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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 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.
_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"
}
] | c24f60e34d82e0cc | [
"feat_admiration",
"feat_amusement",
"feat_anger",
"feat_annoyance",
"feat_approval",
"feat_author",
"feat_caring",
"feat_confusion",
"feat_created_utc",
"feat_curiosity",
"feat_desire",
"feat_disappointment",
"feat_disapproval",
"feat_disgust",
"feat_embarrassment",
"feat_example_very_unclear",
"feat_excitement",
"feat_gratitude",
"feat_grief",
"feat_id",
"feat_joy",
"feat_link_id",
"feat_love",
"feat_nervousness",
"feat_neutral",
"feat_optimism",
"feat_parent_id",
"feat_pride",
"feat_rater_id",
"feat_realization",
"feat_relief",
"feat_remorse",
"feat_sadness",
"feat_subreddit",
"feat_surprise",
"target",
"text"
] | {} | null | false | null |
AutoTrain Dataset for project: twitter-goemotions-binary-fear-classification
Dataset Description
This dataset has been automatically processed by AutoTrain for project twitter-goemotions-binary-fear-classification.
Languages
The BCP-47 code for the dataset's language is unk.
Dataset Structure
Data Instances
A sample from this dataset looks as follows:
[
{
"text": "Downvoting comments you don't like is your right.",
"feat_id": "ed62dkv",
"feat_author": "128bitworm",
"feat_subreddit": "im14andthisisdeep",
"feat_link_id": "t3_ac6bna",
"feat_parent_id": "t1_ed5trip",
"feat_created_utc": 1546542336.0,
"feat_rater_id": 35,
"feat_example_very_unclear": false,
"feat_admiration": 0,
"feat_amusement": 0,
"feat_anger": 0,
"feat_annoyance": 0,
"feat_approval": 0,
"feat_caring": 0,
"feat_confusion": 0,
"feat_curiosity": 0,
"feat_desire": 0,
"feat_disappointment": 0,
"feat_disapproval": 1,
"feat_disgust": 0,
"feat_embarrassment": 0,
"feat_excitement": 0,
"target": 0,
"feat_gratitude": 0,
"feat_grief": 0,
"feat_joy": 0,
"feat_love": 0,
"feat_nervousness": 0,
"feat_optimism": 0,
"feat_pride": 0,
"feat_realization": 0,
"feat_relief": 0,
"feat_remorse": 0,
"feat_sadness": 0,
"feat_surprise": 0,
"feat_neutral": 0
},
{
"text": "I fucking love this",
"feat_id": "edxv95q",
"feat_author": "fueryerhealth",
"feat_subreddit": "FellowKids",
"feat_link_id": "t3_af72i1",
"feat_parent_id": "t3_af72i1",
"feat_created_utc": 1547342464.0,
"feat_rater_id": 19,
"feat_example_very_unclear": false,
"feat_admiration": 1,
"feat_amusement": 0,
"feat_anger": 0,
"feat_annoyance": 0,
"feat_approval": 0,
"feat_caring": 0,
"feat_confusion": 0,
"feat_curiosity": 0,
"feat_desire": 0,
"feat_disappointment": 0,
"feat_disapproval": 0,
"feat_disgust": 0,
"feat_embarrassment": 0,
"feat_excitement": 0,
"target": 0,
"feat_gratitude": 0,
"feat_grief": 0,
"feat_joy": 0,
"feat_love": 1,
"feat_nervousness": 0,
"feat_optimism": 0,
"feat_pride": 0,
"feat_realization": 0,
"feat_relief": 0,
"feat_remorse": 0,
"feat_sadness": 0,
"feat_surprise": 0,
"feat_neutral": 0
}
]
Dataset Fields
The dataset has the following fields (also called "features"):
{
"text": "Value(dtype='string', id=None)",
"feat_id": "Value(dtype='string', id=None)",
"feat_author": "Value(dtype='string', id=None)",
"feat_subreddit": "Value(dtype='string', id=None)",
"feat_link_id": "Value(dtype='string', id=None)",
"feat_parent_id": "Value(dtype='string', id=None)",
"feat_created_utc": "Value(dtype='float32', id=None)",
"feat_rater_id": "Value(dtype='int32', id=None)",
"feat_example_very_unclear": "Value(dtype='bool', id=None)",
"feat_admiration": "Value(dtype='int32', id=None)",
"feat_amusement": "Value(dtype='int32', id=None)",
"feat_anger": "Value(dtype='int32', id=None)",
"feat_annoyance": "Value(dtype='int32', id=None)",
"feat_approval": "Value(dtype='int32', id=None)",
"feat_caring": "Value(dtype='int32', id=None)",
"feat_confusion": "Value(dtype='int32', id=None)",
"feat_curiosity": "Value(dtype='int32', id=None)",
"feat_desire": "Value(dtype='int32', id=None)",
"feat_disappointment": "Value(dtype='int32', id=None)",
"feat_disapproval": "Value(dtype='int32', id=None)",
"feat_disgust": "Value(dtype='int32', id=None)",
"feat_embarrassment": "Value(dtype='int32', id=None)",
"feat_excitement": "Value(dtype='int32', id=None)",
"target": "ClassLabel(names=['0', '1'], id=None)",
"feat_gratitude": "Value(dtype='int32', id=None)",
"feat_grief": "Value(dtype='int32', id=None)",
"feat_joy": "Value(dtype='int32', id=None)",
"feat_love": "Value(dtype='int32', id=None)",
"feat_nervousness": "Value(dtype='int32', id=None)",
"feat_optimism": "Value(dtype='int32', id=None)",
"feat_pride": "Value(dtype='int32', id=None)",
"feat_realization": "Value(dtype='int32', id=None)",
"feat_relief": "Value(dtype='int32', id=None)",
"feat_remorse": "Value(dtype='int32', id=None)",
"feat_sadness": "Value(dtype='int32', id=None)",
"feat_surprise": "Value(dtype='int32', id=None)",
"feat_neutral": "Value(dtype='int32', 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 | 168979 |
| valid | 42246 |
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