TrackWan 14B / 720p β Overfit warmstart checkpoint (Stage B, step 3000)
Training-state checkpoint (PyTorch DCP) from Phase 0 / Stage B of the bidirectional TrackWan teacher recipe (point-track-conditioned I2V, 14B, 720p), built in FastVideo.
What this is
- Stage B overfit of the track pathway (
track_encoder+ patch-embed track slot), head trainable, on a small 50-clip 720p synthetic set. Random track-ID sampling (WANTRACK_FIXED_SAMPLE=0) so the pathway generalizes over arbitrary ID/point assignments (the invariance stage β it can only be learned while the head is trainable, before stage-1 freezes it). - Warm-started from Stage A (
checkpoint-2000): fixed-ID overfit β random-ID overfit, continued 2000β3000. - Maskless and CLIP-free by design:
WANTRACK_PMASK=0(mid-frame masking belongs to stage-2) andWANTRACK_IMAGE_COND=0(image cross-attention is enabled from stage-1 on the pristine merged base; turning it on mid-overfit shocks a CLIP-free-trained seed). - Config:
lr 1e-4(constant),flow_shift 6, sparse conditioning (WANTRACK_SPARSE=1,EXTRA_RANDOM=20),d64track-ID embedding + bias track encoder.
Format & caveats
- Full training-state checkpoint: model + optimizer + scheduler + per-rank RNG, sharded
as
dcp/__<rank>_0.distcp(8 ranks, HSDP 2Γ4). Not afrom_pretrainedmodel β consolidate via the FastVideo export step (03_export.sh) to get a diffusers transformer. - The base is discarded by the Phase-1 merge β only the (now ID/subset-invariant) track pathway is lifted onto a pristine Wan2.1-I2V-14B base. So this checkpoint's value is the track pathway; it is primarily a reproducibility / re-merge-source artifact.
Provenance
Stage A (fixed IDs) β Stage B (random IDs, this ckpt) β export β merge β OpenVid stage-1
(CLIP on) β synthetic stage-2 (masking). See the FastVideo data_pipeline/720_stage_1/ recipe.
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