Trained for 0 epochs and 5500 steps.

Trained with datasets ['text-embeds-sdxl', 'photocb-clip-embeds', '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', 'photo-aesthetics', 'text-1mp', 'photo-concept-bucket']
Learning rate 1e-06, batch size 8, and 4 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: ptx0/terminus-xl-velocity-v1
VAE: madebyollin/sdxl-vae-fp16-fix

README.md

@@ -44,8 +44,8 @@ You may reuse the base model text encoder for inference.
 ## Training settings
 
 - Training epochs: 0
-- Training steps: 5200
-- Learning rate: 4e-07
+- Training steps: 5500
+- Learning rate: 1e-06
 - Effective batch size: 32
   - Micro-batch size: 8
   - Gradient accumulation steps: 4
@@ -188,7 +188,7 @@ You may reuse the base model text encoder for inference.
 - Crop aspect: random
 ### cinemamix-1mp
 - Repeats: 0
-- Total number of images: 9009
+- Total number of images: 8992
 - Total number of aspect buckets: 3
 - Resolution: 1.0 megapixels
 - Cropped: True
@@ -213,7 +213,7 @@ You may reuse the base model text encoder for inference.
 ### bg20k-1024
 - Repeats: 0
 - Total number of images: 89250
-- Total number of aspect buckets: 3
+- Total number of aspect buckets: 2
 - Resolution: 1.0 megapixels
 - Cropped: True
 - Crop style: random

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training_state.json

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unet/config.json

@@ -1,7 +1,7 @@
 {
   "_class_name": "UNet2DConditionModel",
   "_diffusers_version": "0.27.2",
-  "_name_or_path": "/notebooks/datasets/models/checkpoint-5000",
+  "_name_or_path": "/notebooks/datasets/models/checkpoint-5400",
   "act_fn": "silu",
   "addition_embed_type": "text_time",
   "addition_embed_type_num_heads": 64,

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