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Datasets:
Hamalia
/
autotrain-data-triageinfojuri

Tasks:
Text Classification
Languages:
French
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The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
The dataset generation failed
Error code:   DatasetGenerationError
Exception:    DatasetGenerationError
Message:      An error occurred while generating the dataset
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 1016, in __init__
                  self.writer = _parquet.ParquetWriter(
                File "pyarrow/_parquet.pyx", line 1869, 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 1016, in __init__
                  self.writer = _parquet.ParquetWriter(
                File "pyarrow/_parquet.pyx", line 1869, 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 1321, 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 935, 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" } ]
128ce5def5ea0f31
[ "target", "text" ]
{}
null
false
null

AutoTrain Dataset for project: triageinfojuri

Dataset Description

This dataset has been automatically processed by AutoTrain for project triageinfojuri.

Languages

The BCP-47 code for the dataset's language is fr.

Dataset Structure

Data Instances

A sample from this dataset looks as follows:

[
  {
    "target": 11,
    "text": "Je suis intervenant psychosociale depuis 2007 au Regroupement des familles monoparentales et recompos\u00e9es de Laval (RFMRL), organisme sans but lucratif. L\u2019organisme n\u2019offre aucune compensation pour les 14 premiers jours.  Je suis en Arr\u00eat de travail du 28 novembre au 12 d\u00e9cembre 2022 inclusivement pour \u00e9puisement professionnel pour raison m\u00e9dicale.   J\u2019aimerais savoir comment ca fonctionne ?  - M\u2019inscrire tout de suite \u00e0 l\u2019AE (15 semaines avant le 18 d\u00e9cembre ou 26 si apr\u00e8s le 18). Je peux attendre ?  - M\u2019inscrire pour indemnit\u00e9 de la CNESST en m\u00eame temps ?  - On m\u2019a sugg\u00e9r\u00e9 de prendre des vacances."
  },
  {
    "target": 8,
    "text": "J'ai achet\u00e9 une voiture dans un encan, je l'ai fait r\u00e9par\u00e9e chez un garagiste \u00e0 Trois Rivi\u00e8res (Andr\u00e9 Simon Inc.) et la derni\u00e8re estim\u00e9e \u00e9tais de 3500 et la facture finale pr\u00e8s de 10,000 tentative de ne n\u00e9gociation nulle,mercci"
  }
]

Dataset Fields

The dataset has the following fields (also called "features"):

{
  "target": "ClassLabel(names=['ADMINISTRATIF', 'AIN\u00c9S', 'ASSURANCES', 'AUTEUR', 'CONSOMMATION', 'CONSOMMMATION', 'CORPORATIF', 'CRIMINALIT\u00c9', 'CR\u00c9ANCES', 'DIVORCE', 'DPJ', 'EMPLOI', 'FAILLITE', 'FAMILLE', 'FISCALIT\u00c9', 'FRAUDE', 'INAPTITUDE', 'INTERNATIONAL', 'JEUNESSE', 'LOGEMENT', 'LOUAGE', 'L\u00c9SION', 'MUNICIPAL', 'MUNICPAL', 'PERSONNALIT\u00c9', 'PLUMITIFS', 'PROC\u00c9DURES ', 'PROFESSION', 'PROPRI\u00c9T\u00c9', 'Proc\u00e9dures ', 'RENSEIGNEMENTS', 'RESPONSABILIT\u00c9', 'SERVICE', 'SOINS', 'VENTE'], id=None)",
  "text": "Value(dtype='string', 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 619
valid 174
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