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maennyn
/
pv056-topic2-augment

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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 2 new columns ({'__index_level_0__', '{'}) and 16 missing columns ({'params_early_stopping_patience', 'number', 'duration', 'params_gradient_accumulation_steps', 'params_warmup_ratio', 'params_lr_scheduler_type', 'params_learning_rate', 'value', 'params_batch_size', 'datetime_start', 'state', 'params_weight_decay', 'datetime_complete', 'params_dropout', 'params_num_train_epochs', 'params_adam_epsilon'}).

This happened while the csv dataset builder was generating data using

zip://optuna_results/optuna_best_trial_hazard-category.json::/tmp/hf-datasets-cache/medium/datasets/79727867861211-config-parquet-and-info-maennyn-pv056-topic2-augm-d2f5e37e/hub/datasets--maennyn--pv056-topic2-augment/snapshots/090a737d36c20bb523aed320da250a54e5d8945d/optuna_results.zip

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 1871, in _prepare_split_single
                  writer.write_table(table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 623, 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 2293, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2241, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              {: double
              __index_level_0__: string
              -- schema metadata --
              pandas: '{"index_columns": ["__index_level_0__"], "column_indexes": [{"na' + 435
              to
              {'number': Value(dtype='int64', id=None), 'value': Value(dtype='float64', id=None), 'datetime_start': Value(dtype='string', id=None), 'datetime_complete': Value(dtype='string', id=None), 'duration': Value(dtype='string', id=None), 'params_adam_epsilon': Value(dtype='float64', id=None), 'params_batch_size': Value(dtype='int64', id=None), 'params_dropout': Value(dtype='float64', id=None), 'params_early_stopping_patience': Value(dtype='int64', id=None), 'params_gradient_accumulation_steps': Value(dtype='int64', id=None), 'params_learning_rate': Value(dtype='float64', id=None), 'params_lr_scheduler_type': Value(dtype='string', id=None), 'params_num_train_epochs': Value(dtype='int64', id=None), 'params_warmup_ratio': Value(dtype='float64', id=None), 'params_weight_decay': Value(dtype='float64', id=None), 'state': Value(dtype='string', 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 1438, 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 1050, in convert_to_parquet
                  builder.download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 925, in download_and_prepare
                  self._download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1001, 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 1742, 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 1873, 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 2 new columns ({'__index_level_0__', '{'}) and 16 missing columns ({'params_early_stopping_patience', 'number', 'duration', 'params_gradient_accumulation_steps', 'params_warmup_ratio', 'params_lr_scheduler_type', 'params_learning_rate', 'value', 'params_batch_size', 'datetime_start', 'state', 'params_weight_decay', 'datetime_complete', 'params_dropout', 'params_num_train_epochs', 'params_adam_epsilon'}).
              
              This happened while the csv dataset builder was generating data using
              
              zip://optuna_results/optuna_best_trial_hazard-category.json::/tmp/hf-datasets-cache/medium/datasets/79727867861211-config-parquet-and-info-maennyn-pv056-topic2-augm-d2f5e37e/hub/datasets--maennyn--pv056-topic2-augment/snapshots/090a737d36c20bb523aed320da250a54e5d8945d/optuna_results.zip
              
              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)

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

number
int64
value
float64
datetime_start
string
datetime_complete
string
duration
string
params_adam_epsilon
float64
params_batch_size
int64
params_dropout
float64
params_early_stopping_patience
int64
params_gradient_accumulation_steps
int64
params_learning_rate
float64
params_lr_scheduler_type
string
params_num_train_epochs
int64
params_warmup_ratio
float64
params_weight_decay
float64
state
string
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0.000035
cosine_with_restarts
5
0.097825
0.220109
COMPLETE
18
0.667367
2025-04-14 05:07:19.543533
2025-04-14 05:31:57.468192
0 days 00:24:37.924659
0
8
0.354771
3
2
0.000059
cosine_with_restarts
4
0.195581
0.395944
COMPLETE
19
0.760406
2025-04-14 05:31:57.494129
2025-04-14 06:22:20.751727
0 days 00:50:23.257598
0
16
0.161945
3
1
0.000026
cosine
9
0.078417
0.002232
COMPLETE
0
0.745842
2025-04-13 20:24:07.951120
2025-04-13 20:48:43.082810
0 days 00:24:35.131690
0
16
0.314475
2
1
0.000019
linear
4
0.034819
0.294412
COMPLETE
1
0.768568
2025-04-13 20:48:43.102377
2025-04-13 21:31:18.573841
0 days 00:42:35.471464
0.000001
16
0.261898
3
2
0.000106
cosine_with_restarts
10
0.164889
0.012603
COMPLETE
2
0.727797
2025-04-13 21:31:18.589255
2025-04-13 22:08:35.366258
0 days 00:37:16.777003
0
64
0.294212
3
4
0.000274
linear
10
0.10292
0.474571
COMPLETE
3
0.501799
2025-04-13 22:08:35.381231
2025-04-13 22:31:44.635238
0 days 00:23:09.254007
0
32
0.48718
2
2
0.000258
cosine
7
0.245337
0.493292
COMPLETE
4
0.548973
2025-04-13 22:31:44.649840
2025-04-13 23:19:07.049631
0 days 00:47:22.399791
0
32
0.440243
3
2
0.000013
linear
9
0.418937
0.304592
COMPLETE
5
0.754696
2025-04-13 23:19:07.065276
2025-04-13 23:37:31.232068
0 days 00:18:24.166792
0
32
0.111626
3
2
0.000007
polynomial
3
0.238898
0.34115
COMPLETE
6
0.278391
2025-04-13 23:37:31.247788
2025-04-13 23:57:08.990696
0 days 00:19:37.742908
0
8
0.479907
1
2
0.000006
polynomial
3
0.02374
0.017381
COMPLETE
7
0.302904
2025-04-13 23:57:09.005601
2025-04-14 00:10:40.248609
0 days 00:13:31.243008
0.000001
32
0.306241
1
2
0.000006
cosine_with_restarts
2
0.485084
0.449077
COMPLETE
8
0.743569
2025-04-14 00:10:40.263855
2025-04-14 00:30:03.071031
0 days 00:19:22.807176
0
16
0.266994
1
1
0.000074
polynomial
5
0.082203
0.051104
COMPLETE
9
0.732314
2025-04-14 00:30:03.085622
2025-04-14 01:15:17.476371
0 days 00:45:14.390749
0
16
0.456202
3
1
0.00005
linear
8
0.363165
0.467752
COMPLETE
10
0.75519
2025-04-14 01:15:17.611426
2025-04-14 01:43:05.963019
0 days 00:27:48.351593
0
64
0.180933
2
4
0.000117
cosine_with_restarts
6
0.157655
0.139444
COMPLETE
11
0.725849
2025-04-14 01:43:05.979971
2025-04-14 02:15:31.610084
0 days 00:32:25.630113
0
64
0.166741
2
4
0.000119
cosine_with_restarts
6
0.161664
0.133655
COMPLETE
12
0.651861
2025-04-14 02:15:31.625940
2025-04-14 02:33:42.716385
0 days 00:18:11.090445
0
64
0.200562
2
4
0.000114
cosine_with_restarts
7
0.164267
0.146554
COMPLETE
13
0.609301
2025-04-14 02:33:42.731741
2025-04-14 02:57:22.429899
0 days 00:23:39.698158
0
8
0.220867
2
4
0.000142
cosine_with_restarts
6
0.299694
0.110999
COMPLETE
14
0.690134
2025-04-14 02:57:22.445082
2025-04-14 03:29:46.922961
0 days 00:32:24.477879
0
16
0.372677
3
4
0.000028
cosine_with_restarts
10
0.17815
0.198483
COMPLETE
15
0.658496
2025-04-14 03:29:46.937789
2025-04-14 04:12:20.538689
0 days 00:42:33.600900
0.000001
64
0.107666
2
2
0.000366
cosine
8
0.296015
0.075555
COMPLETE
16
0.761799
2025-04-14 04:12:20.553242
2025-04-14 04:39:57.193295
0 days 00:27:36.640053
0
64
0.204911
3
4
0.000044
cosine_with_restarts
5
0.113995
0.202011
COMPLETE
17
0.678262
2025-04-14 04:39:57.207931
2025-04-14 05:07:19.528190
0 days 00:27:22.320259
0
16
0.247983
3
4
0.000035
cosine_with_restarts
5
0.097825
0.220109
COMPLETE
18
0.667367
2025-04-14 05:07:19.543533
2025-04-14 05:31:57.468192
0 days 00:24:37.924659
0
8
0.354771
3
2
0.000059
cosine_with_restarts
4
0.195581
0.395944
COMPLETE
19
0.760406
2025-04-14 05:31:57.494129
2025-04-14 06:22:20.751727
0 days 00:50:23.257598
0
16
0.161945
3
1
0.000026
cosine
9
0.078417
0.002232
COMPLETE
20
0.035202
2025-04-14 06:22:20.888068
2025-04-14 06:49:55.945025
0 days 00:27:35.056957
0
64
0.379104
3
4
0.000012
cosine_with_restarts
5
0.002636
0.185424
COMPLETE
21
0.593993
2025-04-14 06:49:55.961215
2025-04-14 07:35:20.791345
0 days 00:45:24.830130
0
16
0.160724
3
1
0.000026
cosine
9
0.070004
0.000557
COMPLETE
22
0.586166
2025-04-14 07:35:20.806553
2025-04-14 08:25:50.501011
0 days 00:50:29.694458
0
16
0.14149
3
1
0.00007
cosine
9
0.121703
0.068357
COMPLETE
23
0.591673
2025-04-14 08:25:50.516128
2025-04-14 09:21:30.149618
0 days 00:55:39.633490
0
16
0.219554
3
1
0.000038
cosine
10
0.055833
0.03512
COMPLETE
24
0.548058
2025-04-14 09:21:30.164157
2025-04-14 10:06:52.334799
0 days 00:45:22.170642
0
16
0.245778
3
1
0.000182
cosine
8
0.133024
0.096675
COMPLETE
25
0.601774
2025-04-14 10:06:52.349615
2025-04-14 10:47:01.940220
0 days 00:40:09.590605
0
16
0.138634
3
1
0.000073
cosine_with_restarts
7
0.218555
0.260098
COMPLETE
26
0.483984
2025-04-14 10:47:01.955710
2025-04-14 11:34:28.983081
0 days 00:47:27.027371
0.000001
64
0.192816
3
2
0.000016
cosine
9
0.297757
0.00749
COMPLETE
27
0.570049
2025-04-14 11:34:28.998026
2025-04-14 12:29:08.127486
0 days 00:54:39.129460
0
8
0.264089
3
1
0.000039
polynomial
10
0.132837
0.170918
COMPLETE
28
0.567549
2025-04-14 12:29:08.142428
2025-04-14 13:07:00.409978
0 days 00:37:52.267550
0
16
0.215433
2
2
0.000024
cosine_with_restarts
8
0.199093
0.091534
COMPLETE
29
0.249773
2025-04-14 13:07:00.427960
2025-04-14 13:29:51.878212
0 days 00:22:51.450252
0
16
0.340699
2
4
0.00002
linear
4
0.043682
0.258951
COMPLETE
30
0.027159
2025-04-14 13:29:52.024614
2025-04-14 14:17:33.411041
0 days 00:47:41.386427
0
64
0.291574
3
1
0.000009
cosine
9
0.02494
0.377835
COMPLETE
31
0.171832
2025-04-14 14:17:33.427911
2025-04-14 14:49:55.598232
0 days 00:32:22.170321
0
64
0.181902
2
4
0.000097
cosine_with_restarts
6
0.13954
0.223443
COMPLETE
32
0.21989
2025-04-14 14:49:55.613180
2025-04-14 15:17:33.011454
0 days 00:27:37.398274
0
64
0.138796
2
4
0.000174
cosine_with_restarts
5
0.103958
0.136701
COMPLETE
33
0.211691
2025-04-14 15:17:33.026958
2025-04-14 15:49:58.140223
0 days 00:32:25.113265
0
64
0.239451
2
4
0.000238
cosine_with_restarts
6
0.0787
0.033123
COMPLETE
34
0.195033
2025-04-14 15:49:58.155433
2025-04-14 16:22:34.406769
0 days 00:32:36.251336
0
64
0.177913
1
4
0.000089
cosine_with_restarts
7
0.155403
0.058516
COMPLETE
35
0.166313
2025-04-14 16:22:34.421684
2025-04-14 17:14:09.001664
0 days 00:51:34.579980
0
32
0.280464
3
4
0.000044
linear
10
0.224447
0.121613
COMPLETE
36
0.11768
2025-04-14 17:14:09.019882
2025-04-14 17:37:20.763491
0 days 00:23:11.743609
0
64
0.201393
2
2
0.000058
cosine_with_restarts
4
0.27141
0.302364
COMPLETE
37
0.064641
2025-04-14 17:37:20.777523
2025-04-14 17:55:42.117443
0 days 00:18:21.339920
0
32
0.151611
3
2
0.000031
polynomial
3
0.197121
0.171933
COMPLETE
38
0.19702
2025-04-14 17:55:42.132535
2025-04-14 18:32:46.732034
0 days 00:37:04.599499
0
16
0.319532
2
4
0.000315
cosine
7
0.102733
0.222323
COMPLETE
39
0.000177
2025-04-14 18:32:46.747114
2025-04-14 18:47:02.767202
0 days 00:14:16.020088
0
8
0.228803
1
2
0.0002
linear
6
0.001617
0.026897
COMPLETE
End of preview.
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csv files of title augmented data for topic 2

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