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experiment-4-v1-interpolation-model – AI Model by cs-labs | AlphaNeural AI
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Experiment 4 v1 — Interpolation Model (DiT)
Overview
Video inpainting DiT for hourly interpolation between 6-hour forecast endpoints. Fills in 5 intermediate hourly frames given known endpoints.
Model
Interpolation DiT (198.3M params)
Architecture: hidden=768, 12 heads, 5 double + 10 single blocks
Best T2 MAE at RKSI:
2.48 K
(epoch 1/6, early stopped)
Optimizer: Muon (LR=4e-4) + AdamW
Uses frozen VAE from forecast model for encode/decode
Training Config
6 epochs (early stopped at patience=5), batch=12 x 8 GPU
Muon LR=4e-4, warmup=2 epochs
LPIPS lambda=0.1, gradient loss lambda=0.1
Hardware: 8x NVIDIA B200
Data: 43,818 7-frame sequences (2015-2019)
