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Add proper readme

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@@ -23,4 +23,79 @@ configs:
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  path: data/train-*
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  - split: validation
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  path: data/validation-*
 
 
 
 
 
 
 
 
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  path: data/train-*
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  - split: validation
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  path: data/validation-*
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+ license: mit
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+ task_categories:
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+ - question-answering
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+ - text2text-generation
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+ language:
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+ - en
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+ size_categories:
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+ - 10K<n<100K
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  ---
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+
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+
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+ # Dataset Card for "lfqa_preprocessed"
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+
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+ ## Table of Contents
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+ - [Table of Contents](#table-of-contents)
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+ - [Dataset Description](#dataset-description)
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+ - [Dataset Summary](#dataset-summary)
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+ - [Dataset Structure](#dataset-structure)
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+ - [Data Instances](#data-instances)
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+ - [Data Fields](#data-fields)
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+ - [Data Splits](#data-splits)
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+ - [Additional Information](#additional-information)
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+ - [Licensing Information](#licensing-information)
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+
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+ ## Dataset Description
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+
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+ The dataset contains simple, long-form answers to questions and corresponding contexts.
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+ Similar to ELI5 but with context.
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+
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+ This dataset is a filtered version of [**LLukas22/lfqa_preprocessed**](https://huggingface.co/datasets/LLukas22/lfqa_preprocessed),
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+ which in turn is a processed and simplified version of 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.
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+
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+ This dataset (stefanbschneider/lfqa_preprocessed) has filtered out overly long answers (around 3%).
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+ It can be reproduced with the notebook `process-lfqa-dataset.ipynb`.
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+
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+
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+ Details of the original LFQA dataset: [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)
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+
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+
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+ ## Dataset Structure
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+
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+ ### Data Instances
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+
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+ An example of 'train' looks as follows.
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+
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+ ```json
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+ {
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+ "question": "what's the difference between a forest and a wood?",
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+ "answer": "They're used interchangeably a lot. You'll get different answers from different resources, but the ...",
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+ "context": [
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+ "Wood is divided, according to its botanical origin, into two kinds: softwoods, ...",
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+ "Processing and products differs especially with regard to the distinction between softwood and hardwood ..."
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+ ]
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+ }
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+ ```
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+
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+ ### Data Fields
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+
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+ The data fields are the same among all splits.
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+
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+ - `question`: a `string` feature.
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+ - `answer`: a `string` feature.
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+ - `context`: a list feature containing `string` features.
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+
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+ ### Data Splits
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+
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+ | name |train|validation|
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+ |----------|----:|---------:|
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+ | |218894| 2904|
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+
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+
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+ ## Additional Information
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+
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+ ### Licensing Information
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+
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+ This dataset is distributed under the MIT licence.