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Embeddings / STS Benchmark

Sentence similarity

Two sentences → semantic similarity

Model size vs score

Model size versus spearmansentence-transformers/all-MiniLM-L6-v2: 22.71 million parameters; score 0.924. All points use the same pinned protocol.0-1.005-0.6010-0.20160.20210.60261.00sentence-transformers/all-MiniLM-L6-v2 · 22.71M parameters · 0.924Model parameters (millions)spearman · higher is better

1 compatible measurements. Parameter counts come from the architecture instantiated from each pinned model configuration; no weights are loaded for this count. Click a point to inspect its evidence.

Measured results

Pilot comparison · first 32 valid examples · spearman higher is better. No global SOTA claim.

SystemScoreSamplesElapsed¹Evidence
sentence-transformers/all-MiniLM-L6-v2
1110a243fdf4
0.924321sInspect run →
16 Oct 2026, 23:28 UTC

¹ Evaluation elapsed time includes model loading after dataset selection. It is not serving latency or a fair speed comparison.

What this measures

Benchmark origin
Dataset / split
Immutable dataset revision
ab7a5ac0e35aa22088bdcf23e7fd99b220e53308
Upstream license metadata
See upstream terms · consult upstream terms
Protocol
codesota-pilot-v1 / similarity
Selection
First 32 valid examples in the pinned split order. SNLI rows without a valid label are excluded.
Configuration
Seed 42. Greedy generation for math and code. Mean answer-token log likelihood for text classification, completion and declarative multiple-choice recipes. No model judge.
Read scoring and comparison rules →

Planned runs

0 qualified visits in 30 days · priority 32.6. Interest changes execution order, within the approved baseline list.

SystemStatus
sentence-transformers/all-MiniLM-L6-v2completed