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dippatel11/autotrain-whatsapp_chat_summarization-2331373597
Summarization
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Updated
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7
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"
}
] | 3e06001ed05566fa | [
"feat_id",
"target",
"text"
] | {} | null | {} | false | null |
This dataset has been automatically processed by AutoTrain for project whatsapp_chat_summarization.
The BCP-47 code for the dataset's language is en.
A sample from this dataset looks as follows:
[
{
"feat_id": "13682435",
"text": "Ella: Hi, did you get my text?\nJesse: Hey, yeah sorry- It's been crazy here. I'll collect Owen, don't worry about it :)\nElla: Oh thank you!! You're a lifesaver!\nJesse: It's not problem ;) Good luck with your meeting!!\nElla: Thanks again! :)",
"target": "Jesse will collect Owen so that Ella can go for a meeting."
},
{
"feat_id": "13728090",
"text": "William: Hey. Today i saw you were arguing with Blackett.\nWilliam: Are you guys fine?\nElizabeth: Hi. Sorry you had to see us argue.\nElizabeth: It was just a small misunderstanding but we will solve it.\nWilliam: Hope so\nWilliam: You think I should to talk to him about it?\nElizabeth: No don't\nElizabeth: He won't like it that we talked after the argument.\nWilliam: Ok. But if you need any help, don't hesitate to call me\nElizabeth: Definitely",
"target": "Elizabeth had an argument with Blackett today, but she doesn't want William to intermeddle."
}
]
The dataset has the following fields (also called "features"):
{
"feat_id": "Value(dtype='string', id=None)",
"text": "Value(dtype='string', id=None)",
"target": "Value(dtype='string', id=None)"
}
This dataset is split into a train and validation split. The split sizes are as follow:
Split name | Num samples |
---|---|
train | 1600 |
valid | 400 |