# step_04000 — SpatialAV2AV checkpoint **Latest & best-tested full fine-tune weights** for LTX-2.3 (22B) spatial audio-video editing. ## Provenance | Field | Value | |-------|-------| | Source path | `/apdcephfs_zwfy11/share_305172035/helensliang/Projects/LTX-2-SpatialAV2AV/outputs_SpatialAV2AV_train/2026.06.19-17.33.11/checkpoints/model_weights_step_04000.safetensors` | | Training run | `2026.06.19-17.33.11` | | Step | **4000 / 20000** (checkpoints saved every 1000 steps) | | Checkpoint written | 2026-06-22 14:05 | | File size | 37,979,154,726 bytes (~36 GiB) | | Base model | `LTX-2.3/ltx-2.3-22b-dev.safetensors` (full-parameter fine-tune, FSDP FULL_SHARD, 8×H20) | | Training time to this step | ~341 h wall (60 s/step) | ## Why this checkpoint Last checkpoint of the run and the one used in the final inference tests (`test8_step4000_*` / `realtest8_step4000_*`, run 2026-07-05). Video-dominant loss stayed low and stable; stereo L≠R verified on decode. ## Loss (video weight 0.85 / audio weight 0.15) | Step | Loss | v_loss | |------|------|--------| | 1000 | 0.1089 | 0.0937 | | 2000 | 0.1528 | 0.1555 | | 3000 | 0.1099 | 0.1051 | | **4000** | **0.1191** | **0.1221** | ## Key training config - `learning_rate: 1.0e-05`, `steps: 20000`, `batch_size: 1`, gradient checkpointing on - `timestep_sampling_mode: shifted_logit_normal` - `loss_video_weight: 0.85`, `loss_audio_weight: 0.15`, `with_audio: true`, `use_ref_audio: false` - `edit_sample_n_frames: 113`, `edit_min_size: 288` - `resolution_buckets: 288x384x113; 384x288x113; 320x320x113; 352x352x113` - `training_strategy.name: spatialav2av` - data: `SpatialAV2AV_full/all.list` (source→edit stereo pairs) ## ⚠️ Format quirk — read before loading This `.safetensors` file is **actually a `torch.save` (zip/pickle) file**, not safetensors. Magic bytes = `PK\x03\x04`. - ❌ `safetensors` loaders fail with `HeaderTooLarge`. - ✅ `torch.load()` + `transformer.load_state_dict(..., strict=False)` → `missing=0 unexpected=0`. Use `SpatialAV2AV_inference.py --full_weights ` (it handles the injection).