tonyassi/celebrity-classifier

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Celebrity Classifier

Model description

This model classifies a face to a celebrity. It is trained on tonyassi/celebrity-1000 dataset and fine-tuned on google/vit-base-patch16-224-in21k.

Dataset description

tonyassi/celebrity-1000 Top 1000 celebrities. 18,184 images. 256x256. Square cropped to face.

How to use

from transformers import pipeline

# Initialize image classification pipeline
pipe = pipeline("image-classification", model="tonyassi/celebrity-classifier")

# Perform classification
result = pipe('image.png')

# Print results
print(result)

Training and evaluation data

It achieves the following results on the evaluation set:

• —Loss: 0.9089
• —Accuracy: 0.7982

Training hyperparameters

The following hyperparameters were used during training:

• —learning_rate: 5e-05
• —trainbatchsize: 16
• —evalbatchsize: 16
• —seed: 42
• —gradientaccumulationsteps: 4
• —totaltrainbatch_size: 64
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —lrschedulerwarmup_ratio: 0.1
• —num_epochs: 20

Framework versions

• —Transformers 4.35.2
• —Pytorch 2.1.0+cu121
• —Datasets 2.16.1
• —Tokenizers 0.15.0