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VIT-food101-image-classifier

This model was trained from scratch on the food101 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5661
  • Accuracy: 0.933

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
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 64
  • 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
1.1716 0.99 62 1.2149 0.896
0.7758 1.99 124 0.8727 0.906
0.6269 2.99 186 0.6833 0.928
0.5495 3.99 248 0.6041 0.931
0.4973 4.99 310 0.5661 0.933

Framework versions

  • Transformers 4.25.1
  • Pytorch 1.13.1+cu116
  • Datasets 2.8.0
  • Tokenizers 0.13.2
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Dataset used to train StatsGary/VIT-food101-image-classifier

Evaluation results