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Bert Base Uncased Finetuned Sst2
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Bert Base Uncased Finetuned Sst2

Developed by doyoungkim
A sentiment analysis model fine-tuned on the GLUE dataset SST-2 task based on the BERT base model
Text Classification
Transformers
Open Source License:Apache-2.0#Sentiment Analysis#High Accuracy#GLUE Fine-tuning
Downloads 36
Release Time : 3/2/2022

Model Overview

This model is a fine-tuned version of bert-base-uncased on the GLUE dataset SST-2 (Stanford Sentiment Treebank) task, primarily used for sentence-level sentiment classification tasks.

Model Features

High Accuracy
Achieves 92.66% accuracy on the SST-2 test set
Based on BERT Architecture
Utilizes BERT's powerful contextual understanding capabilities for sentiment analysis
Fine-tuning Optimization
Precisely fine-tuned for specific tasks to enhance performance

Model Capabilities

Sentence-level sentiment classification
Text sentiment analysis
Binary classification task processing

Use Cases

Sentiment Analysis
Product Review Sentiment Analysis
Analyze whether user reviews of products are positive or negative
Accuracy 92.66%
Social Media Sentiment Monitoring
Identify emotional tendencies in social media posts
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