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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 | _indexes
dict | _output_all_columns
bool | _split
null |
---|---|---|---|---|---|---|---|
[
{
"filename": "dataset.arrow"
}
] | 8cd73e62cc3c57e0 | [
"target",
"text"
] | {} | null | {} | false | null |
AutoTrain Dataset for project: Poem_Rawiy_detection
Dataset Descritpion
We used the APCD dataset cited hereafter for pretraining the model. The dataset has been cleaned and only the main text and the Qafiyah columns were kept:
@Article{Yousef2019LearningMetersArabicEnglish-arxiv,
author = {Yousef, Waleed A. and Ibrahime, Omar M. and Madbouly, Taha M. and Mahmoud,
Moustafa A.},
title = {Learning Meters of Arabic and English Poems With Recurrent Neural Networks: a Step
Forward for Language Understanding and Synthesis},
journal = {arXiv preprint arXiv:1905.05700},
year = 2019,
url = {https://github.com/hci-lab/LearningMetersPoems}
}
Languages
The BCP-47 code for the dataset's language is ar.
Dataset Structure
Data Instances
A sample from this dataset looks as follows:
[
{
"text": "\u0643\u0644\u0651\u064c \u064a\u064e\u0632\u0648\u0644\u064f \u0633\u064e\u0631\u064a\u0639\u0627\u064b \u0644\u0627 \u062b\u064e\u0628\u0627\u062a\u064e \u0644\u0647\u064f \u0641\u0643\u064f\u0646 \u0644\u0650\u0648\u064e\u0642\u062a\u0643\u064e \u064a\u0627 \u0645\u0650\u0633\u0643\u064a\u0646\u064f \u0645\u064f\u063a\u062a\u064e\u0646\u0650\u0645\u0627",
"target": 27
},
{
"text": "\u0648\u0642\u062f \u0623\u0628\u0631\u0632\u064e \u0627\u0644\u0631\u0651\u064f\u0645\u0651\u064e\u0627\u0646\u064f \u0644\u0644\u0637\u0631\u0641\u0650 \u063a\u064f\u0635\u0652\u0646\u064e\u0647\u064f \u0646\u0647\u0648\u062f\u0627\u064b \u062a\u064f\u0635\u0627\u0646\u064f \u0627\u0644\u0644\u0645\u0633\u064e \u0639\u0646 \u0643\u0641\u0651\u0650 \u0623\u062d\u0645\u0642\u0650",
"target": 23
}
]
Dataset Fields
The dataset has the following fields (also called "features"):
{
"text": "Value(dtype='string', id=None)",
"target": "ClassLabel(num_classes=35, names=['\u0621', '\u0624', '\u0627', '\u0628', '\u062a', '\u062b', '\u062c', '\u062d', '\u062e', '\u062f', '\u0630', '\u0631', '\u0632', '\u0633', '\u0634', '\u0635', '\u0636', '\u0637', '\u0637\u0646', '\u0638', '\u0639', '\u063a', '\u0641', '\u0642', '\u0643', '\u0644', '\u0644\u0627', '\u0645', '\u0646', '\u0647', '\u0647\u0640', '\u0647\u0646', '\u0648', '\u0649', '\u064a'], 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 | 1347718 |
valid | 336950 |
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