Datasets:
Tasks:
Token Classification
Languages:
English
Dataset Preview
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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"
}
] | 343d771f9dd30909 | [
"tags",
"tokens"
] | {} | null | false | null |
AutoTrain Dataset for project: auto2
Dataset Description
This dataset has been automatically processed by AutoTrain for project auto2.
Languages
The BCP-47 code for the dataset's language is en.
Dataset Structure
Data Instances
A sample from this dataset looks as follows:
[
{
"tokens": [
"Pd",
"has",
"been",
"regarded",
"as",
"one",
"of",
"the",
"alternatives",
"to",
"Pt",
"as",
"a",
"promising",
"hydrogen",
"evolution",
"reaction",
"(HER)",
"catalyst.",
"Strategies",
"including",
"Pd-metal",
"alloys",
"(Pd-M)",
"and",
"Pd",
"hydrides",
"(PdH<sub><i>x</i></sub>)",
"have",
"been",
"proposed",
"to",
"boost",
"HER",
"performances.",
"However,",
"the",
"stability",
"issues,",
"e.g.,",
"the",
"dissolution",
"in",
"Pd-M",
"and",
"the",
"hydrogen",
"releasing",
"in",
"PdH<sub><i>x</i></sub>,",
"restrict",
"the",
"industrial",
"application",
"of",
"Pd-based",
"HER",
"catalysts.",
"We",
"here",
"design",
"and",
"synthesize",
"a",
"stable",
"Pd-Cu",
"hydride",
"(",
"PdCu<sub>0.2</sub>H<sub>0.43</sub>",
")",
"catalyst,",
"combining",
"the",
"advantages",
"of",
"both",
"Pd-M",
"and",
"PdH<sub><i>x</i></sub>",
"structures",
"and",
"improving",
"the",
"HER",
"durability",
"simultaneously.",
"The",
"hydrogen",
"intercalation",
"is",
"realized",
"under",
"atmospheric",
"pressure",
"(1.0",
"atm)",
"following",
"our",
"synthetic",
"approach",
"that",
"imparts",
"high",
"stability",
"to",
"the",
"Pd-Cu",
"hydride",
"structure.",
"The",
"obtained",
"PdCu<sub>0.2</sub>H<sub>0.43</sub>",
"catalyst",
"exhibits",
"a",
"small",
"overpotential",
"of",
"28",
"mV",
"at",
"10",
"mA/cm<sup>2</sup>",
",",
"a",
"low",
"Tafel",
"slope",
"of",
"23",
"mV/dec",
",",
"and",
"excellent",
"HER",
"durability",
"due",
"to",
"its",
"appropriate",
"hydrogen",
"adsorption",
"free",
"energy",
"and",
"alleviated",
"metal",
"dissolution",
"rate.",
"</p>",
"<p>"
],
"tags": [
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
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2,
2,
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2,
2,
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2,
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2,
2,
2,
2,
2,
2,
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2,
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2,
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2,
2,
2,
2,
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2,
2,
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2,
2,
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2,
2,
2,
2,
2,
2,
2,
2,
2,
0,
2,
2,
2,
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2,
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2,
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2,
2,
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2,
2,
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2,
2,
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2,
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2,
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2,
2,
2,
2,
2,
0,
2,
2,
2,
2,
4,
2,
5,
5,
2,
5,
5,
2,
2,
2,
4,
2,
2,
5,
5,
2,
2,
2,
2,
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2,
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2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2
]
},
{
"tokens": [
"A",
"critical",
"challenge",
"in",
"energy",
"research",
"is",
"the",
"development",
"of",
"earth",
"abundant",
"and",
"cost-effective",
"materials",
"that",
"catalyze",
"the",
"electrochemical",
"splitting",
"of",
"water",
"into",
"hydrogen",
"and",
"oxygen",
"at",
"high",
"rates",
"and",
"low",
"overpotentials.",
"Key",
"to",
"addressing",
"this",
"issue",
"lies",
"not",
"only",
"in",
"the",
"synthesis",
"of",
"new",
"materials,",
"but",
"also",
"in",
"the",
"elucidation",
"of",
"their",
"active",
"sites,",
"their",
"structure",
"under",
"operating",
"conditions",
"and",
"ultimately,",
"extraction",
"of",
"the",
"structure-function",
"relationships",
"used",
"to",
"spearhead",
"the",
"next",
"generation",
"of",
"catalyst",
"development.",
"In",
"this",
"work,",
"we",
"present",
"a",
"complete",
"cycle",
"of",
"synthesis,",
"operando",
"characterization,",
"and",
"redesign",
"of",
"an",
"amorphous",
"cobalt",
"phosphide",
"(",
"CoP",
"<sub><i>x</i></sub>",
")",
"bifunctional",
"catalyst.",
"The",
"research",
"was",
"driven",
"by",
"integrated",
"electrochemical",
"analysis,",
"Raman",
"spectroscopy",
"and",
"gravimetric",
"measurements",
"utilizing",
"a",
"novel",
"quartz",
"crystal",
"microbalance",
"spectroelectrochemical",
"cell",
"to",
"uncover",
"the",
"catalytically",
"active",
"species",
"of",
"amorphous",
"CoP",
"<sub><i>x</i></sub>",
"and",
"subsequently",
"modify",
"the",
"material",
"to",
"enhance",
"the",
"activity",
"of",
"the",
"elucidated",
"catalytic",
"phases.",
"Illustrating",
"the",
"power",
"of",
"our",
"approach,",
"the",
"second",
"generation",
"cobalt-iron",
"phosphide",
"(",
"CoFeP<sub>x</sub>",
")",
"catalyst,",
"developed",
"through",
"an",
"iteration",
"of",
"the",
"operando",
"measurement",
"directed",
"optimization",
"cycle,",
"is",
"superior",
"in",
"both",
"hydrogen",
"and",
"oxygen",
"evolution",
"reactivity",
"over",
"the",
"previous",
"material",
"and",
"is",
"capable",
"of",
"overall",
"water",
"electrolysis",
"at",
"a",
"current",
"density",
"of",
"10",
"mA",
"cm<sup>-2</sup>",
"with",
"1.5",
"V",
"applied",
"bias",
"in",
"1",
"M",
"KOH",
"electrolyte",
"solution.",
"</p>",
"<p>"
],
"tags": [
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
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2,
2,
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2,
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2,
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2,
2,
2,
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2,
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2,
2,
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2,
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2,
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2,
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0,
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2,
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2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
4,
4,
2,
5,
5,
5,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2
]
}
]
Dataset Fields
The dataset has the following fields (also called "features"):
{
"tokens": "Sequence(feature=Value(dtype='string', id=None), length=-1, id=None)",
"tags": "Sequence(feature=ClassLabel(names=['CATALYST', 'CO-CATALYST', 'O', 'Other', 'PROPERTY_NAME', 'PROPERTY_VALUE'], id=None), length=-1, 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 | 166 |
| valid | 44 |
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