End of training

.gitattributes

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 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+image_0.png filter=lfs diff=lfs merge=lfs -text
+image_1.png filter=lfs diff=lfs merge=lfs -text

<new1>.safetensors

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README.md

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+---
+base_model: CompVis/stable-diffusion-v1-4
+library_name: diffusers
+license: creativeml-openrail-m
+inference: true
+instance_prompt: photo of a <new1> face
+tags:
+- text-to-image
+- diffusers
+- stable-diffusion
+- stable-diffusion-diffusers
+- custom-diffusion
+- diffusers-training
+---
+
+<!-- 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. -->
+
+
+# Custom Diffusion - veddhanth/customdiff1989
+
+These are Custom Diffusion adaption weights for CompVis/stable-diffusion-v1-4. The weights were trained on photo of a <new1> face using [Custom Diffusion](https://www.cs.cmu.edu/~custom-diffusion). You can find some example images in the following. 
+
+![img_0](./image_0.png)
+![img_1](./image_1.png)
+
+
+
+For more details on the training, please follow [this link](https://github.com/huggingface/diffusers/blob/main/examples/custom_diffusion).
+
+
+## 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
+checkpointing_steps: 2500
+checkpoints_total_limit: null
+class_data_dir: /home/snuc/Documents/personalizedrep/personalized-rep/synthetic_data/celeba/celeba_class_dir_rv/1989
+class_prompt: face
+concepts_list: null
+dataloader_num_workers: 2
+enable_xformers_memory_efficient_attention: false
+freeze_model: crossattn_kv
+gradient_accumulation_steps: 1
+gradient_checkpointing: false
+hflip: true
+hub_model_id: null
+hub_token: null
+initializer_token: ktn+pll+ucd
+instance_data_dir: /home/snuc/Documents/personalizedrep/dataset/train/1989/
+instance_prompt: photo of a <new1> face
+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: 1000
+mixed_precision: null
+modifier_token: <new1>
+no_safe_serialization: false
+noaug: false
+num_class_images: 1000
+num_train_epochs: 1
+num_validation_images: 2
+output_dir: customdiff1989
+pretrained_model_name_or_path: CompVis/stable-diffusion-v1-4
+prior_generation_precision: null
+prior_loss_weight: 1.0
+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: 1
+use_8bit_adam: false
+validation_prompt: <new1> face with a neutral expression
+validation_steps: 2000
+variant: null
+with_prior_preservation: true

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+adam_weight_decay: 0.01
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+center_crop: false
+checkpointing_steps: 2500
+checkpoints_total_limit: null
+class_data_dir: /home/snuc/Documents/personalizedrep/personalized-rep/synthetic_data/celeba/celeba_class_dir_rv/1989
+class_prompt: face
+concepts_list: null
+dataloader_num_workers: 2
+enable_xformers_memory_efficient_attention: false
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+gradient_accumulation_steps: 1
+gradient_checkpointing: false
+hflip: true
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+hub_token: null
+initializer_token: ktn+pll+ucd
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+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: 1000
+mixed_precision: null
+modifier_token: <new1>
+no_safe_serialization: false
+noaug: false
+num_class_images: 1000
+num_train_epochs: 1
+num_validation_images: 2
+output_dir: customdiff1989
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+scale_lr: true
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+train_batch_size: 1
+use_8bit_adam: false
+validation_prompt: <new1> face with a neutral expression
+validation_steps: 2000
+variant: null
+with_prior_preservation: false

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