Datasets:
File size: 1,740 Bytes
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pretty_name: FineProofs PRM Context v2 - Solution
task_categories:
- text-classification
tags:
- process-reward-model
- theorem-proving
- fineproofs
configs:
- config_name: default
data_files:
- split: train
path: train.parquet
- split: validation
path: validation.parquet
---
# FineProofs PRM Context v2: Solution
This arm uses `solution` context from `same_problem` rollouts with packing policy `whole_solutions_no_truncation`.
This is one of nine row-matched context variants built from the verified FineProofs rollout collection. Partial-prefix and complete-response targets both use canonical normalized rubric credit derived from clamped points divided by max points. The `correct` column is only a legacy boolean projection at reward >= 0.5; training uses the dense `reward` target.
## Contract
- Run ID: `fineproofs_all_qwen35_9b_direct2phase_m32_20260730`
- Collection model: `Qwen/Qwen3.5-9B`
- Collection model revision: `c202236235762e1c871ad0ccb60c8ee5ba337b9a`
- Context arm: `solution`
- Context mode: `solution`
- Context scope: `same_problem`
- Correctness labels in context: `no`
- Verification SHA-256: `c5a3b92bd6196d4a33cded2c1a01870d1963d323351d573b369b7f97f3b7f648`
The nine arms have identical row keys, labels, rewards, train/validation problem split, and hard endpoint coverage. Held-out problems are removed before splitting and context selection.
## Splits
| Split | Rows | Problems |
| --- | ---: | ---: |
| train | 53,457 | 2,542 |
| validation | 2,602 | 128 |
The local `val.parquet` is published as `validation.parquet`. `dataset_provenance.json`, `verification.json`, and `_SUCCESS.json` contain the live-input provenance, cross-arm checks, and exact published file fingerprints.
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