Trained for 0 epochs and 7800 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 4, 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: segmind/SSD-1B
VAE: madebyollin/sdxl-vae-fp16-fix

README.md

@@ -44,7 +44,7 @@ You may reuse the base model text encoder for inference.
 ## Training settings
 
 - Training epochs: 0
-- Training steps: 7600
+- Training steps: 7800
 - Learning rate: 1e-06
 - Effective batch size: 16
   - Micro-batch size: 4
@@ -69,7 +69,7 @@ You may reuse the base model text encoder for inference.
 ### movieposters
 - Repeats: 25
 - Total number of images: 1728
-- Total number of aspect buckets: 3
+- Total number of aspect buckets: 2
 - Resolution: 1.0 megapixels
 - Cropped: True
 - Crop style: random
@@ -213,7 +213,7 @@ You may reuse the base model text encoder for inference.
 ### bg20k-1024
 - Repeats: 0
 - Total number of images: 89285
-- 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-signs.json

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training_state.json

@@ -1 +1 @@
-{"global_step": 7600, "epoch_step": 783, "epoch": 1, "exhausted_backends": ["nijijourney", "propagandaposters", "bookcovers", "pixel-art", "sports", "moviecollection", "guys", "gay", "ethnic", "celebrities", "experimental", "normalnudes", "yoga", "architecture", "cinemamix-1mp"], "repeats": {"guys": 0, "signs": 24, "nijijourney": 0, "propagandaposters": 0, "bookcovers": 0, "pixel-art": 0, "normalnudes": 0, "celebrities": 0, "sports": 0, "movieposters": 5, "moviecollection": 0, "gay": 0, "ethnic": 0, "experimental": 0, "yoga": 0, "architecture": 0, "cinemamix-1mp": 0}}
+{"global_step": 7800, "epoch_step": 396, "epoch": 1, "exhausted_backends": ["nijijourney", "propagandaposters", "bookcovers", "pixel-art", "sports", "moviecollection", "guys", "gay", "ethnic", "celebrities", "experimental", "normalnudes", "yoga", "architecture", "cinemamix-1mp"], "repeats": {"guys": 0, "signs": 25, "nijijourney": 0, "propagandaposters": 0, "bookcovers": 0, "pixel-art": 0, "normalnudes": 0, "celebrities": 0, "sports": 0, "movieposters": 5, "moviecollection": 0, "gay": 0, "ethnic": 0, "experimental": 0, "yoga": 0, "architecture": 0, "cinemamix-1mp": 0}}

unet/config.json

@@ -1,7 +1,7 @@
 {
   "_class_name": "UNet2DConditionModel",
   "_diffusers_version": "0.29.0.dev0",
-  "_name_or_path": "/notebooks/datasets/lite-models/checkpoint-7000",
+  "_name_or_path": "/notebooks/datasets/lite-models/checkpoint-7600",
   "act_fn": "silu",
   "addition_embed_type": "text_time",
   "addition_embed_type_num_heads": 64,

unet/diffusion_pytorch_model.safetensors

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