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Datasets:
Tychema
/
autotrain-data-ceconomysumdataset

Tasks:
Summarization
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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:    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" } ]
0cf325e7b54d4388
[ "target", "text" ]
{}
null
false
null

AutoTrain Dataset for project: ceconomysumdataset

Dataset Description

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

Languages

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

Dataset Structure

Data Instances

A sample from this dataset looks as follows:

[
  {
    "target": "\u9ed8\u6c99\u4e1c\u6536\u8d2d\u5148\u7075\u8446\u96c5\u540e\u5c06\u91cd\u7ec4\u4e3a5\u4e2a\u90e8\u95e8",
    "text": "\u65b0\u6d6a\u8d22\u7ecf\u8baf \u5317\u4eac\u65f6\u95f4\u5468\u4e00\u665a\u95f4\u6d88\u606f\uff0c\u9ed8\u6c99\u4e1c\u516c\u53f8(MRK)\u603b\u88c1\u517c\u9996\u5e2d\u6267\u884c\u5b98\u7406\u67e5\u5fb7\u00b7\u514b\u62c9\u514b(Richard T. Clark)\u8868\u793a\uff0c\u5728\u5b8c\u6210\u5bf9\u7ade\u4e89\u5bf9\u624b\u5148\u7075\u8446\u96c5\u516c\u53f8(SGP)411\u4ebf\u7f8e\u5143\u7684\u6536\u8d2d\u540e\uff0c\u8be5\u516c\u53f8\u5c06\u91cd\u7ec4\u4e3a5\u4e2a\u90e8\u95e8\u3002\u514b\u62c9\u514b\u5c06\u7ee7\u7eed\u62c5\u4efb\u65b0\u516c\u53f8\u7684CEO\u3002\u6b64\u9879\u4ea4\u6613\u9884\u8ba1\u5c06\u4e8e\u7b2c\u56db\u5b63\u5ea6\u5b8c\u6210\u3002\u65b0\u516c\u53f8\u5c06\u62e5\u67095\u4e2a\u4e3b\u8981\u90e8\u95e8\uff0c\u5305\u62ec\u5168\u7403\u4eba\u7c7b\u5065\u5eb7(Global Human Health)\u3001\u52a8\u7269\u5065\u5eb7(Animal Health)\u3001\u6d88\u8d39\u8005\u5065\u5eb7\u62a4\u7406(Consumer Health Care)\u3001\u9ed8\u6c99\u4e1c\u7814\u7a76\u5b9e\u9a8c\u5ba4(Merck Research Laboratories)\uff0c\u4ee5\u53ca\u9ed8\u6c99\u4e1c\u5236\u9020\u90e8\u95e8(Merck Manufacturing)\u3002\u6b64\u5916\uff0c\u8fd9\u5bb6\u603b\u90e8\u4f4d\u4e8e\u65b0\u6cfd\u897f\u5ddeWhitehouse Station\u7684\u516c\u53f8\u8868\u793a\uff0c\u5148\u7075\u8446\u96c5\u73b0\u4efb\u9886\u5bfc\u5c42\u5927\u7ea640%\u7684\u6210\u5458\u5c06\u6210\u4e3a\u65b0\u516c\u53f8\u7ba1\u7406\u5c42\u7684\u4e00\u90e8\u5206\uff0c\u800c\u8be5\u516c\u53f8\u5458\u5de5\u4e2d\u7684\u7edd\u5927\u90e8\u5206\u4e5f\u5c06\u7559\u5728\u5408\u5e76\u540e\u7684\u516c\u53f8\u3002\u5168\u7403\u4eba\u7c7b\u5065\u5eb7\u90e8\u95e8\u5c06\u7531\u80af\u5c3c\u65af\u00b7\u5f17\u96f7\u6cfd(Kenneth C. Frazier)\u9886\u5bfc\uff0c\u540e\u8005\u73b0\u4efb\u9ed8\u6c99\u4e1c\u6267\u884c\u526f\u603b\u88c1\u517c\u5168\u7403\u4eba\u7c7b\u5065\u5eb7\u90e8\u95e8\u603b\u88c1\u3002\u5148\u7075\u8446\u96c5\u73b0\u4efb\u9ad8\u7ea7\u526f\u603b\u88c1\u517cIntervet Schering-Plough Animal Health\u90e8\u95e8\u603b\u88c1\u52b3\u5c14\u00b7\u53ef\u6c57(Raul E. Kohan)\u5c06\u9886\u5bfc\u65b0\u7684\u9ed8\u6c99\u4e1c\u52a8\u7269\u5065\u5eb7\u90e8\u95e8\u3002\u6d88\u8d39\u8005\u4fdd\u5065\u90e8\u95e8\u5c06\u6682\u65f6\u7531\u65af\u5766\u5229\u00b7\u5df4\u8c22(Stanley F. Barshay)\u9886\u5bfc\uff0c\u540e\u8005\u73b0\u4efb\u5148\u7075\u8446\u96c5\u6d88\u8d39\u8005\u5065\u5eb7\u90e8\u95e8\u8463\u4e8b\u957f\u3002\u5408\u5e76\u540e\u7684\u516c\u53f8\u5c06\u4e3a\u8be5\u90e8\u95e8\u5bfb\u627e\u4e00\u4f4d\u6b63\u5f0f\u9886\u5bfc\u4eba\u3002\u9ed8\u6c99\u4e1c\u7814\u7a76\u5b9e\u9a8c\u5ba4\u90e8\u95e8\u4ecd\u5c06\u7531\u73b0\u4efb\u603b\u88c1\u5f7c\u5f97\u00b7\u91d1(Peter S. Kim)\u9886\u5bfc\u3002\u9ed8\u6c99\u4e1c\u751f\u4ea7\u90e8\u95e8\u5c06\u7531\u5a01\u5229\u00b7\u8fea\u65af(Willie A. Deese)\u9886\u5bfc\uff0c\u540e\u8005\u73b0\u4efb\u9ed8\u6c99\u4e1c\u751f\u4ea7\u4e1a\u52a1\u603b\u88c1\u3002"
  },
  {
    "target": "\u5927\u76d8\u4e94\u8fde\u9633\u5251\u63072900 \u4e0b\u5468\u8fd0\u884c\u8def\u7ebf\u56fe\u5206\u6790",
    "text": "== \u4eca\u65e5\u76d8\u9762\uff1a\u5927\u76d8\u559c\u89c1\u4e94\u8fde\u9633 \u6caa\u6307\u5251\u63072900\u70b9 ==\u5468\u4e94A\u80a1\u7ee7\u7eed\u9707\u8361\u4e0a\u884c\uff0c\u6caa\u6307\u54112900\u70b9\u8fdb\u519b\u3002\u53d7\u9996\u53eaIPO\u843d\u5730\u3001\u56fd\u9645\u6cb9\u4ef7\u7ee7\u7eed\u4e0a\u626c\u3001\u7f8e\u80a1\u9053\u6307\u5fae\u5e45\u6536\u9ad8\u7b49\u56e0\u7d20\u5f71\u54cd\uff0c\u5927\u76d8\u518d\u63a5\u518d\u5389\u53c8\u521b\u53cd\u5f39\u65b0\u9ad8\u3002\u4f46\u80a1\u6307\u4e0a\u884c\u52bf\u5934\u540c\u6bd4\u6628\u65e5\u6709\u6240\u6536\u655b\uff0c\u76d8\u4e2d\u6ce2\u52a8\u52a0\u5267\uff0c\u4e2a\u80a1\u4f9d\u65e7\u662f\u4e24\u6781\u5206\u5316\uff0c\u91d1\u878d\u548c\u751f\u7269\u5236\u836f\u677f\u5757\u7ee7\u7eed\u5145\u5f53\u5e02\u573a\u7684\u9886\u5934\u7f8a\u3002\u800c\u8d44\u6e90\u677f\u5757\u6210\u4e3a\u505a\u7a7a\u7684\u4e3b\u8981\u529b\u91cf\u3002\u622a\u81f3\u6536\u76d8\uff0c\u4e0a\u8bc1\u7efc\u6307\u62a52880.49\u70b9\uff0c\u4e0a\u6da80.93%\uff0c\u76d8\u4e2d\u521b\u51fa2886.50\u70b9\u65b0\u9ad8\uff0c\u6210\u4ea41535\u4ebf\uff1b\u6df1\u8bc1\u6210\u6307\u6536\u5e02\u62a511242.3\u70b9\uff0c\u4e0a\u6da80.81%\uff0c\u6210\u4ea4792.8\u4ebf\u3002\u4e24\u5e02\u5171\u6210\u4ea42327.8\u4ebf\u3002\u540c\u6bd4\u653e\u5927\u7ee7\u7eed\u653e\u5927\u3002== \u76d8\u9762\u5206\u6790\uff1a\u5e02\u573a\u70ed\u70b9\u7ee7\u7eed\u6d3b\u8dc3 \u8d44\u6e90\u7c7b\u677f\u5757\u518d\u6b21\u5012\u6208 ==\u6743\u91cd\u80a1\u4f9d\u7136\u8f83\u4e3a\u5f3a\u52bf\u76d8\u53e3\u663e\u793a\uff0c\u4e2a\u80a1\u5206\u5316\u7684\u8d8b\u52bf\u6ca1\u6709\u6539\u53d8\uff0c\u6743\u91cd\u80a1\u4f9d\u7136\u8f83\u4e3a\u5f3a\u52bf\u3002\u4e07\u79d1\u5927\u6da83.94%\uff0c\u4e2d\u4fe1\u8bc1\u5238\u3001\u6d66\u53d1\u94f6\u884c\u3001\u4e2d\u56fd\u5e73\u5b89\u3001\u4ea4\u901a\u94f6\u884c\u6da8\u5e45\u57281%\u4ee5\u4e0a\uff0c\u77f3\u5316\u53cc\u96c4\u5206\u9053\u626c\u9573\uff0c\u4e2d\u56fd\u77f3\u6cb9\u5fae\u5e45\u6536\u6da80.57%\uff0c\u800c\u4e2d\u56fd\u77f3\u5316\u5219\u4e0b\u8dcc0.48%\u3002\u4e2d\u56fd\u5357\u8f66\u5de8\u91cf\u5c01\u6b7b\u6da8\u505c 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  }
]

Dataset Fields

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

{
  "target": "Value(dtype='string', 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 151575
valid 37894
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