ddpm-pcam-96-first-100

Model description

This diffusion model is trained with the 🤗 Diffusers library on the pcam-96 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: 0.0001
• train_batch_size: 32
• eval_batch_size: 32
• 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