D

Debertav2 Base Uncased

Developed by mlcorelib
BERT is a pre-trained language model based on the Transformer architecture, trained on English corpus through masked language modeling and next sentence prediction tasks.
Downloads 21
Release Time : 3/2/2022

Model Overview

This model is a Transformer pre-trained on English corpus using the Masked Language Modeling (MLM) objective, suitable for various natural language processing tasks.

Model Features

Bidirectional Context Understanding
Through the masked language modeling task, the model learns bidirectional contextual representations of words.
Multi-task Pre-training
Pre-trained simultaneously using both masked language modeling and next sentence prediction tasks.
Case Insensitive
The model is case-insensitive to input text, uniformly converting it to lowercase.

Model Capabilities

Text Feature Extraction
Sentence Relationship Prediction
Masked Word Prediction
Downstream Task Fine-tuning

Use Cases

Text Classification
Sentiment Analysis
Classify text into positive/negative sentiment
Achieved 93.5 accuracy on the SST-2 dataset
Question Answering
Reading Comprehension
Answer questions based on given text
Named Entity Recognition
Entity Extraction
Identify entities such as person names and locations from text
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