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nj1867/roof_classification_new_dataset_4_march

This model is a fine-tuned version of google/vit-base-patch32-384 on an unknown dataset. It achieves the following results on the evaluation set:

  • Train Loss: 0.1523
  • Validation Loss: 0.7698
  • Train Accuracy: 0.8375
  • 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': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 7440, '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': 0.0001}
  • training_precision: float32

Training results

Train Loss Validation Loss Train Accuracy Epoch
4.2343 4.0917 0.0437 0
3.7984 3.8481 0.1313 1
3.3245 3.5615 0.1062 2
2.8352 3.1190 0.3 3
2.3077 2.7024 0.4 4
1.8445 2.4423 0.4625 5
1.4533 2.0483 0.5813 6
1.1535 1.8203 0.65 7
0.9074 1.4581 0.725 8
0.7190 1.3655 0.7812 9
0.5880 1.2685 0.7875 10
0.4729 1.2005 0.7875 11
0.4004 0.9699 0.825 12
0.3349 0.9435 0.8313 13
0.2789 0.8993 0.8438 14
0.2179 0.8071 0.8625 15
0.2061 0.7852 0.8812 16
0.2124 0.7664 0.8625 17
0.1623 0.8276 0.8562 18
0.1523 0.7698 0.8375 19

Framework versions

  • Transformers 4.38.2
  • TensorFlow 2.13.1
  • Datasets 2.18.0
  • Tokenizers 0.15.2
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