# best_ckpt/

**Current best single-layer L10 retriever** (P110, May 2026) — committed to git for direct use by collaborators.

Source experiment: **P110**
- `experiments/expP_110_R10_lr1e4_wt_combfull_l10/ckpts/`
- Config: Round 10 (lr=1e-4, weighted-loss, combined_full data), single layer L10
- Best metric (val full-set L10):
  - precision=0.7171, recall=0.5357, **val_f1=0.6133**, recall@512=0.5256

| File | Type | Format |
|------|------|--------|
| **`l10.pt`** | **real file (~83 MB, committed)** | Single-layer state_dict (latest "best" snapshot, recommended for inference) |
| `l10_best_f1.pt`       | local symlink → `experiments/...` (untracked) | Single-layer state_dict (best F1 epoch) |
| `l10_best_recall_k.pt` | local symlink → `experiments/...` (untracked) | Single-layer state_dict (best recall@K epoch) |

`l10.pt` is the only file committed to git. The other two are convenience symlinks for local
experimentation; pull `experiments/` separately if you need them.

All ckpts are bare-key single-layer format:
```
wq_a.weight       — [1024, 4096]
wq_b.weight       — [N_HEADS*128, 1024]   (N_HEADS=64)
q_norm_weight     — [1024]
weights_proj.weight — [N_HEADS, 4096]
freqs_cis         — RoPE precomputed (optional)
```

## Usage

```bash
# Single-layer inference (default path):
python inference.py --ckpt best_ckpt/l10.pt --layer 10 --data-path ./data/doc_00030.pkl
```

`inference.py` returns **raw logits** (not sigmoid'd). For 0-1 probabilities call `torch.sigmoid(logits)`
externally; for top-K selection use logits directly (sigmoid is monotonic and unnecessary).

## Updating

When a better single-layer L10 ckpt emerges, replace l10.pt with the new real file (and re-commit):

```bash
cp experiments/expP_NEW/ckpts/ckpt_best.pt best_ckpt/l10.pt
git add best_ckpt/l10.pt && git commit -m "Update best_ckpt/l10.pt to expP_NEW"
```

For local-only convenience symlinks:

```bash
ln -sfn ../experiments/expP_NEW/ckpts/ckpt_best_f1.pt     best_ckpt/l10_best_f1.pt
ln -sfn ../experiments/expP_NEW/ckpts/ckpt_best_recall_k.pt best_ckpt/l10_best_recall_k.pt
```

## Previous Joint Format (R601, archived)

Earlier this folder linked to the R601 joint chain ckpt (Pair → PW noweight, val F1=0.7927).
That ckpt has the multi-layer format (`retrievers.l{10,12,20}.*` keys) and lives at:

- `experiments/expR_601_stage2_pw_from_R462_ddp/ckpts/ckpt_joint_best_ens_f1.pt`

⚠️ R-series joint ckpts have a logit-偏负 issue (sigmoid > 0.5 hit rate ~0.13% on test data,
vs P110's ~1.0%) — they have great `recall@K` but cannot use sigmoid threshold 0.5 directly.
**For deployment, prefer P110 (`l10.pt`)** unless you specifically need the joint 3-layer format.