Dataset Viewer
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: TypeError
Message: Couldn't cast array of type
struct<leaderboard_bbh_boolean_expressions: struct<name: string, alias: string, sample_len: int64, acc_norm,none: double, acc_norm_stderr,none: double>, leaderboard_bbh_causal_judgement: struct<name: string, alias: string, sample_len: int64, acc_norm,none: double, acc_norm_stderr,none: double>, leaderboard_bbh_date_understanding: struct<name: string, alias: string, sample_len: int64, acc_norm,none: double, acc_norm_stderr,none: double>, leaderboard_bbh_disambiguation_qa: struct<name: string, alias: string, sample_len: int64, acc_norm,none: double, acc_norm_stderr,none: double>, leaderboard_bbh_formal_fallacies: struct<name: string, alias: string, sample_len: int64, acc_norm,none: double, acc_norm_stderr,none: double>, leaderboard_bbh_geometric_shapes: struct<name: string, alias: string, sample_len: int64, acc_norm,none: double, acc_norm_stderr,none: double>, leaderboard_bbh_hyperbaton: struct<name: string, alias: string, sample_len: int64, acc_norm,none: double, acc_norm_stderr,none: double>, leaderboard_bbh_logical_deduction_five_objects: struct<name: string, alias: string, sample_len: int64, acc_norm,none: double, acc_norm_stderr,none: double>, leaderboard_bbh_logical_deduction_seven_objects: struct<name: string, alias: string, sample_len: int64, acc_norm,none: double, acc_norm_stderr,none: double>, leaderboard_bbh_logical_deduction_three_objects: struct<name: string, alias: string, sample_len: int64, acc_norm,none: double, acc_norm_stderr,none: double>, leaderboard_bbh_mov
...
g, alias: string, sample_len: int64, exact_match,none: double, exact_match_stderr,none: double, exact_match_original,none: double, exact_match_original_stderr,none: double>, leaderboard_math_precalculus_hard: struct<name: string, alias: string, sample_len: int64, exact_match,none: double, exact_match_stderr,none: double, exact_match_original,none: double, exact_match_original_stderr,none: double>, leaderboard_bbh: struct<alias: string, name: string, sample_len: int64, acc_norm,none: double, acc_norm_stderr,none: double, sample_count: struct<acc_norm,none: int64>>, leaderboard_musr: struct<alias: string, name: string, sample_len: int64, acc_norm,none: double, acc_norm_stderr,none: double, sample_count: struct<acc_norm,none: int64>>, leaderboard_math_hard: struct<alias: string, name: string, sample_len: int64, exact_match,none: double, exact_match_stderr,none: double, sample_count: struct<exact_match,none: int64>>, leaderboard_gpqa: struct<alias: string, name: string, sample_len: int64, acc_norm,none: double, acc_norm_stderr,none: double, sample_count: struct<acc_norm,none: int64>>, leaderboard_gpqa_diamond: struct<name: string, alias: string, sample_len: int64, acc_norm,none: double, acc_norm_stderr,none: double>, leaderboard_gpqa_extended: struct<name: string, alias: string, sample_len: int64, acc_norm,none: double, acc_norm_stderr,none: double>, leaderboard_gpqa_main: struct<name: string, alias: string, sample_len: int64, acc_norm,none: double, acc_norm_stderr,none: double>>
to
{'leaderboard_gpqa_diamond': {'name': Value('string'), 'alias': Value('string'), 'sample_len': Value('int64'), 'acc_norm,none': Value('float64'), 'acc_norm_stderr,none': Value('float64')}, 'leaderboard_gpqa_extended': {'name': Value('string'), 'alias': Value('string'), 'sample_len': Value('int64'), 'acc_norm,none': Value('float64'), 'acc_norm_stderr,none': Value('float64')}, 'leaderboard_gpqa_main': {'name': Value('string'), 'alias': Value('string'), 'sample_len': Value('int64'), 'acc_norm,none': Value('float64'), 'acc_norm_stderr,none': Value('float64')}, 'leaderboard_gpqa': {'alias': Value('string'), 'name': Value('string'), 'sample_len': Value('int64'), 'acc_norm,none': Value('float64'), 'acc_norm_stderr,none': Value('float64'), 'sample_count': {'acc_norm,none': Value('int64')}}}
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 2303, in cast_table_to_schema
cast_array_to_feature(
~~~~~~~~~~~~~~~~~~~~~^
table[name] if name in table_column_names else pa.array([None] * len(table), type=schema.field(name).type),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
feature,
^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1852, in wrapper
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
~~~~^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2149, in cast_array_to_feature
raise TypeError(f"Couldn't cast array of type\n{_short_str(array.type)}\nto\n{_short_str(feature)}")
TypeError: Couldn't cast array of type
struct<leaderboard_bbh_boolean_expressions: struct<name: string, alias: string, sample_len: int64, acc_norm,none: double, acc_norm_stderr,none: double>, leaderboard_bbh_causal_judgement: struct<name: string, alias: string, sample_len: int64, acc_norm,none: double, acc_norm_stderr,none: double>, leaderboard_bbh_date_understanding: struct<name: string, alias: string, sample_len: int64, acc_norm,none: double, acc_norm_stderr,none: double>, leaderboard_bbh_disambiguation_qa: struct<name: string, alias: string, sample_len: int64, acc_norm,none: double, acc_norm_stderr,none: double>, leaderboard_bbh_formal_fallacies: struct<name: string, alias: string, sample_len: int64, acc_norm,none: double, acc_norm_stderr,none: double>, leaderboard_bbh_geometric_shapes: struct<name: string, alias: string, sample_len: int64, acc_norm,none: double, acc_norm_stderr,none: double>, leaderboard_bbh_hyperbaton: struct<name: string, alias: string, sample_len: int64, acc_norm,none: double, acc_norm_stderr,none: double>, leaderboard_bbh_logical_deduction_five_objects: struct<name: string, alias: string, sample_len: int64, acc_norm,none: double, acc_norm_stderr,none: double>, leaderboard_bbh_logical_deduction_seven_objects: struct<name: string, alias: string, sample_len: int64, acc_norm,none: double, acc_norm_stderr,none: double>, leaderboard_bbh_logical_deduction_three_objects: struct<name: string, alias: string, sample_len: int64, acc_norm,none: double, acc_norm_stderr,none: double>, leaderboard_bbh_mov
...
g, alias: string, sample_len: int64, exact_match,none: double, exact_match_stderr,none: double, exact_match_original,none: double, exact_match_original_stderr,none: double>, leaderboard_math_precalculus_hard: struct<name: string, alias: string, sample_len: int64, exact_match,none: double, exact_match_stderr,none: double, exact_match_original,none: double, exact_match_original_stderr,none: double>, leaderboard_bbh: struct<alias: string, name: string, sample_len: int64, acc_norm,none: double, acc_norm_stderr,none: double, sample_count: struct<acc_norm,none: int64>>, leaderboard_musr: struct<alias: string, name: string, sample_len: int64, acc_norm,none: double, acc_norm_stderr,none: double, sample_count: struct<acc_norm,none: int64>>, leaderboard_math_hard: struct<alias: string, name: string, sample_len: int64, exact_match,none: double, exact_match_stderr,none: double, sample_count: struct<exact_match,none: int64>>, leaderboard_gpqa: struct<alias: string, name: string, sample_len: int64, acc_norm,none: double, acc_norm_stderr,none: double, sample_count: struct<acc_norm,none: int64>>, leaderboard_gpqa_diamond: struct<name: string, alias: string, sample_len: int64, acc_norm,none: double, acc_norm_stderr,none: double>, leaderboard_gpqa_extended: struct<name: string, alias: string, sample_len: int64, acc_norm,none: double, acc_norm_stderr,none: double>, leaderboard_gpqa_main: struct<name: string, alias: string, sample_len: int64, acc_norm,none: double, acc_norm_stderr,none: double>>
to
{'leaderboard_gpqa_diamond': {'name': Value('string'), 'alias': Value('string'), 'sample_len': Value('int64'), 'acc_norm,none': Value('float64'), 'acc_norm_stderr,none': Value('float64')}, 'leaderboard_gpqa_extended': {'name': Value('string'), 'alias': Value('string'), 'sample_len': Value('int64'), 'acc_norm,none': Value('float64'), 'acc_norm_stderr,none': Value('float64')}, 'leaderboard_gpqa_main': {'name': Value('string'), 'alias': Value('string'), 'sample_len': Value('int64'), 'acc_norm,none': Value('float64'), 'acc_norm_stderr,none': Value('float64')}, 'leaderboard_gpqa': {'alias': Value('string'), 'name': Value('string'), 'sample_len': Value('int64'), 'acc_norm,none': Value('float64'), 'acc_norm_stderr,none': Value('float64'), 'sample_count': {'acc_norm,none': Value('int64')}}}Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
sov33-v12 — Open LLM Leaderboard evaluation results
Champion of the SOV-SIGNAL campaign (Qwen2.5-1.5B + LoRA, corrected gold corpus). This card reports the actual lm_eval Open LLM Leaderboard V2 scores. Disclosed honestly: a 1.5B governance-specialist scores far below frontier models on reasoning tasks — that is expected and stated, not hidden.
Leaderboard V2 results (2026-08-09, lm_eval 0.4.12, bf16, batch 8)
| task | metric | score |
|---|---|---|
| BBH | 0.4088 | |
| MMLU-Pro | 0.2809 | |
| MuSR | 0.4101 | |
| IFEval (inst loose/strict) | 0.4365 / 0.3825 | |
| Math-Hard | 0.0793 | |
| GPQA (n=1192) | acc_norm | 0.3096 ±0.0134 |
SOV-SIGNAL governance (the model's purpose — where it leads)
- sov33-unified row set: 69.07% (472/473 graded) — +5.22 over prior champion
- aggregate: 66.33% (1306/1969)
- contamination = 0, per-row Ed25519 attestation, per-axis Wilson95 published in csoai/sov-signal-ground-truth-v10
Method
- lm_eval 0.4.12, hf backend, trust_remote_code, temp 0, deterministic
- run date 2026-08-09, RunPod RTX 3090
- full metrics: results.json (lm_eval raw output)
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