End of training
Browse files- README.md +2 -2
- checkpoint-2500/image_0.png +0 -0
- checkpoint-2500/image_1.png +0 -0
- checkpoint-2500/image_2.png +0 -0
- checkpoint-2500/image_3.png +0 -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/scheduler.bin +3 -0
- logs/dreambooth-lora/1707322708.1055326/events.out.tfevents.1707322708.ai1.33588.1 +3 -0
- logs/dreambooth-lora/1707322708.1938033/hparams.yml +56 -0
- logs/dreambooth-lora/events.out.tfevents.1707322708.ai1.33588.0 +3 -0
- pytorch_lora_weights.safetensors +1 -1
README.md
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---
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license: creativeml-openrail-m
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base_model: CompVis/stable-diffusion-v1-4
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instance_prompt: a photo of sks
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tags:
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- stable-diffusion
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- stable-diffusion-diffusers
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# LoRA DreamBooth - danaleee/CL_rank4_iter500_valprompt
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These are LoRA adaption weights for CompVis/stable-diffusion-v1-4. The weights were trained on a photo of sks
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![img_0](./image_0.png)
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![img_1](./image_1.png)
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---
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license: creativeml-openrail-m
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base_model: CompVis/stable-diffusion-v1-4
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instance_prompt: a photo of sks teddybear
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tags:
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- stable-diffusion
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- stable-diffusion-diffusers
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# LoRA DreamBooth - danaleee/CL_rank4_iter500_valprompt
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These are LoRA adaption weights for CompVis/stable-diffusion-v1-4. The weights were trained on a photo of sks teddybear using [DreamBooth](https://dreambooth.github.io/). You can find some example images in the following.
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![img_0](./image_0.png)
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![img_1](./image_1.png)
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checkpoint-2500/image_0.png
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checkpoint-2500/image_1.png
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checkpoint-2500/image_2.png
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checkpoint-2500/image_3.png
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checkpoint-2500/optimizer.bin
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size 6595706
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checkpoint-2500/pytorch_lora_weights.safetensors
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checkpoint-2500/random_states_0.pkl
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version https://git-lfs.github.com/spec/v1
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checkpoint-2500/scheduler.bin
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version https://git-lfs.github.com/spec/v1
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logs/dreambooth-lora/1707322708.1055326/events.out.tfevents.1707322708.ai1.33588.1
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version https://git-lfs.github.com/spec/v1
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size 2797
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logs/dreambooth-lora/1707322708.1938033/hparams.yml
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adam_beta1: 0.9
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adam_beta2: 0.999
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adam_epsilon: 1.0e-08
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adam_weight_decay: 0.01
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allow_tf32: false
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center_crop: false
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checkpointing_steps: 500
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checkpoints_total_limit: null
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class_data_dir: null
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class_labels_conditioning: null
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class_prompt: null
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dataloader_num_workers: 0
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enable_xformers_memory_efficient_attention: false
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gradient_accumulation_steps: 1
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gradient_checkpointing: false
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hub_model_id: null
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hub_token: null
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instance_data_dir: /d1/daeun/diffusers/cyw_data/teddybear/
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instance_prompt: a photo of sks teddybear
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learning_rate: 0.0001
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local_rank: 0
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logging_dir: logs
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lr_num_cycles: 1
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lr_power: 1.0
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lr_scheduler: constant
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lr_warmup_steps: 0
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max_grad_norm: 1.0
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max_train_steps: 2500
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mixed_precision: null
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num_class_images: 100
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num_train_epochs: 1250
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num_validation_images: 4
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output_dir: /d1/daeun/diffusers/examples/dreambooth/exp/CL_rank4_iter500_valprompt/
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pre_compute_text_embeddings: false
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pretrained_model_name_or_path: CompVis/stable-diffusion-v1-4
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prior_generation_precision: null
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prior_loss_weight: 1.0
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push_to_hub: true
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rank: 4
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report_to: tensorboard
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resolution: 512
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resume_from_checkpoint: latest
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revision: null
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sample_batch_size: 4
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scale_lr: false
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seed: 0
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text_encoder_use_attention_mask: false
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tokenizer_max_length: null
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tokenizer_name: null
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train_batch_size: 1
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train_text_encoder: false
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use_8bit_adam: false
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validation_epochs: 2500
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validation_prompt: a photo of sks teddybear
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variant: null
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with_prior_preservation: false
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logs/dreambooth-lora/events.out.tfevents.1707322708.ai1.33588.0
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pytorch_lora_weights.safetensors
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