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--- |
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license: apache-2.0 |
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base_model: google/vit-base-patch16-224-in21k |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: adhisetiawan/mnist-test |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information Keras had access to. You should |
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probably proofread and complete it, then remove this comment. --> |
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# adhisetiawan/mnist-test |
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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: 0.7312 |
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- Validation Loss: 0.9257 |
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- Train Accuracy: 0.8 |
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- Epoch: 19 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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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': 1600, '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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| 2.2668 | 2.2081 | 0.4 | 0 | |
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| 2.1502 | 2.1140 | 0.6 | 1 | |
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| 2.0506 | 2.0350 | 0.65 | 2 | |
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| 1.9473 | 1.9239 | 0.7 | 3 | |
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| 1.8164 | 1.8355 | 0.7 | 4 | |
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| 1.7091 | 1.7534 | 0.75 | 5 | |
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| 1.6152 | 1.6683 | 0.8 | 6 | |
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| 1.5122 | 1.5825 | 0.8 | 7 | |
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| 1.4108 | 1.4897 | 0.8 | 8 | |
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| 1.3225 | 1.4149 | 0.8 | 9 | |
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| 1.2426 | 1.3135 | 0.8 | 10 | |
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| 1.1740 | 1.2704 | 0.8 | 11 | |
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| 1.0894 | 1.2213 | 0.85 | 12 | |
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| 1.0230 | 1.1424 | 0.8 | 13 | |
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| 0.9646 | 1.1171 | 0.85 | 14 | |
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| 0.9109 | 1.0744 | 0.8 | 15 | |
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| 0.8547 | 1.0376 | 0.85 | 16 | |
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| 0.8082 | 0.9892 | 0.8 | 17 | |
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| 0.7632 | 0.9604 | 0.85 | 18 | |
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| 0.7312 | 0.9257 | 0.8 | 19 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- TensorFlow 2.15.0 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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