ResNet-50-4-32 Open-Source Image Classification Model - Fine-tuned based on microsoft/resnet-50, with an evaluation accuracy of 64.1%

Resnet 50 4 32

Developed by Celal11

An image classification model fine-tuned based on microsoft/resnet-50, achieving an accuracy of 64.1% on the evaluation set

Image Classification

Transformers

Open Source License:Apache-2.0 #Image Classification #ResNet Architecture #Medium Accuracy

Downloads 26

Release Time : 2/11/2023

Model Overview

This model is a fine-tuned version based on the ResNet-50 architecture, primarily used for image classification tasks. Trained on specific datasets, it enhances classification performance in target domains.

Model Features

Efficient Image Classification

Based on the ResNet-50 architecture, providing efficient image classification capabilities

Fine-Tuning Optimization

Fine-tuned on specific datasets to improve classification accuracy in target domains

Medium-Scale Model

Balances model size and performance, suitable for various application scenarios

Model Capabilities

Image Classification

Feature Extraction

Use Cases

Computer Vision

Object Recognition

Identify specific objects or scenes in images

Achieved 64.1% accuracy on the evaluation set

Image Classification System

Build an automated image classification system

Property	Details
Model Type	Fine - tuned version of microsoft/resnet-50
Training Data	image_folder dataset
Metrics	Accuracy: 0.6409863471719142

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.3833	1.0	224	1.2683	0.5134
1.2404	2.0	448	1.1342	0.5659
1.1492	3.0	672	1.0359	0.6087
1.1433	4.0	896	0.9705	0.6410

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Resnet 50 4 32

Model Overview

Model Features

Model Capabilities

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🚀 resnet-50-4-32

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Model Information

Training Procedure

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