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--- |
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annotations_creators: |
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- other |
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language_creators: |
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- other |
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languages: |
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- sv |
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- da |
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- nb |
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licenses: |
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- cc-by-4.0 |
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multilinguality: |
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- translation |
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pretty_name: overlim |
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size_categories: |
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- unknown |
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source_datasets: |
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- extended|glue |
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- extended|super_glue |
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task_categories: |
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- text-classification |
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- text-scoring |
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task_ids: |
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- natural-language-inference |
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- semantic-similarity-classification |
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- sentiment-classification |
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- text-classification-other-paraphrase-identification |
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- text-classification-other-qa-nli |
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--- |
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# Dataset Card for OverLim |
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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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The _OverLim_ dataset contains some of the GLUE and SuperGLUE tasks automatically |
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translated to Swedish, Danish, and Norwegian (bokmål), using the OpusMT models |
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for MarianMT. |
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The translation quality was not manually checked and may thus be faulty. |
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Results on these datasets should thus be interpreted carefully. |
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### Supported Tasks and Leaderboards |
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The data contains the following tasks from GLUE and SuperGLUE: |
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- GLUE |
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- `mnli` |
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- `mrpc` |
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- `qnli` |
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- `qqp` |
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- `rte` |
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- `sst` |
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- `stsb` |
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- `wnli` |
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- SuperGLUE |
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- `boolq` |
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- `cb` |
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- `copa` |
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- `rte` |
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### Languages |
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- Swedish |
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- Danish |
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- Norwegian (bokmål) |
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## Dataset Structure |
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### Data Instances |
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Every task has their own set of features, but all share an `idx` and `label`. |
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- GLUE |
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- `mnli` |
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- `premise`, `hypothesis` |
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- `mrpc` |
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- `text_a`, `text_b` |
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- `qnli` |
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- `premise`, `hypothesis` |
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- `qqp` |
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- `text_a`, `text_b` |
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- `sst` |
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- `text` |
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- `stsb` |
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- `text_a`, `text_b` |
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- `wnli` |
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- `premise`, `hypothesis` |
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- SuperGLUE |
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- `boolq` |
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- `question`, `passage` |
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- `cb` |
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- `premise`, `hypothesis` |
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- `copa` |
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- `premise`, `choice1`, `choice2`, `question` |
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- `rte` |
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- `premise`, `hypothesis` |
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### Data Splits |
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In order to have test-split, we repurpose the original validation-split as |
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test-split, and split the training-split into a new training- and |
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validation-split, with an 80-20 distribution. |
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## Dataset Creation |
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For more information about the individual tasks see (https://gluebenchmark.com) and (https://super.gluebenchmark.com). |
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### Curation Rationale |
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Training non-English models is easy, but there is a lack of evaluation datasets to compare their actual performance. |
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### Source Data |
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#### Initial Data Collection and Normalization |
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[More Information Needed] |
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#### Who are the source language producers? |
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[More Information Needed] |
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### Annotations |
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#### Annotation process |
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[More Information Needed] |
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#### Who are the annotators? |
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[More Information Needed] |
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### Personal and Sensitive Information |
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[More Information Needed] |
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## Considerations for Using the Data |
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### Social Impact of Dataset |
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[More Information Needed] |
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### Discussion of Biases |
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[More Information Needed] |
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### Other Known Limitations |
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[More Information Needed] |
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## Additional Information |
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### Dataset Curators |
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[More Information Needed] |
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### Licensing Information |
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[More Information Needed] |
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### Citation Information |
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[More Information Needed] |
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### Contributions |
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Thanks to [@robinqrtz](https://github.com/robinqrtz) for adding this dataset. |
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