jayanta/vit-base-patch16-224-in21k-face-recognition

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vit-base-patch16-224-in21k-face-recognition

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: 0.0015
• —Accuracy: 1.0000

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• —learning_rate: 0.00012
• —trainbatchsize: 64
• —evalbatchsize: 64
• —seed: 42
• —gradientaccumulationsteps: 4
• —totaltrainbatch_size: 256
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —lrschedulerwarmup_ratio: 0.1
• —num_epochs: 8

Training results

Framework versions

• —Transformers 4.30.2
• —Pytorch 1.13.1+cu117
• —Datasets 2.13.2
• —Tokenizers 0.11.0