📂 Masha K v3 ‑ root — Parameter Settings

🔧 Network Module

Type: LoRA
Base Model: FLUX – Dev fp32
Trigger words: maxxa

🖼️ Image Processing Parameters

Repeat: 8
Epochs: 8
Save Every N Epochs: 1

⚙️ Training Parameters

Seed: 42
Clip Skip: 1
Text Encoder LR: 0.00002
UNet/DiT LR: 0.0002
LR Scheduler: constant
Optimizer: AdamW
Network Dim: 100
Network Alpha: 128
Gradient Accumulation Steps: 4

🏷️ Label Parameters

Shuffle caption: –
Keep n tokens: –

🧪 Advanced Parameters

Noise offset: 0.008
Multires noise discount: 0.06
Multires noise iterations: 4
conv_dim: 128
conv_alpha: 160
Batch Size: –

📸 Sample Image Settings

Prompt:
maxxa. A blonde woman stands confidently in a forest with ethereal atmosphere. Her body softly accentuated by directional lighting. Her long wavy hair cascades past her shoulders with strand realism. Her blue eyes are enhanced with mascara and subtle eyeliner, paired with red lips, a small nose, and a calm, focused expression. She is wearing a pink top, red leather skirt and red stockings. Her posture is upright and poised, one hand resting on her waist, the other hand on her thigh. Her legs are crossed. She is looking at the viewer, daring expression.
Sampler: dpmpp_2m

✨ This layout keeps each block separated and easy to scan — perfect for logging or archiving.

Do you want me to also create a repeat distribution table (x1, x2, x3 counts for wides, fulls, close‑ups) in the same style so you can track dataset balance alongside these parameters?

Masha K v3 - root - 7