File size: 3,307 Bytes
475c4f1 0779fc8 ad6fc16 475c4f1 0779fc8 f47df80 0779fc8 ad6fc16 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 |
---
dataset_info:
features:
- name: question
dtype: string
- name: answer
dtype: string
- name: context
sequence: string
splits:
- name: train
num_bytes: 1022539863.7823716
num_examples: 202767
- name: validation
num_bytes: 13603278.754966887
num_examples: 2646
download_size: 576539077
dataset_size: 1036143142.5373385
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
license: mit
task_categories:
- question-answering
- text2text-generation
language:
- en
size_categories:
- 100K<n<1M
tags:
- lfqa
---
# 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-512
:-------------------------:|:-------------------------:
 | 
Max answer length: 5964 tokens | Max answer length: 512 tokens (~12x shorter)
Num answers (train): 226147 | Num answers (train): 202767 (~10% 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.
## Blog Post
[Fine-Tuning a Pre-Trained LLM](https://stefanbschneider.github.io/blog/posts/llm-fine-tuning/)
## Licensing Information
This dataset is distributed under the MIT licence. |