autotrain-data-processor commited on
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Processed data from AutoTrain data processor ([2022-09-29 21:03 ]

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README.md ADDED
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+ ---
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+ task_categories:
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+ - text-classification
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+
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+ ---
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+ # AutoTrain Dataset for project: github-emotion-surprise
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+
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+ ## Dataset Description
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+
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+ This dataset has been automatically processed by AutoTrain for project github-emotion-surprise.
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+
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+ ### Languages
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+
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+ The BCP-47 code for the dataset's language is unk.
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+
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+ ## Dataset Structure
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+
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+ ### Data Instances
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+
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+ A sample from this dataset looks as follows:
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+
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+ ```json
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+ [
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+ {
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+ "feat_id": 704844644,
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+ "text": "This change doesn't affect anything but makes the code more clear. If you look at the line about, `currentUrlTree` is set to `urlAfterRedirects`.",
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+ "feat_Anger": 0,
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+ "feat_Love": 0,
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+ "feat_Fear": 0,
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+ "feat_Joy": 1,
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+ "feat_Sadness": 0,
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+ "target": 0
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+ },
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+ {
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+ "feat_id": 886568180,
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+ "text": "Thanks very much for your feedback [USER] Your point is totally fair. My intention was to highlight that camelCase or dash-case class names are perfectly fine to use in Angular templates. Most people, especially beginners, do not know that and end up using the `ngClass` directive. Do you think that rewording the alert towards that direction would make sense?",
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+ "feat_Anger": 0,
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+ "feat_Love": 1,
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+ "feat_Fear": 0,
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+ "feat_Joy": 0,
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+ "feat_Sadness": 0,
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+ "target": 0
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+ }
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+ ]
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+ ```
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+
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+ ### Dataset Fields
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+
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+ The dataset has the following fields (also called "features"):
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+
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+ ```json
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+ {
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+ "feat_id": "Value(dtype='int64', id=None)",
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+ "text": "Value(dtype='string', id=None)",
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+ "feat_Anger": "Value(dtype='int64', id=None)",
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+ "feat_Love": "Value(dtype='int64', id=None)",
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+ "feat_Fear": "Value(dtype='int64', id=None)",
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+ "feat_Joy": "Value(dtype='int64', id=None)",
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+ "feat_Sadness": "Value(dtype='int64', id=None)",
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+ "target": "ClassLabel(num_classes=2, names=['0', '1'], id=None)"
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+ }
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+ ```
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+
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+ ### Dataset Splits
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+
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+ This dataset is split into a train and validation split. The split sizes are as follow:
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+
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+ | Split name | Num samples |
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+ | ------------ | ------------------- |
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+ | train | 1600 |
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+ | valid | 400 |
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