End of training

README.md

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+---
+base_model: stable-diffusion-v1-5/stable-diffusion-v1-5
+library_name: diffusers
+license: creativeml-openrail-m
+inference: true
+instance_prompt: a photo of sks boot
+tags:
+- text-to-image
+- diffusers
+- lora
+- diffusers-training
+- stable-diffusion
+- stable-diffusion-diffusers
+---
+
+<!-- This model card has been generated automatically according to the information the training script had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+
+# LoRA DreamBooth - BJEon121/trained-sd1.5_fancy_boot
+
+These are LoRA adaption weights for stable-diffusion-v1-5/stable-diffusion-v1-5. The weights were trained on a photo of sks boot using [DreamBooth](https://dreambooth.github.io/). You can find some example images in the following. 
+
+
+
+LoRA for the text encoder was enabled: False.
+
+
+## Intended uses & limitations
+
+#### How to use
+
+```python
+# TODO: add an example code snippet for running this diffusion pipeline
+```
+
+#### Limitations and bias
+
+[TODO: provide examples of latent issues and potential remediations]
+
+## Training details
+
+[TODO: describe the data used to train the model]

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+adam_beta2: 0.999
+adam_epsilon: 1.0e-08
+adam_weight_decay: 0.01
+allow_tf32: false
+center_crop: false
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+dataloader_num_workers: 0
+enable_xformers_memory_efficient_attention: false
+gradient_accumulation_steps: 1
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+instance_data_dir: /nas/home/jj275/Personalization_ICCV_2025/data/fancy_boot
+instance_prompt: a photo of sks boot
+learning_rate: 0.0001
+local_rank: -1
+logging_dir: logs
+lr_num_cycles: 1
+lr_power: 1.0
+lr_scheduler: constant
+lr_warmup_steps: 0
+max_grad_norm: 1.0
+max_train_steps: 500
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+num_class_images: 100
+num_train_epochs: 84
+num_validation_images: 4
+output_dir: trained-sd1.5_fancy_boot
+pre_compute_text_embeddings: false
+pretrained_model_name_or_path: stable-diffusion-v1-5/stable-diffusion-v1-5
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+rank: 4
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+use_8bit_adam: false
+validation_epochs: 50
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