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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 25 new columns ({'weighted_top1_wer', 'num_unique_wer', 'oracle_pred', 'top1_pred', 'top1_is_best', 'len', 'num_unique_hypotheses', 'ess_uniform', 'top1_wer', 'weighted_oracle_wer', 'mode_collapse', 'num_hypotheses', 'expected_uniform_wer', 'wer_var', 'Unnamed: 0', 'identical_wer_rate', 'duplicate_rate', 'oracle_wer', 'reference', 'gradient_signal_uniform', 'oracle_diff', 'wer_std', 'oracle_gap', 'all_wers_same', 'preds'}) and 9 missing columns ({'filesize_bytes', 'age_bucket', 'iter', 'md5_hash', 'audio_duration_sec', 'pred', 'child_id', 'session_id', 'orthographic_text'}).

This happened while the csv dataset builder was generating data using

hf://datasets/quinnlue/mwer-hypos/mwer_exs.csv (at revision 08bdfe310591067c196beb6d2ca17c1bfc1997a4), [/tmp/hf-datasets-cache/medium/datasets/30463613955819-config-parquet-and-info-quinnlue-mwer-hypos-b04e1fee/hub/datasets--quinnlue--mwer-hypos/snapshots/08bdfe310591067c196beb6d2ca17c1bfc1997a4/8_samples.csv (origin=hf://datasets/quinnlue/mwer-hypos@08bdfe310591067c196beb6d2ca17c1bfc1997a4/8_samples.csv), /tmp/hf-datasets-cache/medium/datasets/30463613955819-config-parquet-and-info-quinnlue-mwer-hypos-b04e1fee/hub/datasets--quinnlue--mwer-hypos/snapshots/08bdfe310591067c196beb6d2ca17c1bfc1997a4/beam-search.csv (origin=hf://datasets/quinnlue/mwer-hypos@08bdfe310591067c196beb6d2ca17c1bfc1997a4/beam-search.csv), /tmp/hf-datasets-cache/medium/datasets/30463613955819-config-parquet-and-info-quinnlue-mwer-hypos-b04e1fee/hub/datasets--quinnlue--mwer-hypos/snapshots/08bdfe310591067c196beb6d2ca17c1bfc1997a4/mwer_exs.csv (origin=hf://datasets/quinnlue/mwer-hypos@08bdfe310591067c196beb6d2ca17c1bfc1997a4/mwer_exs.csv), /tmp/hf-datasets-cache/medium/datasets/30463613955819-config-parquet-and-info-quinnlue-mwer-hypos-b04e1fee/hub/datasets--quinnlue--mwer-hypos/snapshots/08bdfe310591067c196beb6d2ca17c1bfc1997a4/results.csv (origin=hf://datasets/quinnlue/mwer-hypos@08bdfe310591067c196beb6d2ca17c1bfc1997a4/results.csv)]

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 "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1890, in _prepare_split_single
                  writer.write_table(table)
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 760, in write_table
                  pa_table = table_cast(pa_table, self._schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2272, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              Unnamed: 0: int64
              utterance_id: string
              num_hypotheses: int64
              num_unique_hypotheses: int64
              duplicate_rate: double
              num_unique_wer: int64
              identical_wer_rate: double
              top1_pred: string
              top1_wer: double
              oracle_pred: string
              oracle_wer: double
              oracle_gap: double
              oracle_diff: bool
              top1_is_best: bool
              wer_var: double
              wer_std: double
              expected_uniform_wer: double
              gradient_signal_uniform: double
              ess_uniform: double
              mode_collapse: bool
              all_wers_same: bool
              reference: string
              preds: string
              len: int64
              weighted_oracle_wer: double
              weighted_top1_wer: double
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 3482
              to
              {'utterance_id': Value('string'), 'child_id': Value('string'), 'session_id': Value('string'), 'audio_duration_sec': Value('float64'), 'age_bucket': Value('string'), 'md5_hash': Value('string'), 'filesize_bytes': Value('int64'), 'orthographic_text': Value('string'), 'pred': Value('string'), 'iter': Value('int64')}
              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 1347, 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 980, in convert_to_parquet
                  builder.download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 884, in download_and_prepare
                  self._download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 947, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1739, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1892, 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 25 new columns ({'weighted_top1_wer', 'num_unique_wer', 'oracle_pred', 'top1_pred', 'top1_is_best', 'len', 'num_unique_hypotheses', 'ess_uniform', 'top1_wer', 'weighted_oracle_wer', 'mode_collapse', 'num_hypotheses', 'expected_uniform_wer', 'wer_var', 'Unnamed: 0', 'identical_wer_rate', 'duplicate_rate', 'oracle_wer', 'reference', 'gradient_signal_uniform', 'oracle_diff', 'wer_std', 'oracle_gap', 'all_wers_same', 'preds'}) and 9 missing columns ({'filesize_bytes', 'age_bucket', 'iter', 'md5_hash', 'audio_duration_sec', 'pred', 'child_id', 'session_id', 'orthographic_text'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/quinnlue/mwer-hypos/mwer_exs.csv (at revision 08bdfe310591067c196beb6d2ca17c1bfc1997a4), [/tmp/hf-datasets-cache/medium/datasets/30463613955819-config-parquet-and-info-quinnlue-mwer-hypos-b04e1fee/hub/datasets--quinnlue--mwer-hypos/snapshots/08bdfe310591067c196beb6d2ca17c1bfc1997a4/8_samples.csv (origin=hf://datasets/quinnlue/mwer-hypos@08bdfe310591067c196beb6d2ca17c1bfc1997a4/8_samples.csv), /tmp/hf-datasets-cache/medium/datasets/30463613955819-config-parquet-and-info-quinnlue-mwer-hypos-b04e1fee/hub/datasets--quinnlue--mwer-hypos/snapshots/08bdfe310591067c196beb6d2ca17c1bfc1997a4/beam-search.csv (origin=hf://datasets/quinnlue/mwer-hypos@08bdfe310591067c196beb6d2ca17c1bfc1997a4/beam-search.csv), /tmp/hf-datasets-cache/medium/datasets/30463613955819-config-parquet-and-info-quinnlue-mwer-hypos-b04e1fee/hub/datasets--quinnlue--mwer-hypos/snapshots/08bdfe310591067c196beb6d2ca17c1bfc1997a4/mwer_exs.csv (origin=hf://datasets/quinnlue/mwer-hypos@08bdfe310591067c196beb6d2ca17c1bfc1997a4/mwer_exs.csv), /tmp/hf-datasets-cache/medium/datasets/30463613955819-config-parquet-and-info-quinnlue-mwer-hypos-b04e1fee/hub/datasets--quinnlue--mwer-hypos/snapshots/08bdfe310591067c196beb6d2ca17c1bfc1997a4/results.csv (origin=hf://datasets/quinnlue/mwer-hypos@08bdfe310591067c196beb6d2ca17c1bfc1997a4/results.csv)]
              
              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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utterance_id
string
child_id
string
session_id
string
audio_duration_sec
float64
age_bucket
string
md5_hash
string
filesize_bytes
int64
orthographic_text
string
pred
string
iter
int64
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a
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not
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eating
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S_13d5b9593829b051
0.502
8-11
f0c2c9c9f717f4ce660f33f9ce0ccfa8
26,216
mm
hm
0
U_2767f4bdd7633453
C_63e75214911251ca
S_aaf81c6389ef6ada
0.502
3-4
d7bb960b1144996a905660e7fe99c9f6
42,832
mhm
we
0
U_2f796926a47108b9
C_8b22e51b2b7330a5
S_1ec0801819ae8a32
0.502
3-4
541411e48c7cc79b068c1902d4f472fb
38,169
nice
nice
0
U_33c7731fe2c2a307
C_307729a9d5ccacb3
S_e15ab659be16ea75
0.502
8-11
75db38a5f4a49685184d70cc6bc57fc5
25,572
no
no
0
U_365f9cdb96e4a705
C_9535ba756e681479
S_e8992cfa0812ce3a
0.502
5-7
dc3bc4bfcbe3f2ab64786a221892ea62
30,047
s
s
0
U_3a8be1694c809d7d
C_d212518a7a45c0b6
S_67910608f6e85177
0.502
12+
49450bb3b52032eacc6400da046995cc
30,181
seven
seven
0
U_4314ed6ca8596645
C_e04e54b01b1c652b
S_65af7e8ec376f088
0.502
3-4
abe3d09733f180ca5e6be261d4d8cbe8
35,952
yeah
yeah
0
U_43f816061f3f49dc
C_165b9340ca934b44
S_bd250296b6621efc
0.502
5-7
6cd5f807df95ffddbeeb9ecf4efda316
25,041
mhm
mhm
0
U_4aa07db11298ca98
C_d2fbddadbe604bc4
S_a2ba075d43756a4f
0.502
5-7
bb8d6adc0882354b4e37bf43ae7c6652
28,494
a boy
a boy
0
U_4b0dee29e407b56f
C_58700818bbf27285
S_1f0fa56416a649de
0.502
3-4
3a9d28b1c7e53929acbad08fdf05543b
36,374
where
here we go
0
U_4dda9cbd01d0f4ed
C_2a0f1248c7349c5a
S_fcb1ca3900677a59
0.502
5-7
999439b7af0c9cf4239c428ea30e4dfa
27,685
art
it hurts
0
U_50b1345b3652f89e
C_369248fed274c7f5
S_15b87ee01cd43178
0.502
unknown
08b74f80a28143245c45b4f4d7a71b44
25,320
eh
no
0
U_5d6901aef5ab2631
C_f5c61ded6961cc60
S_723382a14428a6e6
0.502
5-7
b2b2bac624567db3cf69d29f4678bffa
27,273
brib
brib
0
U_69df3bf45ce2ba81
C_2aee6ba62cf585bc
S_3f4a39b5cf1af4c4
0.502
12+
f275da2a7a1868680cf22159264d3a0a
30,743
hammer
hammer
0
U_74a243d67e84e361
C_2156467322a038b8
S_9d2efbf3bd34bf4e
0.502
3-4
3fc3c301b83dd9f9751ce2125c4fab76
22,061
blue
blue
0
U_78c13242e7efcfc1
C_340b5882a6c76cec
S_d825399f9baf9688
0.502
8-11
f9c6ddb85e8e40ba891009b82c63e17c
35,797
worm
worm
0
U_78f3e1fa9ae327cd
C_243d5edbf4972180
S_be2db7c26cf09779
0.502
5-7
5c7f5abf62d8474875807af62bb5bb62
25,078
no
nope
0
U_7cce4e63400d66b2
C_cf9e931e2588baff
S_bfe6da842dbbffe7
0.502
8-11
baa9b54ddb412b95b9d3297601075f6d
18,854
ray
ray
0
U_808fa634cbb0fa62
C_2aee6ba62cf585bc
S_d2af077a36323673
0.502
12+
0f6f47661fb8141a86847a2ae82c5b6e
32,334
chair
chair
0
U_8b4428608195e555
C_1ee353848527a253
S_4292367ffef08b27
0.502
8-11
e3309f82534a321664a58265c6a113ed
28,778
ladder
ladder
0
U_92c0beadccaf59d1
C_00ad9123833bf1cb
S_4117617467ee8e62
0.502
5-7
bea0f2be910a26596a10cf47e44c478f
34,861
sharp
sharp
0
U_92cea4a51cfbb8eb
C_0b03744aff1b4e67
S_b6c5951c604a321d
0.502
12+
617e8cca1609b3b27c6f9c0455ff3d9c
28,580
plate
plate
0
U_9354d157ca7ab1e9
C_3e9aa0e6b0779f01
S_0298e0d08c46f59b
0.502
3-4
3fcea0e15ffa345a2681eb3c950a47fe
37,421
get off
get up
0
U_9407c8682121b6eb
C_c48420d4a300bda0
S_874bec88fdcae979
0.502
8-11
6411b1208288152e5d8067b4a8dc25fa
34,699
truck
truck
0
U_986d83a2c8c48338
C_fc35aea54a8cc67c
S_38a5f95608deb427
0.502
12+
e6e5503ccf5831a62182d7c47db9d5a1
30,459
go
go
0
U_9f0d905bd020ddb1
C_4c52ae7575d26b78
S_34583e8e56146c9f
0.502
3-4
c7e820bedcbdf03efa6c279bfff514c2
35,411
yep
hello
0
U_a4c4a1a279d146a1
C_636e4ba68c50ad2d
S_bd6da5f174f74876
0.502
3-4
bddf8acbebe8a1d03f7075c2736bcf42
34,672
fish
fish
0
U_ace102e6ff318815
C_00ad9123833bf1cb
S_4117617467ee8e62
0.502
5-7
a17824a026b324a62baae0fee5b428c9
32,509
bears
bear
0
U_b4f91c1f0c05ad67
C_82cdd1c99a652d2a
S_30f9b50cdd921c80
0.502
8-11
07e1c00d60d10c5114957b0fcf8171e6
28,399
red
red
0
U_b51e41eea9f81bfa
C_5182c2e2ea22056b
S_40d83381876fee45
0.502
unknown
7d4151467e3a97701533f6078a7f4530
24,001
v
b
0
U_be6c255a2f65ea57
C_6799831728628309
S_e883ce952f19bc79
0.502
5-7
19ed17ce70d3d8482cbfcea4b234dddf
29,411
a shoe
shoe
0
U_c2d8d60e4119140d
C_be57f29be4ed8115
S_863030a698a31772
0.502
12+
d29aa59d6173be32d166c158699bdd11
35,108
spoon
spoon
0
U_c4a5d57ff126ca61
C_687daee57e413f7e
S_732638e18745e200
0.502
8-11
3e944095883d8be51e9fdc0dd249822e
27,439
seven
seven
0
U_ca99c480ebb095b0
C_34267915b84bc67c
S_66790158d0ba8d1d
0.502
5-7
963443ab5345e52aa33ff8c6fb111966
26,957
wait
wait
0
U_d291bc246d19fd83
C_f86c7edbc46bc2fe
S_2882153c1a1d1331
0.502
5-7
5186d9d73d9a949d924dabe7cf9bf65e
28,459
mhm
mhm
0
U_d5464a403339d56d
C_622ca64dbd671038
S_47a5e0b638c79da8
0.502
5-7
7ce6f3c9ad0d8a4696be4afb5418be2a
28,547
snacks
six
0
U_d7c7fd8095c1b981
C_687daee57e413f7e
S_732638e18745e200
0.502
8-11
f93b79d43dbd5e8be916758e2ef23327
27,638
plate
plate
0
U_d90431748fb8974a
C_5faf6987399a8628
S_0905606a3ae21505
0.502
8-11
0d6c72c1bd034187629de2b7e3ad104c
27,640
swing
swing
0
U_dccaa4ca8fbef7c4
C_78c625a46184c002
S_aacfd6d5d26f635b
0.502
8-11
566dd45d580b39e45dd24c311298ebd4
28,026
youtube
you too
0
U_e061b91fdc33ca28
C_c40c6d69c6809045
S_d916664ad42cd70b
0.502
5-7
b00f9cc94eaafb7072c7b0635080f9c6
26,133
twenty
thirty
0
U_09dbd9873daad716
C_d356c5e5589284df
S_b1b4164e0ac6b0c3
0.502
3-4
7f4a9d8295784e5f0abc6b9f93aa6ab9
39,291
yeah
yeah
0
U_7646e6c920a0badb
C_08b1f5b285bcbfdf
S_add872975a858a4e
0.502
8-11
e219a038e4af0e16fc878b5a5a884471
15,894
we
we
0
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