End of training

README.md

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+---
+base_model: stabilityai/stable-diffusion-xl-base-1.0
+library_name: diffusers
+license: creativeml-openrail-m
+tags:
+- stable-diffusion-xl
+- stable-diffusion-xl-diffusers
+- text-to-image
+- diffusers-training
+- diffusers
+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. -->
+
+
+# Text-to-image finetuning - haorandai/Gaussian_Noise_Vehicle_Bicycle_Epsilon0.1_20Samples_With20Constraints
+
+This pipeline was finetuned from **stabilityai/stable-diffusion-xl-base-1.0** on the **haorandai/Gaussian_Noise_Vehicle_Bicycle_Epsilon0.1_20Samples_With20Constraints** dataset. Below are some example images generated with the finetuned pipeline using the following prompt: None: 
+
+
+
+Special VAE used for training: None.
+
+
+## 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/text2image-fine-tune-sdxl/1728291725.1382008/events.out.tfevents.1728291725.datasec2.engr.uconn.edu.2203327.1

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+caption_column: text
+center_crop: true
+checkpointing_steps: 500
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+dataset_name: haorandai/Gaussian_Noise_Vehicle_Bicycle_Epsilon0.1_20Samples_With20Constraints
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+enable_xformers_memory_efficient_attention: false
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+gradient_checkpointing: true
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+image_column: image
+learning_rate: 1.0e-05
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+logging_dir: logs
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+max_train_samples: null
+max_train_steps: 200
+mixed_precision: fp16
+noise_offset: 0
+num_train_epochs: 40
+num_validation_images: 4
+output_dir: /scr/home/biw23007/haoran/different_uf_finetune_xl_model_dir_1e-05_200_withconstraint/haorandai/Gaussian_Noise_Vehicle_Bicycle_Epsilon0.1_20Samples_With20Constraints/
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+random_flip: true
+report_to: tensorboard
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+timestep_bias_end: 1000
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+validation_epochs: 1
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+  ]
+}

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