End of training

.gitattributes

@@ -38,3 +38,6 @@ attn_maps_all/output_globalStep_100_step_0.png filter=lfs diff=lfs merge=lfs -te
 attn_maps_all/output_globalStep_150_step_0.png filter=lfs diff=lfs merge=lfs -text
 attn_maps_all/output_globalStep_200_step_0.png filter=lfs diff=lfs merge=lfs -text
 attn_maps_all/output_globalStep_50_step_0.png filter=lfs diff=lfs merge=lfs -text
+attn_maps_all/output_globalStep_250_step_0.png filter=lfs diff=lfs merge=lfs -text
+attn_maps_all/output_globalStep_300_step_0.png filter=lfs diff=lfs merge=lfs -text
+attn_maps_all/output_globalStep_350_step_0.png filter=lfs diff=lfs merge=lfs -text

README.md

@@ -2,21 +2,21 @@
 ---
 license: creativeml-openrail-m
 base_model: CompVis/stable-diffusion-v1-4
-instance_prompt: photo of a <new1> dog
+instance_prompt: a photo of sks dog
 tags:
 - stable-diffusion
 - stable-diffusion-diffusers
 - text-to-image
 - diffusers
-- custom-diffusion
+- dreambooth
 inference: true
 ---
     
-# Custom Diffusion - SidXXD/test4crossattentionmap-ll
+# DreamBooth - SidXXD/test4crossattentionmap-ll
 
-These are Custom Diffusion adaption weights for CompVis/stable-diffusion-v1-4. The weights were trained on photo of a <new1> dog using [Custom Diffusion](https://www.cs.cmu.edu/~custom-diffusion). You can find some example images in the following. 
+This is a dreambooth model derived from CompVis/stable-diffusion-v1-4. The weights were trained on a photo of sks dog using [DreamBooth](https://dreambooth.github.io/).
+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).
+DreamBooth for the text encoder was enabled: False.

feature_extractor/preprocessor_config.json

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+    "width": 224
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+    0.4578275,
+    0.40821073
+  ],
+  "image_processor_type": "CLIPImageProcessor",
+  "image_std": [
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+    0.26130258,
+    0.27577711
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}

logs/dreambooth/1712129834.1765924/events.out.tfevents.1712129834.cudahpc06.1259145.1

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logs/dreambooth/1712129834.1786177/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
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+class_labels_conditioning: null
+class_prompt: null
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+enable_xformers_memory_efficient_attention: false
+gradient_accumulation_steps: 1
+gradient_checkpointing: false
+hub_model_id: null
+hub_token: null
+instance_data_dir: /home/xide/miniconda3/code/Attack/mist2-wk/data/single/attacked-target/4-parts-ll/pgd_eps_8
+instance_prompt: a photo of sks dog
+learning_rate: 5.0e-06
+local_rank: -1
+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: 400
+mixed_precision: null
+num_class_images: 100
+num_train_epochs: 400
+num_validation_images: 4
+offset_noise: false
+output_dir: model/test4crossattentionmap-ll/
+pre_compute_text_embeddings: false
+pretrained_model_name_or_path: CompVis/stable-diffusion-v1-4
+prior_generation_precision: null
+prior_loss_weight: 1.0
+push_to_hub: true
+report_to: tensorboard
+resolution: 512
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+scale_lr: false
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+text_encoder_use_attention_mask: false
+tokenizer_max_length: null
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+train_batch_size: 1
+train_text_encoder: false
+use_8bit_adam: false
+validation_prompt: null
+validation_scheduler: DPMSolverMultistepScheduler
+validation_steps: 100
+variant: null
+with_prior_preservation: false

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model_index.json

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+  "_class_name": "StableDiffusionPipeline",
+  "_diffusers_version": "0.24.0.dev0",
+  "_name_or_path": "CompVis/stable-diffusion-v1-4",
+  "feature_extractor": [
+    "transformers",
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+  ],
+  "image_encoder": [
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+  "requires_safety_checker": true,
+  "safety_checker": [
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+    "StableDiffusionSafetyChecker"
+  ],
+  "scheduler": [
+    "diffusers",
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+  ],
+  "text_encoder": [
+    "transformers",
+    "CLIPTextModel"
+  ],
+  "tokenizer": [
+    "transformers",
+    "CLIPTokenizer"
+  ],
+  "unet": [
+    "diffusers",
+    "UNet2DConditionModel"
+  ],
+  "vae": [
+    "diffusers",
+    "AutoencoderKL"
+  ]
+}

safety_checker/config.json

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scheduler/scheduler_config.json

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+}

text_encoder/config.json

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tokenizer/special_tokens_map.json

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tokenizer/tokenizer_config.json

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unet/config.json

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vae/config.json

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