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This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4588
  • Accuracy: 0.9014

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: 0.0002
  • train_batch_size: 64
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 15
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.2458 1.23 100 0.4519 0.8633
0.0937 2.47 200 0.4285 0.8754
0.0802 3.7 300 0.4683 0.8754
0.041 4.94 400 0.4088 0.9031
0.0277 6.17 500 0.3979 0.8945
0.0459 7.41 600 0.4253 0.9014
0.024 8.64 700 0.4680 0.8893
0.0267 9.88 800 0.4575 0.8945
0.019 11.11 900 0.4470 0.8893
0.0235 12.35 1000 0.4380 0.9066
0.0129 13.58 1100 0.4557 0.9048
0.0211 14.81 1200 0.4588 0.9014

Framework versions

  • Transformers 4.23.1
  • Pytorch 1.12.1+cu113
  • Datasets 2.6.1
  • Tokenizers 0.13.1
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Evaluation results