diffusion_cifar

Model description

This diffusion model is trained with the 🤗 Diffusers library on the CIFAR10 dataset.

Intended uses & limitations

How to use

# 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: 1e-12
• train_batch_size: 256
• eval_batch_size: 16
• 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