rankcse-listmle-bert-base-uncased Open-source Model - Boost Sentence Similarity Task Evaluation and Training

Rankcse Listmle Bert Base Uncased

Developed by perceptiveshawty

This dataset is used for training and evaluating the SimCSE (Simple Contrastive Learning of Sentence Embeddings) model, supporting sentence similarity tasks.

Text Embedding

Transformers

EnglishOpen Source License:Apache-2.0 #Sentence Similarity Calculation #Unsupervised Contrastive Learning #English Semantic Understanding

Downloads 20

Release Time : 7/25/2023

Model Overview

This dataset is specifically designed for the SimCSE model, used for training and evaluating contrastive learning methods for sentence embeddings, primarily applied to sentence similarity calculation tasks.

Model Features

Contrastive Learning

Uses contrastive learning methods to train sentence embeddings, improving performance in sentence similarity tasks.

High-Quality Dataset

Provides carefully selected and annotated sentence pair datasets suitable for training and evaluation.

Model Capabilities

Sentence similarity calculation

Sentence embedding generation

Use Cases

Natural Language Processing

Semantic Search

Utilizes sentence embeddings to enhance the semantic relevance of search results.

Improves search accuracy and user experience.

Text Clustering

Performs clustering analysis on text based on sentence similarity.

Helps discover themes and patterns in text.

Property	Details
Library Name	transformers
Pipeline Tag	sentence - similarity
Training Datasets	princeton - nlp/datasets - for - simcse
License	Apache 2.0

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Rankcse Listmle Bert Base Uncased

Model Overview

Model Features

Model Capabilities

Use Cases

🚀 Sentence Similarity with Transformers

🚀 Quick Start

📄 License