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The dataset generation failed
Error code: DatasetGenerationError Exception: ArrowNotImplementedError Message: Cannot write struct type '_format_kwargs' with no child field to Parquet. Consider adding a dummy child field. Traceback: Traceback (most recent call last): File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2011, in _prepare_split_single writer.write_table(table) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 583, in write_table self._build_writer(inferred_schema=pa_table.schema) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 404, in _build_writer self.pa_writer = self._WRITER_CLASS(self.stream, schema) File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/parquet/core.py", line 1010, in __init__ self.writer = _parquet.ParquetWriter( File "pyarrow/_parquet.pyx", line 2157, in pyarrow._parquet.ParquetWriter.__cinit__ File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status pyarrow.lib.ArrowNotImplementedError: Cannot write struct type '_format_kwargs' with no child field to Parquet. Consider adding a dummy child field. During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2027, in _prepare_split_single num_examples, num_bytes = writer.finalize() File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 602, in finalize self._build_writer(self.schema) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 404, in _build_writer self.pa_writer = self._WRITER_CLASS(self.stream, schema) File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/parquet/core.py", line 1010, in __init__ self.writer = _parquet.ParquetWriter( File "pyarrow/_parquet.pyx", line 2157, in pyarrow._parquet.ParquetWriter.__cinit__ File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status pyarrow.lib.ArrowNotImplementedError: Cannot write struct type '_format_kwargs' with no child field to Parquet. Consider adding a dummy child field. 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 1529, 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 1154, in convert_to_parquet builder.download_and_prepare( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1027, in download_and_prepare self._download_and_prepare( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1122, 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 1882, 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 2038, in _prepare_split_single raise DatasetGenerationError("An error occurred while generating the dataset") from e datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset
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_data_files
list | _fingerprint
string | _format_columns
sequence | _format_kwargs
dict | _format_type
null | _output_all_columns
bool | _split
null |
---|---|---|---|---|---|---|
[
{
"filename": "data-00000-of-00001.arrow"
}
] | b3bcd462f6f59a54 | [
"answers.answer_start",
"answers.text",
"context",
"feat_id",
"question"
] | {} | null | false | null |
AutoTrain Dataset for project: qa_xlm_roberta_large_tesquad2
Dataset Description
This dataset has been automatically processed by AutoTrain for project qa_xlm_roberta_large_tesquad2.
Languages
The BCP-47 code for the dataset's language is unk.
Dataset Structure
Data Instances
A sample from this dataset looks as follows:
[
{
"context": "7 \u0c0f\u0c2a\u0c4d\u0c30\u0c3f\u0c32\u0c4d 1963\u0c28, \u0c26\u0c47\u0c36\u0c02 \u0c24\u0c28 \u0c05\u0c27\u0c3f\u0c15\u0c3e\u0c30\u0c3f\u0c15 \u0c2a\u0c47\u0c30\u0c41\u0c28\u0c41 \u0c38\u0c4b\u0c37\u0c32\u0c3f\u0c38\u0c4d\u0c1f\u0c4d \u0c2b\u0c46\u0c21\u0c30\u0c32\u0c4d \u0c30\u0c3f\u0c2a\u0c2c\u0c4d\u0c32\u0c3f\u0c15\u0c4d \u0c06\u0c2b\u0c4d \u0c2f\u0c41\u0c17\u0c4b\u0c38\u0c4d\u0c32\u0c47\u0c35\u0c3f\u0c2f\u0c3e\u0c17\u0c3e \u0c2e\u0c3e\u0c30\u0c4d\u0c1a\u0c3f\u0c02\u0c26\u0c3f. \u0c38\u0c02\u0c38\u0c4d\u0c15\u0c30\u0c23\u0c32\u0c41 \u0c2a\u0c4d\u0c30\u0c48\u0c35\u0c47\u0c1f\u0c4d \u0c38\u0c02\u0c38\u0c4d\u0c25\u0c28\u0c41 \u0c2a\u0c4d\u0c30\u0c4b\u0c24\u0c4d\u0c38\u0c39\u0c3f\u0c02\u0c1a\u0c3e\u0c2f\u0c3f \u0c2e\u0c30\u0c3f\u0c2f\u0c41 \u0c35\u0c3e\u0c15\u0c4d \u0c38\u0c4d\u0c35\u0c3e\u0c24\u0c02\u0c24\u0c4d\u0c30\u0c4d\u0c2f\u0c02 \u0c2e\u0c30\u0c3f\u0c2f\u0c41 \u0c2e\u0c24\u0c2a\u0c30\u0c2e\u0c48\u0c28 \u0c35\u0c4d\u0c2f\u0c15\u0c4d\u0c24\u0c40\u0c15\u0c30\u0c23\u0c2a\u0c48 \u0c2a\u0c30\u0c3f\u0c2e\u0c3f\u0c24\u0c41\u0c32\u0c28\u0c41 \u0c2c\u0c3e\u0c17\u0c3e \u0c38\u0c21\u0c32\u0c3f\u0c02\u0c1a\u0c3e\u0c2f\u0c3f. \u0c06 \u0c24\u0c30\u0c4d\u0c35\u0c3e\u0c24 \u0c1f\u0c3f\u0c1f\u0c4b \u0c05\u0c2e\u0c46\u0c30\u0c3f\u0c15\u0c3e \u0c2a\u0c30\u0c4d\u0c2f\u0c1f\u0c28\u0c15\u0c41 \u0c35\u0c46\u0c33\u0c4d\u0c32\u0c3e\u0c21\u0c41. \u0c1a\u0c3f\u0c32\u0c40\u0c32\u0c4b, \u0c06 \u0c26\u0c47\u0c36 \u0c2a\u0c30\u0c4d\u0c2f\u0c1f\u0c28\u0c2a\u0c48 \u0c07\u0c26\u0c4d\u0c26\u0c30\u0c41 \u0c2a\u0c4d\u0c30\u0c2d\u0c41\u0c24\u0c4d\u0c35 \u0c2e\u0c02\u0c24\u0c4d\u0c30\u0c41\u0c32\u0c41 \u0c30\u0c3e\u0c1c\u0c40\u0c28\u0c3e\u0c2e\u0c3e \u0c1a\u0c47\u0c36\u0c3e\u0c30\u0c41. ~ 1960 ~ \u0c36\u0c30\u0c26\u0c43\u0c24\u0c41\u0c35\u0c41\u0c32\u0c4b \u0c1f\u0c3f\u0c1f\u0c4b \u0c10\u0c15\u0c4d\u0c2f\u0c30\u0c3e\u0c1c\u0c4d\u0c2f\u0c38\u0c2e\u0c3f\u0c24\u0c3f \u0c1c\u0c28\u0c30\u0c32\u0c4d \u0c05\u0c38\u0c46\u0c02\u0c2c\u0c4d\u0c32\u0c40 \u0c38\u0c2e\u0c3e\u0c35\u0c47\u0c36\u0c02\u0c32\u0c4b \u0c05\u0c27\u0c4d\u0c2f\u0c15\u0c4d\u0c37\u0c41\u0c21\u0c41 \u0c21\u0c4d\u0c35\u0c48\u0c1f\u0c4d \u0c21\u0c3f. \u0c10\u0c38\u0c46\u0c28\u0c4d\u200c\u0c39\u0c4b\u0c35\u0c30\u0c4d\u200c\u0c28\u0c41 \u0c15\u0c32\u0c3f\u0c36\u0c3e\u0c30\u0c41. \u0c1f\u0c3f\u0c1f\u0c4b \u0c2e\u0c30\u0c3f\u0c2f\u0c41 \u0c10\u0c38\u0c46\u0c28\u0c4d\u200c\u0c39\u0c4b\u0c35\u0c30\u0c4d \u0c06\u0c2f\u0c41\u0c27 \u0c28\u0c3f\u0c2f\u0c02\u0c24\u0c4d\u0c30\u0c23 \u0c28\u0c41\u0c02\u0c21\u0c3f \u0c06\u0c30\u0c4d\u0c25\u0c3f\u0c15 \u0c05\u0c2d\u0c3f\u0c35\u0c43\u0c26\u0c4d\u0c27\u0c3f \u0c35\u0c30\u0c15\u0c41 \u0c05\u0c28\u0c47\u0c15 \u0c05\u0c02\u0c36\u0c3e\u0c32\u0c2a\u0c48 \u0c1a\u0c30\u0c4d\u0c1a\u0c3f\u0c02\u0c1a\u0c3e\u0c30\u0c41. \u0c2f\u0c41\u0c17\u0c4b\u0c38\u0c4d\u0c32\u0c47\u0c35\u0c3f\u0c2f\u0c3e \u0c2f\u0c4a\u0c15\u0c4d\u0c15 \u0c24\u0c1f\u0c38\u0c4d\u0c25\u0c24 \"\u0c05\u0c24\u0c28\u0c3f \u0c35\u0c48\u0c2a\u0c41 \u0c24\u0c1f\u0c38\u0c4d\u0c25\u0c02\u0c17\u0c3e \u0c09\u0c02\u0c26\u0c3f\" \u0c05\u0c28\u0c3f \u0c10\u0c38\u0c46\u0c28\u0c4d\u200c\u0c39\u0c4b\u0c35\u0c30\u0c4d \u0c35\u0c4d\u0c2f\u0c3e\u0c16\u0c4d\u0c2f\u0c3e\u0c28\u0c3f\u0c02\u0c1a\u0c3f\u0c28\u0c2a\u0c4d\u0c2a\u0c41\u0c21\u0c41, \u0c24\u0c1f\u0c38\u0c4d\u0c25\u0c24 \u0c05\u0c28\u0c47\u0c26\u0c3f \u0c28\u0c3f\u0c37\u0c4d\u0c15\u0c4d\u0c30\u0c3f\u0c2f\u0c3e\u0c24\u0c4d\u0c2e\u0c15\u0c24\u0c28\u0c41 \u0c38\u0c42\u0c1a\u0c3f\u0c02\u0c1a\u0c26\u0c41, \u0c15\u0c3e\u0c28\u0c40 \"\u0c2a\u0c15\u0c4d\u0c37\u0c3e\u0c32\u0c41 \u0c24\u0c40\u0c38\u0c41\u0c15\u0c4b\u0c15\u0c2a\u0c4b\u0c35\u0c21\u0c02\" \u0c05\u0c28\u0c3f \u0c05\u0c30\u0c4d\u0c25\u0c02 \u0c05\u0c28\u0c3f \u0c1f\u0c3f\u0c1f\u0c4b \u0c2c\u0c26\u0c41\u0c32\u0c3f\u0c1a\u0c4d\u0c1a\u0c3e\u0c30\u0c41.",
"question": "U.N.\u0c32\u0c4b \u0c1f\u0c3f\u0c1f\u0c4b \u0c10\u0c38\u0c46\u0c28\u0c4d\u200c\u0c39\u0c4b\u0c35\u0c30\u0c4d\u200c\u0c28\u0c41 \u0c0e\u0c2a\u0c4d\u0c2a\u0c41\u0c21\u0c41 \u0c15\u0c32\u0c3f\u0c36\u0c3e\u0c21\u0c41?",
"answers.text": [
" 1960 "
],
"answers.answer_start": [
324
],
"feat_id": [
"56f7f401aef2371900625cc8"
]
},
{
"context": "\u0c38\u0c40\u0c38\u0c3f\u0c2f\u0c02 \u0c2e\u0c30\u0c3f\u0c2f\u0c41 \u0c2c\u0c02\u0c17\u0c3e\u0c30\u0c02 (\u0c30\u0c46\u0c02\u0c21\u0c42 \u0c2a\u0c38\u0c41\u0c2a\u0c41), \u0c2e\u0c30\u0c3f\u0c2f\u0c41 \u0c13\u0c38\u0c4d\u0c2e\u0c3f\u0c2f\u0c02 (\u0c28\u0c40\u0c32\u0c02)\u0c24\u0c4b \u0c15\u0c32\u0c3f\u0c2a\u0c3f, \u0c2c\u0c42\u0c21\u0c3f\u0c26 \u0c32\u0c47\u0c26\u0c3e \u0c35\u0c46\u0c02\u0c21\u0c3f \u0c15\u0c3e\u0c15\u0c41\u0c02\u0c21\u0c3e \u0c38\u0c39\u0c1c \u0c30\u0c02\u0c17\u0c41 \u0c15\u0c32\u0c3f\u0c17\u0c3f\u0c28 \u0c28\u0c3e\u0c32\u0c41\u0c17\u0c41 \u0c2e\u0c42\u0c32\u0c15 \u0c32\u0c4b\u0c39\u0c3e\u0c32\u0c32\u0c4b \u0c30\u0c3e\u0c17\u0c3f \u0c12\u0c15\u0c1f\u0c3f. \u0c38\u0c4d\u0c35\u0c1a\u0c4d\u0c1b\u0c2e\u0c48\u0c28 \u0c30\u0c3e\u0c17\u0c3f \u0c28\u0c3e\u0c30\u0c3f\u0c02\u0c1c-\u0c0e\u0c30\u0c41\u0c2a\u0c41 \u0c30\u0c02\u0c17\u0c41\u0c32\u0c4b \u0c09\u0c02\u0c1f\u0c41\u0c02\u0c26\u0c3f \u0c2e\u0c30\u0c3f\u0c2f\u0c41 \u0c17\u0c3e\u0c32\u0c3f\u0c15\u0c3f \u0c17\u0c41\u0c30\u0c48\u0c28\u0c2a\u0c4d\u0c2a\u0c41\u0c21\u0c41 \u0c0e\u0c30\u0c41\u0c2a\u0c41 \u0c30\u0c02\u0c17\u0c41\u0c28\u0c41 \u0c2a\u0c4a\u0c02\u0c26\u0c41\u0c24\u0c41\u0c02\u0c26\u0c3f. \u0c2a\u0c42\u0c30\u0c3f\u0c02\u0c1a\u0c3f\u0c28 3d \u0c2e\u0c30\u0c3f\u0c2f\u0c41 \u0c38\u0c17\u0c02-\u0c16\u0c3e\u0c33\u0c40 4s \u0c05\u0c1f\u0c3e\u0c2e\u0c3f\u0c15\u0c4d \u0c37\u0c46\u0c32\u0c4d\u200c\u0c32 \u0c2e\u0c27\u0c4d\u0c2f \u0c0e\u0c32\u0c15\u0c4d\u0c1f\u0c4d\u0c30\u0c3e\u0c28\u0c3f\u0c15\u0c4d \u0c2a\u0c30\u0c3f\u0c35\u0c30\u0c4d\u0c24\u0c28\u0c3e\u0c32 \u0c28\u0c41\u0c02\u0c21\u0c3f \u0c30\u0c3e\u0c17\u0c3f \u0c2f\u0c4a\u0c15\u0c4d\u0c15 \u0c32\u0c15\u0c4d\u0c37\u0c23 \u0c30\u0c02\u0c17\u0c41 \u0c2b\u0c32\u0c3f\u0c24\u0c3e\u0c32\u0c41 - \u0c08 \u0c37\u0c46\u0c32\u0c4d\u200c\u0c32 \u0c2e\u0c27\u0c4d\u0c2f \u0c36\u0c15\u0c4d\u0c24\u0c3f \u0c35\u0c4d\u0c2f\u0c24\u0c4d\u0c2f\u0c3e\u0c38\u0c02 \u0c05\u0c26\u0c3f \u0c28\u0c3e\u0c30\u0c3f\u0c02\u0c1c \u0c15\u0c3e\u0c02\u0c24\u0c3f\u0c15\u0c3f \u0c05\u0c28\u0c41\u0c17\u0c41\u0c23\u0c02\u0c17\u0c3e \u0c09\u0c02\u0c1f\u0c41\u0c02\u0c26\u0c3f. \u0c05\u0c26\u0c47 \u0c35\u0c3f\u0c27\u0c3e\u0c28\u0c02 \u0c2c\u0c02\u0c17\u0c3e\u0c30\u0c02 \u0c2e\u0c30\u0c3f\u0c2f\u0c41 \u0c38\u0c40\u0c38\u0c3f\u0c2f\u0c02 \u0c2f\u0c4a\u0c15\u0c4d\u0c15 \u0c2a\u0c38\u0c41\u0c2a\u0c41 \u0c30\u0c02\u0c17\u0c41\u0c15\u0c41 \u0c15\u0c3e\u0c30\u0c23\u0c2e\u0c35\u0c41\u0c24\u0c41\u0c02\u0c26\u0c3f.",
"question": "\u0c28\u0c3f\u0c02\u0c21\u0c3f\u0c28 3d \u0c2e\u0c30\u0c3f\u0c2f\u0c41 \u0c38\u0c17\u0c02-\u0c16\u0c3e\u0c33\u0c40 4s \u0c05\u0c1f\u0c3e\u0c2e\u0c3f\u0c15\u0c4d \u0c37\u0c46\u0c32\u0c4d\u200c\u0c32 \u0c2e\u0c27\u0c4d\u0c2f \u0c36\u0c15\u0c4d\u0c24\u0c3f \u0c35\u0c4d\u0c2f\u0c24\u0c4d\u0c2f\u0c3e\u0c38\u0c02 \u0c15\u0c3e\u0c02\u0c24\u0c3f \u0c2f\u0c4a\u0c15\u0c4d\u0c15 \u0c0f \u0c30\u0c02\u0c17\u0c41\u0c15\u0c41 \u0c05\u0c28\u0c41\u0c17\u0c41\u0c23\u0c02\u0c17\u0c3e \u0c09\u0c02\u0c1f\u0c41\u0c02\u0c26\u0c3f?",
"answers.text": [
"\u0c28\u0c3e\u0c30\u0c3f\u0c02\u0c1c \u0c15\u0c3e\u0c02\u0c24\u0c3f"
],
"answers.answer_start": [
376
],
"feat_id": [
"57098edded30961900e84311"
]
}
]
Dataset Fields
The dataset has the following fields (also called "features"):
{
"context": "Value(dtype='string', id=None)",
"question": "Value(dtype='string', id=None)",
"answers.text": "Sequence(feature=Value(dtype='string', id=None), length=-1, id=None)",
"answers.answer_start": "Sequence(feature=Value(dtype='int32', id=None), length=-1, id=None)",
"feat_id": "Sequence(feature=Value(dtype='string', id=None), length=-1, id=None)"
}
Dataset Splits
This dataset is split into a train and validation split. The split sizes are as follow:
Split name | Num samples |
---|---|
train | 64549 |
valid | 9277 |
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