PROGRESS.md

# MATS-SQL Bundle — Progress Snapshot

**Bundle**: `thanhdath/mats-sql-bundle` (HuggingFace)
**Snapshot date**: 2026-05-13

---

## Original Task

Multi-agent Text2SQL pipeline reaching **pass@8 ≥ 67%** (BIRD-dev, EX). Hard constraints from project owner:

- Planner ≤ 3B params
- Selection ≤ 3B params
- Validator(s) and Fixer ≤ 1B params each (prefer 0.5B)
- Max ORPO iter-2 (no iter-3+)
- **No commercial APIs (no GPT teacher)** — collaborative training must be structurally necessary
- V+F (validators + fixer) must **not hurt** final accuracy and **should contribute** to acc increase
- Results tables must include per-agent parameter counts
- Two specialized validators per paper §Combined Validator: **v_s (selection)** and **v_c (condition)**

---

## Current Progress (latest)

### Best result so far (BIRD-dev, K=8)

| Config | N | pass@8 (recall, oracle) | Trained selector (real, no leak) | Notes |
|---|---|---|---|---|
| 1-stage iter-2 uniform-temp | 1524 | 64.96% | — | leak-pre-patch number was 64.96 |
| 1-stage iter-2 mixed-temp (0.5/0.7/0.9/1.1) | 1525 | **65.38%** | — | best recall |
| 3-stage iter-2 + 0.6B v_s/v_c + ORPO fixer iter-1 | 1525 | 65.05% | — | V+F neutral (0 rescues) |
| 3-stage iter-2 + 0.5B v_s + 0.6B v_c + 0.5B **replanner**-fixer iter-2 | 1525 | 65.11% | **54.30%** | leak-free selector measurement; **fixer iter-2 +0.06pp vs iter-1** |

**Critical finding (2026-05-13):** `compute_bestofn_with_selector.py` had `exec_response = "OK" if is_planner_correct else "Error / no rows"` — passed the gold-graded label to the selector → trivially matched oracle. **Patched** to use actual SQL execution result. Real trained-selector accuracy is **54.30%, NOT 65%**. Selector → oracle gap = 10.81pp.

### Two headline gaps to close (target = headline EX ≥ 67%)

| Gap | Current | Target | Gap | Lever |
|---|---|---|---|---|
| **Oracle pass@8** (recall) | 65.38% (mixed-temp) | ≥70% | +4.6pp | More diverse sampling / better fixer rescues |
| **Selector → oracle** | 57.25 / 65.38 = 87.6% | ≥95% | +8.13pp | Selector v3 (more data / different arch) |

### Selector v2 results (2026-05-13 — row preview added to prompt)

Retrained 3B selector with `OK. Rows preview: <rows>` instead of bare `OK`. Closes ~3-4pp of the ~11pp gap.

| Config (BIRD-dev K=8 iter-2 planner) | Oracle | Selector v1 (no rows) | **Selector v2 (rows)** | v2 gain |
|---|---|---|---|---|
| 1-stage uniform-temp | 64.96% | 53.94% | 56.43% | +2.49pp |
| **1-stage mixed-temp** | **65.38%** | 53.64% | **57.25%** ← headline | +3.61pp |
| 2-stage + ORPO fixer-iter1 | 63.04% | 52.72% | 56.02% | +3.30pp |
| 3-stage + 0.6B V/V + ORPO fixer-iter1 | 65.05% | 53.11% | 56.98% | +3.87pp |
| 3-stage + 0.5B V/V + 0.5B replanner-fixer | 65.11% | 53.51% | 56.66% | +3.15pp |

**Headline pass@8 post-selector = 57.25%** (1-stage mixed-temp + v2 selector). Still −9.75pp from 67%.

### Per-model status

| Agent | Model | Params | Status |
|---|---|---|---|
| Planner | Qwen2.5-Coder-3B-Instruct + ORPO iter-2 (collab) | 3B | trained ✓ |
| Selector | Qwen2.5-Coder-3B-Instruct + SFT (YES/NO binary) | 3B | trained ✓ |
| Validator-Selection (v_s) | Qwen2.5-Coder-0.5B-Instruct + SFT v3 | 0.5B | trained ✓ |
| Validator-Condition (v_c) | Qwen3-0.6B-Instruct + SFT v3 | 0.6B | trained ✓ (0.5B variant truncated, retrain pending) |
| Fixer (re-planner) | Qwen2.5-Coder-0.5B + ORPO iter-2 (replanner data) | 0.5B | trained ✓ |

### V+F contribution diagnostic (mixed-temp iter-2 K=8, 1525 q)

- Validators critique 91.6% of trajectories; old fixer ignored 98.6% → 0 rescues at pass@8
- Replanner fixer (iter-2) currently flipping ~40% of trajectories (winloss=605 at 1360/1534) — net effect being measured

### Key findings

- ORPO planner: SFT 64.11% → iter-1 64.26% → iter-2 64.96% (+0.70pp, diminishing returns)
- Mixed-temp sampling adds +0.42pp over uniform-temp at K=8
- v3 validator data rebalanced from 8% all-OK (over-critique) to 34.5%/61% all-OK
- Fixer dataset re-built as "re-planner" objective (1833 pairs): given a failed planner trajectory, produce a correct alternative from same question's K=4 trajectories
- pass@8 (true recall) is the *upper bound* for trained-selector accuracy; need recall ≥70% to land headline ≥67% after selector picks

---

## What's Next (in priority order)

1. **Phase4 K=8 3-stage eval finishes** (currently 89% done, ETA 30 min) → get pass@8 with replanner-fixer.
2. **Apply patched (leak-free) selector** to all K=8 JSONLs → get true selector accuracy (not oracle).
3. **If pass@8 selector ≥67%: DONE.** Write results table with per-agent sizes.
4. **If pass@8 selector <67%:**
   - Re-mine fixer ORPO data on **iter-2 planner** BIRD-train rollouts (current data was from iter-1 planner → distribution shift).
   - Re-train fixer ORPO iter-2 on fresh data.
   - Consider planner sampling tricks: wider mixed-temp (0.3-1.3), nucleus variation.
5. **Make V+F contribute (currently neutral):** the 0.5B replanner fixer's `winloss` is now high (~40%) — need to check if those flips are net+ or net-. If net-, gate fixer to only run on `planner_exec_ok=False` cases.

---

## Repo contents

```
mats-sql-bundle/
├── PROGRESS.md                                                  # this file
├── models/
│   ├── planner-iter2-collab-3B/                                 # 3B ORPO iter-2 planner
│   ├── selector-3B-sft/                                         # 3B trained selector
│   ├── validator-selection-0.5B-v3/                             # v_s SFT
│   ├── validator-condition-0.6B-v3/                             # v_c SFT
│   └── fixer-replanner-0.5B-iter2-orpo/                         # ORPO iter-2 re-planner fixer
├── data/
│   ├── sft-validator-selection-v3/                              # SFT data for v_s
│   ├── sft-validator-condition-v3/                              # SFT data for v_c
│   ├── hf_fixer_replanner/                                      # ORPO data for fixer iter-2
│   └── hf_planner_collaborative_iter2/                          # ORPO data for planner iter-2
├── recipes/
│   ├── orpo-planner-collab-iter2.yaml
│   ├── orpo-fixer-replanner-0.5b-iter2.yaml
│   ├── validator-selection-fft-0.5b-v3.yaml
│   └── validator-condition-fft-0.5b-v3.yaml
└── scripts/
    ├── run_pipeline_rollouts.py                                 # rollout / 3-stage runner
    ├── compute_bestofn_with_selector.py                         # selector apply (patched)
    ├── compute_bestofn_metrics.py                               # oracle/greedy metrics
    ├── build_validator_2agents_v3.py                            # v_s/v_c data builder
    └── build_fixer_replanner_iter2.py                           # fixer re-planner data builder
```

## How to continue from this bundle

```bash
# 1. Clone the bundle (~16 GB)
git clone https://huggingface.co/datasets/thanhdath/mats-sql-bundle
cd mats-sql-bundle

# 2. Symlink to alignment-handbook layout
ln -s $(pwd)/models /path/to/alignment-handbook/output
ln -s $(pwd)/data /path/to/mats-sql-tist/data/llm_alignment_imported

# 3. Continue from where we left off: BIRD-dev K=8 3-stage with iter-2 planner + 0.5B agents
bash scripts/run_pipeline_rollouts.py --K 8 --mixed_temp "0.5,0.7,0.9,1.1" ...

# 4. To do iter-3 (if needed), re-mine fixer data on iter-2 planner BIRD-train rollouts first.
```

---

**Maintainer**: thanhdath@gmail.com / thanhdath97@gmail.com
**Source repo**: /home/datht/mats-sql-tist (private dev machine)