Version 3.0 (Latest) For in-depth details of version 3.0 training and tooling, see: Kirazuri (Anima) 3.0 Training Diary: https://github.com/motimalu/diffusion-training-configs/blob/main/diffusion-pipe/anima/notes/kirazuri3.0-notes.md Training Details Summary Trainer: diffusion-pipe commit b0aa4f1e03169f3280c8518d37570a448420f8be Training device: NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition Total training time: ~10 days Total samples seen(unbatched steps): ~2,550,000 Training resolutions: 512^2 768^2 1024^2 1280^2 1536^2 Stage 1 Samples seen(unbatched steps): ~2,000,000 Training time: ~125 hrs Learning Rate: 6e-6 Learning Rate Scheduler: Cosine LLM Adaptor Learning Rate: 8e-7 Precision: Mixed BF16 Optimizer: AdamW8bit with Kahan Summation Weight Decay: 0.01 Timestep Sampling Strategy: Logit-Normal Stage 2 Samples seen(unbatched steps): ~550,000 Training time: ~118 hrs Learning Rate: 3e-6 Learning Rate Scheduler: Cosine LLM Adaptor Learning Rate: 0 Flux Shift: Enabled Multi-Scale Loss Weight: 0.5 Precision: Mixed BF16 Optimizer: AdamW8bit with Kahan Summation Weight Decay: 0.01 Timestep Sampling Strategy: Logit-Normal Additional Features Tag Dropout: 30% with protected first 8 tags Tag Shuffle: Applied to last unprotected tags Natural Language: Short and Long Caption variants Changes from Kirazuri (Anima) v2.0 Dataset includes recently curated 7,071 images increasing total size from 35,537 to 42,608 images Dataset cutoff now of 2026/05/12. Trained at 5 total resolutions in two-stage training Stage 1 - 512^2, 768^2, 1024^2 Stage 2 - 1024^2, 1280^2 1536^2 Introduced cosine learning rate scheduler for smooth learning rate transition between training stages Re-captioned full dataset for a second natural language captions variant with updated captioning script