Samples · lm_eval_harness.humaneval

Run #67 · Adapter v1.0.0+humaneval-unsafe-flag · 164/164 Samples angezeigt · Score 0%
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KI-Auswertung

Generiert 2026-05-12 19:41 · claude-sonnet-4-6

Zusammenfassung

Das Modell erreicht eine Pass-Rate von 0 % auf dem HumanEval-Benchmark (0 von 164 Aufgaben bestanden). Kein einziger Testfall wurde erfolgreich abgeschlossen.

Stärken

  • Das Modell produziert keine Laufzeitfehler (0 Errors), die Ausgaben sind syntaktisch verarbeitbar.
  • Die generierten Erklärungen zeigen korrektes konzeptionelles Verständnis der Aufgaben (z. B. Sortier-Optimierung, Balancenzählung).

Schwächen

  • Das Modell gibt ausnahmslos unvollständigen Code zurück: Es beginnt einen Markdown-Codeblock mit ` ```python ` und bricht dann ab, bevor die eigentliche Implementierung folgt.
  • Kein einziger funktionsfähiger Funktionskörper wird generiert, weshalb alle Doctests fehlschlagen.

Auffälligkeiten

Es gibt ein einheitliches, deterministisches Fehlermuster: Jede Antwort besteht aus erklärendem Prosatext gefolgt von einem eingeleiteten, aber leeren oder abgebrochenen Python-Codeblock. Das Stop-Sequenz-Kriterium (`\ndef`, `\nclass` etc.) greift vermutlich zu früh und schneidet die eigentliche Funktionsdefinition ab. Da `do_sample=false` gesetzt ist, tritt dieser Fehler reproduzierbar bei allen 164 Aufgaben auf. Das Problem liegt nicht in der Modellqualität, sondern in der Konfiguration der Stop-Sequenzen.

Empfehlung

Die Stop-Sequenzen im Harness-Adapter anpassen: `\ndef` sollte nicht als Stoppbedingung gelten, da Lösungen häufig mit einer `def`-Zeile beginnen oder Helper-Funktionen enthalten. Alternativ das Prompt-Format auf Completion-Stil (ohne Chat-Wrapper) umstellen, sodass das Modell direkt in den Funktionskörper generiert, ohne einen Markdown-Codeblock einzuleiten.

Übersicht

164 Samples
Verteilung
164
Score-Histogramm
0 – 0.1: 164 0.1 – 0.2: 0 0.2 – 0.3: 0 0.3 – 0.4: 0 0.4 – 0.5: 0 0.5 – 0.6: 0 0.6 – 0.7: 0 0.7 – 0.8: 0 0.8 – 0.9: 0 0.9 – 1: 0
0.0 ────── 1.0
Status Score-Schwelle Score < 0.5
Frage-ID Status Score Prompt Latenz Tokens/s TTFT
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163 failed 0% {…} {"gen_args_0":{"arg_0":["[{\"role\": \"user\", \"content\": \"\\ndef generate_in…
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