| --- |
| language: en |
| license: apache-2.0 |
| library_name: diffusers |
| tags: |
| - stable-diffusion |
| - stable-diffusion-diffusers |
| - text-to-image |
| datasets: YaYaB/onepiece-blip-captions |
| 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. --> |
|
|
| # sd-onepiece-diffusers4 |
|
|
| ## Model description |
|
|
| This diffusion model is trained with the [🤗 Diffusers](https://github.com/huggingface/diffusers) library |
| on the `YaYaB/onepiece-blip-captions` 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: 1 |
| - eval_batch_size: 1 |
| - gradient_accumulation_steps: 4 |
| - optimizer: AdamW with betas=(0.9, 0.999), weight_decay=0.01 and epsilon=1e-08 |
| - lr_scheduler: constant |
| - 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/YaYaB/sd-onepiece-diffusers4/tensorboard?#scalars) |
|
|
|
|
