Weekly MidJourney Style Experiment: Last 500 Images

Update (11/02/23) : adding WEEK 3 FFUsion (ALL IN) LoRA of Hot, Rising, and New

🗓 Current Week's Exploration (10.31.23): This week LoRAs are fine-tuned for the

🏆'Style Capture & Fusion Showdown' (rejected entry)

Week 3 Styles of Hot, Rising, and New MJ categories: 10.31.23

🔥 Previous Week’s LoRAs (10.23.23):
last week styles from the 'Hot', 'Rising', and 'New' category

A recent experiment conducted using the last 500 images from the 'MidJourney' categories: Hot, Rising, and New.

Data Acquisition and Integrity:

• All images were sourced responsibly, with no use of unofficial tools for acquisition.

• The images were obtained using the sanctioned Corporate/Enterprise account.

Technical Overview:

• The images were processed using the ViT-L-14/openai model (quick sloppy run). For testing, the prodigy tool was employed.

• It's important to note that the current quality of results does not align with our typical production standards. However, for those interested in further details, a training set from the official Civitai trainer is available.

• The experiment utilized the capabilities of the Civitai trainer(default out of the box configuration)

09/26/2023 03:48:12 AM

SUBMITTED

09/26/2023 03:48:40 AM

PROCESSING

09/26/2023 05:21:46 AM

READY

• Lora FA text encoder, and the Kohya tools, all operating on the H100 80GB.

We appreciate your continued interest and support. Further updates will be provided as the experiment progresses.

Each one took 20-30min

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📂 MidJ_Last_500_-_Experiment.safetensors

• 📅 Date: 2023-09-26T02:20:38

• 🏷️ Title: MidJ_Last_500_-_Experiment

• 🖼️ Resolution: 1024x1024

• 🧪 Architecture: stable-diffusion-xl-v1-base/lora

• 🌐 Network Dimensions:

  • Dim/Rank: 32.0

  • Alpha: 16.0

• 🔌 Module: networks.lora

• 🔧 Configurations:

  • Learning Rate: 0.0005

  • UNet LR: 0.0005

  • TE LR: 5e-05

  • Optimizer: bitsandbytes.optim.adamw.AdamW8bit(weight_decay=0.1)

  • Scheduler: cosine_with_restarts

  • Warmup Steps: 0

  • Epochs: 10

  • Batches per Epoch: 128

  • Gradient Accumulation Steps: 1

  • Train Images: 500

  • Regularization Images: 0

  • Multires Noise Iterations: 6.0

  • Multires Noise Discount: 0.3

  • Min SNR Gamma: 5.0

  • Zero Terminal SNR: True

  • Max Gradient Norm: 1.0

  • Clip Skip: 1

  • Dataset Directories: 1

  • Image Count: 500 images

• 📈 Stats:

  • UNet Weight (Avg. Magnitude): 3.0170

  • UNet Weight (Avg. Strength): 0.0111

  • Text Encoder (1) - Weight (Avg. Magnitude): 1.7304

  • Text Encoder (1) - Weight (Avg. Strength): 0.0087

  • Text Encoder (2) - Weight (Avg. Magnitude): 1.7614

  • Text Encoder (2) - Weight (Avg. Strength): 0.0068

📂 FF-Midj-Last-v0563.safetensors

• 📅 Date: 2023-09-26T01:16:09

• 🏷️ Title: FF-Midj-Last-v0563

• 🖼️ Resolution: 1024x1024

• 🧪 Architecture: stable-diffusion-xl-v1-base/lora

• 🌐 Network Dimensions:

  • Dim/Rank: 64.0

  • Alpha: 32.0

• 🔌 Module: networks.lora

• 📈 Stats:

  • UNet Weight (Avg. Magnitude): 2.6731

  • UNet Weight (Avg. Strength): 0.0076

  • Text Encoder (1) - Weight (Avg. Magnitude): 2.5809

  • Text Encoder (1) - Weight (Avg. Strength): 0.0091

  • Text Encoder (2) - Weight (Avg. Magnitude): 2.6613

  • Text Encoder (2) - Weight (Avg. Strength): 0.0072

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📂 FF-Midj-Rise-v0564.safetensors

• 📅 Date: 2023-09-26T02:01:20

• 🏷️ Title: FF-Midj-Rise-v0564

• 🖼️ Resolution: 1024x1024

• 🧪 Architecture: stable-diffusion-xl-v1-base/lora

• 🌐 Network Dimensions:

  • Dim/Rank: 64.0

  • Alpha: 32.0

• 🔌 Module: networks.lora

• 📈 Stats:

  • UNet Weight (Avg. Magnitude): 2.6016

  • UNet Weight (Avg. Strength): 0.0074

  • Text Encoder (1) - Weight (Avg. Magnitude): 2.5694

  • Text Encoder (1) - Weight (Avg. Strength): 0.0091

  • Text Encoder (2) - Weight (Avg. Magnitude): 2.6260

  • Text Encoder (2) - Weight (Avg. Strength): 0.0071

📂 FF-Midj-Top-v0564-FA-TX.safetensors

• 📅 Date: 2023-09-26T03:21:49

• 🏷️ Title: FF-Midj-Top-v0564-FA-TX

• 🖼️ Resolution: 1024x1024

• 🧪 Architecture: stable-diffusion-xl-v1-base/lora

• 🌐 Network Dimensions:

  • Dim/Rank: 64.0

  • Alpha: 64.0

• 🔌 Module: networks.lora_fa

• 📈 Stats:

  • Text Encoder (1) - Weight (Avg. Magnitude): 5.8341

  • Text Encoder (1) - Weight (Avg. Strength): 0.0191

  • Text Encoder (2) - Weight (Avg. Magnitude): 6.0269

  • Text Encoder (2) - Weight (Avg. Strength): 0.0153

• ⚠️ Note: No UNet found in this LoRA.

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