Datasets:
Tasks:
Summarization
Languages:
English
metadata
language:
- en
task_categories:
- summarization
AutoTrain Dataset for project: yetipy
Dataset Description
This dataset has been automatically processed by AutoTrain for project yetipy.
Languages
The BCP-47 code for the dataset's language is en.
Dataset Structure
Data Instances
A sample from this dataset looks as follows:
[
{
"feat_code": " \n return self.correctwords(originalwords, [newword], **kwargs)",
"target": "def mergewords(self, newword, *originalwords, **kwargs)",
"text": "TODO: Write documentation",
"feat_loss_without_docstring": 9.7212610245,
"feat_loss_with_docstring": 9.146777153,
"feat_factor": 1.0628072448
},
{
"feat_code": " \n\n if size == 0: return [] #for efficiency\n\n context = []\n e = self\n while len(context) < size:\n e = e.previous(True,scope)\n if not e: break\n context.append(e)\n\n if placeholder:\n while len(context) < size:\n context.append(placeholder)\n\n context.reverse()\n return context",
"target": "def leftcontext(self, size, placeholder=None, scope=None)",
"text": "Returns the left context for an element, as a list. This method crosses sentence/paragraph boundaries by default, which can be restricted by setting scope",
"feat_loss_without_docstring": 3.7681286335,
"feat_loss_with_docstring": 3.9110825062,
"feat_factor": 0.9634490266
}
]
Dataset Fields
The dataset has the following fields (also called "features"):
{
"feat_code": "Value(dtype='string', id=None)",
"target": "Value(dtype='string', id=None)",
"text": "Value(dtype='string', id=None)",
"feat_loss_without_docstring": "Value(dtype='float64', id=None)",
"feat_loss_with_docstring": "Value(dtype='float64', id=None)",
"feat_factor": "Value(dtype='float64', 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 | 80 |
valid | 20 |