End of training
Browse files- README.md +5 -0
- checkpoint-1000/optimizer.bin +3 -0
- checkpoint-1000/random_states_0.pkl +3 -0
- checkpoint-1000/scaler.pt +3 -0
- checkpoint-1000/scheduler.bin +3 -0
- checkpoint-1000/unet/config.json +68 -0
- checkpoint-1000/unet/diffusion_pytorch_model.safetensors +3 -0
- checkpoint-500/optimizer.bin +1 -1
- checkpoint-500/random_states_0.pkl +2 -2
- checkpoint-500/scheduler.bin +1 -1
- checkpoint-500/unet/diffusion_pytorch_model.safetensors +1 -1
- logs/dreambooth/1736755257.623547/events.out.tfevents.1736755257.felab.1668141.1 +3 -0
- logs/dreambooth/1736755257.6262457/hparams.yml +62 -0
- logs/dreambooth/events.out.tfevents.1736755257.felab.1668141.0 +3 -0
- unet/diffusion_pytorch_model.safetensors +1 -1
README.md
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- diffusers-training
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- stable-diffusion
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- stable-diffusion-diffusers
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---
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<!-- This model card has been generated automatically according to the information the training script had access to. You
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- diffusers-training
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- stable-diffusion
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- stable-diffusion-diffusers
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- text-to-image
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- dreambooth
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- diffusers-training
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- stable-diffusion
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- stable-diffusion-diffusers
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---
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<!-- This model card has been generated automatically according to the information the training script had access to. You
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checkpoint-1000/optimizer.bin
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checkpoint-1000/random_states_0.pkl
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checkpoint-1000/unet/config.json
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{
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"_class_name": "UNet2DConditionModel",
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"_diffusers_version": "0.33.0.dev0",
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"_name_or_path": "stable-diffusion-v1-5/stable-diffusion-v1-5",
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"cross_attention_dim": 768,
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"down_block_types": [
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"CrossAttnDownBlock2D",
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"CrossAttnDownBlock2D",
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"mid_block_scale_factor": 1,
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"mid_block_type": "UNetMidBlock2DCrossAttn",
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"norm_eps": 1e-05,
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"sample_size": 64,
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"transformer_layers_per_block": 1,
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"up_block_types": [
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"CrossAttnUpBlock2D",
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"upcast_attention": false,
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}
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checkpoint-1000/unet/diffusion_pytorch_model.safetensors
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checkpoint-500/optimizer.bin
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checkpoint-500/random_states_0.pkl
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checkpoint-500/scheduler.bin
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checkpoint-500/unet/diffusion_pytorch_model.safetensors
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logs/dreambooth/1736755257.6262457/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: "/home/ubuntu/JJY/\uC5B4\uBC18\uC2A4\uD130\uB514/Custom_Diffusion/Custom_data/\uAC15\
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\uC950/regularization2/images"
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class_labels_conditioning: null
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class_prompt: painting
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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: true
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hub_model_id: null
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instance_data_dir: "/home/ubuntu/JJY/\uC5B4\uBC18\uC2A4\uD130\uB514/Custom_Diffusion/Custom_data/\uB2F4\
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\uBCF4/target"
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instance_prompt: a painting of DUM style
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learning_rate: 5.0e-10
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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: 1000
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mixed_precision: null
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num_class_images: 100
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num_train_epochs: 20
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num_validation_images: 4
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offset_noise: false
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output_dir: path_to_saved_model_DUM
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pre_compute_text_embeddings: false
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pretrained_model_name_or_path: stable-diffusion-v1-5/stable-diffusion-v1-5
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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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report_to: tensorboard
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resolution: 512
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resume_from_checkpoint: null
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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: null
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skip_save_text_encoder: false
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snr_gamma: null
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text_encoder_use_attention_mask: false
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train_batch_size: 1
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use_8bit_adam: true
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validation_prompt: null
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validation_scheduler: DPMSolverMultistepScheduler
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with_prior_preservation: true
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unet/diffusion_pytorch_model.safetensors
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