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vit-base-patch16-224-food101-v1

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

  • Loss: 0.2359
  • Accuracy: 0.924

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: 0.0001
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 5

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.0682 0.99 31 0.3073 0.908
0.0425 1.98 62 0.2663 0.915
0.0262 2.98 93 0.2173 0.928
0.0446 4.0 125 0.2195 0.937
0.0642 4.96 155 0.2359 0.924

Framework versions

  • Transformers 4.28.0
  • Pytorch 2.0.0+cu118
  • Datasets 2.12.0
  • Tokenizers 0.13.3
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Dataset used to train ManishW/vit-base-patch16-224-food101-v1

Evaluation results