RAVIKUMAR/ddpm-butterflies-128

---
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/HuggingFace7/ddpm-butterflies-128/tensorboard?#scalars)

license: mit
---

原始信息汇总

ddpm-butterflies-128

模型描述

该扩散模型使用🤗 Diffusers库在huggan/smithsonian_butterflies_subset数据集上进行训练。

使用目的与限制

如何使用

python

TODO: 添加一个运行扩散管道的示例代码片段

限制与偏差

[TODO: 提供潜在问题和潜在修复措施的示例]

训练数据

[TODO: 描述用于训练模型的数据]

训练超参数

以下超参数在训练过程中被使用：

• 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
• mixed_precision: fp16

训练结果

📈 TensorBoard logs