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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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
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
|
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
|
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
|
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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