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--- |
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{{ card_data }} |
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--- |
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<!-- This model card has been generated automatically according to the information the training script had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# {{ model_name | default("Diffusion Model") }} |
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## Model description |
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This diffusion model is trained with the [🤗 Diffusers](https://github.com/huggingface/diffusers) library |
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on the `{{ dataset_name }}` dataset. |
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## Intended uses & limitations |
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#### How to use |
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```python |
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# TODO: add an example code snippet for running this diffusion pipeline |
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``` |
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#### Limitations and bias |
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[TODO: provide examples of latent issues and potential remediations] |
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## Training data |
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[TODO: describe the data used to train the model] |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: {{ learning_rate }} |
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- train_batch_size: {{ train_batch_size }} |
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- eval_batch_size: {{ eval_batch_size }} |
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- gradient_accumulation_steps: {{ gradient_accumulation_steps }} |
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- optimizer: AdamW with betas=({{ adam_beta1 }}, {{ adam_beta2 }}), weight_decay={{ adam_weight_decay }} and epsilon={{ adam_epsilon }} |
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- lr_scheduler: {{ lr_scheduler }} |
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- lr_warmup_steps: {{ lr_warmup_steps }} |
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- ema_inv_gamma: {{ ema_inv_gamma }} |
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- ema_inv_gamma: {{ ema_power }} |
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- ema_inv_gamma: {{ ema_max_decay }} |
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- mixed_precision: {{ mixed_precision }} |
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### Training results |
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📈 [TensorBoard logs](https://huggingface.co/{{ repo_name }}/tensorboard?#scalars) |
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