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BERT Tweet Sentiment 50k 5eps
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BERT Tweet Sentiment 50k 5eps

Developed by joe5campbell
A BERT-base-uncased fine-tuned Twitter sentiment analysis model trained on 50k data for 5 epochs, achieving 82.91% validation accuracy
Text Classification
Transformers
Open Source License:Apache-2.0#Twitter Sentiment Analysis#BERT Fine-tuning#High Accuracy
Downloads 14
Release Time : 3/2/2022

Model Overview

This model is specifically designed for sentiment analysis of Twitter texts, capable of determining the emotional tendency expressed in the text. It is fine-tuned and optimized based on the BERT architecture for a specific dataset.

Model Features

High Accuracy
Achieves 82.91% accuracy on the validation set, with training accuracy as high as 99.13%
BERT Fine-tuning
Fine-tuned based on the powerful BERT-base-uncased model, inheriting BERT's excellent text understanding capabilities
Lightweight Training
Only requires 5 epochs of training to achieve good results, with high training efficiency

Model Capabilities

Text Sentiment Analysis
Twitter Content Understanding
Emotional Tendency Judgment

Use Cases

Social Media Analysis
Twitter Public Opinion Monitoring
Analyze the emotional tendency of tweets on specific topics
Can monitor public sentiment changes in real-time
Brand Reputation Management
Evaluate users' emotional feedback on brands or products
Helps brands promptly identify negative reviews
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