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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: 1.2805
  • Accuracy: 0.5188

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: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 40 1.7942 0.4062
No log 2.0 80 1.5663 0.3563
No log 3.0 120 1.4601 0.4813
No log 4.0 160 1.3494 0.4813
No log 5.0 200 1.3107 0.5062
No log 6.0 240 1.3054 0.475
No log 7.0 280 1.2423 0.575
No log 8.0 320 1.3189 0.5188
No log 9.0 360 1.2515 0.5062
No log 10.0 400 1.2279 0.5437

Framework versions

  • Transformers 4.33.2
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.5
  • Tokenizers 0.13.3
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