ROBERTA_Tweet_Sentiment_50k_2eps Open Source Model - Accurately Conduct Sentiment Classification Analysis of Tweets

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ROBERTA Tweet Sentiment 50k 2eps

Developed by joe5campbell

RoBERTa sentiment analysis model fine-tuned on Twitter data for tweet sentiment classification

Text Classification

Transformers

#Twitter Sentiment Analysis #RoBERTa Fine-tuning #High Accuracy

Downloads 16

Release Time : 3/2/2022

Model Overview

This model is a sentiment analysis model fine-tuned on a 50k-scale dataset based on cardiffnlp/twitter-roberta-base-sentiment, primarily used for tweet sentiment classification tasks

Model Features

Twitter Data Optimization

Specifically optimized for Twitter text, better understanding the linguistic features of social media

Efficient Fine-tuning

Fine-tuned on a 50k-scale dataset, balancing training efficiency and model performance

Model Capabilities

Tweet Sentiment Classification

Social Media Text Analysis

Use Cases

Social Media Analysis

Brand Sentiment Monitoring

Analyze user sentiment trends towards brands on Twitter

Achieves 76.52% validation accuracy

Event Sentiment Analysis

Track public sentiment changes during trending events

Train Loss	Train Accuracy	Validation Loss	Validation Accuracy	Epoch
0.5213	0.7298	0.4817	0.7715	0
0.3553	0.8504	0.5272	0.7652	1

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ROBERTA Tweet Sentiment 50k 2eps

Model Overview

Model Features

Model Capabilities

Use Cases

🚀 ROBERTA_Tweet_Sentiment_50k_2eps

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Model description

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🔧 Technical Details

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