Datasets:

dwidlee
/

systemone-lite-general

license: mit
task_categories:
  - text-classification
language:
  - en
tags:
  - system-one
  - typed-decisions
  - synthetic
size_categories:
  - 10K<n<100K
pretty_name: systemone-lite-general
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: test
        path: data/test-*
      - split: test_hard
        path: data/test_hard-*
      - split: full
        path: data/full-*

systemone-lite-general

Synthetic typed-decision rows for systemone-lite (letter-alias choice labels for causal LM SFT).

Not affiliated with TypeSafe AI / Jev. Labels are rule-based, not human prefs.

Splits

Split	Rows	Notes
`train`	32 400	Stratified mix of 3 gyms
`test`	3 600	iid held-out by task
`test_hard`	5 400	layout / paraphrase / option-subset shift
`full`	36 000	train + iid test

Gyms

TicketDungeon: ticket.route, ticket.needs_human, ticket.urgency
ResourceAllocator: alloc.fund_next, alloc.can_fund_all, alloc.pressure
DebateJudge: debate.winner, debate.enough_evidence, debate.confidence

Downstream numbers (same repo)

Fine-tune → dwidlee/systemone-lite-0.5b:

Split	Base 0.5B	SFT
`test` (n=3600)	0.439	0.679
`test_hard` (n=5400)	0.427	0.652

Load

from datasets import load_dataset
ds = load_dataset("dwidlee/systemone-lite-general")
print(ds)