arm
sf_glm_s_e5first_n200_v1 · pair
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 0.789
- last run
- 2026-09-28 22:23
Inspect itAgainst the baselineWith the 26 arms scored the same way
01metrics
| metric | mean | items | better |
|---|---|---|---|
| ndcg_10 | 0.789 | 200 | higher |
| cost_usd | $0.000732 | 200 | lower |
| duplicate_ids | 0.000 | 200 | neutral |
| found_any | 0.955 | 200 | neutral |
| latency_ms | 3126.9 | 200 | lower |
| llm_named_unknown | 0.000 | 200 | neutral |
| llm_parsed | 1.000 | 200 | neutral |
| mrr_10 | 0.774 | 200 | higher |
| n_relevant | 1.135 | 200 | neutral |
| n_returned | 100.0 | 200 | neutral |
| parsed | 1.000 | 200 | higher |
| rank_of_first | 5.770 | 200 | neutral |
| reasoning_tokens | 0.000 | 200 | neutral |
| recall_10 | 0.860 | 200 | higher |
| recall_100 | 0.954 | 200 | higher |
| tokens_in | 4030.2 | 200 | lower |
| tokens_out | 147.9 | 200 | lower |
| truncated | 0.000 | 200 | neutral |
| unknown_ids | 0.000 | 200 | neutral |
02cost and speed
- cost per item
- $0.000732 · 4,178 tok
- speed per item
- p50 3,007 · p95 4,028 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
| run | made | items | cost | how |
|---|---|---|---|---|
sf_glm_s_e5first_n200_v1_20260928T222308Z | 2026-09-28 22:23 | 200 | $0.146351 | reparse |
04config
config sf_glm_s_e5first_n200_v1 · adapter examples/retrieval-scifact/adapter.py · credentials are never shown
- corpus_id
scifact- family
glm- first_stage
dense- first_stage_doc_prefix
passage:- first_stage_model
intfloat/e5-base-v2- first_stage_query_prefix
query:- max_tokens
700- model
eval-glm-45-air- price_tier
small- prompt_file
prompt.txt- provider
rerank- reasoning
{"enabled": false}- rerank_k
20- snippet_chars
900- temperature
0.0- top_k
100- usd_per_mtok_in
0.06- usd_per_mtok_out
0.22
05conditions
- data.items_sha256
b97dfe735a78eb4978cde41e2ca9a0bff424de9e6a0a2bdada5d167e3423004d- deployment.model
eval-glm-45-air- 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
540198a7e22168501277ba6644f00e3b655d594b7c7460bc7c75e0915dd3b7b1
06rounds
- Round r2 of Evidence retrieval for scientific claims (SciFact), closed: retired in it.