Datasetpublic

dwidlee/systemone-lite-general

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… See the full description on the dataset page: https://huggingface.co/datasets/dwidlee/systemone-lite-general.

sourceHugging Facemitupdated 6d agoView on Hugging Face

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Dataset Card

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

python

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