pcbnew200_flashwam_scratch — FlashWAM (FusedKV / RoPE-fixed), from scratch, place_cube_new 200 traj
FlashWAM (M1_FusedKV_RopeFixed) action-video model trained from scratch (no
LIBERO init) on the 200-trajectory "pick and place new" dataset.
- Model: FasterWAM decoupled,
kv_source_mode: fused_kv, fixed_rope: true
(video DiT Wan2.2-TI2V-5B backbone + 1-layer action DiT).
- Init:
resume: null — trained from scratch (Wan2.2 base video expert,
random action expert), NOT fine-tuned from a LIBERO checkpoint.
- Data:
place_cube_new_lerobot_v21 — 200 episodes / 26,437 frames, 10 Hz,
2 cameras (base + wrist), 7-dim delta action, 8-dim proprio (real gripper widths).
Task: "place the cube in the bowl" (pick-and-place-new).
- Training: 30 epochs / 24,810 steps, global batch 32, lr 1e-4 cosine, bf16.
Completed cleanly (
max_steps reached). Final loss=0.0501, loss_action=0.0062.
Checkpoints (checkpoints/weights/)
Weights-only checkpoints saved every 5 epochs:
| file | step | epoch |
|---|
step_004135.pt | 4,135 | 5 |
step_008270.pt | 8,270 | 10 |
step_012405.pt | 12,405 | 15 |
step_016540.pt | 16,540 | 20 |
step_020675.pt | 20,675 | 25 |
step_024810.pt | 24,810 | 30 (final) |
Each file is ~10.13 GB (bf16 full model: fused video + action experts).
Other files
config.yaml — full training/model config for this run.dataset_stats.json — per-run action/state normalization stats (min/max), needed
at inference for de/normalization. Always pair a checkpoint with THIS run's stats.
Related
Companion run SleepMastger/random_new is the same FlashWAM architecture but
fine-tuned from LIBERO on the 500-trajectory place_cube_new dataset.
