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PseudoTerminal X commited on
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Trained for 1 epochs and 27500 steps.

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Trained with datasets ['text-embeds-sd2x', 'celebrities', 'movieposters', 'normalnudes', 'propagandaposters', 'guys', 'pixel-art', 'signs', 'moviecollection', 'bookcovers', 'nijijourney', 'experimental', 'ethnic', 'sports', 'gay', 'architecture', 'shutterstock', 'cinemamix-1mp', 'nsfw-1024', 'anatomy', 'bg20k-1024', 'yoga']
Learning rate 4e-07, batch size 4, and 1 gradient accumulation steps.
Used DDPM noise scheduler for training with v_prediction prediction type and rescaled_betas_zero_snr=True
Using 'trailing' timestep spacing.
Base model: stabilityai/stable-diffusion-2-1
VAE: None

Files changed (18) hide show
  1. README.md +1 -1
  2. optimizer.bin +1 -1
  3. random_states_0.pkl +2 -2
  4. training_state-anatomy.json +2 -2
  5. training_state-bg20k-1024.json +2 -2
  6. training_state-bookcovers.json +1 -1
  7. training_state-celebrities.json +1 -1
  8. training_state-guys.json +1 -1
  9. training_state-moviecollection.json +1 -1
  10. training_state-movieposters.json +2 -2
  11. training_state-nijijourney.json +1 -1
  12. training_state-nsfw-1024.json +2 -2
  13. training_state-propagandaposters.json +1 -1
  14. training_state-shutterstock.json +2 -2
  15. training_state-signs.json +1 -1
  16. training_state.json +1 -1
  17. unet/config.json +1 -1
  18. unet/diffusion_pytorch_model.safetensors +1 -1
README.md CHANGED
@@ -44,7 +44,7 @@ You may reuse the base model text encoder for inference.
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  ## Training settings
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  - Training epochs: 1
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- - Training steps: 24750
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  - Learning rate: 4e-07
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  - Effective batch size: 4
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  - Micro-batch size: 4
 
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  ## Training settings
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  - Training epochs: 1
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+ - Training steps: 27500
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  - Learning rate: 4e-07
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  - Effective batch size: 4
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  - Micro-batch size: 4
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