
# Dataset Card for "lmqg/qa_squadshifts"

## Dataset Description
- **Repository:** [https://github.com/asahi417/lm-question-generation](https://github.com/asahi417/lm-question-generation)
- **Paper:** [https://arxiv.org/abs/2004.14444](https://arxiv.org/abs/2004.14444)
- **Point of Contact:** [Asahi Ushio](http://asahiushio.com/)

### Dataset Summary
This is SQuADShifts dataset with custom split of training/validation/test following [lmqg/qg_squadshifts](https://huggingface.co/datasets/lmqg/qg_squadshifts).


### Supported Tasks and Leaderboards
* `question-answering`

### Languages
English (en)

## Dataset Structure

### Data Fields
The data fields are the same among all splits.

#### plain_text

- `id`: a `string` feature of id
- `title`: a `string` feature of title of the paragraph 
- `context`: a `string` feature of paragraph 
- `question`: a `string` feature of question
- `answers`: a `json` feature of answers

### Data Splits

|   name      |train  | valid | test |
|-------------|------:|------:|-----:|
|default (all)|9209|6283 |18,844|
| amazon      |3295|1648|4942|
| new_wiki    |2646|1323|3969|
| nyt         |3355|1678|5032|
| reddit      |3268|1634|4901|

## Citation Information

```
@inproceedings{miller2020effect,
  title={The effect of natural distribution shift on question answering models},
  author={Miller, John and Krauth, Karl and Recht, Benjamin and Schmidt, Ludwig},
  booktitle={International Conference on Machine Learning},
  pages={6905--6916},
  year={2020},
  organization={PMLR}
}
```
task_categories:question-answering task_ids:extractive-qa multilinguality:monolingual size_categories:1k<n<10k source_datasets:extended|wikipedia language:en license:cc-by-4.0 arxiv:2004.14444 region:us
{"language": "en", "license": "cc-by-4.0", "multilinguality": "monolingual", "size_categories": "1k<n<10k", "source_datasets": ["extended|wikipedia"], "task_categories": ["question-answering"], "task_ids": ["extractive-qa"], "pretty_name": "SQuADShifts"}
TAGS
#task_categories-question-answering #task_ids-extractive-qa #multilinguality-monolingual #size_categories-1k<n<10k #source_datasets-extended|wikipedia #language-English #license-cc-by-4.0 #arxiv-2004.14444 #region-us 

Dataset Card for "lmqg/qa\_squadshifts"
=======================================


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


* Repository: URL
* Paper: URL
* Point of Contact: Asahi Ushio


### Dataset Summary


This is SQuADShifts dataset with custom split of training/validation/test following lmqg/qg\_squadshifts.


### Supported Tasks and Leaderboards


* 'question-answering'


### Languages


English (en)


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


### Data Fields


The data fields are the same among all splits.


#### plain\_text


* 'id': a 'string' feature of id
* 'title': a 'string' feature of title of the paragraph
* 'context': a 'string' feature of paragraph
* 'question': a 'string' feature of question
* 'answers': a 'json' feature of answers


### Data Splits




### Dataset Summary


This is SQuADShifts dataset with custom split of training/validation/test following lmqg/qg\_squadshifts. ### Supported Tasks and Leaderboards


* 'question-answering' ### Languages


English (en)


Dataset Structure
----------------- ### Data Fields


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


* 'id': a 'string' feature of id
* 'title': a 'string' feature of title of the paragraph
* 'context': a 'string' feature of paragraph
* 'question': a 'string' feature of question
* 'answers': a 'json' feature of answers ### Data Splits
TAGS
#task_categories-question-answering #task_ids-extractive-qa #multilinguality-monolingual #size_categories-1k<n<10k #source_datasets-extended|wikipedia #language-English #license-cc-by-4.0 #arxiv-2004.14444 #region-us 
 ### Dataset Summary


This is SQuADShifts dataset with custom split of training/validation/test following lmqg/qg\_squadshifts. ### Supported Tasks and Leaderboards


* 'question-answering' ### Languages


English (en)


Dataset Structure
----------------- ### Data Fields


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


* 'id': a 'string' feature of id
* 'title': a 'string' feature of title of the paragraph
* 'context': a 'string' feature of paragraph
* 'question': a 'string' feature of question
* 'answers': a 'json' feature of answers ### Data Splits