PseudoTerminal X commited on
Commit
089732e
1 Parent(s): 19d8bcd

Trained for 1 epochs and 32000 steps.

Browse files

Trained with datasets ['text-embeds-pixart-filter', 'photo-concept-bucket', 'moviecollection', 'experimental', 'ethnic', 'sports', 'architecture', 'shutterstock', 'cinemamix-1mp', 'nsfw-1024', 'anatomy', 'bg20k-1024', 'yoga', 'photo-aesthetics', 'text-1mp', 'movieposters', 'normalnudes', 'pixel-art', 'signs', 'midjourney-v6-520k-raw', 'sfwbooru', 'nijijourney-v6-520k-raw', 'dalle3']
Learning rate 1e-06, batch size 24, and 1 gradient accumulation steps.
Used DDPM noise scheduler for training with epsilon prediction type and rescaled_betas_zero_snr=False
Using 'linspace' timestep spacing.
Base model: ptx0/pixart-900m-1024-ft-large
VAE: madebyollin/sdxl-vae-fp16-fix

README.md CHANGED
@@ -62,7 +62,7 @@ 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: 31500
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  - Learning rate: 1e-06
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  - Effective batch size: 192
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  - Micro-batch size: 24
@@ -152,7 +152,7 @@ You may reuse the base model text encoder for inference.
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  ### anatomy
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  - Repeats: 5
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  - Total number of images: ~15168
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- - Total number of aspect buckets: 2
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  - Resolution: 1.0 megapixels
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  - Cropped: True
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  - Crop style: random
@@ -160,7 +160,7 @@ You may reuse the base model text encoder for inference.
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  ### bg20k-1024
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  - Repeats: 0
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  - Total number of images: ~89088
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- - Total number of aspect buckets: 1
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  - Resolution: 1.0 megapixels
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  - Cropped: True
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  - Crop style: random
 
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  ## Training settings
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  - Training epochs: 1
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+ - Training steps: 32000
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  - Learning rate: 1e-06
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  - Effective batch size: 192
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  - Micro-batch size: 24
 
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  ### anatomy
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  - Repeats: 5
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  - Total number of images: ~15168
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+ - Total number of aspect buckets: 3
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  - Resolution: 1.0 megapixels
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  - Cropped: True
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  - Crop style: random
 
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  ### bg20k-1024
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  - Repeats: 0
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  - Total number of images: ~89088
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+ - Total number of aspect buckets: 3
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  - Resolution: 1.0 megapixels
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  - Cropped: True
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  - Crop style: random
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