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The dataset generation failed because of a cast error
Error code:   DatasetGenerationCastError
Exception:    DatasetGenerationCastError
Message:      An error occurred while generating the dataset

All the data files must have the same columns, but at some point there are 80 new columns ({'p05_n119', 'p01_n176', 'p05_n155', 'p09_n188', 'p07_n132', 'p09_n168', 'p09_n189', 'p01_n167', 'p05_n179', 'p09_n114', 'p05_n147', 'p05_n121', 'p07_n113', 'p09_n171', 'p05_n154', 'p09_n160', 'p07_n161', 'p05_n126', 'p09_n190', 'p07_n164', 'p05_n156', 'p09_n142', 'p05_n153', 'p05_n174', 'p05_n116', 'p01_n131', 'p07_n158', 'p09_n124', 'p05_n187', 'p09_n172', 'p07_n139', 'p09_n123', 'p09_n150', 'p01_n136', 'p09_n137', 'p05_n178', 'p09_n169', 'p01_n148', 'p07_n127', 'p05_n125', 'p09_n122', 'p05_n166', 'p05_n134', 'p07_n117', 'p09_n177', 'p09_n112', 'p05_n183', 'p05_n157', 'p01_n191', 'p09_n115', 'p01_n135', 'p09_n163', 'p05_n128', 'p07_n165', 'p09_n152', 'p07_n184', 'p05_n130', 'p01_n162', 'p05_n144', 'p05_n146', 'p07_n149', 'p07_n181', 'p09_n180', 'p07_n185', 'p07_n141', 'p09_n133', 'p05_n140', 'p07_n159', 'p07_n151', 'p05_n129', 'p05_n186', 'p01_n182', 'p01_n138', 'p07_n173', 'p09_n143', 'p05_n145', 'p09_n120', 'p09_n175', 'p09_n170', 'p05_n118'}) and 112 missing columns ({'p04_n103', 'p01_n002', 'p01_n060', 'p06_n036', 'p04_n073', 'p05_n083', 'p01_n057', 'p05_n029', 'p05_n006', 'p01_n093', 'p05_n048', 'p01_n063', 'p05_n027', 'p05_n009', 'p04_n030', 'p06_n021', 'p05_n070', 'p04_n068', 'p01_n102', 'p05_n041', 'p06_n015', 'p05_n095', 'p06_n055', 'p01_n010', 'p02_n100', 'p04_n005', 'p01_n081', 'p06_n020', 'p05_n037', 'p04_n011', 'p01_n111', 'p05_n022', 'p04_n046', 'p01_n053', 'p01_n045', 'p02_n097', 'p02_n001', 'p05_n084', 'p05_n043', 'p05_n065', 'p06_n013', 'p02_n072', 'p05_n078', 'p01_n012', 'p01_n023', 'p04_n058', 'p01_n108', 'p06_n054', 'p06_n018', 'p01_n050', 'p01_n099', 'p02_n101', 'p05_n062', 'p01_n110', 'p06_n039', 'p02_n066', 'p01_n028', 'p06_n061', 'p06_n007', 'p01_n107', 'p06_n109', 'p05_n071', 'p01_n040', 'p06_n096', 'p01_n042', 'p05_n031', 'p05_n025', 'p05_n086', 'p02_n088', 'p04_n049', 'p06_n056', 'p04_n032', 'p01_n067', 'p01_n008', 'p01_n087', 'p05_n047', 'p01_n069', 'p01_n052', 'p04_n074', 'p04_n026', 'p06_n033', 'p05_n004', 'p05_n077', 'p01_n085', 'p01_n090', 'p05_n092', 'p04_n003', 'p04_n038', 'p04_n091', 'p04_n034', 'p05_n075', 'p01_n082', 'p01_n000', 'p05_n094', 'p04_n080', 'p04_n106', 'p02_n079', 'p01_n044', 'p05_n017', 'p04_n035', 'p04_n016', 'p02_n051', 'p02_n098', 'p05_n059', 'p05_n076', 'p06_n024', 'p01_n105', 'p04_n089', 'p02_n104', 'p06_n014', 'p06_n019', 'p05_n064'}).

This happened while the json dataset builder was generating data using

hf://datasets/mvazquez/LSE_eSaude_UVIGO_MSSL/data/val/val.json (at revision d58dec86dc1e680d142ec8e108ed48d06da35188)

Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2011, in _prepare_split_single
                  writer.write_table(table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 585, in write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2302, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2256, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              p09_n114: list<item: list<item: int64>>
                child 0, item: list<item: int64>
                    child 0, item: int64
              p05_n119: list<item: list<item: int64>>
                child 0, item: list<item: int64>
                    child 0, item: int64
              p09_n189: list<item: list<item: int64>>
                child 0, item: list<item: int64>
                    child 0, item: int64
              p09_n152: list<item: list<item: int64>>
                child 0, item: list<item: int64>
                    child 0, item: int64
              p07_n127: list<item: list<item: int64>>
                child 0, item: list<item: int64>
                    child 0, item: int64
              p01_n136: list<item: list<item: int64>>
                child 0, item: list<item: int64>
                    child 0, item: int64
              p01_n162: list<item: list<item: int64>>
                child 0, item: list<item: int64>
                    child 0, item: int64
              p09_n112: list<item: list<item: int64>>
                child 0, item: list<item: int64>
                    child 0, item: int64
              p07_n158: list<item: list<item: int64>>
                child 0, item: list<item: int64>
                    child 0, item: int64
              p07_n173: list<item: list<item: int64>>
                child 0, item: list<item: int64>
                    child 0, item: int64
              p09_n171: list<item: list<item: int64>>
                child 0, item: list<item: int64>
                    child 0, item: int64
              p09_n143: list<item: list<item: int64>>
                child 0, item: list<item: int64>
                    child 0, item: int64
              p09_n137: list<item: list<item: int64>>
                child 0, item: list<item: int64>
                    child 0, item: int64
              p07_n151: list<item: list<item: int64>>
                child 0, item: list<item: int64>
                    child 0, item: int64
              p09_n180: list<item: list<item: int64>>
                child 0, item: list<item: int6
              ...
              m: int64>>
                child 0, item: list<item: int64>
                    child 0, item: int64
              p05_n125: list<item: list<item: int64>>
                child 0, item: list<item: int64>
                    child 0, item: int64
              p01_n131: list<item: list<item: int64>>
                child 0, item: list<item: int64>
                    child 0, item: int64
              p07_n139: list<item: list<item: int64>>
                child 0, item: list<item: int64>
                    child 0, item: int64
              p05_n145: list<item: list<item: int64>>
                child 0, item: list<item: int64>
                    child 0, item: int64
              p09_n168: list<item: list<item: int64>>
                child 0, item: list<item: int64>
                    child 0, item: int64
              p07_n113: list<item: list<item: int64>>
                child 0, item: list<item: int64>
                    child 0, item: int64
              p01_n148: list<item: list<item: int64>>
                child 0, item: list<item: int64>
                    child 0, item: int64
              p01_n138: list<item: list<item: int64>>
                child 0, item: list<item: int64>
                    child 0, item: int64
              p05_n178: list<item: list<item: int64>>
                child 0, item: list<item: int64>
                    child 0, item: int64
              p05_n174: list<item: list<item: int64>>
                child 0, item: list<item: int64>
                    child 0, item: int64
              p07_n185: list<item: list<item: int64>>
                child 0, item: list<item: int64>
                    child 0, item: int64
              p09_n133: list<item: list<item: int64>>
                child 0, item: list<item: int64>
                    child 0, item: int64
              p05_n146: list<item: list<item: int64>>
                child 0, item: list<item: int64>
                    child 0, item: int64
              p09_n124: list<item: list<item: int64>>
                child 0, item: list<item: int64>
                    child 0, item: int64
              to
              {'p01_n002': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'p06_n019': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'p06_n007': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'p01_n053': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'p04_n074': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'p05_n077': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'p05_n027': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'p05_n022': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'p01_n110': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'p06_n036': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'p01_n069': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'p06_n109': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'p04_n089': Sequence(feature=Sequence(feature=Value(dtype='int64', id=N
              ...
              Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'p06_n056': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'p04_n080': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'p05_n062': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'p04_n034': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'p04_n049': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'p06_n033': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'p02_n100': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'p04_n030': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'p06_n054': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'p05_n047': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'p06_n021': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'p01_n081': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None)}
              because column names don't match
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1321, in compute_config_parquet_and_info_response
                  parquet_operations = convert_to_parquet(builder)
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 935, in convert_to_parquet
                  builder.download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1027, in download_and_prepare
                  self._download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1122, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1882, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2013, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
              datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
              
              All the data files must have the same columns, but at some point there are 80 new columns ({'p05_n119', 'p01_n176', 'p05_n155', 'p09_n188', 'p07_n132', 'p09_n168', 'p09_n189', 'p01_n167', 'p05_n179', 'p09_n114', 'p05_n147', 'p05_n121', 'p07_n113', 'p09_n171', 'p05_n154', 'p09_n160', 'p07_n161', 'p05_n126', 'p09_n190', 'p07_n164', 'p05_n156', 'p09_n142', 'p05_n153', 'p05_n174', 'p05_n116', 'p01_n131', 'p07_n158', 'p09_n124', 'p05_n187', 'p09_n172', 'p07_n139', 'p09_n123', 'p09_n150', 'p01_n136', 'p09_n137', 'p05_n178', 'p09_n169', 'p01_n148', 'p07_n127', 'p05_n125', 'p09_n122', 'p05_n166', 'p05_n134', 'p07_n117', 'p09_n177', 'p09_n112', 'p05_n183', 'p05_n157', 'p01_n191', 'p09_n115', 'p01_n135', 'p09_n163', 'p05_n128', 'p07_n165', 'p09_n152', 'p07_n184', 'p05_n130', 'p01_n162', 'p05_n144', 'p05_n146', 'p07_n149', 'p07_n181', 'p09_n180', 'p07_n185', 'p07_n141', 'p09_n133', 'p05_n140', 'p07_n159', 'p07_n151', 'p05_n129', 'p05_n186', 'p01_n182', 'p01_n138', 'p07_n173', 'p09_n143', 'p05_n145', 'p09_n120', 'p09_n175', 'p09_n170', 'p05_n118'}) and 112 missing columns ({'p04_n103', 'p01_n002', 'p01_n060', 'p06_n036', 'p04_n073', 'p05_n083', 'p01_n057', 'p05_n029', 'p05_n006', 'p01_n093', 'p05_n048', 'p01_n063', 'p05_n027', 'p05_n009', 'p04_n030', 'p06_n021', 'p05_n070', 'p04_n068', 'p01_n102', 'p05_n041', 'p06_n015', 'p05_n095', 'p06_n055', 'p01_n010', 'p02_n100', 'p04_n005', 'p01_n081', 'p06_n020', 'p05_n037', 'p04_n011', 'p01_n111', 'p05_n022', 'p04_n046', 'p01_n053', 'p01_n045', 'p02_n097', 'p02_n001', 'p05_n084', 'p05_n043', 'p05_n065', 'p06_n013', 'p02_n072', 'p05_n078', 'p01_n012', 'p01_n023', 'p04_n058', 'p01_n108', 'p06_n054', 'p06_n018', 'p01_n050', 'p01_n099', 'p02_n101', 'p05_n062', 'p01_n110', 'p06_n039', 'p02_n066', 'p01_n028', 'p06_n061', 'p06_n007', 'p01_n107', 'p06_n109', 'p05_n071', 'p01_n040', 'p06_n096', 'p01_n042', 'p05_n031', 'p05_n025', 'p05_n086', 'p02_n088', 'p04_n049', 'p06_n056', 'p04_n032', 'p01_n067', 'p01_n008', 'p01_n087', 'p05_n047', 'p01_n069', 'p01_n052', 'p04_n074', 'p04_n026', 'p06_n033', 'p05_n004', 'p05_n077', 'p01_n085', 'p01_n090', 'p05_n092', 'p04_n003', 'p04_n038', 'p04_n091', 'p04_n034', 'p05_n075', 'p01_n082', 'p01_n000', 'p05_n094', 'p04_n080', 'p04_n106', 'p02_n079', 'p01_n044', 'p05_n017', 'p04_n035', 'p04_n016', 'p02_n051', 'p02_n098', 'p05_n059', 'p05_n076', 'p06_n024', 'p01_n105', 'p04_n089', 'p02_n104', 'p06_n014', 'p06_n019', 'p05_n064'}).
              
              This happened while the json dataset builder was generating data using
              
              hf://datasets/mvazquez/LSE_eSaude_UVIGO_MSSL/data/val/val.json (at revision d58dec86dc1e680d142ec8e108ed48d06da35188)
              
              Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)

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p01_n002
sequence
p06_n019
sequence
p06_n007
sequence
p01_n053
sequence
p04_n074
sequence
p05_n077
sequence
p05_n027
sequence
p05_n022
sequence
p01_n110
sequence
p06_n036
sequence
p01_n069
sequence
p06_n109
sequence
p04_n089
sequence
p01_n044
sequence
p05_n037
sequence
p04_n038
sequence
p06_n055
sequence
p01_n099
sequence
p02_n066
sequence
p04_n035
sequence
p01_n057
sequence
p01_n105
sequence
p04_n058
sequence
p05_n043
sequence
p06_n020
sequence
p02_n001
sequence
p04_n032
sequence
p05_n084
sequence
p01_n102
sequence
p06_n096
sequence
p02_n104
sequence
p01_n090
sequence
p01_n040
sequence
p04_n073
sequence
p01_n067
sequence
p05_n004
sequence
p06_n061
sequence
p05_n092
sequence
p06_n015
sequence
p04_n106
sequence
p05_n095
sequence
p02_n072
sequence
p05_n031
sequence
p01_n060
sequence
p05_n048
sequence
p05_n029
sequence
p01_n000
sequence
p01_n050
sequence
p05_n025
sequence
p04_n011
sequence
p01_n023
sequence
p01_n042
sequence
p01_n111
sequence
p05_n083
sequence
p05_n094
sequence
p04_n103
sequence
p01_n093
sequence
p04_n003
sequence
p05_n078
sequence
p01_n052
sequence
p02_n098
sequence
p06_n013
sequence
p05_n006
sequence
p01_n063
sequence
p02_n097
sequence
p05_n065
sequence
p01_n108
sequence
p06_n018
sequence
p05_n009
sequence
p05_n071
sequence
p04_n091
sequence
p05_n075
sequence
p01_n012
sequence
p05_n076
sequence
p04_n005
sequence
p04_n046
sequence
p01_n045
sequence
p05_n041
sequence
p01_n008
sequence
p02_n101
sequence
p01_n085
sequence
p05_n064
sequence
p05_n017
sequence
p01_n028
sequence
p02_n079
sequence
p01_n010
sequence
p01_n082
sequence
p01_n107
sequence
p02_n088
sequence
p01_n087
sequence
p05_n086
sequence
p06_n024
sequence
p05_n070
sequence
p04_n016
sequence
p04_n068
sequence
p04_n026
sequence
p06_n039
sequence
p06_n014
sequence
p05_n059
sequence
p02_n051
sequence
p06_n056
sequence
p04_n080
sequence
p05_n062
sequence
p04_n034
sequence
p04_n049
sequence
p06_n033
sequence
p02_n100
sequence
p04_n030
sequence
p06_n054
sequence
p05_n047
sequence
p06_n021
sequence
p01_n081
sequence
[ [ 17, 640, 1200 ], [ 8, 11000, 12000 ], [ 36, 18960, 19320 ], [ 39, 19800, 20080 ], [ 39, 20400, 20760 ], [ 1, 25360, 26360 ], [ 41, 30600, 30920 ], [ 37, 32960, 33320 ], [ 50, 34680, 35040 ], [ 12, 38800, 39120 ], [ 25, 44640, 45120 ], [ 59, 48160, 48480 ], [ 45, 49840, 50040 ], [ 12, 50400, 50760 ], [ 7, 52600, 52880 ], [ 13, 53200, 53640 ], [ 10, 56320, 56560 ], [ 7, 57640, 57760 ] ]
[ [ 21, 1000, 1480 ], [ 46, 6120, 6720 ], [ 17, 7120, 7760 ], [ 51, 10880, 11960 ], [ 22, 14600, 15200 ], [ 14, 15360, 16040 ], [ 33, 19360, 20080 ], [ 40, 23400, 23920 ], [ 17, 24400, 25320 ], [ 17, 28680, 29400 ], [ 37, 32720, 32960 ], [ 42, 39520, 40080 ], [ 50, 40240, 40680 ], [ 50, 43360, 43600 ], [ 17, 48160, 48760 ], [ 37, 48920, 49200 ], [ 42, 51720, 52280 ], [ 10, 53440, 53960 ], [ 18, 54880, 56040 ], [ 31, 57000, 57680 ], [ 17, 59680, 60000 ], [ 53, 60160, 60760 ], [ 42, 66280, 66760 ], [ 42, 67320, 67960 ], [ 17, 71560, 72120 ], [ 41, 73720, 74320 ], [ 44, 77120, 78000 ] ]
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YAML Metadata Warning: empty or missing yaml metadata in repo card (https://huggingface.co/docs/hub/datasets-cards)

annotations_creators:

  • expert-generated language:
  • lse language_creators:
  • expert-generated license:
  • mit multilinguality:
  • monolingual pretty_name:
  • LSE_eSaude_UVIGO_MSSL size_categories:
  • n<1K source_datasets:
  • original tags:
  • sign spotting
  • sign language recognition
  • lse task_categories:
  • other task_ids: []

Dataset Card for LSE_eSaude_UVIGO_MSSL

Dataset Summary

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Supported Tasks and Leaderboards

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Languages

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Dataset Structure

Data Instances

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Data Fields

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Data Splits

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Dataset Creation

Curation Rationale

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Source Data

Initial Data Collection and Normalization

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Who are the source language producers?

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Annotations

Annotation process

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Who are the annotators?

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Personal and Sensitive Information

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Considerations for Using the Data

Social Impact of Dataset

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Other Known Limitations

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Additional Information

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Contributions

Thanks to @github-username for adding this dataset.

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