--- 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: ```json [ { "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"): ```json { "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 |