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Videomae Base Finetuned Ucf101 Subset

Developed by cccchristopher
Video classification model fine-tuned on a subset of UCF101 based on the VideoMAE base model
Downloads 30
Release Time : 4/8/2025

Model Overview

This model is a fine-tuned version of the VideoMAE base model on a subset of the UCF101 dataset, primarily used for video classification tasks, achieving an accuracy of 81.94% on the evaluation set.

Model Features

Efficient Video Understanding
Based on the VideoMAE architecture, capable of efficiently processing and understanding video content
Excellent Fine-tuning Performance
Achieves 81.94% accuracy after fine-tuning on a subset of UCF101
Lightweight
Maintains relatively lightweight characteristics by fine-tuning based on the base model

Model Capabilities

Video Classification
Video Content Understanding
Action Recognition

Use Cases

Video Analysis
Action Recognition
Recognize human actions in videos
Achieves 81.94% accuracy on a subset of UCF101
Video Content Classification
Classify and label video content
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