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HuggingFaceTB/SmolLM2-360M-Instruct · HellaSwag (full validation, character-normalized accuracy) · 56.8% 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

d7f995e63ea4c136510891e2
17 Oct 2026, 15:28 UTC

Model revision

a10cc1512eabd3dde888204e902eca88bddb4951

Comparison scope

9ba01dfd8954831947fc9d9e821f5c27a78509f522b87d05d07b1c4f172ae0e6

Evaluator SHA-256

8ba81403e69d93b8121bd05e0ea4f9c55e0dc5c721449f50adfda136d7d976f1

Observed resources

242s elapsed · 1.85 GiB peak torch allocation
Dollar cost: not measured

Download evidence

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

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Read the recorded prediction, reference and outcome for each example.

Scored examples: 10,042
Passed: 5,708
Failed: 4,334
Metric: accuracy_char_normalized

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