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image_classification

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: 1.5938
  • Accuracy: 0.911

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: 3

Training results

Training Loss Epoch Step Validation Loss Accuracy
2.7307 0.99 62 2.5306 0.833
1.8698 2.0 125 1.7637 0.903
1.5629 2.98 186 1.5856 0.915

Framework versions

  • Transformers 4.33.1
  • Pytorch 1.13.1+cu117
  • Datasets 2.14.5
  • Tokenizers 0.13.3
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Finetuned from

Dataset used to train kensvin/image_classification

Evaluation results