jwt2706/google-vit-base-patch16-224-in21k-finetuned-food-classification-86M-v0.1

food-classification-86M-v0.1

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the food101 dataset. It achieves the following results on the evaluation set:

• —Loss: 1.6079
• —Accuracy: 0.892

Model description

Food image classification.

Intended uses & limitations

This was trained for fun and my own learning. But if you want to use it, go ahead.

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: 3

Training results

Framework versions

• —Transformers 4.38.2
• —Pytorch 2.1.0+cu121
• —Datasets 2.18.0
• —Tokenizers 0.15.2