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Roberta Base Finetuned Sst2

Developed by Bhumika
A text classification model based on the RoBERTa architecture, fine-tuned on the SST-2 sentiment analysis task with an accuracy of 94.5%
Text Classification
Transformers
#Sentiment Analysis#High Accuracy#Text Classification
Downloads 53
Release Time : 3/2/2022

Model Overview

This model is a pre-trained model based on the RoBERTa architecture, fine-tuned on the SST-2 sentiment analysis task from the GLUE benchmark, specifically designed for sentence-level sentiment classification tasks.

Model Features

High Accuracy
Achieves 94.5% accuracy on the SST-2 sentiment analysis task
Based on RoBERTa Architecture
Utilizes an improved BERT architecture with stronger contextual understanding capabilities
Task-Specific Fine-Tuning
Optimized specifically for sentiment analysis tasks

Model Capabilities

Text Classification
Sentiment Analysis
Sentence-Level Semantic Understanding

Use Cases

Sentiment Analysis
Product Review Analysis
Analyze whether user reviews of a product are positive or negative
Accurately identifies the sentiment tendency of reviews
Social Media Monitoring
Monitor the sentiment tendency towards a brand or topic on social media
Real-time understanding of public sentiment changes
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