Sentiment_trained_42 Open Source Twitter Sentiment Analysis Model - Freely Analyze Sentiment Tendencies of Twitter Data

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Sentiment Trained 42

Developed by aXhyra

A Twitter sentiment analysis model fine-tuned on distilbert-base-uncased, trained on the tweet_eval dataset

Text Classification

Transformers

Open Source License:Apache-2.0 #Tweet sentiment analysis #Lightweight BERT #High F1 score

Downloads 18

Release Time : 3/2/2022

Model Overview

This model is specifically designed for analyzing sentiment tendencies in Twitter text, performing well in sentiment classification tasks after fine-tuning

Model Features

Efficient and lightweight

Based on DistilBERT architecture, reducing model size while maintaining performance

Twitter text optimization

Specially optimized for training on short Twitter texts

Sentiment analysis

Accurately identifies sentiment tendencies in Twitter text

Model Capabilities

Text classification

Sentiment analysis

Short text processing

Use Cases

Social media analysis

Brand sentiment monitoring

Analyze user sentiment tendencies towards brands or products on Twitter

F1 score 0.7132

Public sentiment monitoring

Monitor changes in public sentiment regarding trending topics

Training Loss	Epoch	Step	Validation Loss	F1
0.6405	1.0	11404	0.6631	0.7046
0.5998	2.0	22808	0.8429	0.7102
0.5118	3.0	34212	1.0906	0.7155
0.3745	4.0	45616	1.3194	0.7132

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Sentiment Trained 42

Model Overview

Model Features

Model Capabilities

Use Cases

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