arm
ag_bert_mini_n200_v1 baseline
One config on ag_news_200, scored one way; its repeats averaged per item.
- dataset
- ag_news_200
- scored against
- gold/ag_news_200 gold
- goal
- News topic classification (AG News)
- runs
- 1
- headline
- correct 0.945
- last run
- 2026-09-27 09:03
01metrics
| metric | mean | items | better |
|---|---|---|---|
| correct | 0.945 | 200 | higher |
| answer_words | 1.000 | 200 | neutral |
| confidence | 0.957 | 200 | neutral |
| correct_after_repair | 0.000 | 200 | neutral |
| cost_usd | $0.000000 | 200 | lower |
| fmt_markdown | 0.000 | 200 | neutral |
| fmt_verbose | 0.000 | 200 | neutral |
| latency_ms | 7.110 | 200 | lower |
| parsed | 1.000 | 200 | higher |
02cost and speed
- cost per item
- $0.000000
- speed per item
- p50 6.3 · p95 12 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 |
|---|---|---|---|---|
ag_bert_mini_n200_v1_20260927T090317Z | 2026-09-27 09:03 | 200 | $0.000000 | measured |
04config
config ag_bert_mini_n200_v1 · adapter examples/classification-ag-news/adapter.py · credentials are never shown
- device
cpu- family
bert- label_order
["World", "Sports", "Business", "Sci/Tech"]- model
mrm8488/bert-mini-finetuned-age_news-classification- precision
fp32- price_tier
free- provider
hf_local
05deploy sheet
- measured by
ag_bert_mini_n200_v1_20260927T090317Zon ag_news_200- against
- gold/ag_news_200
- model sent
mrm8488/bert-mini-finetuned-age_news-classification- model record
mrm8488-bert-mini-finetuned-age_news-classification- server
- not recorded
- build
- e94b474cce6f842ee5a90daa7352f5152fac4572
- settings sent
device: cpulabel_order: ["World", "Sports", "Business", "Sci/Tech"]model: mrm8488/bert-mini-finetuned-age_news-classificationprecision: fp32provider: hf_local- not sent
- bookkeeping:
family, price_tier - declared
deployment.encoder_window: 512deployment.label_order: ['World', 'Sports', 'Business', 'Sci/Tech']deployment.labels: ['World', 'Sports', 'Business', 'Sci/Tech']deployment.labels_sha256: c7a1ee508b78c0e92f28d159d340a6537ac31ff70ff566430fe2507da58464a3deployment.parser_sha256: 87f75633ea16670ab5a3169fe3125c91107f84959e79c56dd2f17c66a418246ddeployment.provider: hf_localdeployment.weight_files: ['model.safetensors:44698846']- adapter
examples/classification-ag-news/adapter.py8e4dffce3505- harness
- 1e80be6531e2
No capture here says what production ran (the adapter's production_ran).
Command: evh deploy-sheet --config ag_bert_mini_n200_v1 [--capture C]
06conditions
- data.items_sha256
d7bf61eb3b27e79d492bbe5a445659813dfcacf6fadcae4d26255c45291bedd2- deployment.build
e94b474cce6f842ee5a90daa7352f5152fac4572- deployment.device
cpu- deployment.model
mrm8488/bert-mini-finetuned-age_news-classification- deployment.quantization
fp32- deployment.source
adapter- fingerprint.version
5- library.numpy
1.26.4- library.openai
3.19.2- 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
e671b1a159664de82a0a5f35d36150d81abc99d45ac19e7df8ec1d66164bcc04- scorer.id
examples/classification-ag-news/adapter.py- scorer.sha256
8e4dffce35059b76949a0c95860cbcb5bd372fbdb6bdf33e0e55f4df78045b94
07the same config, scored other ways
scored against silverscored by a judgescored against a label set, not a reference setunmarked rows are scored against gold
| arm | scored against | headline | mean |
|---|---|---|---|
| ag_bert_mini_n200_v1 · adjudicated | gold/ag_news_200_adj1 gold | correct | 0.905 |
| ag_bert_mini_n200_v1 · linux | gold/ag_news_200 gold | correct | 0.945 |
08rounds
- Round r1 of News topic classification (AG News), closed: one of its arms.