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CynthiaCR/emotions_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: 1.3846
  • Validation Loss: 1.6122
  • Train Accuracy: 0.2687
  • Epoch: 19

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': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 0.0003, 'decay_steps': 12800, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, '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
2.0363 2.0960 0.1 0
2.0822 2.1254 0.0813 1
1.9916 1.9392 0.2062 2
1.9223 1.8385 0.1688 3
1.8213 1.7294 0.2313 4
1.6940 1.6953 0.2625 5
1.7153 1.6009 0.3187 6
1.5788 1.6385 0.275 7
1.5359 1.5635 0.3438 8
1.4768 1.6180 0.325 9
1.4746 1.6063 0.3125 10
1.5163 1.5641 0.3625 11
1.4692 1.5722 0.3063 12
1.4468 1.7363 0.35 13
1.7116 1.7531 0.2687 14
1.5334 1.5908 0.2562 15
1.4988 1.5169 0.3312 16
1.4605 1.5041 0.2812 17
1.3545 1.4824 0.3187 18
1.3846 1.6122 0.2687 19

Framework versions

  • Transformers 4.29.2
  • TensorFlow 2.12.0
  • Datasets 2.12.0
  • Tokenizers 0.13.3
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