DunnBC22/vit-base-patch16-224-in21k_car_or_motorcycle

vit-base-patch16-224-in21kcaror_motorcycle

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset. It achieves the following results on the evaluation set:

• —Loss: 0.0301
• —Accuracy: 0.9938
• —F1: 0.9939
• —Recall: 0.9927
• —Precision: 0.9951

Model description

This is a binary classification model to distinguish between images of cars and images of motorcycles.

For more information on how it was created, check out the following link: https://github.com/DunnBC22/VisionAudioandMultimodalProjects/blob/main/Computer%20Vision/Image%20Classification/Binary%20Classification/Car%20or%20Motorcycle/CarorMotorcycle_ViT.ipynb

Intended uses & limitations

This model is intended to demonstrate my ability to solve a complex problem using technology.

Training and evaluation data

Dataset Source: https://www.kaggle.com/datasets/utkarshsaxenadn/car-vs-bike-classification-dataset

Sample Images From Dataset:

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• —learning_rate: 0.0002
• —trainbatchsize: 16
• —evalbatchsize: 8
• —seed: 42
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —num_epochs: 2

Training results

Framework versions

• —Transformers 4.22.2
• —Pytorch 1.12.1
• —Datasets 2.5.2
• —Tokenizers 0.12.1

License Notice

This model is a fine-tuned derivative of a pretrained model. Users must comply with the original model license.

Dataset Notice

This model was fine-tuned on third-party datasets which may have separate licenses or usage restrictions.