End of training

README.md

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+---
+base_model: stabilityai/stable-diffusion-3-medium-diffusers
+library_name: diffusers
+license: openrail++
+tags:
+- text-to-image
+- diffusers-training
+- diffusers
+- sd3
+- sd3-diffusers
+- template:sd-lora
+instance_prompt: a photo of sks bowl
+widget: []
+---
+
+<!-- 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. -->
+
+
+# SD3 DreamBooth - ozgung/red-bowl-5-SD3
+
+<Gallery />
+
+## Model description
+
+These are ozgung/red-bowl-5-SD3 DreamBooth weights for stabilityai/stable-diffusion-3-medium-diffusers.
+
+The weights were trained  using [DreamBooth](https://dreambooth.github.io/).
+
+Text encoder was fine-tuned: False.
+
+## Trigger words
+
+You should use a photo of sks bowl to trigger the image generation.
+
+## Download model
+
+[Download](ozgung/red-bowl-5-SD3/tree/main) them in the Files & versions tab.
+
+## License
+
+Please adhere to the licensing terms as described `[here](https://huggingface.co/stabilityai/stable-diffusion-3-medium/blob/main/LICENSE)`.
+
+
+## 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]

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checkpoint-500/transformer/config.json

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+  "_class_name": "SD3Transformer2DModel",
+  "_diffusers_version": "0.30.0.dev0",
+  "_name_or_path": "stabilityai/stable-diffusion-3-medium-diffusers",
+  "attention_head_dim": 64,
+  "caption_projection_dim": 1536,
+  "in_channels": 16,
+  "joint_attention_dim": 4096,
+  "num_attention_heads": 24,
+  "num_layers": 24,
+  "out_channels": 16,
+  "patch_size": 2,
+  "pooled_projection_dim": 2048,
+  "pos_embed_max_size": 192,
+  "sample_size": 128
+}

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+adam_beta2: 0.999
+adam_epsilon: 1.0e-08
+adam_weight_decay: 0.0001
+adam_weight_decay_text_encoder: 0.001
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+dataset_name: null
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+gradient_checkpointing: true
+hub_model_id: null
+hub_token: null
+image_column: image
+instance_data_dir: ./IN/ozgung/red-bowl-5-SD3
+instance_prompt: a photo of sks bowl
+learning_rate: 5.0e-06
+local_rank: -1
+logging_dir: logs
+logit_mean: 0.0
+logit_std: 1.0
+lr_num_cycles: 1
+lr_power: 1.0
+lr_scheduler: constant
+lr_warmup_steps: 0
+max_grad_norm: 1.0
+max_sequence_length: 77
+max_train_steps: 800
+mixed_precision: fp16
+mode_scale: 1.29
+num_class_images: 100
+num_train_epochs: 160
+num_validation_images: 4
+optimizer: AdamW
+output_dir: ./OUT/ozgung/red-bowl-5-SD3
+pretrained_model_name_or_path: stabilityai/stable-diffusion-3-medium-diffusers
+prior_generation_precision: null
+prior_loss_weight: 1.0
+prodigy_beta3: null
+prodigy_decouple: true
+prodigy_safeguard_warmup: true
+prodigy_use_bias_correction: true
+push_to_hub: true
+random_flip: false
+repeats: 1
+report_to: tensorboard
+resolution: 512
+resume_from_checkpoint: null
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+sample_batch_size: 4
+scale_lr: false
+seed: 0
+text_encoder_lr: 5.0e-06
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+use_8bit_adam: true
+validation_epochs: 50
+validation_prompt: null
+variant: null
+weighting_scheme: logit_normal
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+  "_diffusers_version": "0.30.0.dev0",
+  "_name_or_path": "stabilityai/stable-diffusion-3-medium-diffusers",
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+    "AutoencoderKL"
+  ]
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+  "num_train_timesteps": 1000,
+  "shift": 3.0
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tokenizer/special_tokens_map.json

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tokenizer/tokenizer_config.json

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tokenizer_2/special_tokens_map.json

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tokenizer_2/tokenizer_config.json

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+}

tokenizer_3/special_tokens_map.json

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tokenizer_3/spiece.model

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