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The dataset generation failed
Error code: DatasetGenerationError
Exception: CastError
Message: Couldn't cast
pass@1: double
pass@1_ci95: list<item: double>
child 0, item: double
pass@1_sd_boot: double
pass@1_by_rollout_index: list<item: double>
child 0, item: double
pass@1_sd_rollouts: double
pass@8: double
pass@8_ci95: list<item: double>
child 0, item: double
pass@8_sd_boot: double
pass@16: double
pass@16_ci95: list<item: double>
child 0, item: double
pass@16_sd_boot: double
cap_rate: double
n_problems: int64
n_rollouts: int64
rollouts_per_problem: int64
max_tokens_used: list<item: int64>
child 0, item: int64
prompt_style: list<item: null>
child 0, item: null
median_output_tokens: int64
mean_output_tokens: double
expected_problems: int64
complete: bool
files: list<item: string>
child 0, item: string
per_problem: struct<aime2024_0: struct<rollout_index: list<item: int64>, correct: list<item: int64>, tokens: list (... 8166 chars omitted)
child 0, aime2024_0: struct<rollout_index: list<item: int64>, correct: list<item: int64>, tokens: list<item: int64>, answ (... 161 chars omitted)
child 0, rollout_index: list<item: int64>
child 0, item: int64
child 1, correct: list<item: int64>
child 0, item: int64
child 2, tokens: list<item: int64>
child 0, item: int64
child 3, answer: list<item: string>
child 0, item: string
child 4, hit_cap: list<item: int64>
child 0, item: int64
child 5, answer_end_frac: list<item: double>
child 0, item: double
child 6, answer_marker: list<item: s
...
child 0, k: int64
child 1, expected_tokens: double
child 2, pass_at_k: double
child 3, majority_at_k: double
child 27, 28: struct<k: int64, expected_tokens: double, pass_at_k: double, majority_at_k: double>
child 0, k: int64
child 1, expected_tokens: double
child 2, pass_at_k: double
child 3, majority_at_k: double
child 28, 29: struct<k: int64, expected_tokens: double, pass_at_k: double, majority_at_k: double>
child 0, k: int64
child 1, expected_tokens: double
child 2, pass_at_k: double
child 3, majority_at_k: double
child 29, 30: struct<k: int64, expected_tokens: double, pass_at_k: double, majority_at_k: double>
child 0, k: int64
child 1, expected_tokens: double
child 2, pass_at_k: double
child 3, majority_at_k: double
child 30, 31: struct<k: int64, expected_tokens: double, pass_at_k: double, majority_at_k: double>
child 0, k: int64
child 1, expected_tokens: double
child 2, pass_at_k: double
child 3, majority_at_k: double
child 31, 32: struct<k: int64, expected_tokens: double, pass_at_k: double, majority_at_k: double>
child 0, k: int64
child 1, expected_tokens: double
child 2, pass_at_k: double
child 3, majority_at_k: double
aggregate_by_k_doc: string
completion: string
rollout_index: int64
committed: bool
correct: bool
problem_key: string
label: string
finish_reason: string
hit_token_cap: bool
output_tokens: int64
steer: string
to
{'problem_key': Value('string'), 'rollout_index': Value('int64'), 'arm': Value('string'), 'steer': Value('string'), 'label': Value('string'), 'committed': Value('bool'), 'correct': Value('bool'), 'hit_token_cap': Value('bool'), 'finish_reason': Value('string'), 'output_tokens': Value('int64'), 'max_tokens_used': Value('int64'), 'completion': Value('string')}
because column names don't match
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1827, in _prepare_split_single
for key, table in generator:
^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 613, in wrapped
for item in generator(*args, **kwargs):
~~~~~~~~~^^^^^^^^^^^^^^^^^
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 2378, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
pass@1: double
pass@1_ci95: list<item: double>
child 0, item: double
pass@1_sd_boot: double
pass@1_by_rollout_index: list<item: double>
child 0, item: double
pass@1_sd_rollouts: double
pass@8: double
pass@8_ci95: list<item: double>
child 0, item: double
pass@8_sd_boot: double
pass@16: double
pass@16_ci95: list<item: double>
child 0, item: double
pass@16_sd_boot: double
cap_rate: double
n_problems: int64
n_rollouts: int64
rollouts_per_problem: int64
max_tokens_used: list<item: int64>
child 0, item: int64
prompt_style: list<item: null>
child 0, item: null
median_output_tokens: int64
mean_output_tokens: double
expected_problems: int64
complete: bool
files: list<item: string>
child 0, item: string
per_problem: struct<aime2024_0: struct<rollout_index: list<item: int64>, correct: list<item: int64>, tokens: list (... 8166 chars omitted)
child 0, aime2024_0: struct<rollout_index: list<item: int64>, correct: list<item: int64>, tokens: list<item: int64>, answ (... 161 chars omitted)
child 0, rollout_index: list<item: int64>
child 0, item: int64
child 1, correct: list<item: int64>
child 0, item: int64
child 2, tokens: list<item: int64>
child 0, item: int64
child 3, answer: list<item: string>
child 0, item: string
child 4, hit_cap: list<item: int64>
child 0, item: int64
child 5, answer_end_frac: list<item: double>
child 0, item: double
child 6, answer_marker: list<item: s
...
child 0, k: int64
child 1, expected_tokens: double
child 2, pass_at_k: double
child 3, majority_at_k: double
child 27, 28: struct<k: int64, expected_tokens: double, pass_at_k: double, majority_at_k: double>
child 0, k: int64
child 1, expected_tokens: double
child 2, pass_at_k: double
child 3, majority_at_k: double
child 28, 29: struct<k: int64, expected_tokens: double, pass_at_k: double, majority_at_k: double>
child 0, k: int64
child 1, expected_tokens: double
child 2, pass_at_k: double
child 3, majority_at_k: double
child 29, 30: struct<k: int64, expected_tokens: double, pass_at_k: double, majority_at_k: double>
child 0, k: int64
child 1, expected_tokens: double
child 2, pass_at_k: double
child 3, majority_at_k: double
child 30, 31: struct<k: int64, expected_tokens: double, pass_at_k: double, majority_at_k: double>
child 0, k: int64
child 1, expected_tokens: double
child 2, pass_at_k: double
child 3, majority_at_k: double
child 31, 32: struct<k: int64, expected_tokens: double, pass_at_k: double, majority_at_k: double>
child 0, k: int64
child 1, expected_tokens: double
child 2, pass_at_k: double
child 3, majority_at_k: double
aggregate_by_k_doc: string
completion: string
rollout_index: int64
committed: bool
correct: bool
problem_key: string
label: string
finish_reason: string
hit_token_cap: bool
output_tokens: int64
steer: string
to
{'problem_key': Value('string'), 'rollout_index': Value('int64'), 'arm': Value('string'), 'steer': Value('string'), 'label': Value('string'), 'committed': Value('bool'), 'correct': Value('bool'), 'hit_token_cap': Value('bool'), 'finish_reason': Value('string'), 'output_tokens': Value('int64'), 'max_tokens_used': Value('int64'), 'completion': Value('string')}
because column names don't match
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
~~~~~~~~~~~~~~~~~~~~~~~~~^
builder, max_dataset_size_bytes=max_dataset_size_bytes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1694, in _prepare_split
for job_id, done, content in self._prepare_split_single(
~~~~~~~~~~~~~~~~~~~~~~~~~~^
gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
):
^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1880, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
problem_key string | rollout_index int64 | arm string | steer string | label string | committed bool | correct bool | hit_token_cap bool | finish_reason string | output_tokens int64 | max_tokens_used int64 | completion string |
|---|---|---|---|---|---|---|---|---|---|---|---|
aime2024_0 | 0 | sp_nn_okay | base | run | true | true | false | stop | 3,125 | 31,744 |
Okay, let's try to figure out this problem. So, Aya goes for a 9-kilometer walk every morning and then stops at a coffee shop. The time she spends walking depends on her speed, and also includes some time in the coffee shop, which is the same t minutes each time. We need to find out how long the walk takes her when ... |
aime2024_0 | 1 | sp_nn_okay | base | run | true | true | false | stop | 2,314 | 31,744 |
Okay, let's see. Aya goes for a 9-kilometer walk every morning and stops at a coffee shop. The problem gives two different speeds she walks at, and the time it takes including the coffee shop time. We need to find out how long her walk takes when she walks at a different speed, s + 1/2 km/h. Hmm, okay.
First, let m... |
aime2024_0 | 2 | sp_nn_okay | base | run | true | true | false | stop | 2,859 | 31,744 |
Okay, so I need to figure out how long Aya's walk takes when she walks at a speed of s + 1/2 km/h. Let me start by understanding the problem step by step.
First, the problem says that every morning Aya walks 9 kilometers and then stops at a coffee shop. The time taken for the walk depends on her speed, and this tim... |
aime2024_0 | 3 | sp_nn_okay | base | run | false | false | true | length | 31,744 | 31,744 |
Okay, let's see. The problem is about Aya's walking speed and time, including her coffee shop stop. We need to find out how long her walk takes when she walks at a speed of s + 1/2 km/h. Hmm, let's break it down step by step.
First, the problem says that when she walks at speed s km/h, the total time including the ... |
aime2024_0 | 4 | sp_nn_okay | base | run | true | true | false | stop | 3,274 | 31,744 |
Okay, let's see. I need to solve this problem about Aya's walking speed and time. Hmm. Let me read it again carefully.
So, every morning, Aya walks 9 kilometers and then stops at a coffee shop. The time she spends walking at speed s is 4 hours, which includes t minutes in the coffee shop. When she walks faster, at ... |
aime2024_0 | 5 | sp_nn_okay | base | run | false | false | true | length | 31,744 | 31,744 | " \n\nOkay, let's try to figure out this problem step by step. So, Aya walks 9 kilometers every morn(...TRUNCATED) |
aime2024_0 | 6 | sp_nn_okay | base | run | true | true | false | stop | 2,357 | 31,744 | " \n\nOkay, let's try to figure out this problem step by step. So, Aya goes for a 9-kilometer walk e(...TRUNCATED) |
aime2024_0 | 7 | sp_nn_okay | base | run | true | true | false | stop | 2,327 | 31,744 | " \n\nOkay, let's try to figure out this problem step by step. So, Aya goes for a 9-kilometer walk e(...TRUNCATED) |
aime2024_0 | 8 | sp_nn_okay | base | run | true | true | false | stop | 2,211 | 31,744 | " \n\nOkay, let's try to solve this problem step by step. So, Aya has a 9-kilometer walk every morni(...TRUNCATED) |
aime2024_0 | 9 | sp_nn_okay | base | run | true | true | false | stop | 2,477 | 31,744 | " \n\nOkay, let's see. So Aya goes for a 9-kilometer walk every morning, then stops at a coffee shop(...TRUNCATED) |
End of preview.
rollouts-olmo7b — evaluation rollouts
Model: allenai/Olmo-3-1025-7B. Tokenizer used for answer positions: allenai/Olmo-3-1025-7B.
Protocol: 32 rollouts per problem (two seeded batches of 16), temperature 0.6, top-p 0.95,
budget 31,744 generated tokens, seed 20260819. Prompts and grader: the paper's repository
(sophicle/reason). Rollout jsonl files are kept as written (one graded rollout per line, with the
completion), under the run directories as on disk (run/, run_regraded/, *_execgraded/);
cell summaries are at <prompt>/<benchmark>/summary/<arm>.json.
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