B

Bert Gomotions

Developed by codewithdark
This is a BERT model fine-tuned on the GoEmotions dataset, specifically designed for multi-label sentiment classification tasks.
Downloads 69
Release Time : 1/29/2025

Model Overview

This model is based on the bert-base-uncased architecture, fine-tuned on the GoEmotions dataset, capable of predicting multiple emotion labels for input text.

Model Features

Multi-label sentiment classification
Capable of predicting multiple emotion labels in text simultaneously
Based on high-quality emotion dataset
Fine-tuned using the GoEmotions dataset, covering 28 emotion categories
Advantages of BERT architecture
Based on bert-base-uncased architecture with powerful text comprehension capabilities

Model Capabilities

Sentiment analysis
Multi-label text classification
Emotion probability prediction

Use Cases

Sentiment analysis
Social media sentiment monitoring
Analyze user sentiment tendencies in social media posts
Can identify multiple emotions such as happiness, anger, sadness, etc.
Customer feedback analysis
Analyze sentiment tendencies in customer reviews
Helps identify customer satisfaction and potential issues
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