File size: 4,965 Bytes
8a5ffa8
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
#!/usr/bin/env python3
"""Independently verify the arithmetic in the peer's Claim 5 raw results."""

from __future__ import annotations

import argparse
import hashlib
import json
import math
import statistics
from pathlib import Path


def exact_mcnemar(left, right):
    left_only = sum(a == 1 and b == 0 for a, b in zip(left, right))
    right_only = sum(a == 0 and b == 1 for a, b in zip(left, right))
    n = left_only + right_only
    if n == 0:
        return left_only, right_only, 1.0
    tail = sum(math.comb(n, k) for k in range(min(left_only, right_only) + 1))
    p = min(1.0, 2.0 * tail / (2**n))
    return left_only, right_only, p


def mean_se(values):
    mean = statistics.mean(values)
    se = statistics.stdev(values) / math.sqrt(len(values))
    return mean, se


def main() -> None:
    parser = argparse.ArgumentParser()
    parser.add_argument("--input", type=Path, required=True)
    parser.add_argument("--matched-input", type=Path, required=True)
    parser.add_argument("--output", type=Path, required=True)
    args = parser.parse_args()

    data = json.loads(args.input.read_text())
    matched = json.loads(args.matched_input.read_text())
    assert data["model"] == "Qwen/Qwen2.5-3B-Instruct"
    assert data["n_train"] == 1000
    assert data["n_eval_per_cat"] == 250
    assert data["n_shot"] == 7
    assert data["epochs"] == 5
    assert data["lora_r"] == 128
    assert data["selected_lr"] == {"qkv": 1e-5, "v": 3e-4}

    base_h = data["base_hits"]["Humanities"]["7shot"]
    assert len(base_h) == 250
    rows = {}
    for arm in ("qkv", "v"):
        seeds = data["final"][arm]["seeds"]
        assert len(seeds) == 3
        acc_0 = []
        acc_7 = []
        tests_vs_base = []
        for seed in seeds:
            hits_0 = seed["hits"]["Humanities"]["0shot"]
            hits_7 = seed["hits"]["Humanities"]["7shot"]
            assert len(hits_0) == len(hits_7) == 250
            measured_0 = 100 * sum(hits_0) / len(hits_0)
            measured_7 = 100 * sum(hits_7) / len(hits_7)
            assert measured_0 == seed["acc"]["Humanities"]["0shot"]
            assert measured_7 == seed["acc"]["Humanities"]["7shot"]
            acc_0.append(measured_0)
            acc_7.append(measured_7)
            b, c, p = exact_mcnemar(base_h, hits_7)
            tests_vs_base.append(
                {
                    "seed": seed["seed"],
                    "base_right_ft_wrong": b,
                    "base_wrong_ft_right": c,
                    "p_exact_two_sided": p,
                }
            )
        mean_0, se_0 = mean_se(acc_0)
        mean_7, se_7 = mean_se(acc_7)
        rows[arm] = {
            "humanities_0shot_mean": mean_0,
            "humanities_0shot_se": se_0,
            "humanities_7shot_mean": mean_7,
            "humanities_7shot_se": se_7,
            "delta_0shot_vs_base_pp": mean_0 - data["base"]["Humanities"]["0shot"],
            "delta_7shot_vs_base_pp": mean_7 - data["base"]["Humanities"]["7shot"],
            "mcnemar_vs_base_7shot": tests_vs_base,
        }

    paired = []
    for qkv, value in zip(
        data["final"]["qkv"]["seeds"], data["final"]["v"]["seeds"]
    ):
        assert qkv["seed"] == value["seed"]
        q_hits = qkv["hits"]["Humanities"]["7shot"]
        v_hits = value["hits"]["Humanities"]["7shot"]
        v_only, q_only, p = exact_mcnemar(v_hits, q_hits)
        paired.append(
            {
                "seed": qkv["seed"],
                "v_right_qkv_wrong": v_only,
                "v_wrong_qkv_right": q_only,
                "delta_v_minus_qkv_pp": 100 * (sum(v_hits) - sum(q_hits)) / 250,
                "p_exact_two_sided": p,
            }
        )

    # The matched-rate control must use the declared common rate and retain
    # the same base measurements.
    assert matched["model"] == data["model"]
    assert matched["matched_lr"] == 1e-4
    assert matched["base"] == data["base"]
    assert matched["base_hits"] == data["base_hits"]

    assert round(rows["qkv"]["humanities_0shot_mean"], 2) == 62.67
    assert round(rows["qkv"]["humanities_7shot_mean"], 2) == 60.00
    assert round(rows["v"]["humanities_0shot_mean"], 2) == 62.13
    assert round(rows["v"]["humanities_7shot_mean"], 2) == 60.27

    payload = {
        "source_sha256": {
            "claim5.json": hashlib.sha256(args.input.read_bytes()).hexdigest(),
            "claim5_matched.json": hashlib.sha256(
                args.matched_input.read_bytes()
            ).hexdigest(),
        },
        "recomputed": rows,
        "paired_v_vs_qkv_7shot": paired,
        "matched_rate_control_checked": True,
        "assertions_passed": 39,
    }
    rendered = json.dumps(payload, indent=2, sort_keys=True) + "\n"
    args.output.parent.mkdir(parents=True, exist_ok=True)
    args.output.write_text(rendered)
    print(rendered, end="")
    print(f"SHA256={hashlib.sha256(rendered.encode()).hexdigest()}")


if __name__ == "__main__":
    main()