SentEval: An Evaluation Toolkit for Universal Sentence Representations

03/14/2018
by   Alexis Conneau, et al.
0

We introduce SentEval, a toolkit for evaluating the quality of universal sentence representations. SentEval encompasses a variety of tasks, including binary and multi-class classification, natural language inference and sentence similarity. The set of tasks was selected based on what appears to be the community consensus regarding the appropriate evaluations for universal sentence representations. The toolkit comes with scripts to download and preprocess datasets, and an easy interface to evaluate sentence encoders. The aim is to provide a fairer, less cumbersome and more centralized way for evaluating sentence representations.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
02/20/2018

SufiSent - Universal Sentence Representations Using Suffix Encodings

Computing universal distributed representations of sentences is a fundam...
research
05/18/2018

Metric for Automatic Machine Translation Evaluation based on Universal Sentence Representations

Sentence representations can capture a wide range of information that ca...
research
03/05/2022

Just Rank: Rethinking Evaluation with Word and Sentence Similarities

Word and sentence embeddings are useful feature representations in natur...
research
04/03/2019

The Effect of Downstream Classification Tasks for Evaluating Sentence Embeddings

One popular method for quantitatively evaluating the performance of sent...
research
09/30/2019

The Universal Decompositional Semantics Dataset and Decomp Toolkit

We present the Universal Decompositional Semantics (UDS) dataset (v1.0),...
research
05/24/2023

Ranger: A Toolkit for Effect-Size Based Multi-Task Evaluation

In this paper, we introduce Ranger - a toolkit to facilitate the easy us...
research
04/19/2022

ELEVATER: A Benchmark and Toolkit for Evaluating Language-Augmented Visual Models

Learning visual representations from natural language supervision has re...

Please sign up or login with your details

Forgot password? Click here to reset