Trained for 0 epochs and 6000 steps.

Trained with datasets ['text-embeds-pixart-filter', 'photo-concept-bucket', 'ideogram', '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 'trailing' timestep spacing.
Base model: terminusresearch/pixart-900m-1024-ft-v0.6
VAE: madebyollin/sdxl-vae-fp16-fix

.gitattributes

@@ -324,3 +324,4 @@ assets/image_97_1.png filter=lfs diff=lfs merge=lfs -text
 assets/image_98_2.png filter=lfs diff=lfs merge=lfs -text
 assets/image_99_0.png filter=lfs diff=lfs merge=lfs -text
 assets/image_9_0.png filter=lfs diff=lfs merge=lfs -text
+training_state-dalle3.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -1562,7 +1562,7 @@ You may reuse the base model text encoder for inference.
 ## Training settings
 
 - Training epochs: 0
-- Training steps: 5000
+- Training steps: 6000
 - Learning rate: 1e-06
 - Effective batch size: 192
  - Micro-batch size: 24

optimizer.bin

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scheduler.bin

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training_state.json

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transformer/diffusion_pytorch_model.safetensors

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