End of training

README.md

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+---
+base_model: runwayml/stable-diffusion-v1-5
+library_name: diffusers
+license: creativeml-openrail-m
+tags:
+- stable-diffusion
+- stable-diffusion-diffusers
+- text-to-image
+- diffusers
+- textual_inversion
+- diffusers-training
+inference: true
+---
+
+<!-- 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. -->
+
+
+# Textual inversion text2image fine-tuning - abhipsabasu/textual_inversion_person_blm
+These are textual inversion adaption weights for runwayml/stable-diffusion-v1-5. You can find some example images in the following. 
+
+
+
+
+## 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]

feature_extractor/preprocessor_config.json

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+  "crop_size": {
+    "height": 224,
+    "width": 224
+  },
+  "do_center_crop": true,
+  "do_convert_rgb": true,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.48145466,
+    0.4578275,
+    0.40821073
+  ],
+  "image_processor_type": "CLIPImageProcessor",
+  "image_std": [
+    0.26862954,
+    0.26130258,
+    0.27577711
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}

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logs/textual_inversion/1727337305.1508489/events.out.tfevents.1727337305.test.2575733.1

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logs/textual_inversion/1727337305.1525607/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
+dataloader_num_workers: 0
+enable_xformers_memory_efficient_attention: false
+gradient_accumulation_steps: 4
+gradient_checkpointing: false
+hub_model_id: null
+hub_token: null
+initializer_token: person
+learnable_property: object
+learning_rate: 0.02
+local_rank: -1
+logging_dir: logs
+lr_num_cycles: 1
+lr_scheduler: constant
+lr_warmup_steps: 0
+max_train_steps: 3000
+mixed_precision: 'no'
+no_safe_serialization: false
+num_train_epochs: 2
+num_validation_images: 4
+num_vectors: 5
+output_dir: textual_inversion_person_blm
+placeholder_token: <blm0>
+pretrained_model_name_or_path: runwayml/stable-diffusion-v1-5
+push_to_hub: true
+repeats: 100
+report_to: tensorboard
+resolution: 512
+resume_from_checkpoint: null
+revision: null
+save_as_full_pipeline: false
+save_steps: 500
+scale_lr: true
+seed: null
+tokenizer_name: null
+train_batch_size: 1
+train_data_dir: /data2/abhipsa/blackbox_bias_mitigation/datasets/celeba
+validation_epochs: null
+validation_prompt: null
+validation_steps: 100
+variant: null

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model_index.json

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+  "_class_name": "StableDiffusionPipeline",
+  "_diffusers_version": "0.31.0.dev0",
+  "_name_or_path": "runwayml/stable-diffusion-v1-5",
+  "feature_extractor": [
+    "transformers",
+    "CLIPImageProcessor"
+  ],
+  "image_encoder": [
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+    null
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+  "requires_safety_checker": true,
+  "safety_checker": [
+    "stable_diffusion",
+    "StableDiffusionSafetyChecker"
+  ],
+  "scheduler": [
+    "diffusers",
+    "PNDMScheduler"
+  ],
+  "text_encoder": [
+    "transformers",
+    "CLIPTextModel"
+  ],
+  "tokenizer": [
+    "transformers",
+    "CLIPTokenizer"
+  ],
+  "unet": [
+    "diffusers",
+    "UNet2DConditionModel"
+  ],
+  "vae": [
+    "diffusers",
+    "AutoencoderKL"
+  ]
+}

safety_checker/config.json

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+    "intermediate_size": 4096,
+    "model_type": "clip_vision_model",
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+    "patch_size": 14
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scheduler/scheduler_config.json

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+  "beta_end": 0.012,
+  "beta_schedule": "scaled_linear",
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+  "timestep_spacing": "leading",
+  "trained_betas": null
+}

text_encoder/config.json

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+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 77,
+  "model_type": "clip_text_model",
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+  "num_hidden_layers": 12,
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+  "projection_dim": 768,
+  "torch_dtype": "float32",
+  "transformers_version": "4.43.3",
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tokenizer/added_tokens.json

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tokenizer/special_tokens_map.json

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tokenizer/tokenizer_config.json

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