Experiment · browser product

Browser default corpus fix

Default data is part of the product claim; a training demo's default corpus must produce non-memorized samples. Retained outcome: worked with caveat.

Outcome
worked with caveat
Family
browser product
Evidence confidence
exact
Record
infrastructure

Evidence readout

the old default corpus was `863 bytes`; a Huge model memorized it with train loss `0.14`; default changed to TinyShakespeare at about `1.1 MB`

What the attempt taught

Default data is part of the product claim; a training demo's default corpus must produce non-memorized samples.

Why it stopped or stayed bounded

The demo was trying to prove learning with a corpus so small that memorization looked like training success.

Method and scope

  • Experiment family: browser product.
  • Record kind: infrastructure.

Disposition

Keep corpus defaults in the same parity review as model and optimizer defaults.

This retained disposition is historical evidence, not authorization to restart the experiment. A new run needs a fresh question, frozen evaluator, explicit resource budget, and scoped tracking issue.

How to read this dossier

This canonical page separates the retained repository decision from the material that informed it. A source may describe an external claim, historical measurement, local observation, or planned procedure; those evidence classes are not interchangeable. Follow the provenance links before reusing a number or method.

Status and disposition describe what PostTrainLLM retained when this record was indexed. They are not a live product promise, a newly run benchmark, or permission to restart historical work. Unknown or unmeasured fields remain unknown rather than being treated as zero.

To reuse the record, first name the exact claim you need and trace it to the linked source. Then check whether the original environment, model revision, data split, evaluator, hardware, and budget match the proposed use. If they do not, treat the record as a hypothesis or design reference and run the smallest fresh comparison that can falsify it. Preserve negative outcomes and regressions beside any improvement; a local win on one slice does not silently become a general capability claim.

Source provenance

The normalized record comes from docs/attempts.json. The links below are the tracked evidence and explanatory sources preserved with the record.