eval-harness

arm

sf_mpnet_n200_v1

One config on scifact_200, scored one way; its repeats averaged per item.

dataset
scifact_200
scored against
gold/scifact_200 gold
goal
Evidence retrieval for scientific claims (SciFact)
runs
1
headline
ndcg_10 0.664
last run
2026-09-28 17:46

Inspect itAgainst the baselineWith the 26 arms scored the same way

01metrics

metricmeanitemsbetter
ndcg_100.664200higher
cost_usd$0.000000200lower
duplicate_ids0.000200neutral
found_any0.935200neutral
latency_ms65.4200lower
mrr_100.635200higher
n_relevant1.135200neutral
n_returned100.0200neutral
parsed1.000200higher
rank_of_first6.880200neutral
recall_100.771200higher
recall_1000.935200higher
unknown_ids0.000200neutral

02cost and speed

cost per item
$0.000000
speed per item
p50 61 · p95 92 ms

Per item, over its items: cost as dollars and tokens (a local model is free but still uses tokens), speed as the median and the slow tail (p95). A goal that names this arm weighs them in its decision.

03runs

runmadeitemscosthow
sf_mpnet_n200_v1_20260928T174635Z2026-09-28 17:46200$0.000000reparse

04config

config sf_mpnet_n200_v1 · adapter examples/retrieval-scifact/adapter.py · credentials are never shown

corpus_id
scifact
device
cpu
encode_batch
32
family
mpnet
model
sentence-transformers/all-mpnet-base-v2
precision
fp32
price_tier
free
provider
dense
top_k
100

05conditions

data.items_sha256
b97dfe735a78eb4978cde41e2ca9a0bff424de9e6a0a2bdada5d167e3423004d
deployment.build
e8c3b32edf5434bc2275fc9bab85f82640a19130
deployment.device
cpu
deployment.model
sentence-transformers/all-mpnet-base-v2
deployment.quantization
fp32
deployment.source
adapter
fingerprint.version
5
library.numpy
1.26.4
library.openai
3.19.2
library.scikit-learn
1.9.1
library.sentence-transformers
3.4.1
library.torch
2.2.2
library.transformers
4.55.4
machine.cpu_count
12
machine.label
mac-dev
machine.platform
Darwin/x86_64
machine.processor
i386
machine.python
3.11.8
machine.release
24.6.0
reference.sha256
b522e08017ebc7dd71c5627bccfdd688c5124096df8a5e6454684141bc361d99
scorer.id
examples/retrieval-scifact/adapter.py
scorer.sha256
46cd2bd89061c9f3bff0493cce7ab292dd6f9b1bae7c7e482af0aebdd1479cee

06rounds