annazhong/vit-base-patch16-224-finetuned-foveated-features-v2

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vit-base-patch16-224-finetuned-foveated-features-v2

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

• —Loss: 1.9396
• —Accuracy: 0.24

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: 5e-05
• —trainbatchsize: 150
• —evalbatchsize: 150
• —seed: 42
• —gradientaccumulationsteps: 4
• —totaltrainbatch_size: 600
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —lrschedulerwarmup_ratio: 0.1
• —num_epochs: 3

Training results

Framework versions

• —Transformers 4.31.0
• —Pytorch 2.0.1+cu118
• —Datasets 2.14.0
• —Tokenizers 0.13.3