File size: 3,931 Bytes
1713963 b826854 1e4be92 b826854 bcf02f8 b826854 1713963 674282f 1713963 1e4be92 dcd9ad6 57d7b84 1713963 674282f 1713963 1e4be92 57d7b84 1713963 b826854 bcf02f8 b826854 |
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 |
---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- en
multilinguality:
- monolingual
size_categories:
- 1M<n<10M
task_categories:
- feature-extraction
- sentence-similarity
pretty_name: Quora Duplicate Questions
tags:
- sentence-transformers
dataset_info:
- config_name: pair
features:
- name: anchor
dtype: string
- name: positive
dtype: string
splits:
- name: train
num_bytes: 19063882.986566573
num_examples: 149263
download_size: 10710908
dataset_size: 19063882.986566573
- config_name: pair-class
features:
- name: sentence1
dtype: string
- name: sentence2
dtype: string
- name: label
dtype:
class_label:
names:
'0': different
'1': duplicate
splits:
- name: train
num_bytes: 54870273
num_examples: 404290
download_size: 34965546
dataset_size: 54870273
- config_name: triplet
features:
- name: anchor
dtype: string
- name: positive
dtype: string
- name: negative
dtype: string
splits:
- name: train
num_bytes: 17575186
num_examples: 101762
download_size: 10954551
dataset_size: 17575186
- config_name: triplet-all
features:
- name: anchor
dtype: string
- name: positive
dtype: string
- name: negative
dtype: string
splits:
- name: train
num_bytes: 483971801
num_examples: 2792280
download_size: 104682424
dataset_size: 483971801
configs:
- config_name: pair
data_files:
- split: train
path: pair/train-*
- config_name: pair-class
data_files:
- split: train
path: pair-class/train-*
- config_name: triplet
data_files:
- split: train
path: triplet/train-*
- config_name: triplet-all
data_files:
- split: train
path: triplet-all/train-*
---
# Dataset Card for Quora Duplicate Questions
This dataset contains the [Quora](https://huggingface.co/datasets/quora) Question Pairs dataset in two formats that are easily used with Sentence Transformers to train embedding models. The data was originally created by Quora for [this Kaggle Competition](https://www.kaggle.com/c/quora-question-pairs).
## Dataset Subsets
### `pair-class` subset
* Columns: "sentence1", "sentence2", "label"
* Column types: `str`, `str`, `class` with `{"0": "different", "1": "duplicate"}`
* Examples:
```python
{
'sentence1': 'What is the step by step guide to invest in share market in india?',
'sentence2': 'What is the step by step guide to invest in share market?',
'label': 0,
}
```
* Collection strategy: A direct copy of [Quora](https://huggingface.co/datasets/quora), but with more conveniently parsable columns.
* Deduplified: No
### `pair` subset
* Columns: "anchor", "positive"
* Column types: `str`, `str`
* Examples:
```python
{
'anchor': 'Astrology: I am a Capricorn Sun Cap moon and cap rising...what does that say about me?',
'positive': "I'm a triple Capricorn (Sun, Moon and ascendant in Capricorn) What does this say about me?",
}
```
* Collection strategy: Filtering away the "different" options from the `pair-class` subset, removing the label column, and renaming the columns.
* Deduplified: No
### `triplet` subset
* Columns: "anchor", "positive", "negative"
* Column types: `str`, `str`, `str`
* Examples:
```python
{
'anchor': 'Why in India do we not have one on one political debate as in USA?",
'positive': 'Why cant we have a public debate between politicians in India like the one in US?',
'negative': 'Can people on Quora stop India Pakistan debate? We are sick and tired seeing this everyday in bulk?',
}
```
* Collection strategy: Taken from [embedding-training-data](https://huggingface.co/datasets/sentence-transformers/embedding-training-data), which states: "Duplicate question pairs from Quora with additional hard negatives (mined & denoised by cross-encoder)".
* Deduplified: No |