diffuse-custom / diffusers /utils /model_card_template.md
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Duplicate from YeOldHermit/Super-Resolution-Anime-Diffusion
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metadata
'[object Object]': null

{{ model_name | default("Diffusion Model") }}

Model description

This diffusion model is trained with the 🤗 Diffusers library on the {{ dataset_name }} 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: {{ learning_rate }}
  • train_batch_size: {{ train_batch_size }}
  • eval_batch_size: {{ eval_batch_size }}
  • gradient_accumulation_steps: {{ gradient_accumulation_steps }}
  • optimizer: AdamW with betas=({{ adam_beta1 }}, {{ adam_beta2 }}), weight_decay={{ adam_weight_decay }} and epsilon={{ adam_epsilon }}
  • lr_scheduler: {{ lr_scheduler }}
  • lr_warmup_steps: {{ lr_warmup_steps }}
  • ema_inv_gamma: {{ ema_inv_gamma }}
  • ema_inv_gamma: {{ ema_power }}
  • ema_inv_gamma: {{ ema_max_decay }}
  • mixed_precision: {{ mixed_precision }}

Training results

📈 [TensorBoard logs](https://huggingface.co/{{ repo_name }}/tensorboard?#scalars)