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End of training

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  1. README.md +17 -12
  2. tf_model.h5 +2 -2
README.md CHANGED
@@ -15,10 +15,10 @@ 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: 1.5656
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- - Validation Loss: 1.7181
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- - Train Accuracy: 0.8
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- - Epoch: 4
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  ## Model description
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@@ -37,23 +37,28 @@ 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': 840, '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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- | 2.2701 | 2.2679 | 0.1 | 0 |
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- | 2.1066 | 2.1493 | 0.4 | 1 |
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- | 1.9323 | 2.0279 | 0.6 | 2 |
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- | 1.7463 | 1.8713 | 0.6667 | 3 |
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- | 1.5656 | 1.7181 | 0.8 | 4 |
 
 
 
 
 
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  ### Framework versions
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  - Transformers 4.31.0
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- - TensorFlow 2.13.0
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- - Datasets 2.14.3
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  - Tokenizers 0.13.3
 
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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: 0.9353
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+ - Validation Loss: 1.0343
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+ - Train Accuracy: 0.8667
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+ - Epoch: 9
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  ## Model description
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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': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 1680, '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}
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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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+ | 2.2697 | 2.1984 | 0.4667 | 0 |
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+ | 2.1245 | 2.0728 | 0.6 | 1 |
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+ | 1.9780 | 1.9057 | 0.8 | 2 |
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+ | 1.8135 | 1.7702 | 0.8667 | 3 |
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+ | 1.6516 | 1.6121 | 0.8667 | 4 |
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+ | 1.4854 | 1.4733 | 0.8667 | 5 |
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+ | 1.3306 | 1.3294 | 0.8667 | 6 |
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+ | 1.1829 | 1.2269 | 0.8333 | 7 |
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+ | 1.0596 | 1.1176 | 0.8667 | 8 |
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+ | 0.9353 | 1.0343 | 0.8667 | 9 |
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  ### Framework versions
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  - Transformers 4.31.0
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+ - TensorFlow 2.12.0
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+ - Datasets 2.14.4
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  - Tokenizers 0.13.3
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