Trained for 0 epochs and 200 steps.

Trained with datasets ['text-embeds-sdxl', 'photocb-clip-embeds', 'celebrities', 'movieposters', 'pixel-art', 'moviecollection', 'ethnic', 'shutterstock', 'cinemamix-1mp', 'nsfw-1024', 'anatomy', 'bg20k-1024', 'yoga', 'photo-aesthetics', 'text-1mp', 'photo-concept-bucket']
Learning rate 4e-07, 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: ptx0/terminus-xl-velocity-v2
VAE: madebyollin/sdxl-vae-fp16-fix

README.md

@@ -1,6 +1,6 @@
 ---
 license: creativeml-openrail-m
-base_model: "ptx0/terminus-xl-velocity-v1"
+base_model: "ptx0/terminus-xl-velocity-v2"
 tags:
   - stable-diffusion
   - stable-diffusion-diffusers
@@ -14,12 +14,12 @@ inference: true
 
 # terminus-xl-velocity-training
 
-This is a full rank finetuned model derived from [ptx0/terminus-xl-velocity-v1](https://huggingface.co/ptx0/terminus-xl-velocity-v1).
+This is a full rank finetuned model derived from [ptx0/terminus-xl-velocity-v2](https://huggingface.co/ptx0/terminus-xl-velocity-v2).
 
 The main validation prompt used during training was:
 
 ```
-a cute anime character named toast
+a cute anime character named toast holding a sign that says SOON, sitting next to a red square on her left side, and a transparent sphere on her right side
 ```
 
 ## Validation settings
@@ -27,7 +27,7 @@ a cute anime character named toast
 - CFG Rescale: `0.7`
 - Steps: `30`
 - Sampler: `euler`
-- Seed: `420420420`
+- Seed: `42`
 - Resolutions: `1024x1024,1152x960,896x1152`
 
 Note: The validation settings are not necessarily the same as the [training settings](#training-settings).
@@ -44,10 +44,10 @@ You may reuse the base model text encoder for inference.
 ## Training settings
 
 - Training epochs: 0
-- Training steps: 6200
-- Learning rate: 1e-06
-- Effective batch size: 32
-  - Micro-batch size: 8
+- Training steps: 200
+- Learning rate: 4e-07
+- Effective batch size: 16
+  - Micro-batch size: 4
   - Gradient accumulation steps: 4
 - Prediction type: v_prediction
 - Rescaled betas zero SNR: True
@@ -59,40 +59,16 @@ You may reuse the base model text encoder for inference.
 ## Datasets
 
 ### celebrities
-- Repeats: 4
-- Total number of images: 1184
+- Repeats: 0
+- Total number of images: 144
 - Total number of aspect buckets: 3
 - Resolution: 1.0 megapixels
 - Cropped: True
 - Crop style: random
 - Crop aspect: random
 ### movieposters
-- Repeats: 25
-- Total number of images: 1728
-- Total number of aspect buckets: 3
-- Resolution: 1.0 megapixels
-- Cropped: True
-- Crop style: random
-- Crop aspect: random
-### normalnudes
-- Repeats: 5
-- Total number of images: 1056
-- Total number of aspect buckets: 3
-- Resolution: 1.0 megapixels
-- Cropped: True
-- Crop style: random
-- Crop aspect: random
-### propagandaposters
 - Repeats: 0
-- Total number of images: 608
-- Total number of aspect buckets: 3
-- Resolution: 1.0 megapixels
-- Cropped: True
-- Crop style: random
-- Crop aspect: random
-### guys
-- Repeats: 5
-- Total number of images: 352
+- Total number of images: 208
 - Total number of aspect buckets: 3
 - Resolution: 1.0 megapixels
 - Cropped: True
@@ -100,15 +76,7 @@ You may reuse the base model text encoder for inference.
 - Crop aspect: random
 ### pixel-art
 - Repeats: 0
-- Total number of images: 1024
-- Total number of aspect buckets: 3
-- Resolution: 1.0 megapixels
-- Cropped: True
-- Crop style: random
-- Crop aspect: random
-### signs
-- Repeats: 25
-- Total number of images: 352
+- Total number of images: 112
 - Total number of aspect buckets: 3
 - Resolution: 1.0 megapixels
 - Cropped: True
@@ -116,31 +84,7 @@ You may reuse the base model text encoder for inference.
 - Crop aspect: random
 ### moviecollection
 - Repeats: 0
-- Total number of images: 1888
-- Total number of aspect buckets: 3
-- Resolution: 1.0 megapixels
-- Cropped: True
-- Crop style: random
-- Crop aspect: random
-### bookcovers
-- Repeats: 0
-- Total number of images: 736
-- Total number of aspect buckets: 3
-- Resolution: 1.0 megapixels
-- Cropped: True
-- Crop style: random
-- Crop aspect: random
-### nijijourney
-- Repeats: 0
-- Total number of images: 608
-- Total number of aspect buckets: 3
-- Resolution: 1.0 megapixels
-- Cropped: True
-- Crop style: random
-- Crop aspect: random
-### experimental
-- Repeats: 0
-- Total number of images: 3040
+- Total number of images: 208
 - Total number of aspect buckets: 3
 - Resolution: 1.0 megapixels
 - Cropped: True
@@ -148,31 +92,7 @@ You may reuse the base model text encoder for inference.
 - Crop aspect: random
 ### ethnic
 - Repeats: 0
-- Total number of images: 3072
-- Total number of aspect buckets: 3
-- Resolution: 1.0 megapixels
-- Cropped: True
-- Crop style: random
-- Crop aspect: random
-### sports
-- Repeats: 0
-- Total number of images: 736
-- Total number of aspect buckets: 3
-- Resolution: 1.0 megapixels
-- Cropped: True
-- Crop style: random
-- Crop aspect: random
-### gay
-- Repeats: 0
-- Total number of images: 1056
-- Total number of aspect buckets: 3
-- Resolution: 1.0 megapixels
-- Cropped: True
-- Crop style: random
-- Crop aspect: random
-### architecture
-- Repeats: 0
-- Total number of images: 4320
+- Total number of images: 368
 - Total number of aspect buckets: 3
 - Resolution: 1.0 megapixels
 - Cropped: True
@@ -180,7 +100,7 @@ You may reuse the base model text encoder for inference.
 - Crop aspect: random
 ### shutterstock
 - Repeats: 0
-- Total number of images: 21059
+- Total number of images: 2608
 - Total number of aspect buckets: 3
 - Resolution: 1.0 megapixels
 - Cropped: True
@@ -188,15 +108,15 @@ You may reuse the base model text encoder for inference.
 - Crop aspect: random
 ### cinemamix-1mp
 - Repeats: 0
-- Total number of images: 8992
-- Total number of aspect buckets: 3
+- Total number of images: 1104
+- Total number of aspect buckets: 1
 - Resolution: 1.0 megapixels
 - Cropped: True
 - Crop style: random
 - Crop aspect: random
 ### nsfw-1024
 - Repeats: 0
-- Total number of images: 10761
+- Total number of images: 1328
 - Total number of aspect buckets: 3
 - Resolution: 1.0 megapixels
 - Cropped: True
@@ -204,7 +124,7 @@ You may reuse the base model text encoder for inference.
 - Crop aspect: random
 ### anatomy
 - Repeats: 5
-- Total number of images: 16385
+- Total number of images: 2032
 - Total number of aspect buckets: 3
 - Resolution: 1.0 megapixels
 - Cropped: True
@@ -212,7 +132,7 @@ You may reuse the base model text encoder for inference.
 - Crop aspect: random
 ### bg20k-1024
 - Repeats: 0
-- Total number of images: 89250
+- Total number of images: 11136
 - Total number of aspect buckets: 3
 - Resolution: 1.0 megapixels
 - Cropped: True
@@ -220,7 +140,7 @@ You may reuse the base model text encoder for inference.
 - Crop aspect: random
 ### yoga
 - Repeats: 0
-- Total number of images: 3584
+- Total number of images: 448
 - Total number of aspect buckets: 3
 - Resolution: 1.0 megapixels
 - Cropped: True
@@ -228,15 +148,15 @@ You may reuse the base model text encoder for inference.
 - Crop aspect: random
 ### photo-aesthetics
 - Repeats: 0
-- Total number of images: 33121
+- Total number of images: 4128
 - Total number of aspect buckets: 3
 - Resolution: 1.0 megapixels
 - Cropped: True
 - Crop style: random
 - Crop aspect: random
 ### text-1mp
-- Repeats: 25
-- Total number of images: 13120
+- Repeats: 5
+- Total number of images: 1616
 - Total number of aspect buckets: 3
 - Resolution: 1.0 megapixels
 - Cropped: True
@@ -244,7 +164,7 @@ You may reuse the base model text encoder for inference.
 - Crop aspect: random
 ### photo-concept-bucket
 - Repeats: 0
-- Total number of images: 567521
+- Total number of images: 70912
 - Total number of aspect buckets: 3
 - Resolution: 1.0 megapixels
 - Cropped: True

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training_state.json

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unet/config.json

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 {
   "_class_name": "UNet2DConditionModel",
   "_diffusers_version": "0.29.0.dev0",
-  "_name_or_path": "/notebooks/datasets/models/checkpoint-6000",
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   "act_fn": "silu",
   "addition_embed_type": "text_time",
   "addition_embed_type_num_heads": 64,

unet/diffusion_pytorch_model-00001-of-00002.safetensors

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unet/diffusion_pytorch_model-00002-of-00002.safetensors

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