arm
cnn_bart_l_v1
One config on cnn_dailymail_20, scored one way; its repeats averaged per item.
- dataset
- cnn_dailymail_20
- scored against
- gold/cnn_dailymail_20 gold
- goal
- Short news summaries (CNN)
- runs
- 1
- headline
- coverage 0.366
- last run
- 2026-09-26 15:37
01metrics
| metric | mean | items | better |
|---|---|---|---|
| coverage | 0.366 | 20 | higher |
| compression | 0.134 | 20 | neutral |
| concision | 0.282 | 20 | higher |
| cost_usd | $0.000000 | 20 | lower |
| fmt_bullets | 0.000 | 20 | neutral |
| fmt_label | 0.000 | 20 | neutral |
| fmt_markdown | 0.000 | 20 | neutral |
| fmt_narration | 0.000 | 20 | neutral |
| fmt_overlong | 0.000 | 20 | neutral |
| fmt_paragraphs | 0.000 | 20 | neutral |
| grounding | 0.871 | 20 | higher |
| input_truncated | 0.200 | 20 | neutral |
| latency_ms | 11861.3 | 20 | lower |
| length_vs_reference | 1.467 | 20 | neutral |
| reference_words | 36.7 | 20 | neutral |
| rouge1 | 0.358 | 20 | higher |
| rougeLsum | 0.330 | 20 | higher |
| summary_words | 50.3 | 20 | neutral |
| tokens_in | 665.8 | 20 | lower |
| tokens_out | 66.2 | 20 | lower |
02cost and speed
- cost per item
- $0.000000 · 732 tok
- speed per item
- p50 11,468 · p95 17,811 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 |
|---|---|---|---|---|
cnn_bart_l_v1_20260926T153353Z | 2026-09-26 15:37 | 20 | $0.000000 | measured |
04config
config cnn_bart_l_v1 · adapter examples/summarization-cnn-dailymail/adapter.py · credentials are never shown
- device
cpu- early_stopping
true- family
bart- length_penalty
2.0- max_length
142- min_length
56- model
facebook/bart-large-cnn- no_repeat_ngram_size
3- num_beams
4- precision
fp32- price_tier
free- provider
hf_local
05conditions
- data.items_sha256
ea2e08a2214a375f00db936da844b4592fd2cd3f93d1f1460735231b7bb83f02- deployment.build
37f520fa929c961707657b28798b30c003dd100b- deployment.device
cpu- deployment.model
facebook/bart-large-cnn- deployment.quantization
fp32- deployment.source
adapter- fingerprint.version
5- library.numpy
1.26.4- library.openai
3.19.2- library.rouge-score
0.1.2- 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
7193289e59b4438f7191ddc149929d6ca637080154b9fca52d5ba3a7259c57a5- scorer.id
examples/summarization-cnn-dailymail/adapter.py- scorer.sha256
51a7b06b1a2eec722a3bd024b7ed832746d06ef44683dd0e9fa8abc5c18d5618