Anthropochrony data
Collection
Tasks, measured runs, SFT sets, estimates, results and logs for Anthropochrony. • 5 items • Updated
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The dataset generation failed
Error code: DatasetGenerationError
Exception: CastError
Message: Couldn't cast
est_id: string
task_id: string
family: string
split: string
frame: string
template_id: string
phrasing_id: string
prompt_estimator: string
prefill: string
estimator: string
label_source: string
card_id: string
messages: list<item: struct<role: string, content: string>>
child 0, item: struct<role: string, content: string>
child 0, role: string
child 1, content: string
prompt_sha: string
T_med_s: double
S: double
P: double
prompt_tokens: int64
max_tokens: int64
target_source: string
seed: int64
model_id: string
model_sha: string
raw_text: string
finish_reason: string
model_called: bool
prompt_tokens_total: int64
effective_max_tokens: int64
parsed: struct<point_s: double, lo_s: double, hi_s: double, tokens: double, attempts: double, pfp: double, u (... 75 chars omitted)
child 0, point_s: double
child 1, lo_s: double
child 2, hi_s: double
child 3, tokens: double
child 4, attempts: double
child 5, pfp: double
child 6, units_used: list<item: string>
child 0, item: string
child 7, has_human_units: bool
child 8, parse_method: string
auditkit_fingerprint: string
actual_s: double
analysis_protocol: string
restricted_statement: bool
source: string
source_revision: string
base_pass1: double
ft_pass1: double
ft_model_sha: string
k: int64
base_model_sha: string
to
{'task_id': Value('string'), 'family': Value('string'), 'split': Value('string'), 'estimator': Value('string'), 'seed': Value('int64'), 'k': Value('int64'), 'base_model_sha': Value('string'), 'ft_model_sha': Value('string'), 'base_pass1': Value('float64'), 'ft_pass1': Value('float64')}
because column names don't match
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1835, in _prepare_split_single
for key, table in generator:
^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 621, in wrapped
for item in generator(*args, **kwargs):
~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 361, 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 2381, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2309, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
est_id: string
task_id: string
family: string
split: string
frame: string
template_id: string
phrasing_id: string
prompt_estimator: string
prefill: string
estimator: string
label_source: string
card_id: string
messages: list<item: struct<role: string, content: string>>
child 0, item: struct<role: string, content: string>
child 0, role: string
child 1, content: string
prompt_sha: string
T_med_s: double
S: double
P: double
prompt_tokens: int64
max_tokens: int64
target_source: string
seed: int64
model_id: string
model_sha: string
raw_text: string
finish_reason: string
model_called: bool
prompt_tokens_total: int64
effective_max_tokens: int64
parsed: struct<point_s: double, lo_s: double, hi_s: double, tokens: double, attempts: double, pfp: double, u (... 75 chars omitted)
child 0, point_s: double
child 1, lo_s: double
child 2, hi_s: double
child 3, tokens: double
child 4, attempts: double
child 5, pfp: double
child 6, units_used: list<item: string>
child 0, item: string
child 7, has_human_units: bool
child 8, parse_method: string
auditkit_fingerprint: string
actual_s: double
analysis_protocol: string
restricted_statement: bool
source: string
source_revision: string
base_pass1: double
ft_pass1: double
ft_model_sha: string
k: int64
base_model_sha: string
to
{'task_id': Value('string'), 'family': Value('string'), 'split': Value('string'), 'estimator': Value('string'), 'seed': Value('int64'), 'k': Value('int64'), 'base_model_sha': Value('string'), 'ft_model_sha': Value('string'), 'base_pass1': Value('float64'), 'ft_pass1': Value('float64')}
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 1379, 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 956, 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 1702, 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 1887, 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.
task_id string | family string | split string | estimator string | seed int64 | k int64 | base_model_sha string | ft_model_sha string | base_pass1 float64 | ft_pass1 float64 |
|---|---|---|---|---|---|---|---|---|---|
BigCodeBench/1000 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0.5 |
BigCodeBench/1004 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/102 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/1048 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 1 | 0.875 |
BigCodeBench/1077 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/124 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/127 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/159 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0.25 | 0 |
BigCodeBench/162 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/174 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/199 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/204 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0.25 | 0 |
BigCodeBench/211 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/215 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0.25 | 0 |
BigCodeBench/219 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/222 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/241 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/250 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/267 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/273 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/295 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 1 | 1 |
BigCodeBench/326 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/331 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/360 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/368 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/374 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/399 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/401 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/424 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/463 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/482 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/486 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/507 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/51 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/530 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/553 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/554 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/560 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/574 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/583 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/591 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0.375 | 1 |
BigCodeBench/603 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/637 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/654 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/707 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0.75 | 0.125 |
BigCodeBench/743 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 1 | 1 |
BigCodeBench/777 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0.375 | 0 |
BigCodeBench/778 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/796 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 1 | 0.375 |
BigCodeBench/801 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/822 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0.875 |
BigCodeBench/826 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/845 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/854 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/866 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/867 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0.5 | 1 |
BigCodeBench/879 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/897 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0.125 |
BigCodeBench/899 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/903 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/923 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0.375 | 0 |
BigCodeBench/942 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/953 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/961 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/963 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0.375 | 0.625 |
BigCodeBench/966 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/969 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/996 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
BigCodeBench/999 | LIB | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
HumanEval/109 | FUNC | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
HumanEval/112 | FUNC | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 1 | 1 |
HumanEval/116 | FUNC | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 1 | 1 |
HumanEval/121 | FUNC | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 1 | 0.875 |
HumanEval/130 | FUNC | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
HumanEval/131 | FUNC | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
HumanEval/138 | FUNC | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0.375 | 1 |
HumanEval/145 | FUNC | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
HumanEval/146 | FUNC | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 1 | 0.25 |
HumanEval/149 | FUNC | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
HumanEval/15 | FUNC | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 1 | 1 |
HumanEval/153 | FUNC | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 1 | 1 |
HumanEval/156 | FUNC | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 1 | 1 |
HumanEval/159 | FUNC | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0.875 | 1 |
HumanEval/16 | FUNC | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 1 | 1 |
HumanEval/163 | FUNC | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
HumanEval/20 | FUNC | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0.875 | 1 |
HumanEval/29 | FUNC | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
HumanEval/30 | FUNC | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 1 | 1 |
HumanEval/37 | FUNC | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
HumanEval/4 | FUNC | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 1 | 1 |
HumanEval/41 | FUNC | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
HumanEval/57 | FUNC | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 1 | 1 |
HumanEval/59 | FUNC | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0.625 | 1 |
HumanEval/63 | FUNC | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 1 | 1 |
HumanEval/67 | FUNC | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
HumanEval/71 | FUNC | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 1 | 1 |
HumanEval/84 | FUNC | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
HumanEval/85 | FUNC | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0.75 | 1 |
HumanEval/86 | FUNC | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0.125 |
HumanEval/93 | FUNC | test | M1-s0 | 0 | 8 | af89d219b53ed9b13b8a4645f9c8028973510324 | e23d9a67034a43b9b6645b5d3cf899fd8eb54e04 | 0 | 0 |
End of preview.
anthropochrony-eval: Estimates, results and figures
Part of Anthropochrony: Measuring and Correcting Human-Time Bias in LLM Self-Estimates (Track 1, problem #8). Code, article and reproduction: https://github.com/isHeSatoshi/anthropochrony
Contents. Every estimate from every estimator on every split, frame and speed card (estimates.jsonl, 55k rows), the parsed values, per-task analysis rows, results/ (metrics, hypotheses, simulations, ROI, extra analyses, gate evidence), the CPU deployment results (x10/), capability pairs and the figures. notebooks/reproduce_results.ipynb in the code repository rebuilds the headline table from the results/ folder here.
Restrictions. Raw model answers and statements are withheld for restricted sources, and few-shot prompts are withheld for all rows because they embed demonstration tasks.
Licenses. Our annotations, labels and run data: CC-BY-NC-4.0 (they derive from Tiny Aya Global outputs and include CC BY-NC 4.0 ClassEval). Upstream task sources keep their own licenses: HumanEval+/MBPP+ Apache-2.0 (HumanEval MIT, MBPP CC-BY-4.0), BigCodeBench Apache-2.0, ClassEval CC BY-NC 4.0, CodeContests CC-BY-4.0, LeetCodeDataset Apache-2.0 metadata with LeetCode-owned statements, TACO Apache-2.0 metadata with third-party statements. Model-generated text is from CohereLabs/tiny-aya-global (CC-BY-NC-4.0 plus the AUP). Teacher guesses are from DeepSeek-V4-Pro.
Intended use. Research on model self-knowledge and time estimation for coding agents. Not for commercial use.
Limitations. One training seed; labels are medians of 8 sampled runs under stated speeds, not measurements on the stated hardware; Python tasks only; the parser audit covered 60 rows and was done by the research agent.
Collection. https://huggingface.co/collections/isHeSatoshi/anthropochrony-data-6af31e776d6f33265b0c33a8
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