metadata

license: mit
base_model: google/vit-base-patch16-224-in21k
tags:
  - generated_from_trainer
datasets:
  - food101
model-index:
  - name: Food-Image-Classification-VIT
    results: []

Food-Image-Classification-VIT

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:

eval_loss: 1.0611
eval_accuracy: 0.7274
eval_runtime: 411.0682
eval_samples_per_second: 61.425
eval_steps_per_second: 7.68
epoch: 0.15
step: 718

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: 0.0002
train_batch_size: 16
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 4

Framework versions

Transformers 4.33.1
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.13.3