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Bert Base Uncased Goemotions Original Finetuned
B
Bert Base Uncased Goemotions Original Finetuned
Developed by justin871030
A sentiment classification model based on the BERT pre-trained model, specifically designed to identify emotional categories in text, supporting multiple sentiment label classifications.
Downloads 78
Release Time : 3/2/2022
Model Overview
This model is built on a case-insensitive BERT pre-trained model with an added linear output layer. During training, label smoothing techniques and weighted loss functions were employed to optimize the model's ability to handle difficult samples.
Model Features
Emoji Support
Added common emojis and symbols to the tokenizer's special vocabulary, enhancing the model's ability to process text containing emojis.
Label Smoothing Technique
Adopted label smoothing during training to improve the model's generalization ability.
Weighted Loss Function
Used weighted loss and focal loss functions to optimize training on difficult samples, improving the model's ability to handle imbalanced data.
Model Capabilities
Text Sentiment Classification
Multi-label Sentiment Recognition
Emoji Understanding
Use Cases
Social Media Analysis
User Comment Sentiment Analysis
Analyze the sentiment tendencies of user comments on social media.
Can identify multiple emotional categories, such as gratitude, anger, happiness, etc.
Customer Service
Customer Feedback Classification
Automatically classify the sentiment tendencies in customer feedback.
Helps quickly identify negative feedback that requires priority handling.
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