Official TextOp Deliverable
This folder is a compact handoff package for the current official TextOp baseline on our dataset.
Included files:
mvae_ckpt_10000.pth
Recommended MVAE checkpoint for downstream use.
dar_ckpt_50000.pth
Latest saved DAR checkpoint from the current training run.
mvae_run.log
MVAE resumed training log.
dar_run.log
DAR training log.
dar_cfg.yaml
Exact DAR config saved by Hydra for this run.
vae_src.log
Source path of the MVAE checkpoint cached into the DAR run.
mvae_reconstruction_sample.npz
One exported MVAE reconstruction sample.
mvae_reconstruction_summary.json
Reconstruction error summary for that sample batch.
Current status:
- MVAE was trained to a late, flatter regime and stopped to free GPU for DAR.
- DAR was trained successfully to
step 50000.
- DAR loss is normal and clearly lower than the early stage.
Useful numbers:
- MVAE
loss/train_total: 0.459224 -> 0.006279
- DAR
loss/train_total: 0.498519 -> 0.100912
- DAR
loss/train_rec: 0.109399 -> 0.021164
- DAR
loss/train_latent_rec: 0.389046 -> 0.079731
- MVAE reconstruction sample mean MSE:
0.004995
- MVAE reconstruction sample mean MAE:
0.039733
What "reconstruction" means here:
- Take a real motion segment from the validation set.
- Encode the future motion into MVAE latent.
- Decode it back into motion using the same model.
- Compare decoded motion against the original future motion.
So reconstruction checks whether the MVAE has learned a good motion representation.
It is not the same thing as DAR text-driven generation.