Upload build_extrinsic.py with huggingface_hub

build_extrinsic.py

@@ -48,6 +48,7 @@ METRICS = {
     "delta_floor_nats_per_byte":   ("likelihood_delta", "nats/utf8_byte"),
     "lmc_barrier_nats_per_token":  ("likelihood_delta", "nats/token"),
     "harmfulness_score":           ("other",            "score_0_1"),
+    "bliss_score":                 ("other",            "BLiSS sub-score"),
 }
 
 # chance levels for single-benchmark accuracy rows
@@ -509,10 +510,53 @@ def build_goldfish(d, ds):
                  "goldfish_crosslingual", lbl, "nats_per_token", r.get(k), None, n, ds,
                  note + " | LIKELIHOOD, not accuracy")
 
+# =================================================================== 7. Beetle merges
+def build_beetle(d, ds):
+    """Beetle merge evaluations. The source already ships a long-format table whose
+    columns line up almost exactly with this schema, so this is mostly a relabelling."""
+    p = d / "beetle_merge_eval_long.csv"
+    if not p.exists(): return
+    src = rd(p)
+    # a released model that some merge names as its ceiling is a jointly-trained comparator;
+    # one named as a parent is a parent. Everything else is a plain reference.
+    ceilings = {r["ceiling"] for r in src if r.get("ceiling")}
+    parents_set = {r[k] for r in src for k in ("parent_a", "parent_b") if r.get(k)}
+    for r in src:
+        kind = r.get("kind")
+        mid_base = r["merge_id"]
+        rung, op, arm = r.get("rung", ""), r.get("operator", ""), r.get("arm", "")
+        if kind == "merge":
+            role = "merged"
+            mid = f"{mid_base}#{rung}" if rung else mid_base
+            parents = "|".join(x for x in (r.get("parent_a"), r.get("parent_b")) if x)
+            note = (f"Beetle merge; arm={arm}; jointly-trained ceiling for this pair is "
+                    f"{r.get('ceiling') or 'n/a'}; eval langs {r.get('eval_langs') or 'n/a'}")
+        else:
+            mid, parents = mid_base, ""
+            if mid_base in ceilings:
+                role, note = "jointly_trained", ("released bilingual model trained directly on the "
+                                                "pair -- the ceiling a Beetle merge is judged against")
+            elif mid_base in parents_set:
+                role, note = "parent", "Beetle merge parent, evaluated alone"
+            else:
+                role, note = "reference", "Beetle reference model"
+        bench, metric_in = r["benchmark"], r.get("metric")
+        ch = f(r.get("chance"))
+        if metric_in == "accuracy":
+            # BLiSS accuracy is reported on 0-100, everything else on 0-1
+            metric = "accuracy_pct" if (ch is not None and ch > 1) else "accuracy"
+        else:
+            bench, metric = f"{bench}:{metric_in}", "bliss_score"
+            note += f" | BLiSS sub-score '{metric_in}', not an accuracy"
+        emit(mid, role, r.get("provenance_family") or "beetle", parents, rung, op,
+             "beetle_merge_eval", bench, metric, r.get("value"),
+             ch if metric.startswith("accuracy") else ch, f(r.get("n")), ds, note)
+
+
 # =================================================================== driver
 BUILDERS = {"merge-accuracy": build_merge_accuracy, "compose-audit": build_compose_audit,
             "crossarch-1b": build_crossarch, "mergebench": build_mergebench,
-            "aim": build_aim, "goldfish": build_goldfish}
+            "aim": build_aim, "goldfish": build_goldfish, "beetle": build_beetle}
 
 def main():
     ap = argparse.ArgumentParser()