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Fl Image Category Multi Label
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Fl Image Category Multi Label
Developed by StephenSKelley
This is an image classification model fine-tuned based on Google's ViT model, trained on the fl_image_category_ds dataset with an accuracy of 66.22%.
Downloads 17
Release Time : 2/22/2023
Model Overview
This model is an image classification model based on the Vision Transformer architecture, specifically fine-tuned for the fl_image_category_ds dataset.
Model Features
Efficient Image Classification
Based on the Vision Transformer architecture, capable of efficiently processing image inputs with 224x224 resolution.
Transfer Learning
Fine-tuned on the ImageNet-21k pre-trained model to enhance performance on specific tasks.
Model Capabilities
Image Classification
Visual Feature Extraction
Use Cases
Image Recognition
General Image Classification
Classify and recognize input images
Achieved 66.22% accuracy on the fl_image_category_ds dataset
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