eval-harness

metric

confidence

better
neutral: a description
kind
descriptive: says what the output was, never whether it was good
decides
no goal
weighed by
no goal
recorded on
ag_news_200, dbpedia_280

01what it measures, and how

The local classifier's probability for the label it chose (the top score of the fine-tune or the zero-shot NLI model). Not a quality: an input to calibration questions.

A project explains its own metric at length with METRIC_DESCRIPTIONS = {"confidence": {"summary": "…", "details": "…"}}.

02on ag_news_200

gold/ag_news_200ag_bert_base_fy_n200_v1: 0.989ag_bert_base_fy_n200_v1 · linux: 0.989ag_bert_base_ta_n200_v1: 0.986ag_bert_base_ta_n200_v1 · linux: 0.986ag_bert_mini_n200_v1 · linux: 0.957ag_bert_mini_n200_v1: 0.957ag_bart_mnli_n200_v1: 0.5720.572better · 0.989

scored against silverscored by a judgewrote the reference it is scored againstscored against a label set, not a reference setunmarked rows are scored against gold

03on dbpedia_280

gold/dbpedia_280db_bert_base_fy_n200_v1: 0.997db_bert_base_fy_n200_v1 · linux: 0.997db_bart_mnli_n200_v1: 0.3170.317better · 0.997

scored against silverscored by a judgewrote the reference it is scored againstscored against a label set, not a reference setunmarked rows are scored against gold