qid1
stringlengths 2
6
| qid2
stringlengths 2
6
|
---|---|
43345 | 43346 |
299890 | 4507 |
111905 | 25820 |
166095 | 166096 |
32422 | 70278 |
13756 | 178040 |
145013 | 29874 |
387498 | 387499 |
526973 | 526974 |
408687 | 85238 |
31337 | 31338 |
36668 | 48942 |
3663 | 7295 |
82964 | 82965 |
249343 | 266156 |
46473 | 89486 |
299045 | 299046 |
34261 | 34262 |
194480 | 81759 |
40583 | 59284 |
98201 | 98202 |
374007 | 374008 |
142328 | 55039 |
22064 | 2265 |
37318 | 6679 |
362986 | 407036 |
155914 | 240652 |
394269 | 394270 |
156452 | 77832 |
10794 | 10795 |
36473 | 72553 |
14333 | 7411 |
205626 | 45071 |
258694 | 92739 |
67593 | 9917 |
100806 | 111905 |
115459 | 14695 |
101795 | 8848 |
372 | 48722 |
174424 | 174425 |
120209 | 53296 |
35932 | 75917 |
2879 | 29028 |
294219 | 377233 |
177990 | 447073 |
146287 | 84086 |
229918 | 28370 |
133051 | 37237 |
166720 | 206380 |
295360 | 514716 |
113596 | 61549 |
232823 | 232824 |
119303 | 297678 |
191817 | 87182 |
19274 | 27786 |
129972 | 9849 |
114006 | 470644 |
188019 | 500415 |
163624 | 60504 |
46666 | 71673 |
18420 | 63168 |
16356 | 62105 |
150879 | 28412 |
10562 | 7708 |
134237 | 14927 |
259519 | 81027 |
145012 | 19254 |
131268 | 137961 |
516558 | 6674 |
53120 | 62741 |
60781 | 6929 |
259519 | 82022 |
137217 | 32423 |
21231 | 55083 |
140195 | 397112 |
106997 | 123836 |
324886 | 324887 |
149680 | 149681 |
185774 | 33833 |
111301 | 43784 |
20868 | 233674 |
43358 | 64170 |
136506 | 162098 |
42017 | 44023 |
105172 | 40999 |
123394 | 93259 |
6577 | 95350 |
161231 | 63179 |
367078 | 367079 |
227689 | 42397 |
133426 | 36806 |
19158 | 213440 |
441518 | 9522 |
109936 | 342423 |
105997 | 113162 |
103198 | 103199 |
19339 | 19340 |
55263 | 58038 |
252476 | 72439 |
94530 | 94531 |
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Dataset Card for Quora Duplicate Questions
This dataset contains the Quora Question Pairs dataset in a format that is easily used with the ParaphraseMiningEvaluator
evaluator in Sentence Transformers. The data was originally created by Quora for this Kaggle Competition.
Usage
from datasets import load_dataset
from sentence_transformers.SentenceTransformer import SentenceTransformer
from sentence_transformers.evaluation import ParaphraseMiningEvaluator
# Load the Quora Duplicates Mining dataset
questions_dataset = load_dataset("sentence-transformers/quora-duplicates-mining", "questions", split="dev")
duplicates_dataset = load_dataset("sentence-transformers/quora-duplicates-mining", "duplicates", split="dev")
# Create a mapping from qid to question & a list of duplicates (qid1, qid2)
qid_to_questions = dict(zip(questions_dataset["qid"], questions_dataset["question"]))
duplicates = list(zip(duplicates_dataset["qid1"], duplicates_dataset["qid2"]))
# Initialize the paraphrase mining evaluator
paraphrase_mining_evaluator = ParaphraseMiningEvaluator(qid_to_questions, duplicates, name="quora-duplicates-dev")
# Load a model to evaluate
model = SentenceTransformer("all-MiniLM-L6-v2")
results = paraphrase_mining_evaluator(model)
print(results)
{
'quora-duplicates-dev_average_precision': 0.5537837023752262,
'quora-duplicates-dev_f1': 0.542585123346778,
'quora-duplicates-dev_precision': 0.5112918195076678,
'quora-duplicates-dev_recall': 0.5779587350751861,
'quora-duplicates-dev_threshold': 0.8290803134441376,
}
Dataset Subsets
questions
subset
- Columns: "question", "qid"
- Column types:
str
,str
- Examples:
{ 'question': 'How do I prepare for TCS IT Wiz?', 'qid': '107646', }
- Collection strategy: A direct copy of the
quora-IR-dataset/duplicate-mining
as generated fromcreate_splits.py
. - Deduplified: No
duplicates
subset
- Columns: "qid1", "qid2"
- Column types:
str
,str
- Examples:
{ 'qid1': '43345', 'qid2': '43346', }
- Collection strategy: A direct copy of the
quora-IR-dataset/duplicate-mining
as generated fromcreate_splits.py
. - Deduplified: No
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