Trained for 3 epochs and 47400 steps.

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 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

@@ -43,8 +43,8 @@ You may reuse the base model text encoder for inference.
 
 ## Training settings
 
-- Training epochs: 2
-- Training steps: 47300
+- Training epochs: 3
+- Training steps: 47400
 - Learning rate: 4e-07
 - Effective batch size: 32
   - Micro-batch size: 4
@@ -212,7 +212,7 @@ You may reuse the base model text encoder for inference.
 - Crop aspect: random
 ### bg20k-1024
 - Repeats: 0
-- Total number of images: 89287
+- Total number of images: 89248
 - Total number of aspect buckets: 3
 - Resolution: 1.0 megapixels
 - Cropped: True

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