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--- |
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language: |
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- en |
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size_categories: |
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- 10K<n<100K |
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--- |
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# Dataset Card for Dataset Name |
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## Dataset Description |
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- **Homepage:** |
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- **Repository:** |
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- **Paper:** |
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- **Leaderboard:** |
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- **Point of Contact:** |
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### Dataset Summary |
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Dataset used to train a language model to do classification on 50 different waste classes. |
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### Languages |
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English |
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## Dataset Structure |
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### Data Instances |
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Phrase | Class | Index |
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"I have this apple phone charger to throw, where should I put it ?" | PHONE CHARGER | 26 |
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"Should I recycle a disposable cup ?" | Plastic Cup | 32 |
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"I have a milk brick" | Tetrapack | 45 |
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### Data Fields |
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- Phrase |
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- Class |
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- Class_index |
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### Data Splits |
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train: 12.5K rows |
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test: 5.38K rows |
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additional data: 7.24K rows (unseen_phrases.csv) |
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## Dataset Creation |
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Manualy with objects and phrases templates. |
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### Annotations |
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#### Annotation process |
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Each object was annotated and then the phrases were annotated according to the object according to its annnotation. |
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#### Who are the annotators? |
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Myself |
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### Personal and Sensitive Information |
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None |
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## Considerations for Using the Data |
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### Social Impact of Dataset |
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None |
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### Discussion of Biases |
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Some classes are more present than others but the dataset is balanced overall. Because it was created using patterns, might not be very robust. |
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### Other Known Limitations |
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Repetition of phrase patterns, have to verify performances of model on external phrases for robustness. |
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