

# Dataset Card for "squad-v1.1-t5-question-generation"
## Dataset Description

- **Homepage:** [https://rajpurkar.github.io/SQuAD-explorer/](https://rajpurkar.github.io/SQuAD-explorer/)
- **Paper:** [SQuAD: 100,000+ Questions for Machine Comprehension of Text](https://arxiv.org/abs/1606.05250)

### Dataset Summary

This is a modified Stanford Question Answering Dataset (SQuAD) to suit question generation with All Questions in One Line (AQOL) just like in [Transformer-based End-to-End Question Generation](https://arxiv.org/pdf/2005.01107v1.pdf)
specifically for the T5 family of models. The prefix is `generate questions: ` so that the task can be unique to a trained model.

Check out the generation notebook [here](https://nbviewer.org/urls/huggingface.co/datasets/derek-thomas/squad-v1.1-t5-question-generation/resolve/main/Squad_V1_Question_Generation.ipynb).

### Supported Tasks and Leaderboards

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Languages

## Dataset Structure

### Data Instances

#### plain_text

An example of 'train' looks as follows.
```
{
    "context": "generate questions: This is a test context.",
    "question": "Is this a test? {sep_token} Is this another Test {sep_token}"
}
```

### Data Fields

The data fields are the same among all splits.

#### plain_text
- `context`: a `string` feature.
- `question`: a `string` feature.

### Data Splits
|   name   |train|validation|
|----------|----:|---------:|
|plain_text|18896|      2067|

### Citation Information

```
@article{2016arXiv160605250R,
       author = {{Rajpurkar}, Pranav and {Zhang}, Jian and {Lopyrev},
                 Konstantin and {Liang}, Percy},
        title = "{SQuAD: 100,000+ Questions for Machine Comprehension of Text}",
      journal = {arXiv e-prints},
         year = 2016,
          eid = {arXiv:1606.05250},
        pages = {arXiv:1606.05250},
archivePrefix = {arXiv},
       eprint = {1606.05250},
}

```

### Contributions

Thanks to [Derek Thomas](https://huggingface.co/derek-thomas) and [Thomas Simonini](https://huggingface.co/ThomasSimonini) for adding this to the hub

Check out: [How to contribute more](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Visitors
[![Visitors](https://api.visitorbadge.io/api/visitors?path=https%3A%2F%2Fhuggingface.co%2Fdatasets%2Fderek-thomas%2Fsquad-v1.1-t5-question-generation&label=Visitors&countColor=%23263759)](https://visitorbadge.io/status?path=https%3A%2F%2Fhuggingface.co%2Fdatasets%2Fderek-thomas%2Fsquad-v1.1-t5-question-generation)
task_categories:text2text-generation annotations_creators:crowdsourced language_creators:crowdsourced multilinguality:monolingual size_categories:10K<n<100K source_datasets:extended|squad language:en license:cc-by-4.0 questiongeneration question-generation text2text-generation arxiv:1606.05250 arxiv:2005.01107 region:us
{"annotations_creators": ["crowdsourced"], "language_creators": ["crowdsourced"], "language": ["en"], "license": ["cc-by-4.0"], "multilinguality": ["monolingual"], "size_categories": ["10K<n<100K"], "source_datasets": ["extended|squad"], "task_categories": ["text2text-generation"], "task_ids": [], "pretty_name": "Question Generation for T5 based on Squad V1.1", "dataset_info": {"features": [{"name": "context", "dtype": "string"}, {"name": "questions", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 20293805, "num_examples": 18896}, {"name": "validation", "num_bytes": 2376313, "num_examples": 2067}], "download_size": 12600387, "dataset_size": 22670118}, "tags": ["questiongeneration", "question-generation", "text2text-generation"]}
TAGS
#task_categories-text2text-generation #annotations_creators-crowdsourced #language_creators-crowdsourced #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-extended|squad #language-English #license-cc-by-4.0 #questiongeneration #question-generation #text2text-generation #arxiv-1606.05250 #arxiv-2005.01107 #region-us 

Dataset Card for "squad-v1.1-t5-question-generation"
====================================================


Dataset Description
-------------------


* Homepage: URL
* Paper: SQuAD: 100,000+ Questions for Machine Comprehension of Text


### Dataset Summary


This is a modified Stanford Question Answering Dataset (SQuAD) to suit question generation with All Questions in One Line (AQOL) just like in Transformer-based End-to-End Question Generation
specifically for the T5 family of models. The prefix is 'generate questions: ' so that the task can be unique to a trained model.


Check out the generation notebook here.


### Supported Tasks and Leaderboards


### Languages


Dataset Structure
-----------------


### Data Instances


#### plain\_text


An example of 'train' looks as follows.


### Data Fields


The data fields are the same among all splits.


#### plain\_text


* 'context': a 'string' feature.
* 'question': a 'string' feature.


### Data Splits



### Contributions


Thanks to Derek Thomas and Thomas Simonini for adding this to the hub


Check out: How to contribute more


### Visitors


![Visitors](URL



### Dataset Summary


This is a modified Stanford Question Answering Dataset (SQuAD) to suit question generation with All Questions in One Line (AQOL) just like in Transformer-based End-to-End Question Generation
specifically for the T5 family of models. The prefix is 'generate questions: ' so that the task can be unique to a trained model.


Check out the generation notebook here. ### Supported Tasks and Leaderboards ### Languages


Dataset Structure
----------------- ### Data Instances #### plain\_text


An example of 'train' looks as follows. ### Data Fields


The data fields are the same among all splits. #### plain\_text


* 'context': a 'string' feature.
* 'question': a 'string' feature. ### Data Splits ### Contributions


Thanks to Derek Thomas and Thomas Simonini for adding this to the hub


Check out: How to contribute more ### Visitors


![Visitors](URL
TAGS
#task_categories-text2text-generation #annotations_creators-crowdsourced #language_creators-crowdsourced #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-extended|squad #language-English #license-cc-by-4.0 #questiongeneration #question-generation #text2text-generation #arxiv-1606.05250 #arxiv-2005.01107 #region-us 
 ### Dataset Summary


This is a modified Stanford Question Answering Dataset (SQuAD) to suit question generation with All Questions in One Line (AQOL) just like in Transformer-based End-to-End Question Generation
specifically for the T5 family of models. The prefix is 'generate questions: ' so that the task can be unique to a trained model.


Check out the generation notebook here. ### Supported Tasks and Leaderboards ### Languages


Dataset Structure
----------------- ### Data Instances #### plain\_text


An example of 'train' looks as follows. ### Data Fields


The data fields are the same among all splits. #### plain\_text


* 'context': a 'string' feature.
* 'question': a 'string' feature. ### Data Splits ### Contributions


Thanks to Derek Thomas and Thomas Simonini for adding this to the hub


Check out: How to contribute more ### Visitors


![Visitors](URL
passage: TAGS
#task_categories-text2text-generation #annotations_creators-crowdsourced #language_creators-crowdsourced #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-extended|squad #language-English #license-cc-by-4.0 #questiongeneration #question-generation #text2text-generation #arxiv-1606.05250 #arxiv-2005.01107 #region-us 
### Dataset Summary


This is a modified Stanford Question Answering Dataset (SQuAD) to suit question generation with All Questions in One Line (AQOL) just like in Transformer-based End-to-End Question Generation
specifically for the T5 family of models. The prefix is 'generate questions: ' so that the task can be unique to a trained model.


Check out the generation notebook here.### Supported Tasks and Leaderboards### Languages


Dataset Structure
-----------------### Data Instances#### plain\_text


An example of 'train' looks as follows.### Data Fields


The data fields are the same among all splits.#### plain\_text


* 'context': a 'string' feature.
* 'question': a 'string' feature.### Data Splits### Contributions


Thanks to Derek Thomas and Thomas Simonini for adding this to the hub


Check out: How to contribute more### Visitors


![Visitors](URL