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End of training

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  1. README.md +8 -8
  2. tf_model.h5 +2 -2
README.md CHANGED
@@ -15,8 +15,8 @@ probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Train Loss: 0.1251
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- - Validation Loss: 0.7054
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  - Train Accuracy: 0.5
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  - Epoch: 4
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@@ -37,18 +37,18 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 480, '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}
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  - training_precision: float32
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  ### Training results
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  | Train Loss | Validation Loss | Train Accuracy | Epoch |
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  |:----------:|:---------------:|:--------------:|:-----:|
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- | 0.6336 | 0.6789 | 0.5 | 0 |
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- | 0.4254 | 0.6683 | 0.5 | 1 |
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- | 0.2796 | 0.6516 | 0.5 | 2 |
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- | 0.1882 | 0.6500 | 0.5 | 3 |
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- | 0.1251 | 0.7054 | 0.5 | 4 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Train Loss: 0.2012
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+ - Validation Loss: 0.7821
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  - Train Accuracy: 0.5
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  - Epoch: 4
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 890, '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}
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  - training_precision: float32
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  ### Training results
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  | Train Loss | Validation Loss | Train Accuracy | Epoch |
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  |:----------:|:---------------:|:--------------:|:-----:|
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+ | 0.6786 | 0.7558 | 0.5 | 0 |
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+ | 0.5386 | 0.8320 | 0.0 | 1 |
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+ | 0.4181 | 0.9427 | 0.0 | 2 |
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+ | 0.2926 | 0.9919 | 0.0 | 3 |
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+ | 0.2012 | 0.7821 | 0.5 | 4 |
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  ### Framework versions
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