BERT_Tweet_Sentiment_100k_2eps Open-source Tweet Sentiment Analysis Model - Accurately Classify the Sentiments of Tweets

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BERT Tweet Sentiment 100k 2eps

Developed by joe5campbell

A sentiment analysis model fine-tuned based on bert-base-uncased for tweet sentiment classification

Text Classification

Transformers

Open Source License:Apache-2.0 #Tweet sentiment analysis #BERT fine-tuning #High accuracy

Downloads 14

Release Time : 3/2/2022

Model Overview

This model is a variant based on the BERT architecture, specifically fine-tuned for tweet sentiment analysis tasks. It can classify tweets into different sentiment categories.

Model Features

Tweet sentiment analysis

Sentiment classification capability optimized specifically for tweet content

Efficient fine-tuning

Efficient fine-tuning based on pre-trained BERT model, requiring only a small amount of training data

High accuracy

Achieves 83.15% accuracy on the validation set

Model Capabilities

Text classification

Sentiment analysis

Tweet content understanding

Use Cases

Social media analysis

Tweet sentiment monitoring

Real-time analysis of sentiment tendencies in tweets on social media

Accurately identifies positive, negative, and neutral sentiments

Brand reputation management

Monitor public emotional reactions to brands or products

Helps brands stay informed about public sentiment changes in a timely manner

Train Loss	Train Accuracy	Validation Loss	Validation Accuracy	Epoch
0.3330	0.8562	0.3847	0.8415	0
0.1259	0.9542	0.6133	0.8315	1

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BERT Tweet Sentiment 100k 2eps

Model Overview

Model Features

Model Capabilities

Use Cases

🚀 BERT_Tweet_Sentiment_100k_2eps

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