WAM_DIT4DIT — context pooling (avg), RoboCasa kitchen, video-only
Wan2.2-TI2V-5B video DiT fine-tuned on RoboCasa (base recipe, effective batch 64:
4 GPU × per-device 8 × grad-accum 2), 4-latin history (nin=25 / nout=41, fdf=2),
with average context pooling of the past latent frames inserted before block L.
| folder | pooling | layer | steps |
|---|---|---|---|
L12/checkpoint-<step> |
avg | 12 | every 20k |
L3/checkpoint-<step> |
avg | 3 | every 20k |
Weights (*.safetensors) + config.json + processor / experiment config only; optimizer
state and training_args.bin are not included. Training code: https://github.com/HEMMO0208/wam
(run_scripts/train/wam_dit4dit/compression/finetune_wam_dit4dit_robocasa_kitchen_ctxpool.sh).
Note: an earlier version of this repo held effective-batch-32 runs; those were removed. All checkpoints here are eff-64.
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