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Tokz-labs
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OpenDecision-predictions

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Tags:

evaluation

predictions

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The dataset generation failed

Error code:   DatasetGenerationError
Exception:    TypeError
Message:      Couldn't cast array of type list<item: string> to string
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 2312, 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 1861, 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 2152, in cast_array_to_feature
                  return array_cast(
                      array,
                  ...<2 lines>...
                      allow_decimal_to_str=allow_decimal_to_str,
                  )
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1863, in wrapper
                  return func(array, *args, **kwargs)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2016, in array_cast
                  raise TypeError(f"Couldn't cast array of type {_short_str(array.type)} to {_short_str(pa_type)}")
              TypeError: Couldn't cast array of type list<item: string> to string
              
              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 1879, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset

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id string	pred string	gold string	status string
emotion-00000	sad	sad	ok
emotion-00001	sad	sad	ok
emotion-00002	affectionate	sad	ok
emotion-00003	happy	happy	ok
emotion-00004	happy	sad	ok
emotion-00005	afraid	afraid	ok
emotion-00006	angry	angry	ok
emotion-00007	affectionate	happy	ok
emotion-00008	happy	happy	ok
emotion-00009	surprised	angry	ok
emotion-00010	happy	afraid	ok
emotion-00011	affectionate	sad	ok
emotion-00012	afraid	afraid	ok
emotion-00013	happy	happy	ok
emotion-00014	surprised	affectionate	ok
emotion-00015	sad	sad	ok
emotion-00016	sad	happy	ok
emotion-00017	angry	sad	ok
emotion-00018	angry	angry	ok
emotion-00019	happy	happy	ok
emotion-00020	affectionate	sad	ok
emotion-00021	affectionate	happy	ok
emotion-00022	happy	happy	ok
emotion-00023	sad	sad	ok
emotion-00024	happy	sad	ok
emotion-00025	afraid	afraid	ok
emotion-00026	angry	angry	ok
emotion-00027	sad	sad	ok
emotion-00028	afraid	afraid	ok
emotion-00029	happy	angry	ok
emotion-00030	sad	afraid	ok
emotion-00031	sad	angry	ok
emotion-00032	sad	sad	ok
emotion-00033	sad	angry	ok
emotion-00034	sad	sad	ok
emotion-00035	happy	happy	ok
emotion-00036	happy	happy	ok
emotion-00037	sad	sad	ok
emotion-00038	happy	happy	ok
emotion-00039	happy	happy	ok
emotion-00040	angry	angry	ok
emotion-00041	sad	sad	ok
emotion-00042	happy	happy	ok
emotion-00043	afraid	sad	ok
emotion-00044	happy	happy	ok
emotion-00045	angry	angry	ok
emotion-00046	affectionate	happy	ok
emotion-00047	happy	happy	ok
emotion-00048	afraid	afraid	ok
emotion-00049	happy	afraid	ok
emotion-00050	sad	sad	ok
emotion-00051	afraid	afraid	ok
emotion-00052	happy	happy	ok
emotion-00053	afraid	sad	ok
emotion-00054	happy	happy	ok
emotion-00055	affectionate	sad	ok
emotion-00056	sad	sad	ok
emotion-00057	happy	happy	ok
emotion-00058	happy	sad	ok
emotion-00059	sad	angry	ok
emotion-00060	sad	sad	ok
emotion-00061	sad	sad	ok
emotion-00062	sad	happy	ok
emotion-00063	happy	happy	ok
emotion-00064	sad	sad	ok
emotion-00065	surprised	surprised	ok
emotion-00066	sad	sad	ok
emotion-00067	happy	angry	ok
emotion-00068	afraid	afraid	ok
emotion-00069	sad	surprised	ok
emotion-00070	affectionate	happy	ok
emotion-00071	sad	affectionate	ok
emotion-00072	surprised	surprised	ok
emotion-00073	affectionate	happy	ok
emotion-00074	afraid	affectionate	ok
emotion-00075	angry	angry	ok
emotion-00076	happy	happy	ok
emotion-00077	surprised	sad	ok
emotion-00078	happy	happy	ok
emotion-00079	affectionate	affectionate	ok
emotion-00080	happy	happy	ok
emotion-00081	angry	angry	ok
emotion-00082	sad	sad	ok
emotion-00083	affectionate	happy	ok
emotion-00084	sad	sad	ok
emotion-00085	sad	sad	ok
emotion-00086	affectionate	happy	ok
emotion-00087	happy	happy	ok
emotion-00088	happy	happy	ok
emotion-00089	sad	sad	ok
emotion-00090	happy	happy	ok
emotion-00091	sad	afraid	ok
emotion-00092	happy	angry	ok
emotion-00093	surprised	afraid	ok
emotion-00094	surprised	angry	ok
emotion-00095	angry	angry	ok
emotion-00096	affectionate	affectionate	ok
emotion-00097	afraid	sad	ok
emotion-00098	sad	angry	ok
emotion-00099	sad	sad	ok

End of preview.

OpenDecision evaluation predictions

Per-example predictions behind the tables of the OpenDecision technical report and the OpenDecision repository. No input text is included; inputs are rebuilt from the public datasets by the evaluation code.

Path	Model	Benchmark
`predictions/{model}/suite_full/{task}_preds.jsonl`	OpenDecision-Large, -Large-Packed, -Small	AG News, CLINC150, IMDb, Rotten Tomatoes, XNLI; complete test sets
`predictions/{model}/heldout/{task}_preds.jsonl`	same	TREC, Emotion, Subjectivity, GoEmotions (multi-label), TREC and Emotion with renamed labels

Suite and held-out rows are {"id", "pred", "gold", "status"} (lists for GoEmotions). Score them with

pip install "opendecision[eval] @ git+https://github.com/tokz-labs/OpenDecision"
huggingface-cli download Tokz-labs/OpenDecision-predictions --repo-type dataset --local-dir preds
python -m opendecision.cli.evaluate --set suite-full --preds preds/predictions/opendecision-large/suite_full
python -m opendecision.cli.evaluate --set heldout --preds preds/predictions/opendecision-large/heldout

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