Weather - base Open - source Image Classification Model - High - precision and Free Deployment, Accurately Identify Image Content

Weather Base

Developed by ChasingMercer

This model is a fine-tuned image classification model based on microsoft/beit-base-patch16-224-pt22k-ft22k, achieving an accuracy of 93.59% on the evaluation set.

Image Classification

Transformers

Open Source License:Apache-2.0 #High-precision image classification #Weather recognition #BEIT fine-tuning

Downloads 21

Release Time : 3/6/2023

Model Overview

A fine-tuned model for image classification tasks, particularly suitable for weather-related image classification.

Model Features

High accuracy

Achieves a classification accuracy of 93.59% on the evaluation set.

Based on BEiT architecture

Utilizes the advanced BEiT (Base version) vision Transformer architecture.

Fine-tuning optimization

Fine-tuned on specific image datasets for optimal performance.

Model Capabilities

Image classification

Weather image recognition

Use Cases

Weather monitoring

Weather condition classification

Automatically identifies weather conditions in images (e.g., sunny, rainy, cloudy, etc.)

Accuracy 93.59%

Environmental monitoring

Meteorological observation assistance

Assists weather observation stations in automatic weather condition recording

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.3368	1.0	171	0.2780	0.9009
0.2129	2.0	342	0.2333	0.9300
0.1827	3.0	513	0.2440	0.9213
0.1475	4.0	684	0.2306	0.9315
0.1284	5.0	855	0.2192	0.9359
0.0526	6.0	1026	0.2184	0.9359

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Weather Base

Model Overview

Model Features

Model Capabilities

Use Cases

🚀 weather-base

🚀 Quick Start

📚 Documentation

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

📄 License