Trained for 4 epochs and 48100 steps.
Browse filesTrained 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 8 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
- README.md +2 -2
- optimizer.bin +1 -1
- random_states_0.pkl +2 -2
- scheduler.bin +1 -1
- training_state-anatomy.json +2 -2
- training_state-bg20k-1024.json +2 -2
- training_state.json +2 -2
- unet/config.json +1 -1
- unet/diffusion_pytorch_model.safetensors +1 -1
README.md
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## Training settings
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- Training epochs:
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- Training steps:
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- Learning rate: 4e-07
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- Effective batch size: 32
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- Micro-batch size: 4
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## Training settings
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- Training epochs: 4
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- Training steps: 48100
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- Learning rate: 4e-07
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- Effective batch size: 32
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- Micro-batch size: 4
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optimizer.bin
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random_states_0.pkl
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