Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
csv
Sub-tasks:
sentiment-classification
Languages:
English
Size:
10K - 100K
License:
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README.md
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### Dataset Summary
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### Supported Tasks and Leaderboards
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## Dataset Structure
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### Data Fields
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### Data Splits
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### Dataset Summary
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This is a custom train/test/validation split of the IMDb Large Movie Review Dataset available from [http://ai.stanford.edu/~amaas/data/sentiment/](http://ai.stanford.edu/~amaas/data/sentiment/).
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### Supported Tasks and Leaderboards
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## Dataset Structure
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#### IMDb_movie_reviews
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An example of 'train':
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```
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{
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"text": "Beautifully photographed and ably acted, generally, but the writing is very slipshod. There are scenes of such unbelievability that there is no joy in the watching. The fact that the young lover has a twin brother, for instance, is so contrived that I groaned out loud. And the "emotion-light bulb connection" seems gimmicky, too.<br /><br />I don\'t know, though. If you have a few glasses of wine and feel like relaxing with something pretty to look at with a few flaccid comedic scenes, this is a pretty good movie. No major effort on the part of the viewer required. But Italian film, especially Italian comedy, is usually much, much better than this."
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"label": 0,
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}
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```
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### Data Fields
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The data fields are the same among all splits.
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#### IMDb_movie_reviews
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- `text`: a `string` feature.
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- `label`: a classification label, with values `neg` (0), `pos` (1).
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### Data Splits
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