Steps: 10%|▉ | 95/1000 [00:50<07:41, 1.96it/s, loss=0.00519, lr=0.0004]
Steps: 10%|▉ | 96/1000 [00:50<07:33, 1.99it/s, loss=0.00519, lr=0.0004]
a cropped photo of the <s1><s2>
Steps: 10%|▉ | 96/1000 [00:50<07:33, 1.99it/s, loss=0.0263, lr=0.0004]
Steps: 10%|▉ | 97/1000 [00:51<08:24, 1.79it/s, loss=0.0263, lr=0.0004]
a close-up photo of the <s1><s2>
Steps: 10%|▉ | 97/1000 [00:51<08:24, 1.79it/s, loss=0.0199, lr=0.0004]
Steps: 10%|▉ | 98/1000 [00:51<08:45, 1.71it/s, loss=0.0199, lr=0.0004]
a photo of the nice <s1><s2>
Steps: 10%|▉ | 98/1000 [00:51<08:45, 1.71it/s, loss=0.00149, lr=0.0004]
Steps: 10%|▉ | 99/1000 [00:52<09:31, 1.58it/s, loss=0.00149, lr=0.0004]
a photo of one <s1><s2>
Steps: 10%|▉ | 99/1000 [00:52<09:31, 1.58it/s, loss=0.00139, lr=0.0004]
Steps: 10%|█ | 100/1000 [00:53<09:02, 1.66it/s, loss=0.00139, lr=0.0004]
a rendition of a <s1><s2>
Steps: 10%|█ | 100/1000 [00:53<09:02, 1.66it/s, loss=0.0273, lr=0.0004]
Steps: 10%|█ | 101/1000 [00:53<08:49, 1.70it/s, loss=0.0273, lr=0.0004]
a photo of a dirty <s1><s2>
Steps: 10%|█ | 101/1000 [00:53<08:49, 1.70it/s, loss=0.0436, lr=0.0004]
Steps: 10%|█ | 102/1000 [00:54<08:42, 1.72it/s, loss=0.0436, lr=0.0004]
a rendition of a <s1><s2>
Steps: 10%|█ | 102/1000 [00:54<08:42, 1.72it/s, loss=0.00439, lr=0.0004]
Steps: 10%|█ | 103/1000 [00:55<09:16, 1.61it/s, loss=0.00439, lr=0.0004]
a photo of the small <s1><s2>
Steps: 10%|█ | 103/1000 [00:55<09:16, 1.61it/s, loss=0.0184, lr=0.0004]
Steps: 10%|█ | 104/1000 [00:55<08:47, 1.70it/s, loss=0.0184, lr=0.0004]
a dark photo of the <s1><s2>
Steps: 10%|█ | 104/1000 [00:55<08:47, 1.70it/s, loss=0.0323, lr=0.0004]
Steps: 10%|█ | 105/1000 [00:56<08:38, 1.73it/s, loss=0.0323, lr=0.0004]
a rendition of a <s1><s2>
Steps: 10%|█ | 105/1000 [00:56<08:38, 1.73it/s, loss=0.0654, lr=0.0004]
Steps: 11%|█ | 106/1000 [00:56<08:37, 1.73it/s, loss=0.0654, lr=0.0004]
a photo of the weird <s1><s2>
Steps: 11%|█ | 106/1000 [00:56<08:37, 1.73it/s, loss=0.0576, lr=0.0004]
Steps: 11%|█ | 107/1000 [00:57<09:11, 1.62it/s, loss=0.0576, lr=0.0004]
a photo of a <s1><s2>
Steps: 11%|█ | 107/1000 [00:57<09:11, 1.62it/s, loss=0.0299, lr=0.0004]
Steps: 11%|█ | 108/1000 [00:58<09:23, 1.58it/s, loss=0.0299, lr=0.0004]
a photo of my <s1><s2>
Steps: 11%|█ | 108/1000 [00:58<09:23, 1.58it/s, loss=0.011, lr=0.0004]
Steps: 11%|█ | 109/1000 [00:58<08:56, 1.66it/s, loss=0.011, lr=0.0004]
a photo of the <s1><s2>
Steps: 11%|█ | 109/1000 [00:58<08:56, 1.66it/s, loss=0.141, lr=0.0004]
Steps: 11%|█ | 110/1000 [00:59<08:41, 1.71it/s, loss=0.141, lr=0.0004]
a photo of a cool <s1><s2>
Steps: 11%|█ | 110/1000 [00:59<08:41, 1.71it/s, loss=0.0237, lr=0.0004]
Steps: 11%|█ | 111/1000 [00:59<08:38, 1.72it/s, loss=0.0237, lr=0.0004]
a dark photo of the <s1><s2>
Steps: 11%|█ | 111/1000 [00:59<08:38, 1.72it/s, loss=0.0767, lr=0.0004]
Steps: 11%|█ | 112/1000 [01:00<08:11, 1.81it/s, loss=0.0767, lr=0.0004]
a rendition of the <s1><s2>
Steps: 11%|█ | 112/1000 [01:00<08:11, 1.81it/s, loss=0.0959, lr=0.0004]
Steps: 11%|█▏ | 113/1000 [01:00<07:58, 1.85it/s, loss=0.0959, lr=0.0004]
a photo of the large <s1><s2>
Steps: 11%|█▏ | 113/1000 [01:00<07:58, 1.85it/s, loss=0.00687, lr=0.0004]
Steps: 11%|█▏ | 114/1000 [01:01<07:50, 1.88it/s, loss=0.00687, lr=0.0004]
the photo of a <s1><s2>
Steps: 11%|█▏ | 114/1000 [01:01<07:50, 1.88it/s, loss=0.0815, lr=0.0004]
Steps: 12%|█▏ | 115/1000 [01:01<07:49, 1.89it/s, loss=0.0815, lr=0.0004]
a photo of a clean <s1><s2>
Steps: 12%|█▏ | 115/1000 [01:01<07:49, 1.89it/s, loss=0.326, lr=0.0004]
Steps: 12%|█▏ | 116/1000 [01:02<08:22, 1.76it/s, loss=0.326, lr=0.0004]
a rendition of the <s1><s2>
Steps: 12%|█▏ | 116/1000 [01:02<08:22, 1.76it/s, loss=0.00675, lr=0.0004]
Steps: 12%|█▏ | 117/1000 [01:02<08:04, 1.82it/s, loss=0.00675, lr=0.0004]
the photo of a <s1><s2>
Steps: 12%|█▏ | 117/1000 [01:02<08:04, 1.82it/s, loss=0.0518, lr=0.0004]
Steps: 12%|█▏ | 118/1000 [01:03<07:53, 1.86it/s, loss=0.0518, lr=0.0004]
a close-up photo of the <s1><s2>
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a photo of the weird <s1><s2>
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a photo of a <s1><s2>
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Steps: 12%|█▏ | 121/1000 [01:05<08:00, 1.83it/s, loss=0.00521, lr=0.0004]
a photo of a dirty <s1><s2>
Steps: 12%|█▏ | 121/1000 [01:05<08:00, 1.83it/s, loss=0.0142, lr=0.0004]
Steps: 12%|█▏ | 122/1000 [01:05<08:20, 1.76it/s, loss=0.0142, lr=0.0004]
a photo of one <s1><s2>
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Steps: 12%|█▏ | 123/1000 [01:06<07:56, 1.84it/s, loss=0.0115, lr=0.0004]
a cropped photo of the <s1><s2>
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Steps: 12%|█▏ | 124/1000 [01:06<07:54, 1.84it/s, loss=0.00388, lr=0.0004]
a photo of a dirty <s1><s2>
Steps: 12%|█▏ | 124/1000 [01:06<07:54, 1.84it/s, loss=0.00639, lr=0.0004]
Steps: 12%|█▎ | 125/1000 [01:07<07:36, 1.92it/s, loss=0.00639, lr=0.0004]
a close-up photo of a <s1><s2>
Steps: 12%|█▎ | 125/1000 [01:07<07:36, 1.92it/s, loss=0.017, lr=0.0004]
Steps: 13%|█▎ | 126/1000 [01:07<08:10, 1.78it/s, loss=0.017, lr=0.0004]
a dark photo of the <s1><s2>
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Steps: 13%|█▎ | 127/1000 [01:08<07:57, 1.83it/s, loss=0.00575, lr=0.0004]
a photo of a <s1><s2>
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a close-up photo of a <s1><s2>
Steps: 13%|█▎ | 128/1000 [01:08<07:50, 1.85it/s, loss=0.0489, lr=0.0004]
Steps: 13%|█▎ | 129/1000 [01:09<08:20, 1.74it/s, loss=0.0489, lr=0.0004]
a photo of the small <s1><s2>
Steps: 13%|█▎ | 129/1000 [01:09<08:20, 1.74it/s, loss=0.0123, lr=0.0004]
Steps: 13%|█▎ | 130/1000 [01:10<08:03, 1.80it/s, loss=0.0123, lr=0.0004]
a photo of the nice <s1><s2>
Steps: 13%|█▎ | 130/1000 [01:10<08:03, 1.80it/s, loss=0.431, lr=0.0004]
Steps: 13%|█▎ | 131/1000 [01:10<08:28, 1.71it/s, loss=0.431, lr=0.0004]
a photo of the nice <s1><s2>
Steps: 13%|█▎ | 131/1000 [01:10<08:28, 1.71it/s, loss=0.00972, lr=0.0004]
Steps: 13%|█▎ | 132/1000 [01:11<08:06, 1.79it/s, loss=0.00972, lr=0.0004]
a photo of a clean <s1><s2>
Steps: 13%|█▎ | 132/1000 [01:11<08:06, 1.79it/s, loss=0.159, lr=0.0004]
Steps: 13%|█▎ | 133/1000 [01:11<07:49, 1.85it/s, loss=0.159, lr=0.0004]
a rendition of the <s1><s2>
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Steps: 13%|█▎ | 134/1000 [01:12<08:13, 1.76it/s, loss=0.0449, lr=0.0004]
a rendition of the <s1><s2>
Steps: 13%|█▎ | 134/1000 [01:12<08:13, 1.76it/s, loss=0.0223, lr=0.0004]
Steps: 14%|█▎ | 135/1000 [01:12<07:53, 1.82it/s, loss=0.0223, lr=0.0004]
a photo of the weird <s1><s2>
Steps: 14%|█▎ | 135/1000 [01:12<07:53, 1.82it/s, loss=0.173, lr=0.0004]
Steps: 14%|█▎ | 136/1000 [01:13<07:40, 1.87it/s, loss=0.173, lr=0.0004]
a good photo of the <s1><s2>
Steps: 14%|█▎ | 136/1000 [01:13<07:40, 1.87it/s, loss=0.0197, lr=0.0004]
Steps: 14%|█▎ | 137/1000 [01:14<08:18, 1.73it/s, loss=0.0197, lr=0.0004]
a photo of a small <s1><s2>
Steps: 14%|█▎ | 137/1000 [01:14<08:18, 1.73it/s, loss=0.00363, lr=0.0004]
Steps: 14%|█▍ | 138/1000 [01:14<08:01, 1.79it/s, loss=0.00363, lr=0.0004]
a photo of a dirty <s1><s2>
Steps: 14%|█▍ | 138/1000 [01:14<08:01, 1.79it/s, loss=0.0122, lr=0.0004]
Steps: 14%|█▍ | 139/1000 [01:15<07:44, 1.85it/s, loss=0.0122, lr=0.0004]
a photo of a clean <s1><s2>
Steps: 14%|█▍ | 139/1000 [01:15<07:44, 1.85it/s, loss=0.0173, lr=0.0004]
Steps: 14%|█▍ | 140/1000 [01:15<07:32, 1.90it/s, loss=0.0173, lr=0.0004]
a photo of the <s1><s2>
Steps: 14%|█▍ | 140/1000 [01:15<07:32, 1.90it/s, loss=0.0263, lr=0.0004]
Steps: 14%|█▍ | 141/1000 [01:16<07:28, 1.91it/s, loss=0.0263, lr=0.0004]
a rendition of a <s1><s2>
Steps: 14%|█▍ | 141/1000 [01:16<07:28, 1.91it/s, loss=0.0813, lr=0.0004]
Steps: 14%|█▍ | 142/1000 [01:16<07:53, 1.81it/s, loss=0.0813, lr=0.0004]
a close-up photo of the <s1><s2>
Steps: 14%|█▍ | 142/1000 [01:16<07:53, 1.81it/s, loss=0.0135, lr=0.0004]
Steps: 14%|█▍ | 143/1000 [01:17<08:13, 1.74it/s, loss=0.0135, lr=0.0004]
a rendering of a <s1><s2>
Steps: 14%|█▍ | 143/1000 [01:17<08:13, 1.74it/s, loss=0.0146, lr=0.0004]
Steps: 14%|█▍ | 144/1000 [01:17<07:45, 1.84it/s, loss=0.0146, lr=0.0004]
a rendition of the <s1><s2>
Steps: 14%|█▍ | 144/1000 [01:17<07:45, 1.84it/s, loss=0.459, lr=0.0004]
Steps: 14%|█▍ | 145/1000 [01:18<07:27, 1.91it/s, loss=0.459, lr=0.0004]
a cropped photo of a <s1><s2>
Steps: 14%|█▍ | 145/1000 [01:18<07:27, 1.91it/s, loss=0.0446, lr=0.0004]
Steps: 15%|█▍ | 146/1000 [01:18<07:20, 1.94it/s, loss=0.0446, lr=0.0004]
a photo of a clean <s1><s2>
Steps: 15%|█▍ | 146/1000 [01:18<07:20, 1.94it/s, loss=0.00536, lr=0.0004]
Steps: 15%|█▍ | 147/1000 [01:19<07:22, 1.93it/s, loss=0.00536, lr=0.0004]
a photo of one <s1><s2>
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Steps: 15%|█▍ | 148/1000 [01:19<07:13, 1.97it/s, loss=0.15, lr=0.0004]
a photo of a nice <s1><s2>
Steps: 15%|█▍ | 148/1000 [01:19<07:13, 1.97it/s, loss=0.0297, lr=0.0004]
Steps: 15%|█▍ | 149/1000 [01:20<07:14, 1.96it/s, loss=0.0297, lr=0.0004]
a rendition of the <s1><s2>
Steps: 15%|█▍ | 149/1000 [01:20<07:14, 1.96it/s, loss=0.0894, lr=0.0004]
Steps: 15%|█▌ | 150/1000 [01:20<07:19, 1.93it/s, loss=0.0894, lr=0.0004]
a close-up photo of a <s1><s2>
Steps: 15%|█▌ | 150/1000 [01:20<07:19, 1.93it/s, loss=0.00859, lr=0.0004]
Steps: 15%|█▌ | 151/1000 [01:21<07:16, 1.94it/s, loss=0.00859, lr=0.0004]
a photo of a <s1><s2>
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Steps: 15%|█▌ | 152/1000 [01:21<07:48, 1.81it/s, loss=0.0199, lr=0.0004]
a photo of the clean <s1><s2>
Steps: 15%|█▌ | 152/1000 [01:21<07:48, 1.81it/s, loss=0.00174, lr=0.0004]
Steps: 15%|█▌ | 153/1000 [01:22<08:13, 1.72it/s, loss=0.00174, lr=0.0004]
a photo of the small <s1><s2>
Steps: 15%|█▌ | 153/1000 [01:22<08:13, 1.72it/s, loss=0.00208, lr=0.0004]
Steps: 15%|█▌ | 154/1000 [01:23<07:51, 1.80it/s, loss=0.00208, lr=0.0004]
a photo of the small <s1><s2>
Steps: 15%|█▌ | 154/1000 [01:23<07:51, 1.80it/s, loss=0.00658, lr=0.0004]
Steps: 16%|█▌ | 155/1000 [01:23<07:41, 1.83it/s, loss=0.00658, lr=0.0004]
a photo of the clean <s1><s2>
Steps: 16%|█▌ | 155/1000 [01:23<07:41, 1.83it/s, loss=0.0325, lr=0.0004]
Steps: 16%|█▌ | 156/1000 [01:24<08:19, 1.69it/s, loss=0.0325, lr=0.0004]
a photo of a cool <s1><s2>
Steps: 16%|█▌ | 156/1000 [01:24<08:19, 1.69it/s, loss=0.00203, lr=0.0004]
Steps: 16%|█▌ | 157/1000 [01:24<07:46, 1.81it/s, loss=0.00203, lr=0.0004]
a rendition of a <s1><s2>
Steps: 16%|█▌ | 157/1000 [01:24<07:46, 1.81it/s, loss=0.0106, lr=0.0004]
Steps: 16%|█▌ | 158/1000 [01:25<07:35, 1.85it/s, loss=0.0106, lr=0.0004]
a photo of the clean <s1><s2>
Steps: 16%|█▌ | 158/1000 [01:25<07:35, 1.85it/s, loss=0.101, lr=0.0004]
Steps: 16%|█▌ | 159/1000 [01:26<08:08, 1.72it/s, loss=0.101, lr=0.0004]
a good photo of a <s1><s2>
Steps: 16%|█▌ | 159/1000 [01:26<08:08, 1.72it/s, loss=0.00352, lr=0.0004]
Steps: 16%|█▌ | 160/1000 [01:26<07:42, 1.82it/s, loss=0.00352, lr=0.0004]
a good photo of a <s1><s2>
Steps: 16%|█▌ | 160/1000 [01:26<07:42, 1.82it/s, loss=0.01, lr=0.0004]
Steps: 16%|█▌ | 161/1000 [01:26<07:26, 1.88it/s, loss=0.01, lr=0.0004]
a cropped photo of the <s1><s2>
Steps: 16%|█▌ | 161/1000 [01:26<07:26, 1.88it/s, loss=0.0131, lr=0.0004]
Steps: 16%|█▌ | 162/1000 [01:27<07:55, 1.76it/s, loss=0.0131, lr=0.0004]
a photo of the clean <s1><s2>
Steps: 16%|█▌ | 162/1000 [01:27<07:55, 1.76it/s, loss=0.0195, lr=0.0004]
Steps: 16%|█▋ | 163/1000 [01:28<07:32, 1.85it/s, loss=0.0195, lr=0.0004]
a photo of a dirty <s1><s2>
Steps: 16%|█▋ | 163/1000 [01:28<07:32, 1.85it/s, loss=0.157, lr=0.0004]
Steps: 16%|█▋ | 164/1000 [01:28<07:55, 1.76it/s, loss=0.157, lr=0.0004]
a photo of the <s1><s2>
Steps: 16%|█▋ | 164/1000 [01:28<07:55, 1.76it/s, loss=0.00936, lr=0.0004]
Steps: 16%|█▋ | 165/1000 [01:29<07:36, 1.83it/s, loss=0.00936, lr=0.0004]
a photo of one <s1><s2>
Steps: 16%|█▋ | 165/1000 [01:29<07:36, 1.83it/s, loss=0.0171, lr=0.0004]
Steps: 17%|█▋ | 166/1000 [01:29<07:27, 1.86it/s, loss=0.0171, lr=0.0004]
a rendition of a <s1><s2>
Steps: 17%|█▋ | 166/1000 [01:29<07:27, 1.86it/s, loss=0.0347, lr=0.0004]
Steps: 17%|█▋ | 167/1000 [01:30<07:30, 1.85it/s, loss=0.0347, lr=0.0004]
a photo of a clean <s1><s2>
Steps: 17%|█▋ | 167/1000 [01:30<07:30, 1.85it/s, loss=0.02, lr=0.0004]
Steps: 17%|█▋ | 168/1000 [01:30<07:15, 1.91it/s, loss=0.02, lr=0.0004]
a photo of the large <s1><s2>
Steps: 17%|█▋ | 168/1000 [01:30<07:15, 1.91it/s, loss=0.0741, lr=0.0004]
Steps: 17%|█▋ | 169/1000 [01:31<07:08, 1.94it/s, loss=0.0741, lr=0.0004]
a photo of a cool <s1><s2>
Steps: 17%|█▋ | 169/1000 [01:31<07:08, 1.94it/s, loss=0.0995, lr=0.0004]
Steps: 17%|█▋ | 170/1000 [01:31<07:00, 1.97it/s, loss=0.0995, lr=0.0004]
a rendition of a <s1><s2>
Steps: 17%|█▋ | 170/1000 [01:31<07:00, 1.97it/s, loss=0.0094, lr=0.0004]
Steps: 17%|█▋ | 171/1000 [01:32<07:40, 1.80it/s, loss=0.0094, lr=0.0004]
a rendition of the <s1><s2>
Steps: 17%|█▋ | 171/1000 [01:32<07:40, 1.80it/s, loss=0.00362, lr=0.0004]
Steps: 17%|█▋ | 172/1000 [01:32<07:31, 1.83it/s, loss=0.00362, lr=0.0004]
a cropped photo of the <s1><s2>
Steps: 17%|█▋ | 172/1000 [01:32<07:31, 1.83it/s, loss=0.15, lr=0.0004]
Steps: 17%|█▋ | 173/1000 [01:33<08:05, 1.70it/s, loss=0.15, lr=0.0004]
a cropped photo of a <s1><s2>
Steps: 17%|█▋ | 173/1000 [01:33<08:05, 1.70it/s, loss=0.0136, lr=0.0004]
Steps: 17%|█▋ | 174/1000 [01:34<07:52, 1.75it/s, loss=0.0136, lr=0.0004]
a cropped photo of a <s1><s2>
Steps: 17%|█▋ | 174/1000 [01:34<07:52, 1.75it/s, loss=0.161, lr=0.0004]
Steps: 18%|█▊ | 175/1000 [01:34<07:36, 1.81it/s, loss=0.161, lr=0.0004]
a close-up photo of a <s1><s2>
Steps: 18%|█▊ | 175/1000 [01:34<07:36, 1.81it/s, loss=0.0422, lr=0.0004]
Steps: 18%|█▊ | 176/1000 [01:35<07:58, 1.72it/s, loss=0.0422, lr=0.0004]
a good photo of the <s1><s2>
Steps: 18%|█▊ | 176/1000 [01:35<07:58, 1.72it/s, loss=0.0218, lr=0.0004]
Steps: 18%|█▊ | 177/1000 [01:35<07:39, 1.79it/s, loss=0.0218, lr=0.0004]
a photo of a <s1><s2>
Steps: 18%|█▊ | 177/1000 [01:35<07:39, 1.79it/s, loss=0.181, lr=0.0004]
Steps: 18%|█▊ | 178/1000 [01:36<07:24, 1.85it/s, loss=0.181, lr=0.0004]
a cropped photo of the <s1><s2>
Steps: 18%|█▊ | 178/1000 [01:36<07:24, 1.85it/s, loss=0.0171, lr=0.0004]
Steps: 18%|█▊ | 179/1000 [01:36<07:16, 1.88it/s, loss=0.0171, lr=0.0004]
a rendition of a <s1><s2>
Steps: 18%|█▊ | 179/1000 [01:36<07:16, 1.88it/s, loss=0.0177, lr=0.0004]
Steps: 18%|█▊ | 180/1000 [01:37<07:01, 1.95it/s, loss=0.0177, lr=0.0004]
a photo of a <s1><s2>
Steps: 18%|█▊ | 180/1000 [01:37<07:01, 1.95it/s, loss=0.0109, lr=0.0004]
Steps: 18%|█▊ | 181/1000 [01:37<07:39, 1.78it/s, loss=0.0109, lr=0.0004]
a cropped photo of a <s1><s2>
Steps: 18%|█▊ | 181/1000 [01:37<07:39, 1.78it/s, loss=0.0627, lr=0.0004]
Steps: 18%|█▊ | 182/1000 [01:38<07:17, 1.87it/s, loss=0.0627, lr=0.0004]
a photo of the small <s1><s2>
Steps: 18%|█▊ | 182/1000 [01:38<07:17, 1.87it/s, loss=0.00471, lr=0.0004]
Steps: 18%|█▊ | 183/1000 [01:38<07:02, 1.93it/s, loss=0.00471, lr=0.0004]
a photo of one <s1><s2>
Steps: 18%|█▊ | 183/1000 [01:38<07:02, 1.93it/s, loss=0.0244, lr=0.0004]
Steps: 18%|█▊ | 184/1000 [01:39<07:39, 1.77it/s, loss=0.0244, lr=0.0004]
a photo of a small <s1><s2>
Steps: 18%|█▊ | 184/1000 [01:39<07:39, 1.77it/s, loss=0.0182, lr=0.0004]
Steps: 18%|█▊ | 185/1000 [01:40<07:32, 1.80it/s, loss=0.0182, lr=0.0004]
a bright photo of the <s1><s2>
Steps: 18%|█▊ | 185/1000 [01:40<07:32, 1.80it/s, loss=0.0129, lr=0.0004]
Steps: 19%|█▊ | 186/1000 [01:40<07:20, 1.85it/s, loss=0.0129, lr=0.0004]
a photo of the <s1><s2>
Steps: 19%|█▊ | 186/1000 [01:40<07:20, 1.85it/s, loss=0.0748, lr=0.0004]
Steps: 19%|█▊ | 187/1000 [01:41<07:03, 1.92it/s, loss=0.0748, lr=0.0004]
a rendering of a <s1><s2>
Steps: 19%|█▊ | 187/1000 [01:41<07:03, 1.92it/s, loss=0.0967, lr=0.0004]
Steps: 19%|█▉ | 188/1000 [01:41<07:39, 1.77it/s, loss=0.0967, lr=0.0004]
a photo of a small <s1><s2>
Steps: 19%|█▉ | 188/1000 [01:41<07:39, 1.77it/s, loss=0.042, lr=0.0004]
Steps: 19%|█▉ | 189/1000 [01:42<07:22, 1.83it/s, loss=0.042, lr=0.0004]
a rendition of the <s1><s2>
Steps: 19%|█▉ | 189/1000 [01:42<07:22, 1.83it/s, loss=0.202, lr=0.0004]
Steps: 19%|█▉ | 190/1000 [01:42<07:14, 1.86it/s, loss=0.202, lr=0.0004]
a rendering of a <s1><s2>
Steps: 19%|█▉ | 190/1000 [01:42<07:14, 1.86it/s, loss=0.00984, lr=0.0004]
Steps: 19%|█▉ | 191/1000 [01:43<06:54, 1.95it/s, loss=0.00984, lr=0.0004]
a photo of a cool <s1><s2>
Steps: 19%|█▉ | 191/1000 [01:43<06:54, 1.95it/s, loss=0.0936, lr=0.0004]
Steps: 19%|█▉ | 192/1000 [01:43<07:09, 1.88it/s, loss=0.0936, lr=0.0004]
a rendition of the <s1><s2>
Steps: 19%|█▉ | 192/1000 [01:43<07:09, 1.88it/s, loss=0.00203, lr=0.0004]
Steps: 19%|█▉ | 193/1000 [01:44<07:02, 1.91it/s, loss=0.00203, lr=0.0004]
a rendition of a <s1><s2>
Steps: 19%|█▉ | 193/1000 [01:44<07:02, 1.91it/s, loss=0.00986, lr=0.0004]
Steps: 19%|█▉ | 194/1000 [01:44<06:54, 1.94it/s, loss=0.00986, lr=0.0004]
a rendition of a <s1><s2>
Steps: 19%|█▉ | 194/1000 [01:44<06:54, 1.94it/s, loss=0.0103, lr=0.0004]
Steps: 20%|█▉ | 195/1000 [01:45<06:48, 1.97it/s, loss=0.0103, lr=0.0004]
a rendition of the <s1><s2>
Steps: 20%|█▉ | 195/1000 [01:45<06:48, 1.97it/s, loss=0.00532, lr=0.0004]
Steps: 20%|█▉ | 196/1000 [01:45<07:21, 1.82it/s, loss=0.00532, lr=0.0004]
a photo of a <s1><s2>
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a photo of one <s1><s2>
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a good photo of a <s1><s2>
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a photo of a <s1><s2>
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a photo of a <s1><s2>
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a photo of the small <s1><s2>
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a close-up photo of the <s1><s2>
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a cropped photo of a <s1><s2>
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a photo of my <s1><s2>
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a good photo of the <s1><s2>
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a photo of the nice <s1><s2>
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a cropped photo of a <s1><s2>
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a close-up photo of the <s1><s2>
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a photo of the weird <s1><s2>
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a photo of the <s1><s2>
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a cropped photo of the <s1><s2>
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a photo of a cool <s1><s2>
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a photo of a nice <s1><s2>
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a photo of a nice <s1><s2>
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a photo of a <s1><s2>
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a rendering of a <s1><s2>
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a photo of a nice <s1><s2>
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a photo of the clean <s1><s2>
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a photo of a nice <s1><s2>
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a photo of the clean <s1><s2>
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a photo of a <s1><s2>
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a good photo of a <s1><s2>
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a good photo of a <s1><s2>
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the photo of a <s1><s2>
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a cropped photo of a <s1><s2>
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a close-up photo of a <s1><s2>
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a good photo of a <s1><s2>
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a cropped photo of a <s1><s2>
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a photo of the clean <s1><s2>
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a close-up photo of the <s1><s2>
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a close-up photo of a <s1><s2>
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a close-up photo of a <s1><s2>
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a good photo of the <s1><s2>
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a cropped photo of the <s1><s2>
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a photo of a small <s1><s2>
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a bright photo of the <s1><s2>
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a rendition of the <s1><s2>
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a photo of the clean <s1><s2>
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a cropped photo of the <s1><s2>
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a photo of the large <s1><s2>
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a rendition of the <s1><s2>
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a photo of the <s1><s2>
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a photo of one <s1><s2>
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a photo of the weird <s1><s2>
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a cropped photo of a <s1><s2>
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a cropped photo of the <s1><s2>
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a dark photo of the <s1><s2>
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a rendition of the <s1><s2>
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a photo of the cool <s1><s2>
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a photo of the cool <s1><s2>
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a photo of the small <s1><s2>
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a photo of a <s1><s2>
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a bright photo of the <s1><s2>
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a photo of my <s1><s2>
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a photo of a dirty <s1><s2>
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a dark photo of the <s1><s2>
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a photo of the small <s1><s2>
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a photo of a <s1><s2>
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a photo of the clean <s1><s2>
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a bright photo of the <s1><s2>
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a photo of a <s1><s2>
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a rendition of a <s1><s2>
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a good photo of the <s1><s2>
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a photo of the weird <s1><s2>
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a photo of the weird <s1><s2>
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a photo of the clean <s1><s2>
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a photo of a dirty <s1><s2>
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a photo of a dirty <s1><s2>
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the photo of a <s1><s2>
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a photo of the cool <s1><s2>
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a close-up photo of the <s1><s2>
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Steps: 27%|██▋ | 272/1000 [02:26<06:35, 1.84it/s, loss=0.0694, lr=0.0004]
a photo of a <s1><s2>
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Steps: 27%|██▋ | 273/1000 [02:26<06:25, 1.89it/s, loss=0.0225, lr=0.0004]
a close-up photo of the <s1><s2>
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Steps: 27%|██▋ | 274/1000 [02:27<06:17, 1.92it/s, loss=0.023, lr=0.0004]
a good photo of a <s1><s2>
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Steps: 28%|██▊ | 275/1000 [02:27<06:46, 1.78it/s, loss=0.0149, lr=0.0004]
a rendering of a <s1><s2>
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a photo of a <s1><s2>
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a rendering of a <s1><s2>
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a photo of the nice <s1><s2>
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a photo of a small <s1><s2>
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a cropped photo of the <s1><s2>
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the photo of a <s1><s2>
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a photo of the small <s1><s2>
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a close-up photo of a <s1><s2>
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a photo of a dirty <s1><s2>
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a photo of a nice <s1><s2>
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a good photo of the <s1><s2>
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a good photo of a <s1><s2>
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a photo of one <s1><s2>
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a photo of a nice <s1><s2>
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a photo of a small <s1><s2>
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a photo of the small <s1><s2>
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a photo of a <s1><s2>
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a good photo of the <s1><s2>
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a dark photo of the <s1><s2>
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a photo of a small <s1><s2>
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a photo of a clean <s1><s2>
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a bright photo of the <s1><s2>
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a photo of the weird <s1><s2>
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a bright photo of the <s1><s2>
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the photo of a <s1><s2>
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a photo of a cool <s1><s2>
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a bright photo of the <s1><s2>
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a good photo of the <s1><s2>
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a rendering of a <s1><s2>
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a photo of a cool <s1><s2>
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a photo of the large <s1><s2>
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a photo of my <s1><s2>
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a rendition of a <s1><s2>
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a photo of a small <s1><s2>
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the photo of a <s1><s2>
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a photo of the cool <s1><s2>
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a photo of the nice <s1><s2>
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a bright photo of the <s1><s2>
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the photo of a <s1><s2>
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a rendition of a <s1><s2>
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a rendering of a <s1><s2>
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a cropped photo of the <s1><s2>
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a close-up photo of a <s1><s2>
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a rendering of a <s1><s2>
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a photo of a small <s1><s2>
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a cropped photo of a <s1><s2>
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a rendition of the <s1><s2>
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a good photo of the <s1><s2>
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a photo of a <s1><s2>
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a bright photo of the <s1><s2>
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a photo of a small <s1><s2>
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a photo of the large <s1><s2>
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a photo of the clean <s1><s2>
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a photo of one <s1><s2>
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a photo of a small <s1><s2>
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a close-up photo of a <s1><s2>
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a photo of my <s1><s2>
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a photo of the weird <s1><s2>
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a photo of a <s1><s2>
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a close-up photo of a <s1><s2>
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a dark photo of the <s1><s2>
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a dark photo of the <s1><s2>
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a rendering of a <s1><s2>
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a photo of the large <s1><s2>
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a photo of a clean <s1><s2>
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a photo of a dirty <s1><s2>
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a rendering of a <s1><s2>
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a photo of the nice <s1><s2>
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a good photo of a <s1><s2>
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a photo of the clean <s1><s2>
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a photo of the nice <s1><s2>
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a photo of the clean <s1><s2>
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a good photo of a <s1><s2>
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a close-up photo of the <s1><s2>
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the photo of a <s1><s2>
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a photo of a dirty <s1><s2>
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a close-up photo of a <s1><s2>
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a photo of the nice <s1><s2>
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a cropped photo of a <s1><s2>
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a bright photo of the <s1><s2>
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a photo of my <s1><s2>
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a photo of my <s1><s2>
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Steps: 36%|███▌ | 358/1000 [03:11<05:36, 1.91it/s, loss=0.0102, lr=0.0004]
a bright photo of the <s1><s2>
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a photo of a dirty <s1><s2>
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a photo of a small <s1><s2>
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a photo of the nice <s1><s2>
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a photo of the nice <s1><s2>
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a good photo of a <s1><s2>
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the photo of a <s1><s2>
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a dark photo of the <s1><s2>
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a photo of a clean <s1><s2>
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a photo of a nice <s1><s2>
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a photo of the clean <s1><s2>
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a dark photo of the <s1><s2>
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a photo of the weird <s1><s2>
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a photo of a nice <s1><s2>
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Steps: 37%|███▋ | 372/1000 [03:19<06:11, 1.69it/s, loss=0.0129, lr=0.0004]
a dark photo of the <s1><s2>
Steps: 37%|███▋ | 372/1000 [03:19<06:11, 1.69it/s, loss=0.00216, lr=0.0004]
Steps: 37%|███▋ | 373/1000 [03:20<06:18, 1.66it/s, loss=0.00216, lr=0.0004]
a photo of a cool <s1><s2>
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a photo of the small <s1><s2>
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a cropped photo of the <s1><s2>
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a photo of the clean <s1><s2>
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a good photo of the <s1><s2>
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Steps: 38%|███▊ | 378/1000 [03:22<05:24, 1.92it/s, loss=0.169, lr=0.0004]
a photo of the large <s1><s2>
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a close-up photo of the <s1><s2>
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a photo of the cool <s1><s2>
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Steps: 38%|███▊ | 381/1000 [03:24<05:30, 1.88it/s, loss=0.0515, lr=0.0004]
a photo of a small <s1><s2>
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a photo of the clean <s1><s2>
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Steps: 38%|███▊ | 383/1000 [03:25<05:34, 1.84it/s, loss=0.00917, lr=0.0004]
a rendition of a <s1><s2>
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Steps: 38%|███▊ | 384/1000 [03:25<05:17, 1.94it/s, loss=0.00676, lr=0.0004]
a photo of the nice <s1><s2>
Steps: 38%|███▊ | 384/1000 [03:25<05:17, 1.94it/s, loss=0.359, lr=0.0004]
Steps: 38%|███▊ | 385/1000 [03:26<05:10, 1.98it/s, loss=0.359, lr=0.0004]
a photo of a small <s1><s2>
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Steps: 39%|███▊ | 386/1000 [03:26<05:04, 2.02it/s, loss=0.28, lr=0.0004]
a photo of the cool <s1><s2>
Steps: 39%|███▊ | 386/1000 [03:26<05:04, 2.02it/s, loss=0.0666, lr=0.0004]
Steps: 39%|███▊ | 387/1000 [03:27<05:04, 2.01it/s, loss=0.0666, lr=0.0004]
a rendition of a <s1><s2>
Steps: 39%|███▊ | 387/1000 [03:27<05:04, 2.01it/s, loss=0.0278, lr=0.0004]
Steps: 39%|███▉ | 388/1000 [03:27<05:28, 1.86it/s, loss=0.0278, lr=0.0004]
a cropped photo of the <s1><s2>
Steps: 39%|███▉ | 388/1000 [03:27<05:28, 1.86it/s, loss=0.0161, lr=0.0004]
Steps: 39%|███▉ | 389/1000 [03:28<05:07, 1.98it/s, loss=0.0161, lr=0.0004]
a rendition of a <s1><s2>
Steps: 39%|███▉ | 389/1000 [03:28<05:07, 1.98it/s, loss=0.167, lr=0.0004]
Steps: 39%|███▉ | 390/1000 [03:28<04:59, 2.04it/s, loss=0.167, lr=0.0004]
a photo of a dirty <s1><s2>
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Steps: 39%|███▉ | 391/1000 [03:29<05:18, 1.91it/s, loss=0.0483, lr=0.0004]
a photo of the large <s1><s2>
Steps: 39%|███▉ | 391/1000 [03:29<05:18, 1.91it/s, loss=0.00784, lr=0.0004]
Steps: 39%|███▉ | 392/1000 [03:29<05:12, 1.95it/s, loss=0.00784, lr=0.0004]
a photo of the nice <s1><s2>
Steps: 39%|███▉ | 392/1000 [03:29<05:12, 1.95it/s, loss=0.00592, lr=0.0004]
Steps: 39%|███▉ | 393/1000 [03:30<05:02, 2.01it/s, loss=0.00592, lr=0.0004]
a close-up photo of the <s1><s2>
Steps: 39%|███▉ | 393/1000 [03:30<05:02, 2.01it/s, loss=0.106, lr=0.0004]
Steps: 39%|███▉ | 394/1000 [03:31<05:23, 1.87it/s, loss=0.106, lr=0.0004]
a bright photo of the <s1><s2>
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Steps: 40%|███▉ | 395/1000 [03:31<05:46, 1.75it/s, loss=0.0243, lr=0.0004]
a photo of a dirty <s1><s2>
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Steps: 40%|███▉ | 396/1000 [03:32<05:35, 1.80it/s, loss=0.00629, lr=0.0004]
a rendition of a <s1><s2>
Steps: 40%|███▉ | 396/1000 [03:32<05:35, 1.80it/s, loss=0.155, lr=0.0004]
Steps: 40%|███▉ | 397/1000 [03:32<05:15, 1.91it/s, loss=0.155, lr=0.0004]
a photo of the small <s1><s2>
Steps: 40%|███▉ | 397/1000 [03:32<05:15, 1.91it/s, loss=0.127, lr=0.0004]
Steps: 40%|███▉ | 398/1000 [03:33<05:12, 1.93it/s, loss=0.127, lr=0.0004]
a close-up photo of a <s1><s2>
Steps: 40%|███▉ | 398/1000 [03:33<05:12, 1.93it/s, loss=0.035, lr=0.0004]
Steps: 40%|███▉ | 399/1000 [03:33<05:14, 1.91it/s, loss=0.035, lr=0.0004]
a rendition of the <s1><s2>
Steps: 40%|███▉ | 399/1000 [03:33<05:14, 1.91it/s, loss=0.0328, lr=0.0004]
Steps: 40%|████ | 400/1000 [03:34<05:10, 1.93it/s, loss=0.0328, lr=0.0004]
a photo of the clean <s1><s2>
Steps: 40%|████ | 400/1000 [03:34<05:10, 1.93it/s, loss=0.00762, lr=0.0004]
Steps: 40%|████ | 401/1000 [03:34<05:01, 1.99it/s, loss=0.00762, lr=0.0004]
a good photo of the <s1><s2>
Steps: 40%|████ | 401/1000 [03:34<05:01, 1.99it/s, loss=0.268, lr=0.0004]
Steps: 40%|████ | 402/1000 [03:35<04:53, 2.04it/s, loss=0.268, lr=0.0004]
a photo of the small <s1><s2>
Steps: 40%|████ | 402/1000 [03:35<04:53, 2.04it/s, loss=0.0388, lr=0.0004]
Steps: 40%|████ | 403/1000 [03:35<05:22, 1.85it/s, loss=0.0388, lr=0.0004]
a photo of a dirty <s1><s2>
Steps: 40%|████ | 403/1000 [03:35<05:22, 1.85it/s, loss=0.059, lr=0.0004]
Steps: 40%|████ | 404/1000 [03:36<05:12, 1.91it/s, loss=0.059, lr=0.0004]
a close-up photo of the <s1><s2>
Steps: 40%|████ | 404/1000 [03:36<05:12, 1.91it/s, loss=0.00572, lr=0.0004]
Steps: 40%|████ | 405/1000 [03:36<05:10, 1.92it/s, loss=0.00572, lr=0.0004]
a photo of a nice <s1><s2>
Steps: 40%|████ | 405/1000 [03:36<05:10, 1.92it/s, loss=0.00473, lr=0.0004]
Steps: 41%|████ | 406/1000 [03:37<05:31, 1.79it/s, loss=0.00473, lr=0.0004]
a photo of a clean <s1><s2>
Steps: 41%|████ | 406/1000 [03:37<05:31, 1.79it/s, loss=0.00587, lr=0.0004]
Steps: 41%|████ | 407/1000 [03:37<05:22, 1.84it/s, loss=0.00587, lr=0.0004]
a good photo of a <s1><s2>
Steps: 41%|████ | 407/1000 [03:37<05:22, 1.84it/s, loss=0.0044, lr=0.0004]
Steps: 41%|████ | 408/1000 [03:38<05:10, 1.90it/s, loss=0.0044, lr=0.0004]
a photo of a dirty <s1><s2>
Steps: 41%|████ | 408/1000 [03:38<05:10, 1.90it/s, loss=0.0121, lr=0.0004]
Steps: 41%|████ | 409/1000 [03:38<05:09, 1.91it/s, loss=0.0121, lr=0.0004]
a close-up photo of a <s1><s2>
Steps: 41%|████ | 409/1000 [03:38<05:09, 1.91it/s, loss=0.0962, lr=0.0004]
Steps: 41%|████ | 410/1000 [03:39<05:02, 1.95it/s, loss=0.0962, lr=0.0004]
a photo of the large <s1><s2>
Steps: 41%|████ | 410/1000 [03:39<05:02, 1.95it/s, loss=0.00194, lr=0.0004]
Steps: 41%|████ | 411/1000 [03:39<04:50, 2.03it/s, loss=0.00194, lr=0.0004]
a cropped photo of a <s1><s2>
Steps: 41%|████ | 411/1000 [03:39<04:50, 2.03it/s, loss=0.0325, lr=0.0004]
Steps: 41%|████ | 412/1000 [03:40<05:23, 1.82it/s, loss=0.0325, lr=0.0004]
a rendition of a <s1><s2>
Steps: 41%|████ | 412/1000 [03:40<05:23, 1.82it/s, loss=0.00856, lr=0.0004]
Steps: 41%|████▏ | 413/1000 [03:41<05:33, 1.76it/s, loss=0.00856, lr=0.0004]
a photo of the clean <s1><s2>
Steps: 41%|████▏ | 413/1000 [03:41<05:33, 1.76it/s, loss=0.00695, lr=0.0004]
Steps: 41%|████▏ | 414/1000 [03:41<05:49, 1.68it/s, loss=0.00695, lr=0.0004]
a rendition of a <s1><s2>
Steps: 41%|████▏ | 414/1000 [03:41<05:49, 1.68it/s, loss=0.102, lr=0.0004]
Steps: 42%|████▏ | 415/1000 [03:42<05:55, 1.64it/s, loss=0.102, lr=0.0004]
a cropped photo of the <s1><s2>
Steps: 42%|████▏ | 415/1000 [03:42<05:55, 1.64it/s, loss=0.00786, lr=0.0004]
Steps: 42%|████▏ | 416/1000 [03:42<05:40, 1.71it/s, loss=0.00786, lr=0.0004]
a photo of a dirty <s1><s2>
Steps: 42%|████▏ | 416/1000 [03:42<05:40, 1.71it/s, loss=0.693, lr=0.0004]
Steps: 42%|████▏ | 417/1000 [03:43<05:21, 1.81it/s, loss=0.693, lr=0.0004]
a photo of the nice <s1><s2>
Steps: 42%|████▏ | 417/1000 [03:43<05:21, 1.81it/s, loss=0.00828, lr=0.0004]
Steps: 42%|████▏ | 418/1000 [03:43<05:09, 1.88it/s, loss=0.00828, lr=0.0004]
a rendering of a <s1><s2>
Steps: 42%|████▏ | 418/1000 [03:43<05:09, 1.88it/s, loss=0.0266, lr=0.0004]
Steps: 42%|████▏ | 419/1000 [03:44<05:07, 1.89it/s, loss=0.0266, lr=0.0004]
a photo of a clean <s1><s2>
Steps: 42%|████▏ | 419/1000 [03:44<05:07, 1.89it/s, loss=0.132, lr=0.0004]
Steps: 42%|████▏ | 420/1000 [03:44<05:06, 1.89it/s, loss=0.132, lr=0.0004]
a bright photo of the <s1><s2>
Steps: 42%|████▏ | 420/1000 [03:44<05:06, 1.89it/s, loss=0.0231, lr=0.0004]
Steps: 42%|████▏ | 421/1000 [03:45<04:50, 2.00it/s, loss=0.0231, lr=0.0004]
a close-up photo of the <s1><s2>
Steps: 42%|████▏ | 421/1000 [03:45<04:50, 2.00it/s, loss=0.0484, lr=0.0004]
Steps: 42%|████▏ | 422/1000 [03:45<04:41, 2.05it/s, loss=0.0484, lr=0.0004]
a photo of my <s1><s2>
Steps: 42%|████▏ | 422/1000 [03:45<04:41, 2.05it/s, loss=0.0283, lr=0.0004]
Steps: 42%|████▏ | 423/1000 [03:46<05:08, 1.87it/s, loss=0.0283, lr=0.0004]
a photo of the cool <s1><s2>
Steps: 42%|████▏ | 423/1000 [03:46<05:08, 1.87it/s, loss=0.00544, lr=0.0004]
Steps: 42%|████▏ | 424/1000 [03:47<05:07, 1.87it/s, loss=0.00544, lr=0.0004]
a photo of one <s1><s2>
Steps: 42%|████▏ | 424/1000 [03:47<05:07, 1.87it/s, loss=0.194, lr=0.0004]
Steps: 42%|████▎ | 425/1000 [03:47<05:24, 1.77it/s, loss=0.194, lr=0.0004]
a photo of my <s1><s2>
Steps: 42%|████▎ | 425/1000 [03:47<05:24, 1.77it/s, loss=0.00996, lr=0.0004]
Steps: 43%|████▎ | 426/1000 [03:48<05:12, 1.83it/s, loss=0.00996, lr=0.0004]
a rendering of a <s1><s2>
Steps: 43%|████▎ | 426/1000 [03:48<05:12, 1.83it/s, loss=0.0341, lr=0.0004]
Steps: 43%|████▎ | 427/1000 [03:48<05:10, 1.84it/s, loss=0.0341, lr=0.0004]
a rendering of a <s1><s2>
Steps: 43%|████▎ | 427/1000 [03:48<05:10, 1.84it/s, loss=0.0334, lr=0.0004]
Steps: 43%|████▎ | 428/1000 [03:49<05:04, 1.88it/s, loss=0.0334, lr=0.0004]
a photo of a small <s1><s2>
Steps: 43%|████▎ | 428/1000 [03:49<05:04, 1.88it/s, loss=0.0062, lr=0.0004]
Steps: 43%|████▎ | 429/1000 [03:49<05:06, 1.86it/s, loss=0.0062, lr=0.0004]
the photo of a <s1><s2>
Steps: 43%|████▎ | 429/1000 [03:49<05:06, 1.86it/s, loss=0.0396, lr=0.0004]
Steps: 43%|████▎ | 430/1000 [03:50<05:30, 1.73it/s, loss=0.0396, lr=0.0004]
a cropped photo of a <s1><s2>
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a close-up photo of the <s1><s2>
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a photo of a small <s1><s2>
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a rendition of a <s1><s2>
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a photo of a dirty <s1><s2>
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a photo of the <s1><s2>
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a photo of one <s1><s2>
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a photo of one <s1><s2>
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a cropped photo of the <s1><s2>
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a photo of one <s1><s2>
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a photo of a clean <s1><s2>
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a photo of a <s1><s2>
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a photo of the nice <s1><s2>
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a photo of one <s1><s2>
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a dark photo of the <s1><s2>
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a photo of a small <s1><s2>
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a cropped photo of a <s1><s2>
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a photo of a small <s1><s2>
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a good photo of a <s1><s2>
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a dark photo of the <s1><s2>
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a photo of a clean <s1><s2>
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the photo of a <s1><s2>
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a rendition of the <s1><s2>
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a good photo of a <s1><s2>
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a close-up photo of the <s1><s2>
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a rendering of a <s1><s2>
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Steps: 46%|████▌ | 456/1000 [04:03<04:16, 2.12it/s, loss=0.107, lr=0.0004]
a photo of a small <s1><s2>
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a rendition of the <s1><s2>
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a photo of the small <s1><s2>
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Steps: 46%|████▌ | 459/1000 [04:05<04:46, 1.89it/s, loss=0.139, lr=0.0004]
a photo of a nice <s1><s2>
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the photo of a <s1><s2>
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a cropped photo of a <s1><s2>
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a good photo of a <s1><s2>
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a close-up photo of the <s1><s2>
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a photo of the <s1><s2>
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a dark photo of the <s1><s2>
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a good photo of the <s1><s2>
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the photo of a <s1><s2>
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a rendition of a <s1><s2>
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a photo of the <s1><s2>
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Steps: 47%|████▋ | 470/1000 [04:11<04:29, 1.97it/s, loss=0.00531, lr=0.0004]
a photo of the nice <s1><s2>
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a photo of my <s1><s2>
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a photo of a nice <s1><s2>
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a photo of the weird <s1><s2>
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a photo of the small <s1><s2>
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a cropped photo of a <s1><s2>
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a rendition of a <s1><s2>
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a photo of the weird <s1><s2>
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a photo of a <s1><s2>
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a photo of the large <s1><s2>
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a rendering of a <s1><s2>
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a good photo of the <s1><s2>
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a photo of the cool <s1><s2>
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a dark photo of the <s1><s2>
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a photo of the nice <s1><s2>
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a photo of the nice <s1><s2>
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a photo of a small <s1><s2>
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a rendition of the <s1><s2>
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a good photo of the <s1><s2>
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a photo of the weird <s1><s2>
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a photo of a cool <s1><s2>
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a rendition of a <s1><s2>
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Steps: 49%|████▉ | 492/1000 [04:23<04:48, 1.76it/s, loss=0.241, lr=0.0004]
a photo of a dirty <s1><s2>
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a close-up photo of a <s1><s2>
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a photo of the clean <s1><s2>
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the photo of a <s1><s2>
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a photo of the clean <s1><s2>
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a cropped photo of a <s1><s2>
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a rendering of a <s1><s2>
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a photo of one <s1><s2>
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a photo of the large <s1><s2>
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a photo of the <s1><s2>
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a photo of the <s1><s2>
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a photo of a small <s1><s2>
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a photo of the large <s1><s2>
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a close-up photo of the <s1><s2>
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Steps: 51%|█████ | 506/1000 [04:31<04:21, 1.89it/s, loss=0.0337, lr=0.0004]
a cropped photo of a <s1><s2>
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a photo of the large <s1><s2>
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a photo of a <s1><s2>
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a good photo of the <s1><s2>
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a bright photo of the <s1><s2>
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a cropped photo of the <s1><s2>
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a close-up photo of the <s1><s2>
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the photo of a <s1><s2>
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a photo of the cool <s1><s2>
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a photo of one <s1><s2>
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a good photo of the <s1><s2>
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a photo of a <s1><s2>
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a photo of the clean <s1><s2>
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a photo of the <s1><s2>
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a rendition of the <s1><s2>
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a photo of the small <s1><s2>
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a bright photo of the <s1><s2>
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a bright photo of the <s1><s2>
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a photo of a cool <s1><s2>
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a photo of the cool <s1><s2>
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a dark photo of the <s1><s2>
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a rendition of the <s1><s2>
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a rendition of the <s1><s2>
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a photo of one <s1><s2>
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a photo of the cool <s1><s2>
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a dark photo of the <s1><s2>
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a photo of the <s1><s2>
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a photo of a <s1><s2>
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a cropped photo of a <s1><s2>
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a photo of the large <s1><s2>
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a good photo of the <s1><s2>
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a rendition of the <s1><s2>
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a close-up photo of a <s1><s2>
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a dark photo of the <s1><s2>
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a photo of the nice <s1><s2>
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a photo of the cool <s1><s2>
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a photo of a small <s1><s2>
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a good photo of the <s1><s2>
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a good photo of the <s1><s2>
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a photo of the nice <s1><s2>
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a cropped photo of the <s1><s2>
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a photo of a small <s1><s2>
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a close-up photo of a <s1><s2>
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a cropped photo of a <s1><s2>
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a photo of a cool <s1><s2>
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a photo of the weird <s1><s2>
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a photo of a dirty <s1><s2>
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a photo of a <s1><s2>
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a good photo of a <s1><s2>
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a photo of the cool <s1><s2>
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a photo of a <s1><s2>
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a photo of the nice <s1><s2>
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a dark photo of the <s1><s2>
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a bright photo of the <s1><s2>
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a close-up photo of the <s1><s2>
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a photo of the small <s1><s2>
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a dark photo of the <s1><s2>
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a close-up photo of the <s1><s2>
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a dark photo of the <s1><s2>
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a photo of the weird <s1><s2>
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a photo of my <s1><s2>
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a photo of a small <s1><s2>
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the photo of a <s1><s2>
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a photo of my <s1><s2>
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a photo of the large <s1><s2>
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a photo of my <s1><s2>
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a photo of a <s1><s2>
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a photo of a small <s1><s2>
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a dark photo of the <s1><s2>
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a photo of a clean <s1><s2>
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a photo of the nice <s1><s2>
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a good photo of a <s1><s2>
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a photo of the <s1><s2>
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a photo of a cool <s1><s2>
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a close-up photo of a <s1><s2>
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the photo of a <s1><s2>
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a bright photo of the <s1><s2>
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a photo of a <s1><s2>
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a photo of the small <s1><s2>
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a good photo of a <s1><s2>
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a cropped photo of the <s1><s2>
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a photo of a cool <s1><s2>
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a photo of my <s1><s2>
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a cropped photo of the <s1><s2>
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the photo of a <s1><s2>
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a dark photo of the <s1><s2>
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a photo of the weird <s1><s2>
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a rendering of a <s1><s2>
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a photo of the nice <s1><s2>
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a photo of the <s1><s2>
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a photo of a cool <s1><s2>
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a photo of the <s1><s2>
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a photo of a <s1><s2>
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a photo of the small <s1><s2>
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a rendition of the <s1><s2>
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a photo of the clean <s1><s2>
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a photo of the large <s1><s2>
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a cropped photo of the <s1><s2>
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a good photo of a <s1><s2>
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Steps: 60%|██████ | 605/1000 [05:22<03:19, 1.98it/s, loss=0.00464, lr=0.0004]
a photo of a small <s1><s2>
Steps: 60%|██████ | 605/1000 [05:22<03:19, 1.98it/s, loss=0.0178, lr=0.0004]
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a photo of the nice <s1><s2>
Steps: 61%|██████ | 606/1000 [05:22<03:13, 2.04it/s, loss=0.322, lr=0.0004]
Steps: 61%|██████ | 607/1000 [05:23<03:30, 1.87it/s, loss=0.322, lr=0.0004]
a photo of the clean <s1><s2>
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Steps: 61%|██████ | 608/1000 [05:24<03:39, 1.78it/s, loss=0.0306, lr=0.0004]
a photo of a nice <s1><s2>
Steps: 61%|██████ | 608/1000 [05:24<03:39, 1.78it/s, loss=0.00946, lr=0.0004]
Steps: 61%|██████ | 609/1000 [05:24<03:34, 1.82it/s, loss=0.00946, lr=0.0004]
a photo of a small <s1><s2>
Steps: 61%|██████ | 609/1000 [05:24<03:34, 1.82it/s, loss=0.092, lr=0.0004]
Steps: 61%|██████ | 610/1000 [05:25<03:25, 1.90it/s, loss=0.092, lr=0.0004]
a photo of the small <s1><s2>
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a dark photo of the <s1><s2>
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a photo of the small <s1><s2>
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Steps: 61%|██████▏ | 613/1000 [05:26<03:20, 1.93it/s, loss=0.0129, lr=0.0004]
a cropped photo of the <s1><s2>
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Steps: 61%|██████▏ | 614/1000 [05:27<03:31, 1.82it/s, loss=0.0133, lr=0.0004]
the photo of a <s1><s2>
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a rendering of a <s1><s2>
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Steps: 62%|██████▏ | 616/1000 [05:28<03:13, 1.98it/s, loss=0.0287, lr=0.0004]
a photo of the <s1><s2>
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Steps: 62%|██████▏ | 617/1000 [05:28<03:12, 1.99it/s, loss=0.063, lr=0.0004]
a rendition of a <s1><s2>
Steps: 62%|██████▏ | 617/1000 [05:28<03:12, 1.99it/s, loss=0.0111, lr=0.0004]
Steps: 62%|██████▏ | 618/1000 [05:29<03:13, 1.97it/s, loss=0.0111, lr=0.0004]
a photo of the small <s1><s2>
Steps: 62%|██████▏ | 618/1000 [05:29<03:13, 1.97it/s, loss=0.00378, lr=0.0004]
Steps: 62%|██████▏ | 619/1000 [05:29<03:23, 1.87it/s, loss=0.00378, lr=0.0004]
a photo of the clean <s1><s2>
Steps: 62%|██████▏ | 619/1000 [05:29<03:23, 1.87it/s, loss=0.0578, lr=0.0004]
Steps: 62%|██████▏ | 620/1000 [05:30<03:31, 1.80it/s, loss=0.0578, lr=0.0004]
a cropped photo of a <s1><s2>
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Steps: 62%|██████▏ | 621/1000 [05:30<03:20, 1.89it/s, loss=0.00292, lr=0.0004]
the photo of a <s1><s2>
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Steps: 62%|██████▏ | 622/1000 [05:31<03:16, 1.92it/s, loss=0.0916, lr=0.0004]
a cropped photo of the <s1><s2>
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Steps: 62%|██████▏ | 623/1000 [05:31<03:07, 2.01it/s, loss=0.0175, lr=0.0004]
a cropped photo of the <s1><s2>
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Steps: 62%|██████▏ | 624/1000 [05:32<03:22, 1.85it/s, loss=0.054, lr=0.0004]
a photo of a small <s1><s2>
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a photo of a nice <s1><s2>
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a cropped photo of a <s1><s2>
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a photo of a <s1><s2>
Steps: 63%|██████▎ | 627/1000 [05:33<03:05, 2.01it/s, loss=0.386, lr=0.0004]
Steps: 63%|██████▎ | 628/1000 [05:34<03:24, 1.82it/s, loss=0.386, lr=0.0004]
a close-up photo of a <s1><s2>
Steps: 63%|██████▎ | 628/1000 [05:34<03:24, 1.82it/s, loss=0.0151, lr=0.0004]
Steps: 63%|██████▎ | 629/1000 [05:34<03:14, 1.91it/s, loss=0.0151, lr=0.0004]
a rendition of a <s1><s2>
Steps: 63%|██████▎ | 629/1000 [05:34<03:14, 1.91it/s, loss=0.0123, lr=0.0004]
Steps: 63%|██████▎ | 630/1000 [05:35<03:09, 1.96it/s, loss=0.0123, lr=0.0004]
a photo of the weird <s1><s2>
Steps: 63%|██████▎ | 630/1000 [05:35<03:09, 1.96it/s, loss=0.0377, lr=0.0004]
Steps: 63%|██████▎ | 631/1000 [05:35<03:06, 1.97it/s, loss=0.0377, lr=0.0004]
a photo of the clean <s1><s2>
Steps: 63%|██████▎ | 631/1000 [05:35<03:06, 1.97it/s, loss=0.00312, lr=0.0004]
Steps: 63%|██████▎ | 632/1000 [05:36<03:20, 1.84it/s, loss=0.00312, lr=0.0004]
a good photo of a <s1><s2>
Steps: 63%|██████▎ | 632/1000 [05:36<03:20, 1.84it/s, loss=0.0252, lr=0.0004]
Steps: 63%|██████▎ | 633/1000 [05:37<03:16, 1.87it/s, loss=0.0252, lr=0.0004]
a photo of the large <s1><s2>
Steps: 63%|██████▎ | 633/1000 [05:37<03:16, 1.87it/s, loss=0.0672, lr=0.0004]
Steps: 63%|██████▎ | 634/1000 [05:37<03:06, 1.96it/s, loss=0.0672, lr=0.0004]
a photo of the small <s1><s2>
Steps: 63%|██████▎ | 634/1000 [05:37<03:06, 1.96it/s, loss=0.16, lr=0.0004]
Steps: 64%|██████▎ | 635/1000 [05:38<03:16, 1.86it/s, loss=0.16, lr=0.0004]
a rendition of a <s1><s2>
Steps: 64%|██████▎ | 635/1000 [05:38<03:16, 1.86it/s, loss=0.0129, lr=0.0004]
Steps: 64%|██████▎ | 636/1000 [05:38<03:05, 1.96it/s, loss=0.0129, lr=0.0004]
a photo of one <s1><s2>
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Steps: 64%|██████▎ | 637/1000 [05:39<02:59, 2.03it/s, loss=0.121, lr=0.0004]
a close-up photo of a <s1><s2>
Steps: 64%|██████▎ | 637/1000 [05:39<02:59, 2.03it/s, loss=0.0073, lr=0.0004]
Steps: 64%|██████▍ | 638/1000 [05:39<03:13, 1.87it/s, loss=0.0073, lr=0.0004]
a rendering of a <s1><s2>
Steps: 64%|██████▍ | 638/1000 [05:39<03:13, 1.87it/s, loss=0.01, lr=0.0004]
Steps: 64%|██████▍ | 639/1000 [05:40<03:22, 1.78it/s, loss=0.01, lr=0.0004]
a photo of a nice <s1><s2>
Steps: 64%|██████▍ | 639/1000 [05:40<03:22, 1.78it/s, loss=0.00776, lr=0.0004]
Steps: 64%|██████▍ | 640/1000 [05:40<03:07, 1.92it/s, loss=0.00776, lr=0.0004]
a cropped photo of the <s1><s2>
Steps: 64%|██████▍ | 640/1000 [05:40<03:07, 1.92it/s, loss=0.0542, lr=0.0004]
Steps: 64%|██████▍ | 641/1000 [05:41<03:01, 1.98it/s, loss=0.0542, lr=0.0004]
a rendition of the <s1><s2>
Steps: 64%|██████▍ | 641/1000 [05:41<03:01, 1.98it/s, loss=0.53, lr=0.0004]
Steps: 64%|██████▍ | 642/1000 [05:41<03:00, 1.99it/s, loss=0.53, lr=0.0004]
a photo of the small <s1><s2>
Steps: 64%|██████▍ | 642/1000 [05:41<03:00, 1.99it/s, loss=0.0042, lr=0.0004]
Steps: 64%|██████▍ | 643/1000 [05:42<02:56, 2.02it/s, loss=0.0042, lr=0.0004]
a bright photo of the <s1><s2>
Steps: 64%|██████▍ | 643/1000 [05:42<02:56, 2.02it/s, loss=0.0289, lr=0.0004]
Steps: 64%|██████▍ | 644/1000 [05:42<02:53, 2.05it/s, loss=0.0289, lr=0.0004]
a rendition of the <s1><s2>
Steps: 64%|██████▍ | 644/1000 [05:42<02:53, 2.05it/s, loss=0.0812, lr=0.0004]
Steps: 64%|██████▍ | 645/1000 [05:43<02:53, 2.04it/s, loss=0.0812, lr=0.0004]
a photo of the <s1><s2>
Steps: 64%|██████▍ | 645/1000 [05:43<02:53, 2.04it/s, loss=0.0283, lr=0.0004]
Steps: 65%|██████▍ | 646/1000 [05:43<02:49, 2.09it/s, loss=0.0283, lr=0.0004]
a photo of the large <s1><s2>
Steps: 65%|██████▍ | 646/1000 [05:43<02:49, 2.09it/s, loss=0.0795, lr=0.0004]
Steps: 65%|██████▍ | 647/1000 [05:44<02:51, 2.06it/s, loss=0.0795, lr=0.0004]
a bright photo of the <s1><s2>
Steps: 65%|██████▍ | 647/1000 [05:44<02:51, 2.06it/s, loss=0.0418, lr=0.0004]
Steps: 65%|██████▍ | 648/1000 [05:44<03:06, 1.89it/s, loss=0.0418, lr=0.0004]
a dark photo of the <s1><s2>
Steps: 65%|██████▍ | 648/1000 [05:44<03:06, 1.89it/s, loss=0.0032, lr=0.0004]
Steps: 65%|██████▍ | 649/1000 [05:45<03:16, 1.78it/s, loss=0.0032, lr=0.0004]
a photo of a <s1><s2>
Steps: 65%|██████▍ | 649/1000 [05:45<03:16, 1.78it/s, loss=0.00802, lr=0.0004]
Steps: 65%|██████▌ | 650/1000 [05:45<03:14, 1.80it/s, loss=0.00802, lr=0.0004]
a photo of a small <s1><s2>
Steps: 65%|██████▌ | 650/1000 [05:45<03:14, 1.80it/s, loss=0.00414, lr=0.0004]
Steps: 65%|██████▌ | 651/1000 [05:46<03:03, 1.90it/s, loss=0.00414, lr=0.0004]
a good photo of a <s1><s2>
Steps: 65%|██████▌ | 651/1000 [05:46<03:03, 1.90it/s, loss=0.0796, lr=0.0004]
Steps: 65%|██████▌ | 652/1000 [05:46<02:54, 1.99it/s, loss=0.0796, lr=0.0004]
a rendition of the <s1><s2>
Steps: 65%|██████▌ | 652/1000 [05:46<02:54, 1.99it/s, loss=0.0283, lr=0.0004]
Steps: 65%|██████▌ | 653/1000 [05:47<02:53, 2.00it/s, loss=0.0283, lr=0.0004]
a photo of the clean <s1><s2>
Steps: 65%|██████▌ | 653/1000 [05:47<02:53, 2.00it/s, loss=0.00727, lr=0.0004]
Steps: 65%|██████▌ | 654/1000 [05:47<03:09, 1.83it/s, loss=0.00727, lr=0.0004]
a bright photo of the <s1><s2>
Steps: 65%|██████▌ | 654/1000 [05:47<03:09, 1.83it/s, loss=0.00509, lr=0.0004]
Steps: 66%|██████▌ | 655/1000 [05:48<03:00, 1.91it/s, loss=0.00509, lr=0.0004]
a close-up photo of a <s1><s2>
Steps: 66%|██████▌ | 655/1000 [05:48<03:00, 1.91it/s, loss=0.124, lr=0.0004]
Steps: 66%|██████▌ | 656/1000 [05:48<02:56, 1.95it/s, loss=0.124, lr=0.0004]
a close-up photo of a <s1><s2>
Steps: 66%|██████▌ | 656/1000 [05:48<02:56, 1.95it/s, loss=0.0274, lr=0.0004]
Steps: 66%|██████▌ | 657/1000 [05:49<02:51, 2.00it/s, loss=0.0274, lr=0.0004]
a dark photo of the <s1><s2>
Steps: 66%|██████▌ | 657/1000 [05:49<02:51, 2.00it/s, loss=0.00388, lr=0.0004]
Steps: 66%|██████▌ | 658/1000 [05:49<03:04, 1.85it/s, loss=0.00388, lr=0.0004]
a photo of my <s1><s2>
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a rendering of a <s1><s2>
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a good photo of the <s1><s2>
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Steps: 66%|██████▌ | 661/1000 [05:51<03:16, 1.73it/s, loss=0.141, lr=0.0004]
a close-up photo of a <s1><s2>
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a photo of a dirty <s1><s2>
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a close-up photo of the <s1><s2>
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Steps: 66%|██████▋ | 664/1000 [05:53<02:52, 1.94it/s, loss=0.0192, lr=0.0004]
a photo of the clean <s1><s2>
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Steps: 66%|██████▋ | 665/1000 [05:53<02:50, 1.97it/s, loss=0.333, lr=0.0004]
a photo of a dirty <s1><s2>
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a bright photo of the <s1><s2>
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a dark photo of the <s1><s2>
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a good photo of a <s1><s2>
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Steps: 67%|██████▋ | 669/1000 [05:56<03:02, 1.81it/s, loss=0.028, lr=0.0004]
the photo of a <s1><s2>
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a photo of the clean <s1><s2>
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Steps: 67%|██████▋ | 671/1000 [05:56<02:46, 1.97it/s, loss=0.0254, lr=0.0004]
a photo of a clean <s1><s2>
Steps: 67%|██████▋ | 671/1000 [05:56<02:46, 1.97it/s, loss=0.0137, lr=0.0004]
Steps: 67%|██████▋ | 672/1000 [05:57<02:42, 2.02it/s, loss=0.0137, lr=0.0004]
a photo of a dirty <s1><s2>
Steps: 67%|██████▋ | 672/1000 [05:57<02:42, 2.02it/s, loss=0.00711, lr=0.0004]
Steps: 67%|██████▋ | 673/1000 [05:57<02:39, 2.05it/s, loss=0.00711, lr=0.0004]
a photo of the clean <s1><s2>
Steps: 67%|██████▋ | 673/1000 [05:57<02:39, 2.05it/s, loss=0.0999, lr=0.0004]
Steps: 67%|██████▋ | 674/1000 [05:58<02:43, 1.99it/s, loss=0.0999, lr=0.0004]
a photo of the clean <s1><s2>
Steps: 67%|██████▋ | 674/1000 [05:58<02:43, 1.99it/s, loss=0.0121, lr=0.0004]
Steps: 68%|██████▊ | 675/1000 [05:58<02:43, 1.99it/s, loss=0.0121, lr=0.0004]
a good photo of the <s1><s2>
Steps: 68%|██████▊ | 675/1000 [05:58<02:43, 1.99it/s, loss=0.00326, lr=0.0004]
Steps: 68%|██████▊ | 676/1000 [05:59<02:41, 2.00it/s, loss=0.00326, lr=0.0004]
a photo of one <s1><s2>
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Steps: 68%|██████▊ | 677/1000 [06:00<02:52, 1.87it/s, loss=0.0247, lr=0.0004]
a photo of the weird <s1><s2>
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Steps: 68%|██████▊ | 678/1000 [06:00<02:47, 1.92it/s, loss=0.0027, lr=0.0004]
a photo of a nice <s1><s2>
Steps: 68%|██████▊ | 678/1000 [06:00<02:47, 1.92it/s, loss=0.401, lr=0.0004]
Steps: 68%|██████▊ | 679/1000 [06:01<02:57, 1.81it/s, loss=0.401, lr=0.0004]
a photo of a clean <s1><s2>
Steps: 68%|██████▊ | 679/1000 [06:01<02:57, 1.81it/s, loss=0.00592, lr=0.0004]
Steps: 68%|██████▊ | 680/1000 [06:01<03:00, 1.77it/s, loss=0.00592, lr=0.0004]
a photo of a nice <s1><s2>
Steps: 68%|██████▊ | 680/1000 [06:01<03:00, 1.77it/s, loss=0.0326, lr=0.0004]
Steps: 68%|██████▊ | 681/1000 [06:02<02:49, 1.88it/s, loss=0.0326, lr=0.0004]
a photo of one <s1><s2>
Steps: 68%|██████▊ | 681/1000 [06:02<02:49, 1.88it/s, loss=0.11, lr=0.0004]
Steps: 68%|██████▊ | 682/1000 [06:02<03:04, 1.73it/s, loss=0.11, lr=0.0004]
a good photo of the <s1><s2>
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Steps: 68%|██████▊ | 683/1000 [06:03<02:52, 1.84it/s, loss=0.012, lr=0.0004]
a photo of a cool <s1><s2>
Steps: 68%|██████▊ | 683/1000 [06:03<02:52, 1.84it/s, loss=0.0655, lr=0.0004]
Steps: 68%|██████▊ | 684/1000 [06:03<02:44, 1.92it/s, loss=0.0655, lr=0.0004]
a photo of a <s1><s2>
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Steps: 68%|██████▊ | 685/1000 [06:04<02:42, 1.94it/s, loss=0.0367, lr=0.0004]
a bright photo of the <s1><s2>
Steps: 68%|██████▊ | 685/1000 [06:04<02:42, 1.94it/s, loss=0.00181, lr=0.0004]
Steps: 69%|██████▊ | 686/1000 [06:04<02:36, 2.01it/s, loss=0.00181, lr=0.0004]
a photo of one <s1><s2>
Steps: 69%|██████▊ | 686/1000 [06:04<02:36, 2.01it/s, loss=0.0233, lr=0.0004]
Steps: 69%|██████▊ | 687/1000 [06:05<02:34, 2.02it/s, loss=0.0233, lr=0.0004]
a photo of a small <s1><s2>
Steps: 69%|██████▊ | 687/1000 [06:05<02:34, 2.02it/s, loss=0.0935, lr=0.0004]
Steps: 69%|██████▉ | 688/1000 [06:05<02:29, 2.08it/s, loss=0.0935, lr=0.0004]
a close-up photo of the <s1><s2>
Steps: 69%|██████▉ | 688/1000 [06:05<02:29, 2.08it/s, loss=0.388, lr=0.0004]
Steps: 69%|██████▉ | 689/1000 [06:06<02:45, 1.88it/s, loss=0.388, lr=0.0004]
a close-up photo of the <s1><s2>
Steps: 69%|██████▉ | 689/1000 [06:06<02:45, 1.88it/s, loss=0.00183, lr=0.0004]
Steps: 69%|██████▉ | 690/1000 [06:06<02:37, 1.97it/s, loss=0.00183, lr=0.0004]
a photo of the cool <s1><s2>
Steps: 69%|██████▉ | 690/1000 [06:06<02:37, 1.97it/s, loss=0.0276, lr=0.0004]
Steps: 69%|██████▉ | 691/1000 [06:07<02:41, 1.92it/s, loss=0.0276, lr=0.0004]
a cropped photo of the <s1><s2>
Steps: 69%|██████▉ | 691/1000 [06:07<02:41, 1.92it/s, loss=0.00923, lr=0.0004]
Steps: 69%|██████▉ | 692/1000 [06:07<02:34, 1.99it/s, loss=0.00923, lr=0.0004]
a bright photo of the <s1><s2>
Steps: 69%|██████▉ | 692/1000 [06:07<02:34, 1.99it/s, loss=0.00684, lr=0.0004]
Steps: 69%|██████▉ | 693/1000 [06:08<02:45, 1.85it/s, loss=0.00684, lr=0.0004]
a rendition of a <s1><s2>
Steps: 69%|██████▉ | 693/1000 [06:08<02:45, 1.85it/s, loss=0.00152, lr=0.0004]
Steps: 69%|██████▉ | 694/1000 [06:08<02:37, 1.94it/s, loss=0.00152, lr=0.0004]
a photo of the large <s1><s2>
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Steps: 70%|██████▉ | 695/1000 [06:09<02:45, 1.84it/s, loss=0.0144, lr=0.0004]
a rendering of a <s1><s2>
Steps: 70%|██████▉ | 695/1000 [06:09<02:45, 1.84it/s, loss=0.0138, lr=0.0004]
Steps: 70%|██████▉ | 696/1000 [06:09<02:39, 1.91it/s, loss=0.0138, lr=0.0004]
a photo of the nice <s1><s2>
Steps: 70%|██████▉ | 696/1000 [06:09<02:39, 1.91it/s, loss=0.0217, lr=0.0004]
Steps: 70%|██████▉ | 697/1000 [06:10<02:32, 1.98it/s, loss=0.0217, lr=0.0004]
a photo of one <s1><s2>
Steps: 70%|██████▉ | 697/1000 [06:10<02:32, 1.98it/s, loss=0.133, lr=0.0004]
Steps: 70%|██████▉ | 698/1000 [06:10<02:31, 2.00it/s, loss=0.133, lr=0.0004]
a photo of the clean <s1><s2>
Steps: 70%|██████▉ | 698/1000 [06:10<02:31, 2.00it/s, loss=0.0773, lr=0.0004]
Steps: 70%|██████▉ | 699/1000 [06:11<02:45, 1.82it/s, loss=0.0773, lr=0.0004]
a photo of a clean <s1><s2>
Steps: 70%|██████▉ | 699/1000 [06:11<02:45, 1.82it/s, loss=0.00698, lr=0.0004]
Steps: 70%|███████ | 700/1000 [06:12<02:40, 1.87it/s, loss=0.00698, lr=0.0004]
a photo of the cool <s1><s2>
Steps: 70%|███████ | 700/1000 [06:12<02:40, 1.87it/s, loss=0.0286, lr=0.0004]
Steps: 70%|███████ | 701/1000 [06:12<02:35, 1.92it/s, loss=0.0286, lr=0.0004]
a photo of the clean <s1><s2>
Steps: 70%|███████ | 701/1000 [06:12<02:35, 1.92it/s, loss=0.0085, lr=0.0004]
Steps: 70%|███████ | 702/1000 [06:13<02:32, 1.96it/s, loss=0.0085, lr=0.0004]
a photo of the <s1><s2>
Steps: 70%|███████ | 702/1000 [06:13<02:32, 1.96it/s, loss=0.102, lr=0.0004]
Steps: 70%|███████ | 703/1000 [06:13<02:41, 1.84it/s, loss=0.102, lr=0.0004]
a good photo of a <s1><s2>
Steps: 70%|███████ | 703/1000 [06:13<02:41, 1.84it/s, loss=0.00352, lr=0.0004]
Steps: 70%|███████ | 704/1000 [06:14<02:39, 1.86it/s, loss=0.00352, lr=0.0004]
a photo of the <s1><s2>
Steps: 70%|███████ | 704/1000 [06:14<02:39, 1.86it/s, loss=0.0263, lr=0.0004]
Steps: 70%|███████ | 705/1000 [06:14<02:30, 1.95it/s, loss=0.0263, lr=0.0004]
a photo of one <s1><s2>
Steps: 70%|███████ | 705/1000 [06:14<02:30, 1.95it/s, loss=0.0154, lr=0.0004]
Steps: 71%|███████ | 706/1000 [06:15<02:28, 1.98it/s, loss=0.0154, lr=0.0004]
a photo of one <s1><s2>
Steps: 71%|███████ | 706/1000 [06:15<02:28, 1.98it/s, loss=0.0088, lr=0.0004]
Steps: 71%|███████ | 707/1000 [06:15<02:39, 1.84it/s, loss=0.0088, lr=0.0004]
a photo of my <s1><s2>
Steps: 71%|███████ | 707/1000 [06:15<02:39, 1.84it/s, loss=0.0143, lr=0.0004]
Steps: 71%|███████ | 708/1000 [06:16<02:47, 1.74it/s, loss=0.0143, lr=0.0004]
a photo of my <s1><s2>
Steps: 71%|███████ | 708/1000 [06:16<02:47, 1.74it/s, loss=0.0302, lr=0.0004]
Steps: 71%|███████ | 709/1000 [06:17<02:51, 1.70it/s, loss=0.0302, lr=0.0004]
a good photo of a <s1><s2>
Steps: 71%|███████ | 709/1000 [06:17<02:51, 1.70it/s, loss=0.0114, lr=0.0004]
Steps: 71%|███████ | 710/1000 [06:17<02:40, 1.80it/s, loss=0.0114, lr=0.0004]
a photo of my <s1><s2>
Steps: 71%|███████ | 710/1000 [06:17<02:40, 1.80it/s, loss=0.0124, lr=0.0004]
Steps: 71%|███████ | 711/1000 [06:18<02:32, 1.90it/s, loss=0.0124, lr=0.0004]
a photo of the <s1><s2>
Steps: 71%|███████ | 711/1000 [06:18<02:32, 1.90it/s, loss=0.0117, lr=0.0004]
Steps: 71%|███████ | 712/1000 [06:18<02:27, 1.96it/s, loss=0.0117, lr=0.0004]
a good photo of the <s1><s2>
Steps: 71%|███████ | 712/1000 [06:18<02:27, 1.96it/s, loss=0.0225, lr=0.0004]
Steps: 71%|███████▏ | 713/1000 [06:18<02:23, 2.00it/s, loss=0.0225, lr=0.0004]
a cropped photo of a <s1><s2>
Steps: 71%|███████▏ | 713/1000 [06:18<02:23, 2.00it/s, loss=0.0695, lr=0.0004]
Steps: 71%|███████▏ | 714/1000 [06:19<02:19, 2.05it/s, loss=0.0695, lr=0.0004]
a rendition of the <s1><s2>
Steps: 71%|███████▏ | 714/1000 [06:19<02:19, 2.05it/s, loss=0.0224, lr=0.0004]
Steps: 72%|███████▏ | 715/1000 [06:20<02:29, 1.91it/s, loss=0.0224, lr=0.0004]
a rendition of a <s1><s2>
Steps: 72%|███████▏ | 715/1000 [06:20<02:29, 1.91it/s, loss=0.00142, lr=0.0004]
Steps: 72%|███████▏ | 716/1000 [06:20<02:22, 1.99it/s, loss=0.00142, lr=0.0004]
a good photo of a <s1><s2>
Steps: 72%|███████▏ | 716/1000 [06:20<02:22, 1.99it/s, loss=0.214, lr=0.0004]
Steps: 72%|███████▏ | 717/1000 [06:21<02:35, 1.82it/s, loss=0.214, lr=0.0004]
a photo of a nice <s1><s2>
Steps: 72%|███████▏ | 717/1000 [06:21<02:35, 1.82it/s, loss=0.00281, lr=0.0004]
Steps: 72%|███████▏ | 718/1000 [06:21<02:30, 1.87it/s, loss=0.00281, lr=0.0004]
a photo of a clean <s1><s2>
Steps: 72%|███████▏ | 718/1000 [06:21<02:30, 1.87it/s, loss=0.0672, lr=0.0004]
Steps: 72%|███████▏ | 719/1000 [06:22<02:24, 1.95it/s, loss=0.0672, lr=0.0004]
a photo of a cool <s1><s2>
Steps: 72%|███████▏ | 719/1000 [06:22<02:24, 1.95it/s, loss=0.0338, lr=0.0004]
Steps: 72%|███████▏ | 720/1000 [06:22<02:24, 1.94it/s, loss=0.0338, lr=0.0004]
a cropped photo of the <s1><s2>
Steps: 72%|███████▏ | 720/1000 [06:22<02:24, 1.94it/s, loss=0.0288, lr=0.0004]
Steps: 72%|███████▏ | 721/1000 [06:23<02:19, 2.00it/s, loss=0.0288, lr=0.0004]
a photo of a dirty <s1><s2>
Steps: 72%|███████▏ | 721/1000 [06:23<02:19, 2.00it/s, loss=0.0209, lr=0.0004]
Steps: 72%|███████▏ | 722/1000 [06:23<02:15, 2.06it/s, loss=0.0209, lr=0.0004]
a photo of the clean <s1><s2>
Steps: 72%|███████▏ | 722/1000 [06:23<02:15, 2.06it/s, loss=0.0148, lr=0.0004]
Steps: 72%|███████▏ | 723/1000 [06:24<02:13, 2.07it/s, loss=0.0148, lr=0.0004]
a photo of the <s1><s2>
Steps: 72%|███████▏ | 723/1000 [06:24<02:13, 2.07it/s, loss=0.473, lr=0.0004]
Steps: 72%|███████▏ | 724/1000 [06:24<02:16, 2.03it/s, loss=0.473, lr=0.0004]
a rendition of a <s1><s2>
Steps: 72%|███████▏ | 724/1000 [06:24<02:16, 2.03it/s, loss=0.00935, lr=0.0004]
Steps: 72%|███████▎ | 725/1000 [06:25<02:29, 1.84it/s, loss=0.00935, lr=0.0004]
a good photo of the <s1><s2>
Steps: 72%|███████▎ | 725/1000 [06:25<02:29, 1.84it/s, loss=0.00179, lr=0.0004]
Steps: 73%|███████▎ | 726/1000 [06:25<02:26, 1.87it/s, loss=0.00179, lr=0.0004]
a photo of the clean <s1><s2>
Steps: 73%|███████▎ | 726/1000 [06:25<02:26, 1.87it/s, loss=0.0489, lr=0.0004]
Steps: 73%|███████▎ | 727/1000 [06:26<02:20, 1.94it/s, loss=0.0489, lr=0.0004]
a photo of a cool <s1><s2>
Steps: 73%|███████▎ | 727/1000 [06:26<02:20, 1.94it/s, loss=0.0155, lr=0.0004]
Steps: 73%|███████▎ | 728/1000 [06:26<02:28, 1.83it/s, loss=0.0155, lr=0.0004]
a cropped photo of a <s1><s2>
Steps: 73%|███████▎ | 728/1000 [06:26<02:28, 1.83it/s, loss=0.00375, lr=0.0004]
Steps: 73%|███████▎ | 729/1000 [06:27<02:21, 1.92it/s, loss=0.00375, lr=0.0004]
a cropped photo of a <s1><s2>
Steps: 73%|███████▎ | 729/1000 [06:27<02:21, 1.92it/s, loss=0.0342, lr=0.0004]
Steps: 73%|███████▎ | 730/1000 [06:27<02:28, 1.81it/s, loss=0.0342, lr=0.0004]
a good photo of the <s1><s2>
Steps: 73%|███████▎ | 730/1000 [06:27<02:28, 1.81it/s, loss=0.00245, lr=0.0004]
Steps: 73%|███████▎ | 731/1000 [06:28<02:34, 1.74it/s, loss=0.00245, lr=0.0004]
a photo of the small <s1><s2>
Steps: 73%|███████▎ | 731/1000 [06:28<02:34, 1.74it/s, loss=0.0181, lr=0.0004]
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a dark photo of the <s1><s2>
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a good photo of a <s1><s2>
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a photo of a clean <s1><s2>
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a photo of a <s1><s2>
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a good photo of a <s1><s2>
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a photo of the large <s1><s2>
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a photo of the cool <s1><s2>
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Steps: 74%|███████▍ | 739/1000 [06:32<02:18, 1.89it/s, loss=0.00178, lr=0.0004]
a close-up photo of a <s1><s2>
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a rendering of a <s1><s2>
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a close-up photo of a <s1><s2>
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a photo of a dirty <s1><s2>
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a rendering of a <s1><s2>
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a photo of my <s1><s2>
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a photo of a clean <s1><s2>
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a rendition of a <s1><s2>
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a cropped photo of a <s1><s2>
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a photo of a small <s1><s2>
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a photo of a nice <s1><s2>
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a photo of a dirty <s1><s2>
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a rendition of a <s1><s2>
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a photo of the large <s1><s2>
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a photo of a <s1><s2>
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a rendition of the <s1><s2>
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a photo of the clean <s1><s2>
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a photo of the weird <s1><s2>
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a close-up photo of the <s1><s2>
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a photo of the large <s1><s2>
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a photo of a cool <s1><s2>
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a photo of the <s1><s2>
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a bright photo of the <s1><s2>
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a photo of a small <s1><s2>
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a photo of the nice <s1><s2>
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a rendering of a <s1><s2>
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a photo of a cool <s1><s2>
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a good photo of a <s1><s2>
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a photo of the small <s1><s2>
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a photo of a cool <s1><s2>
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a photo of a clean <s1><s2>
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a photo of a <s1><s2>
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a photo of the nice <s1><s2>
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a photo of the cool <s1><s2>
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a photo of a nice <s1><s2>
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a photo of a clean <s1><s2>
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a photo of a dirty <s1><s2>
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a photo of the weird <s1><s2>
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a photo of a small <s1><s2>
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a cropped photo of the <s1><s2>
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a dark photo of the <s1><s2>
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a rendition of the <s1><s2>
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Steps: 78%|███████▊ | 781/1000 [06:55<02:06, 1.73it/s, loss=0.014, lr=0.0004]
a photo of a nice <s1><s2>
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Steps: 78%|███████▊ | 782/1000 [06:55<02:02, 1.79it/s, loss=0.0465, lr=0.0004]
a photo of the clean <s1><s2>
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a photo of the large <s1><s2>
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Steps: 78%|███████▊ | 784/1000 [06:57<02:09, 1.67it/s, loss=0.0517, lr=0.0004]
a photo of a clean <s1><s2>
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a photo of the nice <s1><s2>
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Steps: 79%|███████▊ | 786/1000 [06:58<01:56, 1.83it/s, loss=0.0196, lr=0.0004]
a photo of the <s1><s2>
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Steps: 79%|███████▊ | 787/1000 [06:58<02:04, 1.70it/s, loss=0.0626, lr=0.0004]
a photo of the cool <s1><s2>
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Steps: 79%|███████▉ | 788/1000 [06:59<02:00, 1.76it/s, loss=0.0545, lr=0.0004]
a photo of the clean <s1><s2>
Steps: 79%|███████▉ | 788/1000 [06:59<02:00, 1.76it/s, loss=0.0224, lr=0.0004]
Steps: 79%|███████▉ | 789/1000 [06:59<01:57, 1.79it/s, loss=0.0224, lr=0.0004]
a photo of a cool <s1><s2>
Steps: 79%|███████▉ | 789/1000 [06:59<01:57, 1.79it/s, loss=0.178, lr=0.0004]
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a rendition of a <s1><s2>
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Steps: 79%|███████▉ | 791/1000 [07:00<01:58, 1.76it/s, loss=0.0142, lr=0.0004]
a photo of one <s1><s2>
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Steps: 79%|███████▉ | 792/1000 [07:01<01:59, 1.74it/s, loss=0.0469, lr=0.0004]
a rendition of the <s1><s2>
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Steps: 79%|███████▉ | 793/1000 [07:01<01:51, 1.85it/s, loss=0.0107, lr=0.0004]
a photo of the cool <s1><s2>
Steps: 79%|███████▉ | 793/1000 [07:01<01:51, 1.85it/s, loss=0.00834, lr=0.0004]
Steps: 79%|███████▉ | 794/1000 [07:02<01:46, 1.94it/s, loss=0.00834, lr=0.0004]
a cropped photo of a <s1><s2>
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Steps: 80%|███████▉ | 795/1000 [07:02<01:44, 1.96it/s, loss=0.0159, lr=0.0004]
a good photo of the <s1><s2>
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Steps: 80%|███████▉ | 796/1000 [07:03<01:40, 2.03it/s, loss=0.00429, lr=0.0004]
a photo of the small <s1><s2>
Steps: 80%|███████▉ | 796/1000 [07:03<01:40, 2.03it/s, loss=0.257, lr=0.0004]
Steps: 80%|███████▉ | 797/1000 [07:03<01:46, 1.90it/s, loss=0.257, lr=0.0004]
a photo of a nice <s1><s2>
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Steps: 80%|███████▉ | 798/1000 [07:04<01:42, 1.97it/s, loss=0.0194, lr=0.0004]
a photo of one <s1><s2>
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Steps: 80%|███████▉ | 799/1000 [07:04<01:41, 1.99it/s, loss=0.0428, lr=0.0004]
a photo of the small <s1><s2>
Steps: 80%|███████▉ | 799/1000 [07:04<01:41, 1.99it/s, loss=0.196, lr=0.0004]
Steps: 80%|████████ | 800/1000 [07:05<01:40, 2.00it/s, loss=0.196, lr=0.0004]
a photo of a small <s1><s2>
Steps: 80%|████████ | 800/1000 [07:05<01:40, 2.00it/s, loss=0.0227, lr=0.0004]
Steps: 80%|████████ | 801/1000 [07:05<01:36, 2.06it/s, loss=0.0227, lr=0.0004]
a close-up photo of a <s1><s2>
Steps: 80%|████████ | 801/1000 [07:05<01:36, 2.06it/s, loss=0.146, lr=0.0004]
Steps: 80%|████████ | 802/1000 [07:06<01:34, 2.09it/s, loss=0.146, lr=0.0004]
a photo of the clean <s1><s2>
Steps: 80%|████████ | 802/1000 [07:06<01:34, 2.09it/s, loss=0.201, lr=0.0004]
Steps: 80%|████████ | 803/1000 [07:06<01:41, 1.94it/s, loss=0.201, lr=0.0004]
a photo of a nice <s1><s2>
Steps: 80%|████████ | 803/1000 [07:06<01:41, 1.94it/s, loss=0.00172, lr=0.0004]
Steps: 80%|████████ | 804/1000 [07:07<01:37, 2.01it/s, loss=0.00172, lr=0.0004]
a cropped photo of the <s1><s2>
Steps: 80%|████████ | 804/1000 [07:07<01:37, 2.01it/s, loss=0.0265, lr=0.0004]
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a photo of the cool <s1><s2>
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Steps: 81%|████████ | 806/1000 [07:08<01:51, 1.73it/s, loss=0.0152, lr=0.0004]
a photo of a nice <s1><s2>
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Steps: 81%|████████ | 807/1000 [07:09<01:48, 1.78it/s, loss=0.00593, lr=0.0004]
a photo of the small <s1><s2>
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a close-up photo of a <s1><s2>
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a photo of a clean <s1><s2>
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a bright photo of the <s1><s2>
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a rendition of a <s1><s2>
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a photo of the nice <s1><s2>
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Steps: 81%|████████▏ | 813/1000 [07:12<01:37, 1.92it/s, loss=0.0058, lr=0.0004]
a cropped photo of the <s1><s2>
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a photo of a dirty <s1><s2>
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a photo of my <s1><s2>
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a photo of the cool <s1><s2>
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Steps: 82%|████████▏ | 817/1000 [07:14<01:47, 1.71it/s, loss=0.0218, lr=0.0004]
a photo of the small <s1><s2>
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a photo of the clean <s1><s2>
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a cropped photo of the <s1><s2>
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Steps: 82%|████████▏ | 820/1000 [07:16<01:37, 1.85it/s, loss=0.0201, lr=0.0004]
a dark photo of the <s1><s2>
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Steps: 82%|████████▏ | 821/1000 [07:16<01:37, 1.84it/s, loss=0.0496, lr=0.0004]
a bright photo of the <s1><s2>
Steps: 82%|████████▏ | 821/1000 [07:16<01:37, 1.84it/s, loss=0.0499, lr=0.0004]
Steps: 82%|████████▏ | 822/1000 [07:17<01:35, 1.86it/s, loss=0.0499, lr=0.0004]
a photo of a small <s1><s2>
Steps: 82%|████████▏ | 822/1000 [07:17<01:35, 1.86it/s, loss=0.00745, lr=0.0004]
Steps: 82%|████████▏ | 823/1000 [07:17<01:40, 1.76it/s, loss=0.00745, lr=0.0004]
a good photo of the <s1><s2>
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Steps: 82%|████████▏ | 824/1000 [07:18<01:45, 1.67it/s, loss=0.00132, lr=0.0004]
a photo of the nice <s1><s2>
Steps: 82%|████████▏ | 824/1000 [07:18<01:45, 1.67it/s, loss=0.0238, lr=0.0004]
Steps: 82%|████████▎ | 825/1000 [07:19<01:40, 1.75it/s, loss=0.0238, lr=0.0004]
a photo of the nice <s1><s2>
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Steps: 83%|████████▎ | 826/1000 [07:19<01:34, 1.84it/s, loss=0.00572, lr=0.0004]
a photo of the large <s1><s2>
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Steps: 83%|████████▎ | 827/1000 [07:20<01:32, 1.87it/s, loss=0.0724, lr=0.0004]
a photo of the small <s1><s2>
Steps: 83%|████████▎ | 827/1000 [07:20<01:32, 1.87it/s, loss=0.043, lr=0.0004]
Steps: 83%|████████▎ | 828/1000 [07:20<01:39, 1.73it/s, loss=0.043, lr=0.0004]
a close-up photo of the <s1><s2>
Steps: 83%|████████▎ | 828/1000 [07:20<01:39, 1.73it/s, loss=0.0352, lr=0.0004]
Steps: 83%|████████▎ | 829/1000 [07:21<01:32, 1.86it/s, loss=0.0352, lr=0.0004]
a photo of the large <s1><s2>
Steps: 83%|████████▎ | 829/1000 [07:21<01:32, 1.86it/s, loss=0.0859, lr=0.0004]
Steps: 83%|████████▎ | 830/1000 [07:21<01:31, 1.86it/s, loss=0.0859, lr=0.0004]
a photo of a dirty <s1><s2>
Steps: 83%|████████▎ | 830/1000 [07:21<01:31, 1.86it/s, loss=0.0893, lr=0.0004]
Steps: 83%|████████▎ | 831/1000 [07:22<01:34, 1.79it/s, loss=0.0893, lr=0.0004]
a photo of a cool <s1><s2>
Steps: 83%|████████▎ | 831/1000 [07:22<01:34, 1.79it/s, loss=0.0065, lr=0.0004]
Steps: 83%|████████▎ | 832/1000 [07:22<01:29, 1.87it/s, loss=0.0065, lr=0.0004]
a good photo of a <s1><s2>
Steps: 83%|████████▎ | 832/1000 [07:22<01:29, 1.87it/s, loss=0.0495, lr=0.0004]
Steps: 83%|████████▎ | 833/1000 [07:23<01:27, 1.91it/s, loss=0.0495, lr=0.0004]
a photo of the clean <s1><s2>
Steps: 83%|████████▎ | 833/1000 [07:23<01:27, 1.91it/s, loss=0.391, lr=0.0004]
Steps: 83%|████████▎ | 834/1000 [07:23<01:23, 1.98it/s, loss=0.391, lr=0.0004]
a dark photo of the <s1><s2>
Steps: 83%|████████▎ | 834/1000 [07:23<01:23, 1.98it/s, loss=0.376, lr=0.0004]
Steps: 84%|████████▎ | 835/1000 [07:24<01:22, 2.00it/s, loss=0.376, lr=0.0004]
a dark photo of the <s1><s2>
Steps: 84%|████████▎ | 835/1000 [07:24<01:22, 2.00it/s, loss=0.0116, lr=0.0004]
Steps: 84%|████████▎ | 836/1000 [07:24<01:23, 1.97it/s, loss=0.0116, lr=0.0004]
a bright photo of the <s1><s2>
Steps: 84%|████████▎ | 836/1000 [07:24<01:23, 1.97it/s, loss=0.0751, lr=0.0004]
Steps: 84%|████████▎ | 837/1000 [07:25<01:19, 2.04it/s, loss=0.0751, lr=0.0004]
a rendition of the <s1><s2>
Steps: 84%|████████▎ | 837/1000 [07:25<01:19, 2.04it/s, loss=0.00595, lr=0.0004]
Steps: 84%|████████▍ | 838/1000 [07:25<01:26, 1.87it/s, loss=0.00595, lr=0.0004]
a photo of my <s1><s2>
Steps: 84%|████████▍ | 838/1000 [07:25<01:26, 1.87it/s, loss=0.00894, lr=0.0004]
Steps: 84%|████████▍ | 839/1000 [07:26<01:22, 1.95it/s, loss=0.00894, lr=0.0004]
a photo of my <s1><s2>
Steps: 84%|████████▍ | 839/1000 [07:26<01:22, 1.95it/s, loss=0.00529, lr=0.0004]
Steps: 84%|████████▍ | 840/1000 [07:27<01:27, 1.83it/s, loss=0.00529, lr=0.0004]
a photo of the clean <s1><s2>
Steps: 84%|████████▍ | 840/1000 [07:27<01:27, 1.83it/s, loss=0.00988, lr=0.0004]
Steps: 84%|████████▍ | 841/1000 [07:27<01:22, 1.93it/s, loss=0.00988, lr=0.0004]
a photo of one <s1><s2>
Steps: 84%|████████▍ | 841/1000 [07:27<01:22, 1.93it/s, loss=0.00688, lr=0.0004]
Steps: 84%|████████▍ | 842/1000 [07:27<01:19, 1.99it/s, loss=0.00688, lr=0.0004]
a rendering of a <s1><s2>
Steps: 84%|████████▍ | 842/1000 [07:27<01:19, 1.99it/s, loss=0.0623, lr=0.0004]
Steps: 84%|████████▍ | 843/1000 [07:28<01:19, 1.98it/s, loss=0.0623, lr=0.0004]
a photo of the nice <s1><s2>
Steps: 84%|████████▍ | 843/1000 [07:28<01:19, 1.98it/s, loss=0.0132, lr=0.0004]
Steps: 84%|████████▍ | 844/1000 [07:29<01:24, 1.85it/s, loss=0.0132, lr=0.0004]
a photo of the clean <s1><s2>
Steps: 84%|████████▍ | 844/1000 [07:29<01:24, 1.85it/s, loss=0.0111, lr=0.0004]
Steps: 84%|████████▍ | 845/1000 [07:29<01:21, 1.89it/s, loss=0.0111, lr=0.0004]
a photo of the small <s1><s2>
Steps: 84%|████████▍ | 845/1000 [07:29<01:21, 1.89it/s, loss=0.015, lr=0.0004]
Steps: 85%|████████▍ | 846/1000 [07:30<01:18, 1.96it/s, loss=0.015, lr=0.0004]
a photo of the cool <s1><s2>
Steps: 85%|████████▍ | 846/1000 [07:30<01:18, 1.96it/s, loss=0.106, lr=0.0004]
Steps: 85%|████████▍ | 847/1000 [07:30<01:22, 1.85it/s, loss=0.106, lr=0.0004]
a photo of the small <s1><s2>
Steps: 85%|████████▍ | 847/1000 [07:30<01:22, 1.85it/s, loss=0.0126, lr=0.0004]
Steps: 85%|████████▍ | 848/1000 [07:31<01:19, 1.91it/s, loss=0.0126, lr=0.0004]
a photo of a nice <s1><s2>
Steps: 85%|████████▍ | 848/1000 [07:31<01:19, 1.91it/s, loss=0.00543, lr=0.0004]
Steps: 85%|████████▍ | 849/1000 [07:31<01:17, 1.94it/s, loss=0.00543, lr=0.0004]
a photo of the small <s1><s2>
Steps: 85%|████████▍ | 849/1000 [07:31<01:17, 1.94it/s, loss=0.0257, lr=0.0004]
Steps: 85%|████████▌ | 850/1000 [07:32<01:21, 1.83it/s, loss=0.0257, lr=0.0004]
a good photo of the <s1><s2>
Steps: 85%|████████▌ | 850/1000 [07:32<01:21, 1.83it/s, loss=0.00917, lr=0.0004]
Steps: 85%|████████▌ | 851/1000 [07:32<01:17, 1.93it/s, loss=0.00917, lr=0.0004]
a photo of the large <s1><s2>
Steps: 85%|████████▌ | 851/1000 [07:32<01:17, 1.93it/s, loss=0.111, lr=0.0004]
Steps: 85%|████████▌ | 852/1000 [07:33<01:15, 1.97it/s, loss=0.111, lr=0.0004]
a photo of a nice <s1><s2>
Steps: 85%|████████▌ | 852/1000 [07:33<01:15, 1.97it/s, loss=0.0604, lr=0.0004]
Steps: 85%|████████▌ | 853/1000 [07:33<01:14, 1.96it/s, loss=0.0604, lr=0.0004]
a cropped photo of a <s1><s2>
Steps: 85%|████████▌ | 853/1000 [07:33<01:14, 1.96it/s, loss=0.0457, lr=0.0004]
Steps: 85%|████████▌ | 854/1000 [07:34<01:19, 1.83it/s, loss=0.0457, lr=0.0004]
a cropped photo of the <s1><s2>
Steps: 85%|████████▌ | 854/1000 [07:34<01:19, 1.83it/s, loss=0.0359, lr=0.0004]
Steps: 86%|████████▌ | 855/1000 [07:35<01:23, 1.73it/s, loss=0.0359, lr=0.0004]
a photo of the small <s1><s2>
Steps: 86%|████████▌ | 855/1000 [07:35<01:23, 1.73it/s, loss=0.00435, lr=0.0004]
Steps: 86%|████████▌ | 856/1000 [07:35<01:23, 1.72it/s, loss=0.00435, lr=0.0004]
a cropped photo of the <s1><s2>
Steps: 86%|████████▌ | 856/1000 [07:35<01:23, 1.72it/s, loss=0.00302, lr=0.0004]
Steps: 86%|████████▌ | 857/1000 [07:36<01:18, 1.83it/s, loss=0.00302, lr=0.0004]
a photo of the clean <s1><s2>
Steps: 86%|████████▌ | 857/1000 [07:36<01:18, 1.83it/s, loss=0.0254, lr=0.0004]
Steps: 86%|████████▌ | 858/1000 [07:36<01:14, 1.91it/s, loss=0.0254, lr=0.0004]
a rendering of a <s1><s2>
Steps: 86%|████████▌ | 858/1000 [07:36<01:14, 1.91it/s, loss=0.0084, lr=0.0004]
Steps: 86%|████████▌ | 859/1000 [07:37<01:11, 1.98it/s, loss=0.0084, lr=0.0004]
the photo of a <s1><s2>
Steps: 86%|████████▌ | 859/1000 [07:37<01:11, 1.98it/s, loss=0.166, lr=0.0004]
Steps: 86%|████████▌ | 860/1000 [07:37<01:10, 1.98it/s, loss=0.166, lr=0.0004]
a close-up photo of a <s1><s2>
Steps: 86%|████████▌ | 860/1000 [07:37<01:10, 1.98it/s, loss=0.123, lr=0.0004]
Steps: 86%|████████▌ | 861/1000 [07:38<01:09, 1.99it/s, loss=0.123, lr=0.0004]
a good photo of a <s1><s2>
Steps: 86%|████████▌ | 861/1000 [07:38<01:09, 1.99it/s, loss=0.0206, lr=0.0004]
Steps: 86%|████████▌ | 862/1000 [07:38<01:08, 2.01it/s, loss=0.0206, lr=0.0004]
a photo of one <s1><s2>
Steps: 86%|████████▌ | 862/1000 [07:38<01:08, 2.01it/s, loss=0.135, lr=0.0004]
Steps: 86%|████████▋ | 863/1000 [07:38<01:06, 2.08it/s, loss=0.135, lr=0.0004]
a photo of the <s1><s2>
Steps: 86%|████████▋ | 863/1000 [07:38<01:06, 2.08it/s, loss=0.0831, lr=0.0004]
Steps: 86%|████████▋ | 864/1000 [07:39<01:04, 2.12it/s, loss=0.0831, lr=0.0004]
a photo of the nice <s1><s2>
Steps: 86%|████████▋ | 864/1000 [07:39<01:04, 2.12it/s, loss=0.0198, lr=0.0004]
Steps: 86%|████████▋ | 865/1000 [07:39<01:05, 2.08it/s, loss=0.0198, lr=0.0004]
a rendition of a <s1><s2>
Steps: 86%|████████▋ | 865/1000 [07:39<01:05, 2.08it/s, loss=0.0222, lr=0.0004]
Steps: 87%|████████▋ | 866/1000 [07:40<01:02, 2.13it/s, loss=0.0222, lr=0.0004]
a good photo of the <s1><s2>
Steps: 87%|████████▋ | 866/1000 [07:40<01:02, 2.13it/s, loss=0.228, lr=0.0004]
Steps: 87%|████████▋ | 867/1000 [07:41<01:12, 1.85it/s, loss=0.228, lr=0.0004]
a close-up photo of the <s1><s2>
Steps: 87%|████████▋ | 867/1000 [07:41<01:12, 1.85it/s, loss=0.0184, lr=0.0004]
Steps: 87%|████████▋ | 868/1000 [07:41<01:14, 1.76it/s, loss=0.0184, lr=0.0004]
a rendition of a <s1><s2>
Steps: 87%|████████▋ | 868/1000 [07:41<01:14, 1.76it/s, loss=0.00189, lr=0.0004]
Steps: 87%|████████▋ | 869/1000 [07:42<01:16, 1.72it/s, loss=0.00189, lr=0.0004]
a cropped photo of a <s1><s2>
Steps: 87%|████████▋ | 869/1000 [07:42<01:16, 1.72it/s, loss=0.00671, lr=0.0004]
Steps: 87%|████████▋ | 870/1000 [07:42<01:11, 1.82it/s, loss=0.00671, lr=0.0004]
a photo of my <s1><s2>
Steps: 87%|████████▋ | 870/1000 [07:42<01:11, 1.82it/s, loss=0.0214, lr=0.0004]
Steps: 87%|████████▋ | 871/1000 [07:43<01:10, 1.83it/s, loss=0.0214, lr=0.0004]
a photo of a cool <s1><s2>
Steps: 87%|████████▋ | 871/1000 [07:43<01:10, 1.83it/s, loss=0.0416, lr=0.0004]
Steps: 87%|████████▋ | 872/1000 [07:43<01:06, 1.92it/s, loss=0.0416, lr=0.0004]
the photo of a <s1><s2>
Steps: 87%|████████▋ | 872/1000 [07:43<01:06, 1.92it/s, loss=0.0209, lr=0.0004]
Steps: 87%|████████▋ | 873/1000 [07:44<01:09, 1.82it/s, loss=0.0209, lr=0.0004]
a photo of the clean <s1><s2>
Steps: 87%|████████▋ | 873/1000 [07:44<01:09, 1.82it/s, loss=0.0127, lr=0.0004]
Steps: 87%|████████▋ | 874/1000 [07:44<01:05, 1.92it/s, loss=0.0127, lr=0.0004]
a dark photo of the <s1><s2>
Steps: 87%|████████▋ | 874/1000 [07:44<01:05, 1.92it/s, loss=0.0825, lr=0.0004]
Steps: 88%|████████▊ | 875/1000 [07:45<01:02, 1.99it/s, loss=0.0825, lr=0.0004]
a photo of the nice <s1><s2>
Steps: 88%|████████▊ | 875/1000 [07:45<01:02, 1.99it/s, loss=0.148, lr=0.0004]
Steps: 88%|████████▊ | 876/1000 [07:45<01:01, 2.03it/s, loss=0.148, lr=0.0004]
a photo of the clean <s1><s2>
Steps: 88%|████████▊ | 876/1000 [07:45<01:01, 2.03it/s, loss=0.178, lr=0.0004]
Steps: 88%|████████▊ | 877/1000 [07:46<01:06, 1.86it/s, loss=0.178, lr=0.0004]
a photo of a cool <s1><s2>
Steps: 88%|████████▊ | 877/1000 [07:46<01:06, 1.86it/s, loss=0.0377, lr=0.0004]
Steps: 88%|████████▊ | 878/1000 [07:46<01:02, 1.97it/s, loss=0.0377, lr=0.0004]
a good photo of a <s1><s2>
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a photo of the nice <s1><s2>
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a cropped photo of the <s1><s2>
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a photo of the small <s1><s2>
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a photo of the small <s1><s2>
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a good photo of a <s1><s2>
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a photo of the clean <s1><s2>
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a rendition of a <s1><s2>
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Steps: 89%|████████▊ | 886/1000 [07:51<01:01, 1.85it/s, loss=0.012, lr=0.0004]
a photo of the clean <s1><s2>
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a photo of a clean <s1><s2>
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Steps: 89%|████████▉ | 888/1000 [07:52<00:57, 1.95it/s, loss=0.013, lr=0.0004]
a cropped photo of a <s1><s2>
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a photo of a dirty <s1><s2>
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Steps: 89%|████████▉ | 890/1000 [07:53<00:59, 1.84it/s, loss=0.0634, lr=0.0004]
a cropped photo of a <s1><s2>
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a cropped photo of the <s1><s2>
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a photo of the <s1><s2>
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Steps: 89%|████████▉ | 893/1000 [07:54<00:53, 2.01it/s, loss=0.0288, lr=0.0004]
a photo of the nice <s1><s2>
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a photo of the nice <s1><s2>
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Steps: 90%|████████▉ | 895/1000 [07:55<00:50, 2.08it/s, loss=0.00358, lr=0.0004]
a photo of a clean <s1><s2>
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Steps: 90%|████████▉ | 896/1000 [07:56<00:54, 1.92it/s, loss=0.0285, lr=0.0004]
a photo of a nice <s1><s2>
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Steps: 90%|████████▉ | 897/1000 [07:56<00:51, 2.00it/s, loss=0.00938, lr=0.0004]
a photo of one <s1><s2>
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Steps: 90%|████████▉ | 898/1000 [07:57<00:53, 1.92it/s, loss=0.0248, lr=0.0004]
a photo of the cool <s1><s2>
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Steps: 90%|████████▉ | 899/1000 [07:57<00:51, 1.97it/s, loss=0.0346, lr=0.0004]
a rendition of a <s1><s2>
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Steps: 90%|█████████ | 900/1000 [07:58<00:49, 2.02it/s, loss=0.0034, lr=0.0004]
a photo of the cool <s1><s2>
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Steps: 90%|█████████ | 901/1000 [07:58<00:47, 2.07it/s, loss=0.194, lr=0.0004]
a dark photo of the <s1><s2>
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Steps: 90%|█████████ | 902/1000 [07:59<00:52, 1.85it/s, loss=0.0765, lr=0.0004]
a rendition of a <s1><s2>
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Steps: 90%|█████████ | 903/1000 [08:00<00:56, 1.70it/s, loss=0.00323, lr=0.0004]
a rendition of the <s1><s2>
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Steps: 90%|█████████ | 904/1000 [08:00<00:53, 1.80it/s, loss=0.00791, lr=0.0004]
a photo of one <s1><s2>
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a photo of the clean <s1><s2>
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a good photo of a <s1><s2>
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a bright photo of the <s1><s2>
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a photo of the weird <s1><s2>
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a photo of a cool <s1><s2>
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Steps: 91%|█████████ | 910/1000 [08:03<00:47, 1.90it/s, loss=0.00561, lr=0.0004]
a photo of a dirty <s1><s2>
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a photo of a small <s1><s2>
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a good photo of a <s1><s2>
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a photo of one <s1><s2>
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a rendering of a <s1><s2>
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a photo of the <s1><s2>
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Steps: 92%|█████████▏| 916/1000 [08:07<00:43, 1.91it/s, loss=0.00536, lr=0.0004]
a good photo of the <s1><s2>
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Steps: 92%|█████████▏| 917/1000 [08:07<00:41, 1.98it/s, loss=0.0445, lr=0.0004]
a bright photo of the <s1><s2>
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Steps: 92%|█████████▏| 918/1000 [08:07<00:40, 2.04it/s, loss=0.113, lr=0.0004]
a rendition of the <s1><s2>
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Steps: 92%|█████████▏| 919/1000 [08:08<00:39, 2.06it/s, loss=0.0677, lr=0.0004]
a photo of the cool <s1><s2>
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Steps: 92%|█████████▏| 920/1000 [08:08<00:39, 2.05it/s, loss=0.137, lr=0.0004]
a photo of my <s1><s2>
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Steps: 92%|█████████▏| 921/1000 [08:09<00:37, 2.08it/s, loss=0.0165, lr=0.0004]
a photo of the weird <s1><s2>
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Steps: 92%|█████████▏| 922/1000 [08:09<00:38, 2.02it/s, loss=0.00415, lr=0.0004]
a photo of a nice <s1><s2>
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a bright photo of the <s1><s2>
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Steps: 92%|█████████▏| 924/1000 [08:11<00:42, 1.77it/s, loss=0.0228, lr=0.0004]
a good photo of the <s1><s2>
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a photo of a small <s1><s2>
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the photo of a <s1><s2>
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a photo of the small <s1><s2>
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Steps: 93%|█████████▎| 928/1000 [08:13<00:40, 1.77it/s, loss=0.0769, lr=0.0004]
a photo of a dirty <s1><s2>
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Steps: 93%|█████████▎| 929/1000 [08:13<00:37, 1.89it/s, loss=0.0192, lr=0.0004]
a rendition of a <s1><s2>
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Steps: 93%|█████████▎| 930/1000 [08:14<00:38, 1.82it/s, loss=0.61, lr=0.0004]
a photo of a nice <s1><s2>
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Steps: 93%|█████████▎| 931/1000 [08:14<00:36, 1.91it/s, loss=0.0116, lr=0.0004]
a photo of a small <s1><s2>
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Steps: 93%|█████████▎| 932/1000 [08:15<00:35, 1.94it/s, loss=0.0774, lr=0.0004]
a rendition of the <s1><s2>
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Steps: 93%|█████████▎| 933/1000 [08:15<00:34, 1.95it/s, loss=0.0485, lr=0.0004]
a close-up photo of a <s1><s2>
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Steps: 93%|█████████▎| 934/1000 [08:16<00:33, 1.99it/s, loss=0.064, lr=0.0004]
a rendition of the <s1><s2>
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Steps: 94%|█████████▎| 935/1000 [08:16<00:35, 1.82it/s, loss=0.059, lr=0.0004]
a close-up photo of a <s1><s2>
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Steps: 94%|█████████▎| 936/1000 [08:17<00:34, 1.86it/s, loss=0.0171, lr=0.0004]
a rendering of a <s1><s2>
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Steps: 94%|█████████▎| 937/1000 [08:17<00:32, 1.91it/s, loss=0.0432, lr=0.0004]
a rendition of a <s1><s2>
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Steps: 94%|█████████▍| 938/1000 [08:18<00:34, 1.79it/s, loss=0.0171, lr=0.0004]
a photo of the large <s1><s2>
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Steps: 94%|█████████▍| 939/1000 [08:19<00:35, 1.70it/s, loss=0.00676, lr=0.0004]
a rendition of a <s1><s2>
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Steps: 94%|█████████▍| 940/1000 [08:19<00:34, 1.75it/s, loss=0.00282, lr=0.0004]
a rendition of the <s1><s2>
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Steps: 94%|█████████▍| 941/1000 [08:20<00:32, 1.82it/s, loss=0.00309, lr=0.0004]
a close-up photo of the <s1><s2>
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Steps: 94%|█████████▍| 942/1000 [08:20<00:30, 1.91it/s, loss=0.00602, lr=0.0004]
a close-up photo of the <s1><s2>
Steps: 94%|█████████▍| 942/1000 [08:20<00:30, 1.91it/s, loss=0.164, lr=0.0004]
Steps: 94%|█████████▍| 943/1000 [08:21<00:31, 1.82it/s, loss=0.164, lr=0.0004]
a rendering of a <s1><s2>
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Steps: 94%|█████████▍| 944/1000 [08:21<00:30, 1.85it/s, loss=0.0044, lr=0.0004]
a photo of the weird <s1><s2>
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Steps: 94%|█████████▍| 945/1000 [08:22<00:29, 1.88it/s, loss=0.0446, lr=0.0004]
a rendition of the <s1><s2>
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Steps: 95%|█████████▍| 946/1000 [08:22<00:29, 1.86it/s, loss=0.0301, lr=0.0004]
a photo of the small <s1><s2>
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Steps: 95%|█████████▍| 947/1000 [08:23<00:28, 1.87it/s, loss=0.056, lr=0.0004]
a good photo of the <s1><s2>
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Steps: 95%|█████████▍| 948/1000 [08:24<00:27, 1.90it/s, loss=0.00495, lr=0.0004]
a photo of the <s1><s2>
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Steps: 95%|█████████▍| 949/1000 [08:24<00:27, 1.82it/s, loss=0.00259, lr=0.0004]
a photo of one <s1><s2>
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Steps: 95%|█████████▌| 950/1000 [08:25<00:26, 1.89it/s, loss=0.0143, lr=0.0004]
a bright photo of the <s1><s2>
Steps: 95%|█████████▌| 950/1000 [08:25<00:26, 1.89it/s, loss=0.0324, lr=0.0004]
Steps: 95%|█████████▌| 951/1000 [08:25<00:28, 1.73it/s, loss=0.0324, lr=0.0004]
a photo of one <s1><s2>
Steps: 95%|█████████▌| 951/1000 [08:25<00:28, 1.73it/s, loss=0.0114, lr=0.0004]
Steps: 95%|█████████▌| 952/1000 [08:26<00:26, 1.81it/s, loss=0.0114, lr=0.0004]
a close-up photo of the <s1><s2>
Steps: 95%|█████████▌| 952/1000 [08:26<00:26, 1.81it/s, loss=0.0151, lr=0.0004]
Steps: 95%|█████████▌| 953/1000 [08:26<00:26, 1.76it/s, loss=0.0151, lr=0.0004]
a photo of the <s1><s2>
Steps: 95%|█████████▌| 953/1000 [08:26<00:26, 1.76it/s, loss=0.00789, lr=0.0004]
Steps: 95%|█████████▌| 954/1000 [08:27<00:25, 1.84it/s, loss=0.00789, lr=0.0004]
a close-up photo of the <s1><s2>
Steps: 95%|█████████▌| 954/1000 [08:27<00:25, 1.84it/s, loss=0.0327, lr=0.0004]
Steps: 96%|█████████▌| 955/1000 [08:27<00:24, 1.84it/s, loss=0.0327, lr=0.0004]
a cropped photo of a <s1><s2>
Steps: 96%|█████████▌| 955/1000 [08:27<00:24, 1.84it/s, loss=0.0411, lr=0.0004]
Steps: 96%|█████████▌| 956/1000 [08:28<00:25, 1.75it/s, loss=0.0411, lr=0.0004]
a rendering of a <s1><s2>
Steps: 96%|█████████▌| 956/1000 [08:28<00:25, 1.75it/s, loss=0.0252, lr=0.0004]
Steps: 96%|█████████▌| 957/1000 [08:29<00:23, 1.83it/s, loss=0.0252, lr=0.0004]
a bright photo of the <s1><s2>
Steps: 96%|█████████▌| 957/1000 [08:29<00:23, 1.83it/s, loss=0.0794, lr=0.0004]
Steps: 96%|█████████▌| 958/1000 [08:29<00:22, 1.88it/s, loss=0.0794, lr=0.0004]
a photo of a nice <s1><s2>
Steps: 96%|█████████▌| 958/1000 [08:29<00:22, 1.88it/s, loss=0.0863, lr=0.0004]
Steps: 96%|█████████▌| 959/1000 [08:30<00:21, 1.93it/s, loss=0.0863, lr=0.0004]
a photo of the <s1><s2>
Steps: 96%|█████████▌| 959/1000 [08:30<00:21, 1.93it/s, loss=0.0245, lr=0.0004]
Steps: 96%|█████████▌| 960/1000 [08:30<00:22, 1.77it/s, loss=0.0245, lr=0.0004]
a rendition of the <s1><s2>
Steps: 96%|█████████▌| 960/1000 [08:30<00:22, 1.77it/s, loss=0.0471, lr=0.0004]
Steps: 96%|█████████▌| 961/1000 [08:31<00:21, 1.79it/s, loss=0.0471, lr=0.0004]
a close-up photo of a <s1><s2>
Steps: 96%|█████████▌| 961/1000 [08:31<00:21, 1.79it/s, loss=0.0218, lr=0.0004]
Steps: 96%|█████████▌| 962/1000 [08:31<00:20, 1.86it/s, loss=0.0218, lr=0.0004]
a dark photo of the <s1><s2>
Steps: 96%|█████████▌| 962/1000 [08:31<00:20, 1.86it/s, loss=0.265, lr=0.0004]
Steps: 96%|█████████▋| 963/1000 [08:32<00:19, 1.88it/s, loss=0.265, lr=0.0004]
a photo of a small <s1><s2>
Steps: 96%|█████████▋| 963/1000 [08:32<00:19, 1.88it/s, loss=0.0169, lr=0.0004]
Steps: 96%|█████████▋| 964/1000 [08:32<00:18, 1.97it/s, loss=0.0169, lr=0.0004]
a photo of a nice <s1><s2>
Steps: 96%|█████████▋| 964/1000 [08:32<00:18, 1.97it/s, loss=0.126, lr=0.0004]
Steps: 96%|█████████▋| 965/1000 [08:33<00:17, 1.97it/s, loss=0.126, lr=0.0004]
a photo of a clean <s1><s2>
Steps: 96%|█████████▋| 965/1000 [08:33<00:17, 1.97it/s, loss=0.039, lr=0.0004]
Steps: 97%|█████████▋| 966/1000 [08:33<00:18, 1.85it/s, loss=0.039, lr=0.0004]
a photo of the <s1><s2>
Steps: 97%|█████████▋| 966/1000 [08:33<00:18, 1.85it/s, loss=0.00825, lr=0.0004]
Steps: 97%|█████████▋| 967/1000 [08:34<00:19, 1.69it/s, loss=0.00825, lr=0.0004]
a photo of a clean <s1><s2>
Steps: 97%|█████████▋| 967/1000 [08:34<00:19, 1.69it/s, loss=0.0322, lr=0.0004]
Steps: 97%|█████████▋| 968/1000 [08:35<00:17, 1.79it/s, loss=0.0322, lr=0.0004]
a photo of my <s1><s2>
Steps: 97%|█████████▋| 968/1000 [08:35<00:17, 1.79it/s, loss=0.0482, lr=0.0004]
Steps: 97%|█████████▋| 969/1000 [08:35<00:18, 1.72it/s, loss=0.0482, lr=0.0004]
a photo of a <s1><s2>
Steps: 97%|█████████▋| 969/1000 [08:35<00:18, 1.72it/s, loss=0.0154, lr=0.0004]
Steps: 97%|█████████▋| 970/1000 [08:36<00:16, 1.83it/s, loss=0.0154, lr=0.0004]
a photo of a small <s1><s2>
Steps: 97%|█████████▋| 970/1000 [08:36<00:16, 1.83it/s, loss=0.013, lr=0.0004]
Steps: 97%|█████████▋| 971/1000 [08:36<00:15, 1.87it/s, loss=0.013, lr=0.0004]
a photo of the clean <s1><s2>
Steps: 97%|█████████▋| 971/1000 [08:36<00:15, 1.87it/s, loss=0.0367, lr=0.0004]
Steps: 97%|█████████▋| 972/1000 [08:37<00:14, 1.92it/s, loss=0.0367, lr=0.0004]
a dark photo of the <s1><s2>
Steps: 97%|█████████▋| 972/1000 [08:37<00:14, 1.92it/s, loss=0.00972, lr=0.0004]
Steps: 97%|█████████▋| 973/1000 [08:37<00:13, 1.95it/s, loss=0.00972, lr=0.0004]
a photo of the nice <s1><s2>
Steps: 97%|█████████▋| 973/1000 [08:37<00:13, 1.95it/s, loss=0.0261, lr=0.0004]
Steps: 97%|█████████▋| 974/1000 [08:38<00:13, 1.93it/s, loss=0.0261, lr=0.0004]
a photo of my <s1><s2>
Steps: 97%|█████████▋| 974/1000 [08:38<00:13, 1.93it/s, loss=0.0559, lr=0.0004]
Steps: 98%|█████████▊| 975/1000 [08:38<00:13, 1.82it/s, loss=0.0559, lr=0.0004]
a photo of a dirty <s1><s2>
Steps: 98%|█████████▊| 975/1000 [08:38<00:13, 1.82it/s, loss=0.0151, lr=0.0004]
Steps: 98%|█████████▊| 976/1000 [08:39<00:13, 1.83it/s, loss=0.0151, lr=0.0004]
a photo of a clean <s1><s2>
Steps: 98%|█████████▊| 976/1000 [08:39<00:13, 1.83it/s, loss=0.0069, lr=0.0004]
Steps: 98%|█████████▊| 977/1000 [08:39<00:12, 1.89it/s, loss=0.0069, lr=0.0004]
a photo of a nice <s1><s2>
Steps: 98%|█████████▊| 977/1000 [08:39<00:12, 1.89it/s, loss=0.0313, lr=0.0004]
Steps: 98%|█████████▊| 978/1000 [08:40<00:11, 1.96it/s, loss=0.0313, lr=0.0004]
a good photo of a <s1><s2>
Steps: 98%|█████████▊| 978/1000 [08:40<00:11, 1.96it/s, loss=0.0345, lr=0.0004]
Steps: 98%|█████████▊| 979/1000 [08:40<00:10, 2.00it/s, loss=0.0345, lr=0.0004]
a photo of the clean <s1><s2>
Steps: 98%|█████████▊| 979/1000 [08:40<00:10, 2.00it/s, loss=0.041, lr=0.0004]
Steps: 98%|█████████▊| 980/1000 [08:41<00:10, 1.82it/s, loss=0.041, lr=0.0004]
a good photo of a <s1><s2>
Steps: 98%|█████████▊| 980/1000 [08:41<00:10, 1.82it/s, loss=0.00499, lr=0.0004]
Steps: 98%|█████████▊| 981/1000 [08:41<00:10, 1.87it/s, loss=0.00499, lr=0.0004]
a rendition of the <s1><s2>
Steps: 98%|█████████▊| 981/1000 [08:41<00:10, 1.87it/s, loss=0.00718, lr=0.0004]
Steps: 98%|█████████▊| 982/1000 [08:42<00:09, 1.90it/s, loss=0.00718, lr=0.0004]
a photo of the large <s1><s2>
Steps: 98%|█████████▊| 982/1000 [08:42<00:09, 1.90it/s, loss=0.00466, lr=0.0004]
Steps: 98%|█████████▊| 983/1000 [08:42<00:08, 1.92it/s, loss=0.00466, lr=0.0004]
a photo of the large <s1><s2>
Steps: 98%|█████████▊| 983/1000 [08:42<00:08, 1.92it/s, loss=0.00924, lr=0.0004]
Steps: 98%|█████████▊| 984/1000 [08:43<00:08, 1.80it/s, loss=0.00924, lr=0.0004]
a photo of one <s1><s2>
Steps: 98%|█████████▊| 984/1000 [08:43<00:08, 1.80it/s, loss=0.0259, lr=0.0004]
Steps: 98%|█████████▊| 985/1000 [08:44<00:08, 1.76it/s, loss=0.0259, lr=0.0004]
a cropped photo of a <s1><s2>
Steps: 98%|█████████▊| 985/1000 [08:44<00:08, 1.76it/s, loss=0.0268, lr=0.0004]
Steps: 99%|█████████▊| 986/1000 [08:44<00:07, 1.85it/s, loss=0.0268, lr=0.0004]
a bright photo of the <s1><s2>
Steps: 99%|█████████▊| 986/1000 [08:44<00:07, 1.85it/s, loss=0.00351, lr=0.0004]
Steps: 99%|█████████▊| 987/1000 [08:45<00:06, 1.93it/s, loss=0.00351, lr=0.0004]
a photo of a nice <s1><s2>
Steps: 99%|█████████▊| 987/1000 [08:45<00:06, 1.93it/s, loss=0.322, lr=0.0004]
Steps: 99%|█████████▉| 988/1000 [08:45<00:06, 1.97it/s, loss=0.322, lr=0.0004]
a photo of a cool <s1><s2>
Steps: 99%|█████████▉| 988/1000 [08:45<00:06, 1.97it/s, loss=0.0978, lr=0.0004]
Steps: 99%|█████████▉| 989/1000 [08:46<00:05, 2.02it/s, loss=0.0978, lr=0.0004]
a photo of a cool <s1><s2>
Steps: 99%|█████████▉| 989/1000 [08:46<00:05, 2.02it/s, loss=0.0232, lr=0.0004]
Steps: 99%|█████████▉| 990/1000 [08:46<00:04, 2.09it/s, loss=0.0232, lr=0.0004]
a cropped photo of a <s1><s2>
Steps: 99%|█████████▉| 990/1000 [08:46<00:04, 2.09it/s, loss=0.108, lr=0.0004]
Steps: 99%|█████████▉| 991/1000 [08:47<00:04, 1.92it/s, loss=0.108, lr=0.0004]
a photo of the clean <s1><s2>
Steps: 99%|█████████▉| 991/1000 [08:47<00:04, 1.92it/s, loss=0.0106, lr=0.0004]
Steps: 99%|█████████▉| 992/1000 [08:47<00:04, 1.89it/s, loss=0.0106, lr=0.0004]
a photo of the <s1><s2>
Steps: 99%|█████████▉| 992/1000 [08:47<00:04, 1.89it/s, loss=0.00767, lr=0.0004]
Steps: 99%|█████████▉| 993/1000 [08:48<00:03, 1.98it/s, loss=0.00767, lr=0.0004]
a photo of a clean <s1><s2>
Steps: 99%|█████████▉| 993/1000 [08:48<00:03, 1.98it/s, loss=0.0662, lr=0.0004]
Steps: 99%|█████████▉| 994/1000 [08:48<00:03, 1.84it/s, loss=0.0662, lr=0.0004]
a close-up photo of the <s1><s2>
Steps: 99%|█████████▉| 994/1000 [08:48<00:03, 1.84it/s, loss=0.0105, lr=0.0004]
Steps: 100%|█████████▉| 995/1000 [08:49<00:02, 1.89it/s, loss=0.0105, lr=0.0004]
a photo of the large <s1><s2>
Steps: 100%|█████████▉| 995/1000 [08:49<00:02, 1.89it/s, loss=0.0157, lr=0.0004]
Steps: 100%|█████████▉| 996/1000 [08:49<00:02, 1.94it/s, loss=0.0157, lr=0.0004]
a cropped photo of the <s1><s2>
Steps: 100%|█████████▉| 996/1000 [08:49<00:02, 1.94it/s, loss=0.119, lr=0.0004]
Steps: 100%|█████████▉| 997/1000 [08:50<00:01, 1.97it/s, loss=0.119, lr=0.0004]
a photo of the cool <s1><s2>
Steps: 100%|█████████▉| 997/1000 [08:50<00:01, 1.97it/s, loss=0.0204, lr=0.0004]
Steps: 100%|█████████▉| 998/1000 [08:50<00:01, 1.84it/s, loss=0.0204, lr=0.0004]
a good photo of a <s1><s2>
Steps: 100%|█████████▉| 998/1000 [08:50<00:01, 1.84it/s, loss=0.00656, lr=0.0004]
Steps: 100%|█████████▉| 999/1000 [08:51<00:00, 1.74it/s, loss=0.00656, lr=0.0004]
the photo of a <s1><s2>
Steps: 100%|█████████▉| 999/1000 [08:51<00:00, 1.74it/s, loss=0.0391, lr=0.0004]
Steps: 100%|██████████| 1000/1000 [08:51<00:00, 1.85it/s, loss=0.0391, lr=0.0004]
Current Learned Embeddings for <s1>:, id 49408 tensor([ 0.0001, 0.0033, -0.0144, 0.0123], device='cuda:0')
Current Learned Embeddings for <s2>:, id 49409 tensor([-0.0261, 0.0331, 0.0063, -0.0012], device='cuda:0')
Saving weights to checkpoints/step_1000.safetensors
LORA Unet Moved 0.002899408107623458
LORA CLIP Moved 0.0002070308692054823
Current Learned Embeddings for <s1>:, id 49408 tensor([ 0.0001, 0.0033, -0.0144, 0.0123], device='cuda:0')
Current Learned Embeddings for <s2>:, id 49409 tensor([-0.0261, 0.0331, 0.0063, -0.0012], device='cuda:0')
Saving weights to checkpoints/final_lora.safetensors
Steps: 100%|██████████| 1000/1000 [08:51<00:00, 1.85it/s, loss=0.112, lr=0.0004]
Steps: 100%|██████████| 1000/1000 [08:52<00:00, 1.88it/s, loss=0.112, lr=0.0004]
Version Details
- Version ID
4395d94cdba2205d0ea50d571d00a64cbb164e79dde0e46608f270194874c11b- Version Created
- February 14, 2023