Datasets:
Tasks:
Text Classification
Modalities:
Text
Sub-tasks:
sentiment-classification
Languages:
Polish
Size:
100K - 1M
License:
Update README.md (#3)
Browse files- Update README.md (68b3b7ccbb15a1ce451d19655da920a216545593)
Co-authored-by: Albert Sawczyn <[email protected]>
README.md
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@@ -40,7 +40,12 @@ The task is to predict the correct label of the review.
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**Measurements**: Accuracy, F1 Macro
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**Example**:
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## Data splits
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**Measurements**: Accuracy, F1 Macro
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**Example**:
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Input: `Na samym wejściu hotel śmierdzi . W pokojach jest pleśń na ścianach , brudny dywan . W łazience śmierdzi chemią , hotel nie grzeje w pokojach panuje chłód . Wyposażenie pokoju jest stare , kran się rusza , drzwi na balkon nie domykają się . Jedzenie jest w małych ilościach i nie smaczne . Nie polecam nikomu tego hotelu .`
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Input (translated by DeepL): `At the very entrance the hotel stinks . In the rooms there is mold on the walls , dirty carpet . The bathroom smells of chemicals , the hotel does not heat in the rooms are cold . The room furnishings are old , the faucet moves , the door to the balcony does not close . The food is in small quantities and not tasty . I would not recommend this hotel to anyone .`
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Output: `1` (negative)
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## Data splits
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