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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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