Prot10/vit-base-patch16-224-for-pre_evaluation

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vit-base-patch16-224-for-pre_evaluation

This model is a fine-tuned version of google/vit-base-patch16-224 on the None dataset. It achieves the following results on the evaluation set:

• —Loss: 1.6048
• —Accuracy: 0.3929

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: 32
• —evalbatchsize: 32
• —seed: 42
• —gradientaccumulationsteps: 4
• —totaltrainbatch_size: 128
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —lrschedulerwarmup_ratio: 0.1
• —num_epochs: 30

Training results

Framework versions

• —Transformers 4.33.1
• —Pytorch 2.0.1+cu118
• —Datasets 2.14.5
• —Tokenizers 0.13.3