readme: ---
  language: en
  license: apache-2.0
  library_name: diffusers
  tags: []
  datasets: huggan/smithsonian_butterflies_subset
  metrics: []
  ---
  
  <!-- 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. -->
  
  # ddpm-butterflies-128
  
  ## Model description
  
  This diffusion model is trained with the [🤗 Diffusers](https://github.com/huggingface/diffusers) library 
  on the `huggan/smithsonian_butterflies_subset` dataset.
  
  ## 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 data
  
  [TODO: describe the data used to train the model]
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 0.0001
  - train_batch_size: 16
  - eval_batch_size: 16
  - gradient_accumulation_steps: 1
  - optimizer: AdamW with betas=(None, None), weight_decay=None and epsilon=None
  - lr_scheduler: None
  - lr_warmup_steps: 500
  - ema_inv_gamma: None
  - ema_inv_gamma: None
  - ema_inv_gamma: None
  - mixed_precision: fp16
  
  ### Training results
  
  📈 [TensorBoard logs](https://huggingface.co/xtlu/ddpm-butterflies-128/tensorboard?#scalars)
  
  