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image_classification

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: 1.5284
  • Accuracy: 0.5563

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
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 9

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 40 1.4223 0.525
No log 2.0 80 1.5923 0.4938
No log 3.0 120 1.4860 0.5563
No log 4.0 160 1.4983 0.5625
No log 5.0 200 1.5151 0.5938
No log 6.0 240 1.6818 0.5062
No log 7.0 280 1.6757 0.5125
No log 8.0 320 1.4647 0.5875
No log 9.0 360 1.4922 0.5875

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.17.0
  • Tokenizers 0.15.2
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