End of training
Browse files- .gitattributes +4 -0
- README.md +95 -0
- checkpoint-1000/optimizer.bin +3 -0
- checkpoint-1000/pytorch_lora_weights.safetensors +3 -0
- checkpoint-1000/random_states_0.pkl +3 -0
- checkpoint-1000/scaler.pt +3 -0
- checkpoint-1000/scheduler.bin +3 -0
- checkpoint-1500/optimizer.bin +3 -0
- checkpoint-1500/pytorch_lora_weights.safetensors +3 -0
- checkpoint-1500/random_states_0.pkl +3 -0
- checkpoint-1500/scaler.pt +3 -0
- checkpoint-1500/scheduler.bin +3 -0
- checkpoint-2000/optimizer.bin +3 -0
- checkpoint-2000/pytorch_lora_weights.safetensors +3 -0
- checkpoint-2000/random_states_0.pkl +3 -0
- checkpoint-2000/scaler.pt +3 -0
- checkpoint-2000/scheduler.bin +3 -0
- checkpoint-2500/optimizer.bin +3 -0
- checkpoint-2500/pytorch_lora_weights.safetensors +3 -0
- checkpoint-2500/random_states_0.pkl +3 -0
- checkpoint-2500/scaler.pt +3 -0
- checkpoint-2500/scheduler.bin +3 -0
- checkpoint-3000/optimizer.bin +3 -0
- checkpoint-3000/pytorch_lora_weights.safetensors +3 -0
- checkpoint-3000/random_states_0.pkl +3 -0
- checkpoint-3000/scaler.pt +3 -0
- checkpoint-3000/scheduler.bin +3 -0
- checkpoint-500/optimizer.bin +3 -0
- checkpoint-500/pytorch_lora_weights.safetensors +3 -0
- checkpoint-500/random_states_0.pkl +3 -0
- checkpoint-500/scaler.pt +3 -0
- checkpoint-500/scheduler.bin +3 -0
- image_0.png +3 -0
- image_1.png +3 -0
- image_2.png +3 -0
- image_3.png +3 -0
- logs/dreambooth-sd3-lora/1752683294.459341/events.out.tfevents.1752683294.sd3-v4.202622.1 +3 -0
- logs/dreambooth-sd3-lora/1752683294.5195315/hparams.yml +76 -0
- logs/dreambooth-sd3-lora/events.out.tfevents.1752683294.sd3-v4.202622.0 +3 -0
- pytorch_lora_weights.safetensors +3 -0
.gitattributes
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*.zip filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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image_0.png filter=lfs diff=lfs merge=lfs -text
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image_1.png filter=lfs diff=lfs merge=lfs -text
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image_2.png filter=lfs diff=lfs merge=lfs -text
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README.md
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| 1 |
+
---
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| 2 |
+
base_model: stabilityai/stable-diffusion-3.5-large
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| 3 |
+
library_name: diffusers
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| 4 |
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license: other
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| 5 |
+
instance_prompt: meli icon or illustration
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| 6 |
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widget:
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+
- text: meli icon or illustration of a dog, white_background, meli_style, meli_figure,
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| 8 |
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yellow_theme
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| 9 |
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output:
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| 10 |
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url: image_0.png
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+
- text: meli icon or illustration of a dog, white_background, meli_style, meli_figure,
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+
yellow_theme
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| 13 |
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output:
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| 14 |
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url: image_1.png
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| 15 |
+
- text: meli icon or illustration of a dog, white_background, meli_style, meli_figure,
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| 16 |
+
yellow_theme
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| 17 |
+
output:
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| 18 |
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url: image_2.png
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| 19 |
+
- text: meli icon or illustration of a dog, white_background, meli_style, meli_figure,
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| 20 |
+
yellow_theme
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| 21 |
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output:
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| 22 |
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url: image_3.png
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| 23 |
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tags:
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| 24 |
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- text-to-image
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| 25 |
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- diffusers-training
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| 26 |
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- diffusers
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| 27 |
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- lora
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| 28 |
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- template:sd-lora
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| 29 |
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- sd3.5-large
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| 30 |
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- sd3.5
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| 31 |
+
- sd3.5-diffusers
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| 32 |
+
---
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| 33 |
+
|
| 34 |
+
<!-- This model card has been generated automatically according to the information the training script had access to. You
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should probably proofread and complete it, then remove this comment. -->
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| 37 |
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# SD3.5-Large DreamBooth LoRA - nm9404/ilus_4_feedback
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<Gallery />
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## Model description
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These are nm9404/ilus_4_feedback DreamBooth LoRA weights for stabilityai/stable-diffusion-3.5-large.
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The weights were trained using [DreamBooth](https://dreambooth.github.io/) with the [SD3 diffusers trainer](https://github.com/huggingface/diffusers/blob/main/examples/dreambooth/README_sd3.md).
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Was LoRA for the text encoder enabled? False.
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## Trigger words
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You should use `meli icon or illustration` to trigger the image generation.
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## Download model
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[Download the *.safetensors LoRA](nm9404/ilus_4_feedback/tree/main) in the Files & versions tab.
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## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)
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```py
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from diffusers import AutoPipelineForText2Image
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import torch
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pipeline = AutoPipelineForText2Image.from_pretrained(stabilityai/stable-diffusion-3.5-large, torch_dtype=torch.float16).to('cuda')
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| 64 |
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pipeline.load_lora_weights('nm9404/ilus_4_feedback', weight_name='pytorch_lora_weights.safetensors')
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image = pipeline('meli icon or illustration of a dog, white_background, meli_style, meli_figure, yellow_theme').images[0]
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```
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### Use it with UIs such as AUTOMATIC1111, Comfy UI, SD.Next, Invoke
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- **LoRA**: download **[`diffusers_lora_weights.safetensors` here 💾](/nm9404/ilus_4_feedback/blob/main/diffusers_lora_weights.safetensors)**.
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- Rename it and place it on your `models/Lora` folder.
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- On AUTOMATIC1111, load the LoRA by adding `<lora:your_new_name:1>` to your prompt. On ComfyUI just [load it as a regular LoRA](https://comfyanonymous.github.io/ComfyUI_examples/lora/).
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For more details, including weighting, merging and fusing LoRAs, check the [documentation on loading LoRAs in diffusers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters)
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| 76 |
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## License
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Please adhere to the licensing terms as described [here](https://huggingface.co/stabilityai/stable-diffusion-3.5-large/blob/main/LICENSE.md).
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## Intended uses & limitations
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#### How to use
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```python
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# TODO: add an example code snippet for running this diffusion pipeline
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```
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#### Limitations and bias
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[TODO: provide examples of latent issues and potential remediations]
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## Training details
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[TODO: describe the data used to train the model]
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adam_beta1: 0.9
|
| 2 |
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adam_beta2: 0.999
|
| 3 |
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adam_epsilon: 1.0e-08
|
| 4 |
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adam_weight_decay: 0.0001
|
| 5 |
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adam_weight_decay_text_encoder: 0.001
|
| 6 |
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allow_tf32: false
|
| 7 |
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cache_dir: null
|
| 8 |
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cache_latents: false
|
| 9 |
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caption_column: text
|
| 10 |
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center_crop: true
|
| 11 |
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checkpointing_steps: 500
|
| 12 |
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checkpoints_total_limit: null
|
| 13 |
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class_data_dir: null
|
| 14 |
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class_prompt: null
|
| 15 |
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dataloader_num_workers: 8
|
| 16 |
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dataset_config_name: null
|
| 17 |
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dataset_name: preprocessed_assets
|
| 18 |
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gradient_accumulation_steps: 4
|
| 19 |
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gradient_checkpointing: false
|
| 20 |
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hub_model_id: ''
|
| 21 |
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hub_token: null
|
| 22 |
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image_column: image
|
| 23 |
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instance_data_dir: null
|
| 24 |
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instance_prompt: meli icon or illustration
|
| 25 |
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learning_rate: 0.0001
|
| 26 |
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local_rank: -1
|
| 27 |
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logging_dir: logs
|
| 28 |
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logit_mean: 0.0
|
| 29 |
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logit_std: 1.0
|
| 30 |
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lora_blocks: null
|
| 31 |
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lora_dropout: 0.0
|
| 32 |
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lora_layers: null
|
| 33 |
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lr_num_cycles: 1
|
| 34 |
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lr_power: 1.0
|
| 35 |
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lr_scheduler: cosine
|
| 36 |
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lr_warmup_steps: 0
|
| 37 |
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max_grad_norm: 1.0
|
| 38 |
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max_sequence_length: 77
|
| 39 |
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max_train_steps: 3000
|
| 40 |
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mixed_precision: fp16
|
| 41 |
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mode_scale: 1.29
|
| 42 |
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num_class_images: 100
|
| 43 |
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num_train_epochs: 35
|
| 44 |
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num_validation_images: 4
|
| 45 |
+
optimizer: AdamW
|
| 46 |
+
output_dir: $./finetune/lora/ilus_4_feedback
|
| 47 |
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precondition_outputs: 1
|
| 48 |
+
pretrained_model_name_or_path: stabilityai/stable-diffusion-3.5-large
|
| 49 |
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prior_generation_precision: null
|
| 50 |
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prior_loss_weight: 1.0
|
| 51 |
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prodigy_beta3: null
|
| 52 |
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prodigy_decouple: true
|
| 53 |
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prodigy_safeguard_warmup: true
|
| 54 |
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prodigy_use_bias_correction: true
|
| 55 |
+
push_to_hub: true
|
| 56 |
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random_flip: true
|
| 57 |
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rank: 4
|
| 58 |
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repeats: 1
|
| 59 |
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report_to: tensorboard
|
| 60 |
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resolution: 512
|
| 61 |
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resume_from_checkpoint: null
|
| 62 |
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revision: null
|
| 63 |
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sample_batch_size: 4
|
| 64 |
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scale_lr: false
|
| 65 |
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seed: 1337
|
| 66 |
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text_encoder_lr: 5.0e-06
|
| 67 |
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train_batch_size: 1
|
| 68 |
+
train_text_encoder: false
|
| 69 |
+
upcast_before_saving: false
|
| 70 |
+
use_8bit_adam: false
|
| 71 |
+
validation_epochs: 50
|
| 72 |
+
validation_prompt: meli icon or illustration of a dog, white_background, meli_style,
|
| 73 |
+
meli_figure, yellow_theme
|
| 74 |
+
variant: null
|
| 75 |
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weighting_scheme: logit_normal
|
| 76 |
+
with_prior_preservation: false
|
logs/dreambooth-sd3-lora/events.out.tfevents.1752683294.sd3-v4.202622.0
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