Datasets:
Tasks:
Text Classification
Modalities:
Text
Sub-tasks:
multi-class-classification
Languages:
English
Size:
10K - 100K
ArXiv:
License:
| YAML tags: | |
| annotations_creators: | |
| - expert-generated | |
| - crowdsourced | |
| language_creators: | |
| - expert-generated | |
| languages: | |
| - en-US | |
| licenses: | |
| - other-individual-licenses | |
| multilinguality: | |
| - monolingual | |
| pretty_name: '' | |
| size_categories: | |
| - unknown | |
| source_datasets: | |
| - original | |
| - extended|ade_corpus_v2 | |
| - extended|banking77 | |
| task_categories: | |
| - text-classification | |
| task_ids: | |
| - multi-class-classification | |
| # Dataset Card for RAFT | |
| ## Table of Contents | |
| - [Table of Contents](#table-of-contents) | |
| - [Dataset Description](#dataset-description) | |
| - [Dataset Summary](#dataset-summary) | |
| - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) | |
| - [Languages](#languages) | |
| - [Dataset Structure](#dataset-structure) | |
| - [Data Instances](#data-instances) | |
| - [Data Fields](#data-fields) | |
| - [Data Splits](#data-splits) | |
| - [Dataset Creation](#dataset-creation) | |
| - [Curation Rationale](#curation-rationale) | |
| - [Source Data](#source-data) | |
| - [Annotations](#annotations) | |
| - [Personal and Sensitive Information](#personal-and-sensitive-information) | |
| - [Considerations for Using the Data](#considerations-for-using-the-data) | |
| - [Social Impact of Dataset](#social-impact-of-dataset) | |
| - [Discussion of Biases](#discussion-of-biases) | |
| - [Other Known Limitations](#other-known-limitations) | |
| - [Additional Information](#additional-information) | |
| - [Dataset Curators](#dataset-curators) | |
| - [Licensing Information](#licensing-information) | |
| - [Citation Information](#citation-information) | |
| - [Contributions](#contributions) | |
| ## Dataset Description | |
| - **Homepage:** raft.elicit.org | |
| - **Repository:** https://huggingface.co/datasets/ought/raft | |
| - **Paper:** forthcoming | |
| - **Leaderboard:** https://huggingface.co/spaces/ought/raft-leaderboard | |
| - **Point of Contact:** [email protected] | |
| ### Dataset Summary | |
| The Real-world Annotation for Few-shot Tasks (RAFT) dataset is an aggregation of English-language datasets found in the real world. Associated with each dataset is a binary or multiclass classification task, intended to improve our understanding of how language models perform on tasks that have concrete, real-world value. Only 50 labeled examples are provided in each dataset. | |
| ### Supported Tasks and Leaderboards | |
| - `text-classification`: Each subtask in RAFT is a text classification task, and the provided train and test sets can be used to submit to the [RAFT Leaderboard](https://huggingface.co/spaces/ought/raft-leaderboard) To prevent overfitting and tuning on a held-out test set, the leaderboard is only evaluated once per week. Each task has its macro-f1 score calculated, then those scores are averaged to produce the overall leaderboard score. | |
| ### Languages | |
| The only language intentionally included in the dataset is American English (en-US). However, we have not examined every single example in the train and test sets. | |
| ## Dataset Structure | |
| ### Data Instances | |
| | Dataset | First Example | | |
| | ----------- | ----------- | | |
| | Ade Corpus V2 | <pre>Sentence: No regional side effects were noted.<br>ID: 0<br>Label: 2</pre> | | |
| | Banking 77 | <pre>Query: Is it possible for me to change my PIN number?<br>ID: 0<br>Label: 23<br></pre> | | |
| | Neurips Impact Statement Risks | <pre>Paper title: Auto-Panoptic: Cooperative Multi-Component Architecture Search for Panoptic Segmentation...<br>Paper link: https://proceedings.neurips.cc/paper/2020/file/ec1f764517b7ffb52057af6df18142b7-Paper.pdf...<br>Impact statement: This work makes the first attempt to search for all key components of panoptic pipeline and manages to accomplish this via the p...<br>ID: 0<br>Label: 1</pre> | | |
| | One Stop English | <pre>Article: For 85 years, it was just a grey blob on classroom maps of the solar system. But, on 15 July, Pluto was seen in high resolution ...<br>ID: 0<br>Label: 3<br></pre> | | |
| | Overruling | <pre>Sentence: in light of both our holding today and previous rulings in johnson, dueser, and gronroos, we now explicitly overrule dupree....<br>ID: 0<br>Label: 2<br></pre> | | |
| | Semiconductor Org Types | <pre>Paper title: 3Gb/s AC-coupled chip-to-chip communication using a low-swing pulse receiver...<br>Organization name: North Carolina State Univ.,Raleigh,NC,USA<br>ID: 0<br>Label: 3<br></pre> | | |
| | Systematic Review Inclusion | <pre>Title: Prototyping and transforming facial textures for perception research...<br>Abstract: Wavelet based methods for prototyping facial textures for artificially transforming the age of facial images were described. Pro...<br>Authors: Tiddeman, B.; Burt, M.; Perrett, D.<br>Journal: IEEE Comput Graphics Appl<br>ID: 0<br>Label: 2</pre> | | |
| | Tai Safety Research | <pre>Title: Malign generalization without internal search<br>Abstract Note: In my last post, I challenged the idea that inner alignment failures should be explained by appealing to agents which perform ex...<br>Url: https://www.alignmentforum.org/posts/ynt9TD6PrYw6iT49m/malign-generalization-without-internal-search...<br>Publication Year: 2020<br>Item Type: blogPost<br>Author: Barnett, Matthew<br>Publication Title: AI Alignment Forum<br>ID: 0<br>Label: 1</pre> | | |
| | Terms Of Service | <pre>Sentence: Crowdtangle may change these terms of service, as described above, notwithstanding any provision to the contrary in any agreemen...<br>ID: 0<br>Label: 2<br></pre> | | |
| | Tweet Eval Hate | <pre>Tweet: New to Twitter-- any men on here know what the process is to get #verified?...<br>ID: 0<br>Label: 2<br></pre> | | |
| | Twitter Complaints | <pre>Tweet text: @HMRCcustomers No this is my first job<br>ID: 0<br>Label: 2</pre> | | |
| ### Data Fields | |
| The ID field is used for indexing data points. It will be used to match your submissions with the true test labels, so you must include it in your submission. All other columns contain textual data. Some contain links and URLs to websites on the internet. | |
| All output fields are designated with the "Label" column header. The 0 value in this column indicates that the entry is unlabeled, and should only appear in the unlabeled test set. Other values in this column are various other labels. To get their textual value for a given dataset: | |
| ``` | |
| # Load the dataset | |
| dataset = datasets.load_dataset("ought/raft", "ade_corpus_v2") | |
| # First, get the object that holds information about the "Label" feature in the dataset. | |
| label_info = dataset.features["Label"] | |
| # Use the int2str method to access the textual labels. | |
| print([label_info.int2str(i) for i in (0, 1, 2)]) | |
| # ['Unlabeled', 'ADE-related', 'not ADE-related'] | |
| ``` | |
| ### Data Splits | |
| There are two splits provided: train data and unlabeled test data. | |
| The training examples were chosen at random. No attempt was made to ensure that classes were balanced or proportional in the training data -- indeed, the Banking 77 task with 77 different classes if used cannot fit all of its classes into the 50 training examples. | |
| | Dataset | Train Size | Test Size | | | |
| |--------------------------------|------------|-----------|---| | |
| | Ade Corpus V2 | 50 | 5000 | | | |
| | Banking 77 | 50 | 5000 | | | |
| | Neurips Impact Statement Risks | 50 | 150 | | | |
| | One Stop English | 50 | 518 | | | |
| | Overruling | 50 | 2350 | | | |
| | Semiconductor Org Types | 50 | 449 | | | |
| | Systematic Review Inclusion | 50 | 2244 | | | |
| | TAI Safety Research | 50 | 1639 | | | |
| | Terms Of Service | 50 | 5000 | | | |
| | Tweet Eval Hate | 50 | 2966 | | | |
| | Twitter Complaints | 50 | 3399 | | | |
| | **Total** | **550** | **28715** | | | |
| ## Dataset Creation | |
| ### Curation Rationale | |
| [More Information Needed] | |
| ### Source Data | |
| #### Initial Data Collection and Normalization | |
| [More Information Needed] | |
| #### Who are the source language producers? | |
| [More Information Needed] | |
| ### Annotations | |
| #### Annotation process | |
| [More Information Needed] | |
| #### Who are the annotators? | |
| [More Information Needed] | |
| ### Personal and Sensitive Information | |
| [More Information Needed] | |
| ## Considerations for Using the Data | |
| ### Social Impact of Dataset | |
| [More Information Needed] | |
| ### Discussion of Biases | |
| [More Information Needed] | |
| ### Other Known Limitations | |
| [More Information Needed] | |
| ## Additional Information | |
| ### Dataset Curators | |
| [More Information Needed] | |
| ### Licensing Information | |
| RAFT aggregates many other datasets, each of which is provided under its own license. Generally, those licenses permit research and commercial use. | |
| | Dataset | License | | |
| | ----------- | ----------- | | |
| | Ade Corpus V2 | Test | | |
| | Banking 77 | | | |
| | Neurips Impact Statement Risks | | | |
| | One Stop English | | | |
| | Overruling | | | |
| | Semiconductor Org Types | | | |
| | Systematic Review Inclusion | | | |
| | Tai Safety Research | | | |
| | Terms Of Service | | | |
| | Tweet Eval Hate | | | |
| | Twitter Complaints | | | |
| ### Citation Information | |
| [More Information Needed] | |
| ### Contributions | |
| Thanks to [@neel-alex](https://github.com/neel-alex), [@uvafan](https://github.com/uvafan), and [@lewtun](https://github.com/lewtun) for adding this dataset. |