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--- |
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annotations_creators: |
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- found |
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language_creators: |
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- found |
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language: |
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- en |
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license: mit |
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multilinguality: monolingual |
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size_categories: |
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- 100<n<1K |
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source_datasets: |
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- original |
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task_categories: |
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- tabular-classification |
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pretty_name: TextDataHW1 |
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--- |
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# Dataset Card for TextDataHW1 |
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This dataset contains text descriptors of National Collegiate Athletics Association (NCAA) schools and labels for their athletic conference. |
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## Dataset Details |
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### Dataset Description |
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The original split contains text descriptions of 101 different National Collegiate Athletics Association (NCAA) schools, and are labeled by their athletic conference. |
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The data was augmented, using 303 rows of EDA, 202 rows of character level noise, 303 rows of backtranslation, and 202 rows of paraphrasing |
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Google Gemini was used for code debugging only |
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- **Curated by:** Ethan Kessler |
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- **License:** MIT |
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## Uses |
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### Direct Use |
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<!-- This section describes suitable use cases for the dataset. --> |
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This dataset is for use in training a classifier model on text data |
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### Out-of-Scope Use |
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<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. --> |
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More Information Needed |
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## Dataset Structure |
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<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. --> |
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The original split contains text descriptions of 101 different National Collegiate Athletics Association (NCAA) schools, and are labeled by their athletic conference. |
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The labels for the conferences are as follows: |
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American = 0 |
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ACC = 1 |
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Big XII = 2 |
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Big East = 3 |
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B1G = 4 |
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SEC = 5 |
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Pac-12 = 6 |
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The data was augmented, using 303 rows of EDA, 202 rows of character level noise, 303 rows of backtranslation, and 202 rows of paraphrasing. |
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## Dataset Creation |
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### Curation Rationale |
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<!-- Motivation for the creation of this dataset. --> |
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More Information Needed |
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### Source Data |
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<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). --> |
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#### Data Collection and Processing |
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<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. --> |
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More Information Needed |
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#### Who are the source data producers? |
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<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. --> |
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The text data was produced by the dataset author |
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### Annotations [optional] |
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<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. --> |
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#### Labeling process |
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<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. --> |
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the original split data was labelled manually based on common knowledge |
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#### Who are the annotators? |
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<!-- This section describes the people or systems who created the annotations. --> |
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More Information Needed |
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#### Personal and Sensitive Information |
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<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. --> |
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More Information Needed |
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## Bias, Risks, and Limitations |
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<!-- This section is meant to convey both technical and sociotechnical limitations. --> |
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More Information Needed] |
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### Recommendations |
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> |
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Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. |
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## Dataset Card Contact |
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More Information Needed |
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