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Distilbert Base Uncased Finetuned Emotion
基于DistilBERT的轻量级文本情感分类模型，在emotion数据集上微调，准确率达92.4%
Downloads 17
Release Time : 3/2/2022
Model Overview
该模型是DistilBERT的微调版本，专门用于文本情感分类任务，能够识别六种基本情绪（愤怒、恐惧、快乐、悲伤、惊讶、中性）
Model Features
高效轻量
采用蒸馏技术压缩的BERT架构，在保持性能的同时减少40%参数量
高准确率
在emotion测试集上达到92.4%的准确率和0.924的F1分数
快速推理
相比原始BERT模型，推理速度提升约60%
Model Capabilities
文本情感分类
情绪识别
短文本分析
Use Cases
社交媒体分析
用户评论情绪监测
自动分析社交媒体评论中的用户情绪倾向
可实时识别92%以上的情绪标签
客户服务
客服对话分析
识别客户对话中的情绪状态以优化服务策略
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