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Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
version: timestamp[s]
status: string
note: string
eval_code: struct<repo: string, commit: string>
child 0, repo: string
child 1, commit: string
primary_metric: string
metrics: list<item: struct<id: string, label: string, kind: string, higher_is_better: bool, definition: strin (... 3 chars omitted)
child 0, item: struct<id: string, label: string, kind: string, higher_is_better: bool, definition: string>
child 0, id: string
child 1, label: string
child 2, kind: string
child 3, higher_is_better: bool
child 4, definition: string
verification_levels: struct<verified: string, internal: string, reported: string>
child 0, verified: string
child 1, internal: string
child 2, reported: string
benchmarks: list<item: struct<id: string, name: string, short: string, persons: int64, persons_scored: int64, it (... 164 chars omitted)
child 0, item: struct<id: string, name: string, short: string, persons: int64, persons_scored: int64, items: int64, (... 152 chars omitted)
child 0, id: string
child 1, name: string
child 2, short: string
child 3, persons: int64
child 4, persons_scored: int64
child 5, items: int64
child 6, events: int64
child 7, cutoff: timestamp[s]
child 8, license: string
child 9, source_url: string
child 10, protocol: string
child 11, published_reference: string
child 12, confounds: list<item: string>
child 0, item: string
config: struct<model_dtyp
...
child 0, fit_seconds: double
child 1, usd_per_1k: null
child 4, douban-tridomain-transfer: struct<recall@10: double, interval: list<item: double>, n: int64, ndcg@10: double, controls: struct< (... 151 chars omitted)
child 0, recall@10: double
child 1, interval: list<item: double>
child 0, item: double
child 2, n: int64
child 3, ndcg@10: double
child 4, controls: struct<>
child 5, cell: string
child 6, run: struct<experiment: string, commit: string, date: timestamp[s], seed: int64>
child 0, experiment: string
child 1, commit: string
child 2, date: timestamp[s]
child 3, seed: int64
child 7, cost: struct<fit_seconds: double, usd_per_1k: null>
child 0, fit_seconds: double
child 1, usd_per_1k: null
results: struct<amazon2014-beauty: struct<recall@10: double>, steam-2018: struct<recall@10: double>, amazon20 (... 161 chars omitted)
child 0, amazon2014-beauty: struct<recall@10: double>
child 0, recall@10: double
child 1, steam-2018: struct<recall@10: double>
child 0, recall@10: double
child 2, amazon2014-five-category-transfer: struct<recall@10: double>
child 0, recall@10: double
child 3, amazon2014-taste-transfer: struct<recall@10: double>
child 0, recall@10: double
child 4, douban-tridomain-transfer: struct<recall@10: double>
child 0, recall@10: double
leaderboard_release: timestamp[s]
eval_code_commit: string
to
{'config': {'model_dtype': Value('string'), 'model_name': Value('string'), 'model_sha': Value('string'), 'display_name': Value('string'), 'architecture': Value('string'), 'url': Value('string')}, 'results': {'amazon2014-beauty': {'recall@10': Value('float64')}, 'steam-2018': {'recall@10': Value('float64')}, 'amazon2014-five-category-transfer': {'recall@10': Value('float64')}, 'amazon2014-taste-transfer': {'recall@10': Value('float64')}, 'douban-tridomain-transfer': {'recall@10': Value('float64')}}, 'record': {'amazon2014-beauty': {'recall@10': Value('float64'), 'interval': Value('null'), 'n': Value('int64'), 'ndcg@10': Value('float64'), 'controls': {}, 'cell': Value('string'), 'run': {'experiment': Value('string'), 'commit': Value('string'), 'date': Value('timestamp[s]'), 'seed': Value('int64')}, 'cost': {'fit_seconds': Value('float64'), 'usd_per_1k': Value('null')}}, 'steam-2018': {'recall@10': Value('float64'), 'interval': List(Value('float64')), 'n': Value('int64'), 'ndcg@10': Value('float64'), 'controls': {}, 'cell': Value('string'), 'run': {'experiment': Value('string'), 'commit': Value('string'), 'date': Value('timestamp[s]'), 'seed': Value('int64')}, 'cost': {'fit_seconds': Value('float64'), 'usd_per_1k': Value('null')}}, 'amazon2014-five-category-transfer': {'recall@10': Value('float64'), 'interval': List(Value('float64')), 'n': Value('int64'), 'ndcg@10': Value('float64'), 'controls': {}, 'cell': Value('string'), 'run': {'experiment': Value('string'), 'commit': Value('string'), 'date': Value('timestamp[s]'), 'seed': Value('int64')}, 'cost': {'fit_seconds': Value('float64'), 'usd_per_1k': Value('null')}}, 'amazon2014-taste-transfer': {'recall@10': Value('float64'), 'interval': List(Value('float64')), 'n': Value('int64'), 'ndcg@10': Value('float64'), 'controls': {}, 'cell': Value('string'), 'run': {'experiment': Value('string'), 'commit': Value('string'), 'date': Value('timestamp[s]'), 'seed': Value('int64')}, 'cost': {'fit_seconds': Value('float64'), 'usd_per_1k': Value('null')}}, 'douban-tridomain-transfer': {'recall@10': Value('float64'), 'interval': List(Value('float64')), 'n': Value('int64'), 'ndcg@10': Value('float64'), 'controls': {}, 'cell': Value('string'), 'run': {'experiment': Value('string'), 'commit': Value('string'), 'date': Value('timestamp[s]'), 'seed': Value('int64')}, 'cost': {'fit_seconds': Value('float64'), 'usd_per_1k': Value('null')}}}, 'leaderboard_release': Value('timestamp[s]'), 'eval_code_commit': Value('string')}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 147, 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 127, 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 483, 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 2840, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2373, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2398, 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 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
version: timestamp[s]
status: string
note: string
eval_code: struct<repo: string, commit: string>
child 0, repo: string
child 1, commit: string
primary_metric: string
metrics: list<item: struct<id: string, label: string, kind: string, higher_is_better: bool, definition: strin (... 3 chars omitted)
child 0, item: struct<id: string, label: string, kind: string, higher_is_better: bool, definition: string>
child 0, id: string
child 1, label: string
child 2, kind: string
child 3, higher_is_better: bool
child 4, definition: string
verification_levels: struct<verified: string, internal: string, reported: string>
child 0, verified: string
child 1, internal: string
child 2, reported: string
benchmarks: list<item: struct<id: string, name: string, short: string, persons: int64, persons_scored: int64, it (... 164 chars omitted)
child 0, item: struct<id: string, name: string, short: string, persons: int64, persons_scored: int64, items: int64, (... 152 chars omitted)
child 0, id: string
child 1, name: string
child 2, short: string
child 3, persons: int64
child 4, persons_scored: int64
child 5, items: int64
child 6, events: int64
child 7, cutoff: timestamp[s]
child 8, license: string
child 9, source_url: string
child 10, protocol: string
child 11, published_reference: string
child 12, confounds: list<item: string>
child 0, item: string
config: struct<model_dtyp
...
child 0, fit_seconds: double
child 1, usd_per_1k: null
child 4, douban-tridomain-transfer: struct<recall@10: double, interval: list<item: double>, n: int64, ndcg@10: double, controls: struct< (... 151 chars omitted)
child 0, recall@10: double
child 1, interval: list<item: double>
child 0, item: double
child 2, n: int64
child 3, ndcg@10: double
child 4, controls: struct<>
child 5, cell: string
child 6, run: struct<experiment: string, commit: string, date: timestamp[s], seed: int64>
child 0, experiment: string
child 1, commit: string
child 2, date: timestamp[s]
child 3, seed: int64
child 7, cost: struct<fit_seconds: double, usd_per_1k: null>
child 0, fit_seconds: double
child 1, usd_per_1k: null
results: struct<amazon2014-beauty: struct<recall@10: double>, steam-2018: struct<recall@10: double>, amazon20 (... 161 chars omitted)
child 0, amazon2014-beauty: struct<recall@10: double>
child 0, recall@10: double
child 1, steam-2018: struct<recall@10: double>
child 0, recall@10: double
child 2, amazon2014-five-category-transfer: struct<recall@10: double>
child 0, recall@10: double
child 3, amazon2014-taste-transfer: struct<recall@10: double>
child 0, recall@10: double
child 4, douban-tridomain-transfer: struct<recall@10: double>
child 0, recall@10: double
leaderboard_release: timestamp[s]
eval_code_commit: string
to
{'config': {'model_dtype': Value('string'), 'model_name': Value('string'), 'model_sha': Value('string'), 'display_name': Value('string'), 'architecture': Value('string'), 'url': Value('string')}, 'results': {'amazon2014-beauty': {'recall@10': Value('float64')}, 'steam-2018': {'recall@10': Value('float64')}, 'amazon2014-five-category-transfer': {'recall@10': Value('float64')}, 'amazon2014-taste-transfer': {'recall@10': Value('float64')}, 'douban-tridomain-transfer': {'recall@10': Value('float64')}}, 'record': {'amazon2014-beauty': {'recall@10': Value('float64'), 'interval': Value('null'), 'n': Value('int64'), 'ndcg@10': Value('float64'), 'controls': {}, 'cell': Value('string'), 'run': {'experiment': Value('string'), 'commit': Value('string'), 'date': Value('timestamp[s]'), 'seed': Value('int64')}, 'cost': {'fit_seconds': Value('float64'), 'usd_per_1k': Value('null')}}, 'steam-2018': {'recall@10': Value('float64'), 'interval': List(Value('float64')), 'n': Value('int64'), 'ndcg@10': Value('float64'), 'controls': {}, 'cell': Value('string'), 'run': {'experiment': Value('string'), 'commit': Value('string'), 'date': Value('timestamp[s]'), 'seed': Value('int64')}, 'cost': {'fit_seconds': Value('float64'), 'usd_per_1k': Value('null')}}, 'amazon2014-five-category-transfer': {'recall@10': Value('float64'), 'interval': List(Value('float64')), 'n': Value('int64'), 'ndcg@10': Value('float64'), 'controls': {}, 'cell': Value('string'), 'run': {'experiment': Value('string'), 'commit': Value('string'), 'date': Value('timestamp[s]'), 'seed': Value('int64')}, 'cost': {'fit_seconds': Value('float64'), 'usd_per_1k': Value('null')}}, 'amazon2014-taste-transfer': {'recall@10': Value('float64'), 'interval': List(Value('float64')), 'n': Value('int64'), 'ndcg@10': Value('float64'), 'controls': {}, 'cell': Value('string'), 'run': {'experiment': Value('string'), 'commit': Value('string'), 'date': Value('timestamp[s]'), 'seed': Value('int64')}, 'cost': {'fit_seconds': Value('float64'), 'usd_per_1k': Value('null')}}, 'douban-tridomain-transfer': {'recall@10': Value('float64'), 'interval': List(Value('float64')), 'n': Value('int64'), 'ndcg@10': Value('float64'), 'controls': {}, 'cell': Value('string'), 'run': {'experiment': Value('string'), 'commit': Value('string'), 'date': Value('timestamp[s]'), 'seed': Value('int64')}, 'cost': {'fit_seconds': Value('float64'), 'usd_per_1k': Value('null')}}}, 'leaderboard_release': Value('timestamp[s]'), 'eval_code_commit': Value('string')}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
User simulation leaderboard: results
One file per system per release, under <org>/<system>/results_<timestamp>.json.
results holds the score the leaderboard displays (Recall@10 per benchmark). record holds
everything that makes the row citable and is not shown in the grid: the person-clustered
bootstrap interval, n, NDCG@10, the popularity and stranger controls, the evaluation cell, and
the run that produced it (experiment id, commit, date, seed).
These files are generated, never edited: tools/leaderboard_export.py in Jean's evaluation
repository writes the site's leaderboard.json from each run's own results.json, and
convert.py in the leaderboard repository turns that into the files here. A rerun adds a file;
no file is rewritten.
Leaderboard: https://jeantechnologies.com/evals · Methodology: https://jeantechnologies.com/docs/leaderboard-methodology
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