add readme

README.md

@@ -23,4 +23,76 @@ configs:
     path: data/train-*
   - split: validation
     path: data/validation-*
+license: mit
+task_categories:
+- question-answering
+- text2text-generation
+language:
+- en
+size_categories:
+- 100K<n<1M
 ---
+
+# Dataset Card
+
+## 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
+
+The dataset contains simple, long-form answers to questions and corresponding contexts.
+Similar to ELI5 but with context.
+
+This dataset is a filtered version of [LLukas22/lfqa_preprocessed](https://huggingface.co/datasets/LLukas22/lfqa_preprocessed),
+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.
+
+I have filtered out overly long answers, based on the number of tokens in the answer using the LED tokenizer.
+It can be reproduced with the notebook `process-lfqa-dataset.ipynb`. 
+
+LLukas22/lfqa_preprocessed             |  stefanbschneider/lfqa-max-answer-length-1024
+:-------------------------:|:-------------------------:
+![](plots/answer-lengths-tokens-original.png)  |  ![](plots/answer-lengths-tokens-filtered.png)
+Max answer length: 5964 tokens | Max answer length: 1024 tokens (~6x shorter)
+Num answers (train): 226147    | Num answers (train): 218894 (~3% less)
+
+
+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)
+
+
+## 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.
+
+
+### Licensing Information
+
+This dataset is distributed under the MIT licence.