Add sampled zero-shot baseline runner

scripts/run_zero_shot_baseline.sh

@@ -0,0 +1,41 @@
+#!/usr/bin/env bash
+set -euo pipefail
+
+# Run a sampled zero-shot baseline for publication comparison.
+# Default evaluates Qwen/Qwen3-8B without any adapter on 200 examples per split.
+# Usage:
+#   EVAL_BATCH_SIZE=4 BASELINE_MAX_SAMPLES=200 bash scripts/run_zero_shot_baseline.sh outputs/baselines/qwen3-8b-zero-shot
+
+OUT_DIR="${1:-outputs/baselines/qwen3-8b-zero-shot}"
+MODEL_ID="${BASELINE_MODEL:-Qwen/Qwen3-8B}"
+MAX_SAMPLES="${BASELINE_MAX_SAMPLES:-200}"
+
+source .venv/bin/activate
+export CUDA_VISIBLE_DEVICES="${CUDA_VISIBLE_DEVICES:-0}"
+export PYTHONPATH="$PWD/src:${PYTHONPATH:-}"
+export TOKENIZERS_PARALLELISM=false
+
+python scripts/check_gpu.py
+mkdir -p "$OUT_DIR"
+
+python scripts/evaluate_model.py \
+  --model "$MODEL_ID" \
+  --dataset nraptisss/TMF921-intent-to-config-research-sota \
+  --output_dir "$OUT_DIR" \
+  --batch_size "${EVAL_BATCH_SIZE:-4}" \
+  --max_samples_per_split "$MAX_SAMPLES" \
+  --max_new_tokens "${EVAL_MAX_NEW_TOKENS:-1536}" \
+  --gold_length_buffer "${EVAL_GOLD_LENGTH_BUFFER:-96}" \
+  --save_every "${EVAL_SAVE_EVERY:-25}"
+
+python scripts/normalize_eval_metrics.py --eval_dir "$OUT_DIR"
+
+python - <<PY
+import json
+from pathlib import Path
+p = Path("$OUT_DIR") / "all_normalized_metrics.json"
+m = json.loads(p.read_text())
+print("Zero-shot baseline:", "$MODEL_ID")
+for split, s in m.items():
+    print(f"{split}: n={s.get('num_examples')} parse={s.get('parse_json'):.4f} norm_field_f1={s.get('norm_field_f1'):.4f} norm_key_f1={s.get('norm_key_f1'):.4f} norm_exact={s.get('norm_exact_match'):.4f}")
+PY