language: en | |
license: apache-2.0 | |
library_name: diffusers | |
tags: [] | |
datasets: imagefolder | |
metrics: [] | |
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# ddpm-hkdb-fld-256-200ep | |
## Model description | |
This diffusion model is trained with the [π€ Diffusers](https://github.com/huggingface/diffusers) library | |
on the `imagefolder` 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 | |
π [TensorBoard logs](https://huggingface.co/geevegeorge/ddpm-hkdb-fld-256-200ep/tensorboard?#scalars) | |