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metadata
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
  - image-classification
  - vision
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: food101-vit-base-patch16-224-in21k
    results: []

food101-vit-base-patch16-224-in21k

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: 0.3853
  • Accuracy: 0.908

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: 2e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 1337
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10.0

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.8312 1.0 9469 0.6893 0.8576
0.6401 2.0 18938 0.4571 0.8784
0.7021 3.0 28407 0.4081 0.8905
0.8365 4.0 37876 0.3962 0.8946
0.3562 5.0 47345 0.3932 0.8954
0.3552 6.0 56814 0.3876 0.9004
0.3962 7.0 66283 0.3854 0.9049
0.4242 8.0 75752 0.3865 0.9066
0.2785 9.0 85221 0.3867 0.9070
0.3446 10.0 94690 0.3853 0.908

Framework versions

  • Transformers 4.38.0
  • Pytorch 2.1.2+cu118
  • Datasets 2.19.1
  • Tokenizers 0.15.2