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asingh15
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fineproofs-branch-rollout-distribution

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The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
built_at_utc: string
incomplete_sampled_trace_count: int64
max_reasoning_chars: int64
offset_unit: string
problem_count: int64
run_id: string
schema_version: string
shard_count: int64
shards: list<item: struct<compressed_bytes: int64, incomplete_sampled_trace_count: int64, name: string, prob (... 78 chars omitted)
  child 0, item: struct<compressed_bytes: int64, incomplete_sampled_trace_count: int64, name: string, problem_count:  (... 66 chars omitted)
      child 0, compressed_bytes: int64
      child 1, incomplete_sampled_trace_count: int64
      child 2, name: string
      child 3, problem_count: int64
      child 4, reasoning_chars: int64
      child 5, sha256: string
      child 6, trace_count: int64
total_reasoning_chars: int64
trace_count: int64
trajectory_patterns: struct<falling: int64, flat: int64, rising: int64, volatile: int64>
  child 0, falling: int64
  child 1, flat: int64
  child 2, rising: int64
  child 3, volatile: int64
point_fields: list<item: string>
  child 0, item: string
base_endpoints: struct<count: int64, grade_at_least_half_count: int64, grade_below_half_count: int64, histogram: str (... 179 chars omitted)
  child 0, count: int64
  child 1, grade_at_least_half_count: int64
  child 2, grade_below_half_count: int64
  child 3, histogram: struct<counts: list<item: int64>, edges: list<item: double>>
      child 0, counts: list<item: int64>
          child 0, item: int64
      child 1, edges: list<item: double>
          child 0, item: double
  child 4, m
...
 child 73, 80: int64
  child 74, 81: int64
  child 75, 82: int64
  child 76, 84: int64
  child 77, 86: int64
  child 78, 88: int64
  child 79, 93: int64
  child 80, 95: int64
  child 81, 97: int64
  child 82, 100: int64
  child 83, 111: int64
  child 84, 113: int64
  child 85, 114: int64
  child 86, 115: int64
  child 87, 125: int64
  child 88, 128: int64
  child 89, 132: int64
  child 90, 156: int64
prefix_values: struct<count: int64, exact_one_count: int64, exact_zero_count: int64, histogram: struct<counts: list (... 163 chars omitted)
  child 0, count: int64
  child 1, exact_one_count: int64
  child 2, exact_zero_count: int64
  child 3, histogram: struct<counts: list<item: int64>, edges: list<item: double>>
      child 0, counts: list<item: int64>
          child 0, item: int64
      child 1, edges: list<item: double>
          child 0, item: double
  child 4, max: double
  child 5, mean: double
  child 6, median: double
  child 7, min: double
  child 8, p10: double
  child 9, p25: double
  child 10, p75: double
  child 11, p90: double
  child 12, std: double
construction: struct<continuation_grades: int64, continuations_per_prefix: int64, prefix_rows: int64, selected_bas (... 119 chars omitted)
  child 0, continuation_grades: int64
  child 1, continuations_per_prefix: int64
  child 2, prefix_rows: int64
  child 3, selected_base_trajectories: int64
  child 4, semantic_problem_prefixes: int64
  child 5, skipped_non_grade_journal_rows: int64
  child 6, source_problems: int64
to
{'base_endpoints': {'count': Value('int64'), 'grade_at_least_half_count': Value('int64'), 'grade_below_half_count': Value('int64'), 'histogram': {'counts': List(Value('int64')), 'edges': List(Value('float64'))}, 'max': Value('float64'), 'mean': Value('float64'), 'median': Value('float64'), 'min': Value('float64'), 'p10': Value('float64'), 'p25': Value('float64'), 'p75': Value('float64'), 'p90': Value('float64'), 'std': Value('float64')}, 'built_at_utc': Value('string'), 'construction': {'continuation_grades': Value('int64'), 'continuations_per_prefix': Value('int64'), 'prefix_rows': Value('int64'), 'selected_base_trajectories': Value('int64'), 'semantic_problem_prefixes': Value('int64'), 'skipped_non_grade_journal_rows': Value('int64'), 'source_problems': Value('int64')}, 'continuation_grades': {'at_least_half_credit_count': Value('int64'), 'count': Value('int64'), 'full_credit_count': Value('int64'), 'histogram': {'counts': List(Value('int64')), 'edges': List(Value('float64'))}, 'max': Value('float64'), 'mean': Value('float64'), 'median': Value('float64'), 'min': Value('float64'), 'p10': Value('float64'), 'p25': Value('float64'), 'p75': Value('float64'), 'p90': Value('float64'), 'partial_count': Value('int64'), 'std': Value('float64'), 'truncated_count': Value('int64'), 'zero_count': Value('int64')}, 'depth_summary': List({'count': Value('int64'), 'depth_bin': Value('int64'), 'group': Value('string'), 'max': Value('float64'), 'mean': Value('float64'), 'median': Value('float6
...
': Value('int64'), '31': Value('int64'), '32': Value('int64'), '33': Value('int64'), '34': Value('int64'), '35': Value('int64'), '36': Value('int64'), '37': Value('int64'), '38': Value('int64'), '39': Value('int64'), '40': Value('int64'), '41': Value('int64'), '42': Value('int64'), '43': Value('int64'), '44': Value('int64'), '45': Value('int64'), '46': Value('int64'), '47': Value('int64'), '48': Value('int64'), '49': Value('int64'), '50': Value('int64'), '51': Value('int64'), '52': Value('int64'), '53': Value('int64'), '54': Value('int64'), '55': Value('int64'), '56': Value('int64'), '57': Value('int64'), '58': Value('int64'), '59': Value('int64'), '60': Value('int64'), '61': Value('int64'), '62': Value('int64'), '63': Value('int64'), '64': Value('int64'), '65': Value('int64'), '66': Value('int64'), '67': Value('int64'), '68': Value('int64'), '70': Value('int64'), '74': Value('int64'), '75': Value('int64'), '76': Value('int64'), '78': Value('int64'), '80': Value('int64'), '81': Value('int64'), '82': Value('int64'), '84': Value('int64'), '86': Value('int64'), '88': Value('int64'), '93': Value('int64'), '95': Value('int64'), '97': Value('int64'), '100': Value('int64'), '111': Value('int64'), '113': Value('int64'), '114': Value('int64'), '115': Value('int64'), '125': Value('int64'), '128': Value('int64'), '132': Value('int64'), '156': Value('int64')}, 'trajectory_patterns': {'falling': Value('int64'), 'flat': Value('int64'), 'rising': Value('int64'), 'volatile': Value('int64')}}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 149, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                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 129, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 489, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2818, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2355, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2380, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              built_at_utc: string
              incomplete_sampled_trace_count: int64
              max_reasoning_chars: int64
              offset_unit: string
              problem_count: int64
              run_id: string
              schema_version: string
              shard_count: int64
              shards: list<item: struct<compressed_bytes: int64, incomplete_sampled_trace_count: int64, name: string, prob (... 78 chars omitted)
                child 0, item: struct<compressed_bytes: int64, incomplete_sampled_trace_count: int64, name: string, problem_count:  (... 66 chars omitted)
                    child 0, compressed_bytes: int64
                    child 1, incomplete_sampled_trace_count: int64
                    child 2, name: string
                    child 3, problem_count: int64
                    child 4, reasoning_chars: int64
                    child 5, sha256: string
                    child 6, trace_count: int64
              total_reasoning_chars: int64
              trace_count: int64
              trajectory_patterns: struct<falling: int64, flat: int64, rising: int64, volatile: int64>
                child 0, falling: int64
                child 1, flat: int64
                child 2, rising: int64
                child 3, volatile: int64
              point_fields: list<item: string>
                child 0, item: string
              base_endpoints: struct<count: int64, grade_at_least_half_count: int64, grade_below_half_count: int64, histogram: str (... 179 chars omitted)
                child 0, count: int64
                child 1, grade_at_least_half_count: int64
                child 2, grade_below_half_count: int64
                child 3, histogram: struct<counts: list<item: int64>, edges: list<item: double>>
                    child 0, counts: list<item: int64>
                        child 0, item: int64
                    child 1, edges: list<item: double>
                        child 0, item: double
                child 4, m
              ...
               child 73, 80: int64
                child 74, 81: int64
                child 75, 82: int64
                child 76, 84: int64
                child 77, 86: int64
                child 78, 88: int64
                child 79, 93: int64
                child 80, 95: int64
                child 81, 97: int64
                child 82, 100: int64
                child 83, 111: int64
                child 84, 113: int64
                child 85, 114: int64
                child 86, 115: int64
                child 87, 125: int64
                child 88, 128: int64
                child 89, 132: int64
                child 90, 156: int64
              prefix_values: struct<count: int64, exact_one_count: int64, exact_zero_count: int64, histogram: struct<counts: list (... 163 chars omitted)
                child 0, count: int64
                child 1, exact_one_count: int64
                child 2, exact_zero_count: int64
                child 3, histogram: struct<counts: list<item: int64>, edges: list<item: double>>
                    child 0, counts: list<item: int64>
                        child 0, item: int64
                    child 1, edges: list<item: double>
                        child 0, item: double
                child 4, max: double
                child 5, mean: double
                child 6, median: double
                child 7, min: double
                child 8, p10: double
                child 9, p25: double
                child 10, p75: double
                child 11, p90: double
                child 12, std: double
              construction: struct<continuation_grades: int64, continuations_per_prefix: int64, prefix_rows: int64, selected_bas (... 119 chars omitted)
                child 0, continuation_grades: int64
                child 1, continuations_per_prefix: int64
                child 2, prefix_rows: int64
                child 3, selected_base_trajectories: int64
                child 4, semantic_problem_prefixes: int64
                child 5, skipped_non_grade_journal_rows: int64
                child 6, source_problems: int64
              to
              {'base_endpoints': {'count': Value('int64'), 'grade_at_least_half_count': Value('int64'), 'grade_below_half_count': Value('int64'), 'histogram': {'counts': List(Value('int64')), 'edges': List(Value('float64'))}, 'max': Value('float64'), 'mean': Value('float64'), 'median': Value('float64'), 'min': Value('float64'), 'p10': Value('float64'), 'p25': Value('float64'), 'p75': Value('float64'), 'p90': Value('float64'), 'std': Value('float64')}, 'built_at_utc': Value('string'), 'construction': {'continuation_grades': Value('int64'), 'continuations_per_prefix': Value('int64'), 'prefix_rows': Value('int64'), 'selected_base_trajectories': Value('int64'), 'semantic_problem_prefixes': Value('int64'), 'skipped_non_grade_journal_rows': Value('int64'), 'source_problems': Value('int64')}, 'continuation_grades': {'at_least_half_credit_count': Value('int64'), 'count': Value('int64'), 'full_credit_count': Value('int64'), 'histogram': {'counts': List(Value('int64')), 'edges': List(Value('float64'))}, 'max': Value('float64'), 'mean': Value('float64'), 'median': Value('float64'), 'min': Value('float64'), 'p10': Value('float64'), 'p25': Value('float64'), 'p75': Value('float64'), 'p90': Value('float64'), 'partial_count': Value('int64'), 'std': Value('float64'), 'truncated_count': Value('int64'), 'zero_count': Value('int64')}, 'depth_summary': List({'count': Value('int64'), 'depth_bin': Value('int64'), 'group': Value('string'), 'max': Value('float64'), 'mean': Value('float64'), 'median': Value('float6
              ...
              ': Value('int64'), '31': Value('int64'), '32': Value('int64'), '33': Value('int64'), '34': Value('int64'), '35': Value('int64'), '36': Value('int64'), '37': Value('int64'), '38': Value('int64'), '39': Value('int64'), '40': Value('int64'), '41': Value('int64'), '42': Value('int64'), '43': Value('int64'), '44': Value('int64'), '45': Value('int64'), '46': Value('int64'), '47': Value('int64'), '48': Value('int64'), '49': Value('int64'), '50': Value('int64'), '51': Value('int64'), '52': Value('int64'), '53': Value('int64'), '54': Value('int64'), '55': Value('int64'), '56': Value('int64'), '57': Value('int64'), '58': Value('int64'), '59': Value('int64'), '60': Value('int64'), '61': Value('int64'), '62': Value('int64'), '63': Value('int64'), '64': Value('int64'), '65': Value('int64'), '66': Value('int64'), '67': Value('int64'), '68': Value('int64'), '70': Value('int64'), '74': Value('int64'), '75': Value('int64'), '76': Value('int64'), '78': Value('int64'), '80': Value('int64'), '81': Value('int64'), '82': Value('int64'), '84': Value('int64'), '86': Value('int64'), '88': Value('int64'), '93': Value('int64'), '95': Value('int64'), '97': Value('int64'), '100': Value('int64'), '111': Value('int64'), '113': Value('int64'), '114': Value('int64'), '115': Value('int64'), '125': Value('int64'), '128': Value('int64'), '132': Value('int64'), '156': Value('int64')}, 'trajectory_patterns': {'falling': Value('int64'), 'flat': Value('int64'), 'rising': Value('int64'), 'volatile': Value('int64')}}
              because column names don't match
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FineProofs Branch Rollout Distribution

Per-prefix aggregate statistics for run fineproofs_qwen35_9b_resp81920_gptoss120b_m32_20260722.
Each row represents one collected response prefix and summarizes exactly 32 fresh Qwen3.5-9B continuations graded by GPT-OSS-120B against the problem rubric. mean_grade is a mean normalized rubric grade in [0, 1]; it is not a Bernoulli success rate.
Files

data/prefix_values.parquet: 103,518 prefix rows with trajectory metadata, empirical grade statistics, and a 20-bin continuation-grade histogram.
data/summary.json: collection-wide distributions, depth summaries, and PRM-build accounting.
data/trace_manifest.json: integrity and coverage metadata for the reasoning export.
data/traces/*.json.gz: all 8,328 selected base reasoning trajectories, sharded by the first two hexadecimal characters of the problem ID. Each trace is stored once with exact UTF-16 offsets for every collected prefix step.
The 20 histogram bins partition [0, 1] at intervals of 0.05; grade 1.0 is in the last bin. The much larger sampled continuation texts and judge records are not duplicated here.
Downloads last month: 20
Total file size:
141 MB
FineProofs Branch Rollout Distribution

Files

Space using asingh15/fineproofs-branch-rollout-distribution 1
