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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 (... 8176 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
finish_reason: string
label: string
completion: string
output_tokens: int64
rollout_index: int64
correct: bool
committed: bool
hit_token_cap: bool
steer: string
problem_key: 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 (... 8176 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
finish_reason: string
label: string
completion: string
output_tokens: int64
rollout_index: int64
correct: bool
committed: bool
hit_token_cap: bool
steer: string
problem_key: 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 | none | base | run | false | false | false | stop | 2,576 | 31,744 | 240
Okay, let's see. So the problem is about Aya's walk and her time spent in the coffee shop. The key here is that when she walks at different speeds, the total time changes, but the time spent in the coffee shop, t, remains the same. The question is asking for the total time when she walks at s + 0.5 km/h.
First,... |
aime2024_0 | 1 | none | base | run | true | true | false | stop | 1,772 | 31,744 | 240
Okay, let's see. So Aya walks 9 kilometers every morning, right? And she stops at a coffee shop afterwards. The problem gives me two different scenarios with her walking speed and the total time taken, including the time spent in the coffee shop. Then it asks for the total time when she walks at s + 0.5 km/h. Hmm... |
aime2024_0 | 2 | none | base | run | true | true | false | stop | 768 | 31,744 | 1. Determine the walking time at speed $s$:
- Total time at speed $s$: 4 hours = 240 minutes.
- Time spent walking: 240 minutes - $t$ minutes.
- Distance = speed × time: $9 = s \cdot \left(\frac{240 - t}{60}\right)$.
- Simplify: $s = \frac{540}{240 - t}$.
2. Determine the walking time at speed $s+2$:
... |
aime2024_0 | 3 | none | base | run | true | true | true | length | 31,744 | 31,744 | Okay, let's try to solve this problem step by step. First, I need to understand what's given and what's being asked.
So, Aya walks 9 kilometers every morning. When she walks at a speed of s km/h, the total time for the walk and the coffee shop is 4 hours. When she walks faster, at s + 2 km/h, the total time is 2 hour... |
aime2024_0 | 4 | none | base | run | true | false | true | length | 31,744 | 31,744 | " 240\n\nOkay, let's see. So Aya walks 9 kilometers every morning, right? And she stops at a coffee (...TRUNCATED) |
aime2024_0 | 5 | none | base | run | true | true | false | stop | 7,584 | 31,744 | " The first walk takes 4 hours, so $9 = 4s$. The second walk takes 2 hours and 24 minutes, or $\\fra(...TRUNCATED) |
aime2024_0 | 6 | none | base | run | true | false | false | stop | 426 | 31,744 | " Let $d$ be the distance from Aya's house to the coffee shop. The time it takes her to walk there a(...TRUNCATED) |
aime2024_0 | 7 | none | base | run | true | false | false | stop | 280 | 31,744 | " When Aya walks at $s$ kilometers per hour, she spends $4-t$ hours walking. When Aya walks at $s+2$(...TRUNCATED) |
aime2024_0 | 8 | none | base | run | true | false | false | stop | 198 | 31,744 | " The difference in time taken is $4-2\\frac{24}{60}=\\frac{4}{5}$ hours, which is the time differen(...TRUNCATED) |
aime2024_0 | 9 | none | base | run | true | false | false | stop | 178 | 31,744 | " She spends $4$ hours walking at $s$ kilometers per hour, so she walks $4s$ kilometers. She spends (...TRUNCATED) |
End of preview.
rollouts-olmo32b-rl — evaluation rollouts
Model: GRPO ck300 merged from allenai/Olmo-3-1125-32B (adapters: ReasoningRegisters/olmo32b). Tokenizer used for answer positions: allenai/Olmo-3-1125-32B.
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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