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vit-base-patch16-224-in21k-finetuned-lora-food101

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: 0.1408
  • Accuracy: 0.964

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: 0.005
  • train_batch_size: 128
  • eval_batch_size: 128
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 512
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 5
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 9 0.5739 0.874
2.1968 2.0 18 0.2064 0.944
0.3323 3.0 27 0.1521 0.96
0.2087 4.0 36 0.1408 0.964
0.1678 5.0 45 0.1352 0.962

Framework versions

  • Transformers 4.26.1
  • Pytorch 1.13.1+cu117
  • Datasets 2.9.0
  • Tokenizers 0.12.1
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Dataset used to train RubyZhi/vit-base-patch16-224-in21k-finetuned-lora-food101

Evaluation results