Description
STS17
An MTEB dataset
Massive Text Embedding Benchmark
Semeval-2017 task 1: Semantic textual similarity-multilingual and cross-lingual focused evaluation
Task category
t2t
Domains
News, Web, Written
Reference
https://alt.qcri.org/semeval2017/task1/
How to evaluate on this task
You can evaluate an embedding model on this dataset using the following code:
import mteb
task = mteb.get_tasks(["STS17"])
evaluator = mteb.MTEB(task)
model =… See the full description on the dataset page: https://huggingface.co/datasets/mteb/sts17-crosslingual-sts.
What can I do with this?
Tags
task_categories:sentence-similaritytask_ids:semantic-similarity-scoringannotations_creators:human-annotatedmultilinguality:multilinguallanguage:aralanguage:deulanguage:englanguage:fralanguage:italanguage:korlanguage:nldlanguage:spalanguage:turlicense:unknownsize_categories:10K<n<100Kformat:jsonmodality:textlibrary:datasetslibrary:dasklibrary:polars