ModelVersion01 Open-Source Image Classification Model - Free to Use, Achieving 72.24% Accuracy in Image Classification

Modelversion01

Developed by sudo-s

This model is a fine-tuned image classification model based on google/vit-base-patch16-224-in21k on the sudo-s/herbier_mesuem1 dataset, achieving an accuracy of 72.24%.

Image Classification

Transformers

Open Source License:Apache-2.0 #Plant Image Classification #ViT Fine-tuned Model #Museum Specimen Identification

Downloads 30

Release Time : 6/19/2022

Model Overview

This is an image classification model based on the Vision Transformer architecture, primarily used for classifying images in specific datasets.

Model Features

Based on ViT Architecture

Utilizes the Vision Transformer architecture, offering powerful image feature extraction capabilities.

Efficient Fine-tuning

Efficiently fine-tuned on a specific dataset, achieving an accuracy of 72.24%.

Lightweight Training

Requires only 1 training epoch to achieve good results.

Model Capabilities

Image Classification

Feature Extraction

Use Cases

Botany

Plant Specimen Classification

Can be used to classify and identify plant specimen images.

Achieved an accuracy of 72.24% on the evaluation set.

Museum Collection Management

Collection Image Classification

Can be used for automatic classification and management of museum collection images.

Training Loss	Epoch	Step	Validation Loss	Accuracy
3.1304	0.16	100	3.1546	0.3254
2.6514	0.31	200	2.5058	0.4854
2.0636	0.47	300	2.0647	0.5771
1.7812	0.63	400	1.7536	0.6423
1.5857	0.78	500	1.5272	0.6974
1.3055	0.94	600	1.3888	0.7224

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Modelversion01

Model Overview

Model Features

Model Capabilities

Use Cases

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Model description

Intended uses & limitations

Training and evaluation data

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