End of training

.gitattributes

@@ -33,3 +33,7 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+image_0.png filter=lfs diff=lfs merge=lfs -text
+image_1.png filter=lfs diff=lfs merge=lfs -text
+image_2.png filter=lfs diff=lfs merge=lfs -text
+image_3.png filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,74 @@
+---
+base_model: lora1
+library_name: diffusers
+license: openrail++
+tags:
+- text-to-image
+- text-to-image
+- diffusers-training
+- diffusers
+- lora
+- template:sd-lora
+- stable-diffusion-xl
+- stable-diffusion-xl-diffusers
+instance_prompt: a photo of a sher teapot
+widget:
+- text: A photo of a sher teapot in a road
+  output:
+    url: image_0.png
+- text: A photo of a sher teapot in a road
+  output:
+    url: image_1.png
+- text: A photo of a sher teapot in a road
+  output:
+    url: image_2.png
+- text: A photo of a sher teapot in a road
+  output:
+    url: image_3.png
+---
+
+<!-- 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. -->
+
+
+# SDXL LoRA DreamBooth - William2357/outputmerge1
+
+<Gallery />
+
+## Model description
+
+These are William2357/outputmerge1 LoRA adaption weights for lora1.
+
+The weights were trained  using [DreamBooth](https://dreambooth.github.io/).
+
+LoRA for the text encoder was enabled: False.
+
+Special VAE used for training: madebyollin/sdxl-vae-fp16-fix.
+
+## Trigger words
+
+You should use a photo of a sher teapot to trigger the image generation.
+
+## Download model
+
+Weights for this model are available in Safetensors format.
+
+[Download](William2357/outputmerge1/tree/main) them in the Files & versions tab.
+
+
+
+## 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]

logs/dreambooth-lora-sd-xl/1721408348.418794/events.out.tfevents.1721408348.d31c945baa18.113.1

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logs/dreambooth-lora-sd-xl/1721408348.422995/hparams.yml

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+adam_beta1: 0.9
+adam_beta2: 0.999
+adam_epsilon: 1.0e-08
+adam_weight_decay: 0.0001
+adam_weight_decay_text_encoder: 0.001
+allow_tf32: false
+cache_dir: null
+caption_column: null
+center_crop: false
+checkpointing_steps: 1000000
+checkpoints_total_limit: null
+class_data_dir: null
+class_prompt: null
+dataloader_num_workers: 0
+dataset_config_name: null
+dataset_name: null
+do_edm_style_training: false
+enable_xformers_memory_efficient_attention: false
+gradient_accumulation_steps: 4
+gradient_checkpointing: false
+hub_model_id: null
+hub_token: null
+image_column: image
+instance_data_dir: dreambooth/dataset/teapot
+instance_prompt: a photo of a sher teapot
+learning_rate: 0.0001
+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: 500
+mixed_precision: fp16
+num_class_images: 100
+num_train_epochs: 250
+num_validation_images: 4
+optimizer: AdamW
+output_dir: outputmerge1
+output_kohya_format: false
+pretrained_model_name_or_path: lora1
+pretrained_vae_model_name_or_path: madebyollin/sdxl-vae-fp16-fix
+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
+rank: 4
+repeats: 1
+report_to: tensorboard
+resolution: 1024
+resume_from_checkpoint: null
+revision: null
+sample_batch_size: 4
+scale_lr: false
+seed: 0
+snr_gamma: null
+text_encoder_lr: 5.0e-06
+train_batch_size: 1
+train_text_encoder: false
+use_8bit_adam: false
+use_dora: false
+validation_epochs: 25
+validation_prompt: A photo of a sher teapot in a road
+variant: null
+with_prior_preservation: false

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