dmytrobaida/autotrain-ukrainian-telegram-sentiment-analysis-70044138081
Text Classification
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Updated
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24
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3
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"
}
] | db823e7768e31a0f | [
"target",
"text"
] | {} | null | false | null |
This dataset has been automatically processed by AutoTrain for project ukrainian-telegram-sentiment-analysis.
The BCP-47 code for the dataset's language is unk.
A sample from this dataset looks as follows:
[
{
"text": "\u0421\u043e\u0432\u043e\u043a",
"target": 1
},
{
"text": "\u0422\u0440\u0430\u043d\u0448 \u0434\u043e\u043f\u043e\u043c\u043e\u0433\u0438 \u0432\u043a\u043b\u044e\u0447\u0430\u0442\u0438\u043c\u0435: - 4 HIMARS \u0456 \u0431\u043e\u0454\u043f\u0440\u0438\u043f\u0430\u0441\u0438 \u0434\u043e \u043d\u0438\u0445 - 1000 \u0441\u043d\u0430\u0440\u044f\u0434\u0456\u0432 \u00ab\u0432\u0438\u0441\u043e\u043a\u043e\u0442\u043e\u0447\u043d\u043e\u0457\u00bb 155-\u043c\u043c \u0430\u0440\u0442\u0438\u043b\u0435\u0440\u0456\u0457 - \u0442\u0440\u0438 \u0442\u0430\u043a\u0442\u0438\u0447\u043d\u0456 \u0430\u0432\u0442\u043e\u043c\u043e\u0431\u0456\u043b\u0456 - \u043f\u0456\u0434\u0440\u0438\u0432\u043d\u0456 \u0431\u043e\u0454\u043f\u0440\u0438\u043f\u0430\u0441\u0438 - \u043a\u043e\u043d\u0442\u0440-\u0431\u0430\u0442\u0430\u0440\u0435\u0439\u043d\u0456 \u0441\u0438\u0441\u0442\u0435\u043c\u0438 - \u0437\u0430\u043f\u0447\u0430\u0441\u0442\u0438\u043d\u0438.",
"target": 1
}
]
The dataset has the following fields (also called "features"):
{
"text": "Value(dtype='string', id=None)",
"target": "ClassLabel(names=['0', '1'], id=None)"
}
This dataset is split into a train and validation split. The split sizes are as follow:
Split name | Num samples |
---|---|
train | 2399 |
valid | 601 |