| --- |
| language: en |
| license: apache-2.0 |
| library_name: diffusers |
| tags: [] |
| datasets: CelebA |
| 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. --> |
|
|
| # diffusion_conditional |
| |
| ## Model description |
| |
| This diffusion model is trained with the [🤗 Diffusers](https://github.com/huggingface/diffusers) library |
| on the `CelebA` 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: 1 |
| - gradient_accumulation_steps: 1 |
| - optimizer: AdamW with betas=(0.95, 0.999), weight_decay=1e-06 and epsilon=1e-08 |
| - lr_scheduler: cosine |
| - lr_warmup_steps: 500 |
| - ema_inv_gamma: 1.0 |
| - ema_inv_gamma: 0.75 |
| - ema_inv_gamma: 0.9999 |
| - mixed_precision: fp16 |
| |
| ### Training results |
| |
| 📈 [TensorBoard logs](https://huggingface.co/shalpin87/diffusion_conditional/tensorboard?#scalars) |
| |
| |
