Datasets:
Tasks:
Text Classification
Formats:
parquet
Languages:
English
Size:
1K - 10K
Tags:
structured-decisions
calibration
probabilistic-classification
system-one
workflow-evaluation
Synthetic
License:
Commit History
Yesterday
-
bench: save per-decision probabilities and add them to the eval-results PR
Verified signaturescore_with_jobs.py already scores every decision but keeps only the summary. This PR: - writes `predictions.jsonl` next to `results.json`: one line per decision with case id, workflow, question id, type and the normalized probabilities over the gold options (the vector `score_one` scores, after the yes/no to true/false mapping); - has `submit_results.py` add that file to the model-repo PR as `eval/typed-decisions/predictions.jsonl` when it is present next to the results file (`--predictions` points elsewhere). Scoring is unchanged. Replaying a published Jev run (OpenDecider's whole-case file, which their benchmarks README lists as Jev 1.13 through TypeSafe's API) through both versions with vLLM, HTTP and `datasets` mocked gives a byte-identical `results.json` (accuracy 0.7305), and re-scoring `predictions.jsonl` gives the same accuracy, KL, Brier and ECE. The tie rule (first-listed option vs split credit) is left for a separate change; with the probabilities saved it can be re-appli…0f4bce1
16 days ago
-
Add HF Jobs how-to for benchmarking a model (#42)
- Add HF Jobs how-to for benchmarking a model (4cca1526864ab7819b5e298f1e5111249d7511c6) - Add bench/ scripts referenced by the README section (1ce7b5db35b4d7f6d5cb6c38d49cd775e301132c) Co-authored-by: Nathan Habib <SaylorTwift@users.noreply.huggingface.co>e49e13d -
Add HF Jobs how-to for benchmarking a model (#40)
- Add HF Jobs how-to for benchmarking a model (ffabd9610489d71ca05bef053191a42e031690ff) - Add bench/score_with_jobs.{sh,py} referenced by the README section (b1cf7e94404c41ccd5118ebb1337777789cee6af) Co-authored-by: Nathan Habib <SaylorTwift@users.noreply.huggingface.co>e742f0a
