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Resnet 50 Fashion Mnist Quality Drift
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Resnet 50 Fashion Mnist Quality Drift

Developed by arize-ai
An image classification model fine-tuned on the fashion_mnist_quality_drift dataset based on ResNet-50 architecture, with 73% accuracy
Image Classification
Transformers
Open Source License:Apache-2.0#Fashion Image Classification#Quality Drift Detection#ResNet Fine-tuning
Downloads 44
Release Time : 8/1/2022

Model Overview

This model is a fine-tuned version of ResNet-50 on the Fashion MNIST quality drift dataset, primarily used for image classification tasks.

Model Features

High-Quality Image Classification
Achieves 73% accuracy on the Fashion MNIST quality drift dataset
Transfer Learning Optimization
Fine-tuned based on the pre-trained ResNet-50 model to enhance domain-specific performance
Stable Training Process
Utilizes linear learning rate scheduling and Adam optimizer, with training loss steadily decreasing

Model Capabilities

Fashion item image classification
Quality drift data recognition
Multi-category image recognition

Use Cases

E-commerce
Automatic Fashion Product Classification
Used in automatic product image classification systems for e-commerce platforms
73% accuracy
Quality Control
Visual Quality Inspection of Products
Detects quality variations and drifts in fashion products
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