Kengi/food_classifier

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

  • Train Loss: 0.3700
  • Validation Loss: 0.3118
  • Train Accuracy: 0.924
  • Epoch: 4

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:

  • optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 20000, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
  • training_precision: float32

Training results

Train Loss Validation Loss Train Accuracy Epoch
2.7522 1.5990 0.833 0
1.2011 0.7689 0.889 1
0.6871 0.5054 0.907 2
0.4777 0.3800 0.91 3
0.3700 0.3118 0.924 4

Framework versions

  • Transformers 4.34.1
  • TensorFlow 2.14.0
  • Datasets 2.14.6
  • Tokenizers 0.14.1
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