End of training

README.md

@@ -2,7 +2,7 @@
 ---
 license: creativeml-openrail-m
 base_model: stabilityai/stable-diffusion-2-1
-instance_prompt: A traffic cone falling on its side on the road
+instance_prompt: A ksk traffic cone falling on its side on the road
 tags:
 - stable-diffusion
 - stable-diffusion-diffusers
@@ -14,7 +14,7 @@ inference: true
     
 # DreamBooth - Redamancy2299/dreambooth2
 
-This is a dreambooth model derived from stabilityai/stable-diffusion-2-1. The weights were trained on A traffic cone falling on its side on the road using [DreamBooth](https://dreambooth.github.io/).
+This is a dreambooth model derived from stabilityai/stable-diffusion-2-1. The weights were trained on A ksk traffic cone falling on its side on the road using [DreamBooth](https://dreambooth.github.io/).
 You can find some example images in the following. 
 
 

checkpoint-1000/optimizer.bin

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logs/dreambooth/1688629776.7927942/events.out.tfevents.1688629776.szth-acg-bcc04f1143.szth.baidu.com.30670.1

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logs/dreambooth/1688629776.7946873/hparams.yml

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+adam_beta1: 0.9
+adam_beta2: 0.999
+adam_epsilon: 1.0e-08
+adam_weight_decay: 0.01
+allow_tf32: false
+center_crop: false
+checkpointing_steps: 500
+checkpoints_total_limit: null
+class_data_dir: null
+class_labels_conditioning: null
+class_prompt: null
+dataloader_num_workers: 0
+enable_xformers_memory_efficient_attention: false
+gradient_accumulation_steps: 1
+gradient_checkpointing: false
+hub_model_id: null
+hub_token: null
+instance_data_dir: ./zhuitong
+instance_prompt: A traffic cone falling on its side on the road
+learning_rate: 8.0e-05
+local_rank: 0
+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: 1200
+mixed_precision: null
+num_class_images: 100
+num_train_epochs: 200
+num_validation_images: 4
+offset_noise: false
+output_dir: sd_output/dreambooth2
+pre_compute_text_embeddings: false
+pretrained_model_name_or_path: stabilityai/stable-diffusion-2-1
+prior_generation_precision: null
+prior_loss_weight: 1.0
+push_to_hub: true
+report_to: tensorboard
+resolution: 512
+resume_from_checkpoint: null
+revision: null
+sample_batch_size: 4
+scale_lr: false
+seed: null
+set_grads_to_none: false
+skip_save_text_encoder: false
+text_encoder_use_attention_mask: false
+tokenizer_max_length: null
+tokenizer_name: null
+train_batch_size: 1
+train_text_encoder: false
+use_8bit_adam: false
+validation_images: null
+validation_prompt: null
+validation_steps: 100
+with_prior_preservation: false

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logs/dreambooth/1688630085.3985026/hparams.yml

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+adam_beta1: 0.9
+adam_beta2: 0.999
+adam_epsilon: 1.0e-08
+adam_weight_decay: 0.01
+allow_tf32: false
+center_crop: false
+checkpointing_steps: 500
+checkpoints_total_limit: null
+class_data_dir: null
+class_labels_conditioning: null
+class_prompt: null
+dataloader_num_workers: 0
+enable_xformers_memory_efficient_attention: false
+gradient_accumulation_steps: 1
+gradient_checkpointing: false
+hub_model_id: null
+hub_token: null
+instance_data_dir: ./zhuitong
+instance_prompt: A ksk traffic cone falling on its side on the road
+learning_rate: 8.0e-05
+local_rank: 0
+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: 1200
+mixed_precision: null
+num_class_images: 100
+num_train_epochs: 200
+num_validation_images: 4
+offset_noise: false
+output_dir: sd_output/dreambooth2
+pre_compute_text_embeddings: false
+pretrained_model_name_or_path: stabilityai/stable-diffusion-2-1
+prior_generation_precision: null
+prior_loss_weight: 1.0
+push_to_hub: true
+report_to: tensorboard
+resolution: 512
+resume_from_checkpoint: null
+revision: null
+sample_batch_size: 4
+scale_lr: false
+seed: null
+set_grads_to_none: false
+skip_save_text_encoder: false
+text_encoder_use_attention_mask: false
+tokenizer_max_length: null
+tokenizer_name: null
+train_batch_size: 1
+train_text_encoder: false
+use_8bit_adam: false
+validation_images: null
+validation_prompt: null
+validation_steps: 100
+with_prior_preservation: false

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tokenizer/tokenizer_config.json

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   },
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   "pad_token": "<|endoftext|>",
   "special_tokens_map_file": "./special_tokens_map.json",
   "tokenizer_class": "CLIPTokenizer",

vae/config.json

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 {
   "_class_name": "AutoencoderKL",
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   "act_fn": "silu",
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