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McGill-NLP/AfriqueQwen3.5-0.8B-50Langs · HellaSwag (full validation, character-normalized accuracy) · 50.2% accuracy_char_normalized

Full benchmark split · 10042 scored examples. Full pinned split; primary character-normalized accuracy: argmax summed conditional answer-token log likelihood divided by Python len(choice), excluding the leading delimiter; raw accuracy is a separate diagnostic. Explicit pinned prompt schema, no chat/BOS. Left context truncated only if prompt plus answer exceeds 1024 tokens. Generic text diagnostic does not validate specialist declared tasks.

Run ID / completed

0ee6969a29784e0e6f9e166a
17 Oct 2026, 16:22 UTC

Model revision

f49099d79e51bbb783fae622877c4c3415142c82

Comparison scope

e83048a65cc6e110ed09bc40c410945ce72105f15f101b049aa100bf096278dd

Evaluator SHA-256

eb01abebdaa64a9d8003d37b2006b198582b99f61377a6fe6d0645db15934307

Observed resources

511s elapsed · 5.55 GiB peak torch allocation
Dollar cost: not measured

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result.json samples.jsonl environment.json evaluate.py manifest.json

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Scored examples: 10,042
Passed: 5,037
Failed: 5,005
Metric: accuracy_char_normalized

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