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Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
seed_tag: string
n_prob: int64
metrics: struct<orm_rerank@1: double, oracle@1: double, orm_rerank@2: double, oracle@2: double, orm_rerank@4: (... 150 chars omitted)
child 0, orm_rerank@1: double
child 1, oracle@1: double
child 2, orm_rerank@2: double
child 3, oracle@2: double
child 4, orm_rerank@4: double
child 5, oracle@4: double
child 6, orm_rerank@8: double
child 7, oracle@8: double
child 8, orm_rerank@16: double
child 9, oracle@16: double
child 10, orm_rerank@32: double
child 11, oracle@32: double
per_problem_scores: struct<0: list<item: struct<correct: bool, orm_score: double>>, 1: list<item: struct<correct: bool, (... 29296 chars omitted)
child 0, 0: list<item: struct<correct: bool, orm_score: double>>
child 0, item: struct<correct: bool, orm_score: double>
child 0, correct: bool
child 1, orm_score: double
child 1, 1: list<item: struct<correct: bool, orm_score: double>>
child 0, item: struct<correct: bool, orm_score: double>
child 0, correct: bool
child 1, orm_score: double
child 2, 2: list<item: struct<correct: bool, orm_score: double>>
child 0, item: struct<correct: bool, orm_score: double>
child 0, correct: bool
child 1, orm_score: double
child 3, 3: list<item: struct<correct: bool, orm_score: double>>
child 0, item: struct<correct: bool, orm_score: double>
child 0, correct: bool
child 1, orm_score: double
child 4, 4: list<item: s
...
nt64>
child 0, acc: double
child 1, n_correct: int64
child 2, n_total: int64
child 2, N=8: struct<acc: double, n_correct: int64, n_total: int64>
child 0, acc: double
child 1, n_correct: int64
child 2, n_total: int64
child 3, N=16: struct<acc: double, n_correct: int64, n_total: int64>
child 0, acc: double
child 1, n_correct: int64
child 2, n_total: int64
child 4, N=32: struct<acc: double, n_correct: int64, n_total: int64>
child 0, acc: double
child 1, n_correct: int64
child 2, n_total: int64
s42: struct<N=2: struct<acc: double, n_correct: int64, n_total: int64>, N=4: struct<acc: double, n_correc (... 208 chars omitted)
child 0, N=2: struct<acc: double, n_correct: int64, n_total: int64>
child 0, acc: double
child 1, n_correct: int64
child 2, n_total: int64
child 1, N=4: struct<acc: double, n_correct: int64, n_total: int64>
child 0, acc: double
child 1, n_correct: int64
child 2, n_total: int64
child 2, N=8: struct<acc: double, n_correct: int64, n_total: int64>
child 0, acc: double
child 1, n_correct: int64
child 2, n_total: int64
child 3, N=16: struct<acc: double, n_correct: int64, n_total: int64>
child 0, acc: double
child 1, n_correct: int64
child 2, n_total: int64
child 4, N=32: struct<acc: double, n_correct: int64, n_total: int64>
child 0, acc: double
child 1, n_correct: int64
child 2, n_total: int64
to
{'s42': {'N=2': {'acc': Value('float64'), 'n_correct': Value('int64'), 'n_total': Value('int64')}, 'N=4': {'acc': Value('float64'), 'n_correct': Value('int64'), 'n_total': Value('int64')}, 'N=8': {'acc': Value('float64'), 'n_correct': Value('int64'), 'n_total': Value('int64')}, 'N=16': {'acc': Value('float64'), 'n_correct': Value('int64'), 'n_total': Value('int64')}, 'N=32': {'acc': Value('float64'), 'n_correct': Value('int64'), 'n_total': Value('int64')}}, 's43': {'N=2': {'acc': Value('float64'), 'n_correct': Value('int64'), 'n_total': Value('int64')}, 'N=4': {'acc': Value('float64'), 'n_correct': Value('int64'), 'n_total': Value('int64')}, 'N=8': {'acc': Value('float64'), 'n_correct': Value('int64'), 'n_total': Value('int64')}, 'N=16': {'acc': Value('float64'), 'n_correct': Value('int64'), 'n_total': Value('int64')}, 'N=32': {'acc': Value('float64'), 'n_correct': Value('int64'), 'n_total': Value('int64')}}}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
return get_rows(
^^^^^^^^^
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2690, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2227, in __iter__
for key, pa_table in self._iter_arrow():
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2251, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 494, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 384, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 299, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 128, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2321, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2249, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
seed_tag: string
n_prob: int64
metrics: struct<orm_rerank@1: double, oracle@1: double, orm_rerank@2: double, oracle@2: double, orm_rerank@4: (... 150 chars omitted)
child 0, orm_rerank@1: double
child 1, oracle@1: double
child 2, orm_rerank@2: double
child 3, oracle@2: double
child 4, orm_rerank@4: double
child 5, oracle@4: double
child 6, orm_rerank@8: double
child 7, oracle@8: double
child 8, orm_rerank@16: double
child 9, oracle@16: double
child 10, orm_rerank@32: double
child 11, oracle@32: double
per_problem_scores: struct<0: list<item: struct<correct: bool, orm_score: double>>, 1: list<item: struct<correct: bool, (... 29296 chars omitted)
child 0, 0: list<item: struct<correct: bool, orm_score: double>>
child 0, item: struct<correct: bool, orm_score: double>
child 0, correct: bool
child 1, orm_score: double
child 1, 1: list<item: struct<correct: bool, orm_score: double>>
child 0, item: struct<correct: bool, orm_score: double>
child 0, correct: bool
child 1, orm_score: double
child 2, 2: list<item: struct<correct: bool, orm_score: double>>
child 0, item: struct<correct: bool, orm_score: double>
child 0, correct: bool
child 1, orm_score: double
child 3, 3: list<item: struct<correct: bool, orm_score: double>>
child 0, item: struct<correct: bool, orm_score: double>
child 0, correct: bool
child 1, orm_score: double
child 4, 4: list<item: s
...
nt64>
child 0, acc: double
child 1, n_correct: int64
child 2, n_total: int64
child 2, N=8: struct<acc: double, n_correct: int64, n_total: int64>
child 0, acc: double
child 1, n_correct: int64
child 2, n_total: int64
child 3, N=16: struct<acc: double, n_correct: int64, n_total: int64>
child 0, acc: double
child 1, n_correct: int64
child 2, n_total: int64
child 4, N=32: struct<acc: double, n_correct: int64, n_total: int64>
child 0, acc: double
child 1, n_correct: int64
child 2, n_total: int64
s42: struct<N=2: struct<acc: double, n_correct: int64, n_total: int64>, N=4: struct<acc: double, n_correc (... 208 chars omitted)
child 0, N=2: struct<acc: double, n_correct: int64, n_total: int64>
child 0, acc: double
child 1, n_correct: int64
child 2, n_total: int64
child 1, N=4: struct<acc: double, n_correct: int64, n_total: int64>
child 0, acc: double
child 1, n_correct: int64
child 2, n_total: int64
child 2, N=8: struct<acc: double, n_correct: int64, n_total: int64>
child 0, acc: double
child 1, n_correct: int64
child 2, n_total: int64
child 3, N=16: struct<acc: double, n_correct: int64, n_total: int64>
child 0, acc: double
child 1, n_correct: int64
child 2, n_total: int64
child 4, N=32: struct<acc: double, n_correct: int64, n_total: int64>
child 0, acc: double
child 1, n_correct: int64
child 2, n_total: int64
to
{'s42': {'N=2': {'acc': Value('float64'), 'n_correct': Value('int64'), 'n_total': Value('int64')}, 'N=4': {'acc': Value('float64'), 'n_correct': Value('int64'), 'n_total': Value('int64')}, 'N=8': {'acc': Value('float64'), 'n_correct': Value('int64'), 'n_total': Value('int64')}, 'N=16': {'acc': Value('float64'), 'n_correct': Value('int64'), 'n_total': Value('int64')}, 'N=32': {'acc': Value('float64'), 'n_correct': Value('int64'), 'n_total': Value('int64')}}, 's43': {'N=2': {'acc': Value('float64'), 'n_correct': Value('int64'), 'n_total': Value('int64')}, 'N=4': {'acc': Value('float64'), 'n_correct': Value('int64'), 'n_total': Value('int64')}, 'N=8': {'acc': Value('float64'), 'n_correct': Value('int64'), 'n_total': Value('int64')}, 'N=16': {'acc': Value('float64'), 'n_correct': Value('int64'), 'n_total': Value('int64')}, 'N=32': {'acc': Value('float64'), 'n_correct': Value('int64'), 'n_total': Value('int64')}}}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
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Check out the documentation for more information.
MATH500 OOD Stress Test
GSM8K-trained ORM does not transfer to MATH500; Majority becomes the stronger baseline.
Files
math500_orm_rerank_s{42,43}.json— per-problem ORM scores on Vanilla N=32 trajectories.math500_pareto_full.json— aggregated Pareto across N.math500_rescored/s{42,43}_rescored.json— re-verified per-problem correctness via the LaTeX-robustmath-verifygrader.math500_majority_aggregated_v3.json— Majority@N via canonical SymPy clustering. Recommended source for MATH500 Majority numbers.
Numbers (mean ± sample std)
| Method (n_seeds) | N=2 | N=4 | N=8 | N=16 | N=32 |
|---|---|---|---|---|---|
| Majority@N (n=2) | 7.10 ± 0.99 | 8.70 ± 1.56 | 13.20 ± 0.28 | 15.40 ± 1.13 | 17.20 ± 0.85 |
| ORM Rerank@N (n=2) | 6.60 ± 0.57 | 7.40 ± 1.13 | 6.70 ± 0.71 | 7.50 ± 1.84 | 6.10 ± 0.14 |
| PRM-Guided K=N, be=64 | 13.45 ± 0.68 (n=4) | 14.00 ± 1.23 (n=4) | 13.72 ± 0.84 (n=5) | 14.35 ± 0.41 (n=4) | 15.00 ± 1.13 (n=2) |
| Oracle@N (n=2) | 12.00 ± 0.57 | 21.90 ± 0.99 | 31.10 ± 0.14 | 42.70 ± 0.14 | 54.10 ± 0.14 |
Vanilla N=1 = 6.90% (1 seed). At N=1, Majority/ORM/Oracle reduce to Vanilla.
Sampler caveat
Vanilla MATH500 uses temperature 1.0, alg_temp 0; PRM-Guided uses temperature 0.5, alg_temp 0.5. MATH500 is OOD, not sampler-controlled.
Reproduce
python -m src.prm.score_math500_orm \
--seed_tag s42 \
--orm_checkpoint <path-to-bidir-orm-dream7b>
python -m src.evaluation.aggregate_math500_majority \
--trajectory_dir ./data/prm_trajectories \
--output_path ./eval_results/math500_majority.json \
--seed_tags 42,43
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