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The dataset generation failed
Error code: DatasetGenerationError
Exception: ArrowInvalid
Message: JSON parse error: Invalid value. in row 0
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 324, in _generate_tables
df = pandas_read_json(f)
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 38, in pandas_read_json
return pd.read_json(path_or_buf, **kwargs)
~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 815, in read_json
return json_reader.read()
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1014, in read
obj = self._get_object_parser(self.data)
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1040, in _get_object_parser
obj = FrameParser(json, **kwargs).parse()
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1176, in parse
self._parse()
~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1392, in _parse
ujson_loads(json, precise_float=self.precise_float), dtype=None
~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ValueError: Trailing data
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1816, in _prepare_split_single
for key, table in generator:
^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 613, in wrapped
for item in generator(*args, **kwargs):
~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 327, in _generate_tables
raise e
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 290, in _generate_tables
pa_table = paj.read_json(
io.BytesIO(batch), read_options=paj.ReadOptions(block_size=block_size)
)
File "pyarrow/_json.pyx", line 342, in pyarrow._json.read_json
File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
return check_status(status)
File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
raise convert_status(status)
pyarrow.lib.ArrowInvalid: JSON parse error: Invalid value. in row 0
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
~~~~~~~~~~~~~~~~~~~~~~~~~^
builder, max_dataset_size_bytes=max_dataset_size_bytes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1683, in _prepare_split
for job_id, done, content in self._prepare_split_single(
~~~~~~~~~~~~~~~~~~~~~~~~~~^
gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
):
^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1869, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
current_steps int64 | total_steps int64 | loss float64 | lr float64 | epoch float64 | percentage float64 | elapsed_time string | remaining_time string | eval_loss float64 |
|---|---|---|---|---|---|---|---|---|
10 | 62,414 | 0.452055 | 0 | 0.00016 | 0.02 | 0:00:54 | 3 days, 22:13:20 | null |
20 | 62,414 | 0.469378 | 0 | 0.00032 | 0.03 | 0:01:47 | 3 days, 21:27:00 | null |
30 | 62,414 | 0.444894 | 0 | 0.000481 | 0.05 | 0:02:40 | 3 days, 20:45:36 | null |
40 | 62,414 | 0.427749 | 0 | 0.000641 | 0.06 | 0:03:33 | 3 days, 20:32:45 | null |
50 | 62,414 | 0.456652 | 0 | 0.000801 | 0.08 | 0:04:25 | 3 days, 20:09:29 | null |
60 | 62,414 | 0.428114 | 0 | 0.000961 | 0.1 | 0:05:18 | 3 days, 20:04:33 | null |
70 | 62,414 | 0.464112 | 0 | 0.001122 | 0.11 | 0:06:11 | 3 days, 19:52:15 | null |
80 | 62,414 | 0.400228 | 0 | 0.001282 | 0.13 | 0:07:04 | 3 days, 19:50:45 | null |
90 | 62,414 | 0.420574 | 0 | 0.001442 | 0.14 | 0:07:57 | 3 days, 19:53:23 | null |
100 | 62,414 | 0.444299 | 0 | 0.001602 | 0.16 | 0:08:50 | 3 days, 19:53:49 | null |
110 | 62,414 | 0.463192 | 0 | 0.001762 | 0.18 | 0:09:44 | 3 days, 19:54:18 | null |
120 | 62,414 | 0.435658 | 0 | 0.001923 | 0.19 | 0:10:36 | 3 days, 19:48:08 | null |
130 | 62,414 | 0.460221 | 0 | 0.002083 | 0.21 | 0:11:29 | 3 days, 19:43:02 | null |
140 | 62,414 | 0.441362 | 0 | 0.002243 | 0.22 | 0:12:21 | 3 days, 19:36:52 | null |
150 | 62,414 | 0.414642 | 0 | 0.002403 | 0.24 | 0:13:14 | 3 days, 19:33:45 | null |
160 | 62,414 | 0.421945 | 0 | 0.002564 | 0.26 | 0:14:06 | 3 days, 19:30:52 | null |
170 | 62,414 | 0.392057 | 0 | 0.002724 | 0.27 | 0:14:58 | 3 days, 19:23:19 | null |
180 | 62,414 | 0.396852 | 0 | 0.002884 | 0.29 | 0:15:50 | 3 days, 19:15:10 | null |
190 | 62,414 | 0.383881 | 0 | 0.003044 | 0.3 | 0:16:42 | 3 days, 19:12:25 | null |
200 | 62,414 | 0.382345 | 0 | 0.003204 | 0.32 | 0:17:34 | 3 days, 19:08:07 | null |
210 | 62,414 | 0.385558 | 0 | 0.003365 | 0.34 | 0:18:27 | 3 days, 19:06:39 | null |
220 | 62,414 | 0.372487 | 0 | 0.003525 | 0.35 | 0:19:19 | 3 days, 19:04:39 | null |
230 | 62,414 | 0.361122 | 0 | 0.003685 | 0.37 | 0:20:13 | 3 days, 19:06:27 | null |
240 | 62,414 | 0.32743 | 0 | 0.003845 | 0.38 | 0:21:06 | 3 days, 19:06:12 | null |
250 | 62,414 | 0.296684 | 0 | 0.004006 | 0.4 | 0:21:58 | 3 days, 19:04:39 | null |
260 | 62,414 | 0.339876 | 0 | 0.004166 | 0.42 | 0:22:50 | 3 days, 19:00:44 | null |
270 | 62,414 | 0.323986 | 0 | 0.004326 | 0.43 | 0:23:42 | 3 days, 18:57:40 | null |
280 | 62,414 | 0.311393 | 0 | 0.004486 | 0.45 | 0:24:34 | 3 days, 18:54:34 | null |
290 | 62,414 | 0.322208 | 0 | 0.004646 | 0.46 | 0:25:26 | 3 days, 18:49:03 | null |
300 | 62,414 | 0.297506 | 0 | 0.004807 | 0.48 | 0:26:18 | 3 days, 18:47:10 | null |
310 | 62,414 | 0.287239 | 0 | 0.004967 | 0.5 | 0:27:10 | 3 days, 18:45:11 | null |
320 | 62,414 | 0.282061 | 0 | 0.005127 | 0.51 | 0:28:03 | 3 days, 18:43:58 | null |
330 | 62,414 | 0.310423 | 0 | 0.005287 | 0.53 | 0:28:55 | 3 days, 18:41:51 | null |
340 | 62,414 | 0.281512 | 0 | 0.005447 | 0.54 | 0:29:48 | 3 days, 18:41:14 | null |
350 | 62,414 | 0.271821 | 0 | 0.005608 | 0.56 | 0:30:41 | 3 days, 18:42:03 | null |
360 | 62,414 | 0.284795 | 0 | 0.005768 | 0.58 | 0:31:33 | 3 days, 18:40:46 | null |
370 | 62,414 | 0.273057 | 0 | 0.005928 | 0.59 | 0:32:27 | 3 days, 18:41:33 | null |
380 | 62,414 | 0.288034 | 0 | 0.006088 | 0.61 | 0:33:18 | 3 days, 18:38:18 | null |
390 | 62,414 | 0.261296 | 0 | 0.006249 | 0.62 | 0:34:11 | 3 days, 18:37:33 | null |
400 | 62,414 | 0.254756 | 0 | 0.006409 | 0.64 | 0:35:04 | 3 days, 18:36:47 | null |
410 | 62,414 | 0.242298 | 0 | 0.006569 | 0.66 | 0:35:56 | 3 days, 18:34:11 | null |
420 | 62,414 | 0.265147 | 0 | 0.006729 | 0.67 | 0:36:48 | 3 days, 18:34:17 | null |
430 | 62,414 | 0.246269 | 0.000001 | 0.006889 | 0.69 | 0:37:42 | 3 days, 18:34:53 | null |
440 | 62,414 | 0.257305 | 0.000001 | 0.00705 | 0.7 | 0:38:34 | 3 days, 18:33:59 | null |
450 | 62,414 | 0.241094 | 0.000001 | 0.00721 | 0.72 | 0:39:27 | 3 days, 18:33:03 | null |
460 | 62,414 | 0.251754 | 0.000001 | 0.00737 | 0.74 | 0:40:19 | 3 days, 18:31:41 | null |
470 | 62,414 | 0.232962 | 0.000001 | 0.00753 | 0.75 | 0:41:11 | 3 days, 18:29:53 | null |
480 | 62,414 | 0.235152 | 0.000001 | 0.007691 | 0.77 | 0:42:04 | 3 days, 18:29:27 | null |
490 | 62,414 | 0.243727 | 0.000001 | 0.007851 | 0.79 | 0:42:57 | 3 days, 18:29:37 | null |
500 | 62,414 | 0.236276 | 0.000001 | 0.008011 | 0.8 | 0:43:51 | 3 days, 18:30:17 | null |
510 | 62,414 | 0.214615 | 0.000001 | 0.008171 | 0.82 | 0:44:43 | 3 days, 18:29:06 | null |
520 | 62,414 | 0.221905 | 0.000001 | 0.008331 | 0.83 | 0:45:35 | 3 days, 18:26:57 | null |
530 | 62,414 | 0.220924 | 0.000001 | 0.008492 | 0.85 | 0:46:28 | 3 days, 18:27:28 | null |
540 | 62,414 | 0.232456 | 0.000001 | 0.008652 | 0.87 | 0:47:21 | 3 days, 18:26:31 | null |
550 | 62,414 | 0.200006 | 0.000001 | 0.008812 | 0.88 | 0:48:13 | 3 days, 18:24:30 | null |
560 | 62,414 | 0.223117 | 0.000001 | 0.008972 | 0.9 | 0:49:05 | 3 days, 18:23:13 | null |
570 | 62,414 | 0.217076 | 0.000001 | 0.009133 | 0.91 | 0:49:58 | 3 days, 18:22:57 | null |
580 | 62,414 | 0.2305 | 0.000001 | 0.009293 | 0.93 | 0:50:50 | 3 days, 18:20:22 | null |
590 | 62,414 | 0.224521 | 0.000001 | 0.009453 | 0.95 | 0:51:43 | 3 days, 18:20:28 | null |
600 | 62,414 | 0.210502 | 0.000001 | 0.009613 | 0.96 | 0:52:35 | 3 days, 18:18:50 | null |
610 | 62,414 | 0.188884 | 0.000001 | 0.009773 | 0.98 | 0:53:27 | 3 days, 18:16:48 | null |
620 | 62,414 | 0.209624 | 0.000001 | 0.009934 | 0.99 | 0:54:20 | 3 days, 18:16:18 | null |
630 | 62,414 | 0.197488 | 0.000001 | 0.010094 | 1.01 | 0:55:12 | 3 days, 18:14:04 | null |
640 | 62,414 | 0.233016 | 0.000001 | 0.010254 | 1.03 | 0:56:05 | 3 days, 18:13:16 | null |
650 | 62,414 | 0.204837 | 0.000001 | 0.010414 | 1.04 | 0:56:57 | 3 days, 18:12:20 | null |
660 | 62,414 | 0.20924 | 0.000001 | 0.010575 | 1.06 | 0:57:50 | 3 days, 18:12:15 | null |
670 | 62,414 | 0.199129 | 0.000001 | 0.010735 | 1.07 | 0:58:42 | 3 days, 18:10:46 | null |
680 | 62,414 | 0.194759 | 0.000001 | 0.010895 | 1.09 | 0:59:35 | 3 days, 18:10:38 | null |
690 | 62,414 | 0.181495 | 0.000001 | 0.011055 | 1.11 | 1:00:28 | 3 days, 18:09:45 | null |
700 | 62,414 | 0.205434 | 0.000001 | 0.011215 | 1.12 | 1:01:20 | 3 days, 18:08:40 | null |
710 | 62,414 | 0.188916 | 0.000001 | 0.011376 | 1.14 | 1:02:13 | 3 days, 18:08:21 | null |
720 | 62,414 | 0.184569 | 0.000001 | 0.011536 | 1.15 | 1:03:06 | 3 days, 18:07:30 | null |
730 | 62,414 | 0.196262 | 0.000001 | 0.011696 | 1.17 | 1:03:59 | 3 days, 18:06:53 | null |
740 | 62,414 | 0.19333 | 0.000001 | 0.011856 | 1.19 | 1:04:52 | 3 days, 18:06:16 | null |
750 | 62,414 | 0.191349 | 0.000001 | 0.012017 | 1.2 | 1:05:44 | 3 days, 18:05:31 | null |
760 | 62,414 | 0.18502 | 0.000001 | 0.012177 | 1.22 | 1:06:38 | 3 days, 18:06:13 | null |
770 | 62,414 | 0.197589 | 0.000001 | 0.012337 | 1.23 | 1:07:30 | 3 days, 18:04:56 | null |
780 | 62,414 | 0.193486 | 0.000001 | 0.012497 | 1.25 | 1:08:23 | 3 days, 18:03:38 | null |
790 | 62,414 | 0.160355 | 0.000001 | 0.012657 | 1.27 | 1:09:15 | 3 days, 18:02:47 | null |
800 | 62,414 | 0.179917 | 0.000001 | 0.012818 | 1.28 | 1:10:08 | 3 days, 18:01:41 | null |
810 | 62,414 | 0.189744 | 0.000001 | 0.012978 | 1.3 | 1:11:00 | 3 days, 18:00:59 | null |
820 | 62,414 | 0.191999 | 0.000001 | 0.013138 | 1.31 | 1:11:52 | 3 days, 17:59:12 | null |
830 | 62,414 | 0.1937 | 0.000001 | 0.013298 | 1.33 | 1:12:45 | 3 days, 17:58:34 | null |
840 | 62,414 | 0.166426 | 0.000001 | 0.013459 | 1.35 | 1:13:38 | 3 days, 17:57:50 | null |
850 | 62,414 | 0.167278 | 0.000001 | 0.013619 | 1.36 | 1:14:30 | 3 days, 17:56:06 | null |
860 | 62,414 | 0.183748 | 0.000001 | 0.013779 | 1.38 | 1:15:22 | 3 days, 17:54:24 | null |
870 | 62,414 | 0.188511 | 0.000001 | 0.013939 | 1.39 | 1:16:15 | 3 days, 17:54:11 | null |
880 | 62,414 | 0.16199 | 0.000001 | 0.014099 | 1.41 | 1:17:07 | 3 days, 17:52:48 | null |
890 | 62,414 | 0.173409 | 0.000001 | 0.01426 | 1.43 | 1:17:59 | 3 days, 17:51:50 | null |
900 | 62,414 | 0.158591 | 0.000001 | 0.01442 | 1.44 | 1:18:51 | 3 days, 17:50:03 | null |
910 | 62,414 | 0.167276 | 0.000001 | 0.01458 | 1.46 | 1:19:43 | 3 days, 17:48:40 | null |
920 | 62,414 | 0.162179 | 0.000001 | 0.01474 | 1.47 | 1:20:36 | 3 days, 17:48:10 | null |
930 | 62,414 | 0.176718 | 0.000001 | 0.014901 | 1.49 | 1:21:28 | 3 days, 17:46:46 | null |
940 | 62,414 | 0.191757 | 0.000001 | 0.015061 | 1.51 | 1:22:21 | 3 days, 17:45:48 | null |
950 | 62,414 | 0.174768 | 0.000001 | 0.015221 | 1.52 | 1:23:13 | 3 days, 17:44:14 | null |
960 | 62,414 | 0.17372 | 0.000001 | 0.015381 | 1.54 | 1:24:04 | 3 days, 17:42:31 | null |
970 | 62,414 | 0.171904 | 0.000001 | 0.015541 | 1.55 | 1:25:06 | 3 days, 17:50:45 | null |
980 | 62,414 | 0.150434 | 0.000001 | 0.015702 | 1.57 | 1:26:04 | 3 days, 17:55:31 | null |
990 | 62,414 | 0.173524 | 0.000001 | 0.015862 | 1.59 | 1:27:07 | 3 days, 18:05:30 | null |
1,000 | 62,414 | 0.159743 | 0.000001 | 0.016022 | 1.6 | 1:28:06 | 3 days, 18:11:01 | null |
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