# Dataset Card for "lfqa_preprocessed"

## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
  - [Dataset Summary](#dataset-summary)
- [Dataset Structure](#dataset-structure)
  - [Data Instances](#data-instances)
  - [Data Fields](#data-fields)
  - [Data Splits](#data-splits)
- [Additional Information](#additional-information)
  - [Licensing Information](#licensing-information)

## Dataset Description

- **Homepage:** [https://towardsdatascience.com/long-form-qa-beyond-eli5-an-updated-dataset-and-approach-319cb841aabb](https://towardsdatascience.com/long-form-qa-beyond-eli5-an-updated-dataset-and-approach-319cb841aabb)


### Dataset Summary

This is a simplified version of [vblagoje's](https://huggingface.co/vblagoje) *[lfqa_support_docs](https://huggingface.co/datasets/vblagoje/lfqa_support_docs)* and *[lfqa](https://huggingface.co/datasets/vblagoje/lfqa)* datasets.
It was generated by me to have a more straight forward way to train Seq2Seq models on context based long form question answering tasks.

## Dataset Structure

### Data Instances

An example of 'train' looks as follows.

```json
{
    "question": "what's the difference between a forest and a wood?",
    "answer": "They're used interchangeably a lot. You'll get different answers from different resources, but the ...",
    "context": [
        "Wood is divided, according to its botanical origin, into two kinds: softwoods, ...",
        "Processing and products differs especially with regard to the distinction between softwood and hardwood ..."
    ]
}
```

### Data Fields

The data fields are the same among all splits.

- `question`: a `string` feature.
- `answer`: a `string` feature.
- `context`: a list feature containing `string` features.

### Data Splits

|   name   |train|validation|
|----------|----:|---------:|
|          |226147|     3020|


## Additional Information

### Licensing Information

This dataset is distributed under the MIT licence.
task_categories:question-answering task_categories:sentence-similarity size_categories:100K<n<1M language:en license:mit region:us
{"language": ["en"], "license": "mit", "size_categories": ["100K<n<1M"], "task_categories": ["question-answering", "sentence-similarity"]}
TAGS
#task_categories-question-answering #task_categories-sentence-similarity #size_categories-100K<n<1M #language-English #license-mit #region-us 

Dataset Card for "lfqa\_preprocessed"
=====================================


Table of Contents
-----------------


* Table of Contents
* Dataset Description
	+ Dataset Summary
* Dataset Structure
	+ Data Instances
	+ Data Fields
	+ Data Splits
* Additional Information
	+ Licensing Information


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


* Homepage: URL


### Dataset Summary


This is a simplified version of vblagoje's *lfqa\_support\_docs* and *lfqa* datasets.
It was generated by me to have a more straight forward way to train Seq2Seq models on context based long form question answering tasks.


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


### Data Instances


An example of 'train' looks as follows.


### Data Fields


The data fields are the same among all splits.


* 'question': a 'string' feature.
* 'answer': a 'string' feature.
* 'context': a list feature containing 'string' features.


### Data Splits



Additional Information
----------------------


### Licensing Information


This dataset is distributed under the MIT licence.



### Dataset Summary


This is a simplified version of vblagoje's *lfqa\_support\_docs* and *lfqa* datasets.
It was generated by me to have a more straight forward way to train Seq2Seq models on context based long form question answering tasks.


Dataset Structure
----------------- ### Data Instances


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


The data fields are the same among all splits.


* 'question': a 'string' feature.
* 'answer': a 'string' feature.
* 'context': a list feature containing 'string' features. ### Data Splits



Additional Information
---------------------- ### Licensing Information


This dataset is distributed under the MIT licence.
TAGS
#task_categories-question-answering #task_categories-sentence-similarity #size_categories-100K<n<1M #language-English #license-mit #region-us 
 ### Dataset Summary


This is a simplified version of vblagoje's *lfqa\_support\_docs* and *lfqa* datasets.
It was generated by me to have a more straight forward way to train Seq2Seq models on context based long form question answering tasks.


Dataset Structure
----------------- ### Data Instances


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


The data fields are the same among all splits.


* 'question': a 'string' feature.
* 'answer': a 'string' feature.
* 'context': a list feature containing 'string' features. ### Data Splits



Additional Information
---------------------- ### Licensing Information


This dataset is distributed under the MIT licence.
passage: TAGS
#task_categories-question-answering #task_categories-sentence-similarity #size_categories-100K<n<1M #language-English #license-mit #region-us 
### Dataset Summary


This is a simplified version of vblagoje's *lfqa\_support\_docs* and *lfqa* datasets.
It was generated by me to have a more straight forward way to train Seq2Seq models on context based long form question answering tasks.


Dataset Structure
-----------------### Data Instances


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


The data fields are the same among all splits.


* 'question': a 'string' feature.
* 'answer': a 'string' feature.
* 'context': a list feature containing 'string' features.### Data Splits



Additional Information
----------------------### Licensing Information


This dataset is distributed under the MIT licence.