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Swin Base Patch4 Window7 224 20epochs Finetuned Memes
S
Swin Base Patch4 Window7 224 20epochs Finetuned Memes
Developed by jayanta
基于Swin Transformer架构的图像分类模型，在memes数据集上微调20轮，验证集准确率达84.78%
Downloads 13
Release Time : 9/17/2022
Model Overview
这是一个基于Swin Transformer的视觉模型，专门针对网络表情包(memes)图像分类任务进行了优化。模型在图像分类任务上表现出色，特别适合处理社交媒体中的视觉内容。
Model Features
高性能图像分类
在memes数据集上达到84.78%的准确率，F1分数85.04%
Swin Transformer架构
采用先进的层次化窗口注意力机制，有效处理视觉信息
轻量级微调
仅需20轮训练即可达到优异性能，训练效率高
Model Capabilities
图像分类
视觉内容理解
表情包识别
Use Cases
社交媒体分析
表情包分类
自动识别和分类网络流行的表情包图像
准确率84.78%
内容审核
不当内容识别
识别可能包含不当内容的视觉素材
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