End of training

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README.md

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+
+---
+license: creativeml-openrail-m
+base_model: runwayml/stable-diffusion-v1-5
+instance_prompt: photo of a sks person
+tags:
+- stable-diffusion
+- stable-diffusion-diffusers
+- text-to-image
+- diffusers
+- custom-diffusion
+inference: true
+---
+    
+# Custom Diffusion - SidXXD/Clean-m_213
+
+These are Custom Diffusion adaption weights for runwayml/stable-diffusion-v1-5. The weights were trained on photo of a sks person using [Custom Diffusion](https://www.cs.cmu.edu/~custom-diffusion). You can find some example images in the following. 
+
+
+
+
+For more details on the training, please follow [this link](https://github.com/huggingface/diffusers/blob/main/examples/custom_diffusion).

logs/custom-diffusion/1737560023.741578/events.out.tfevents.1737560023.cudahpc06.1911677.1

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+adam_beta2: 0.999
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+adam_weight_decay: 0.01
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+class_prompt: null
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+dataloader_num_workers: 2
+enable_xformers_memory_efficient_attention: false
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+gradient_accumulation_steps: 1
+gradient_checkpointing: false
+hflip: true
+hub_model_id: null
+hub_token: null
+initializer_token: ktn
+instance_data_dir: /home/xide/miniconda3/code/data/Untarget_training_img_20/Clean/m-213
+instance_prompt: photo of a sks person
+learning_rate: 1.0e-05
+local_rank: -1
+logging_dir: logs
+lr_scheduler: constant
+lr_warmup_steps: 0
+max_grad_norm: 1.0
+max_train_steps: 250
+mixed_precision: null
+modifier_token: sks
+no_safe_serialization: true
+noaug: false
+num_class_images: 200
+num_train_epochs: 1
+num_validation_images: 2
+output_dir: /home/xide/miniconda3/code/diffusers_old/examples/custom_diffusion/model/ICML_KV_ablation/Clean-m_213
+pretrained_model_name_or_path: runwayml/stable-diffusion-v1-5
+prior_generation_precision: null
+prior_loss_weight: 0
+push_to_hub: true
+real_prior: false
+report_to: tensorboard
+resolution: 512
+resume_from_checkpoint: null
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+sample_batch_size: 4
+scale_lr: true
+seed: 42
+set_grads_to_none: false
+tokenizer_name: null
+train_batch_size: 2
+use_8bit_adam: false
+validation_prompt: null
+validation_steps: 50
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