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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: aditnnda/felidae_klasifikasi |
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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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# aditnnda/felidae_klasifikasi |
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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: 0.9213 |
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- Train Accuracy: 0.7869 |
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- Validation Loss: 0.8231 |
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- Validation Accuracy: 0.7869 |
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- Epoch: 9 |
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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': 1820, '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 | Train Accuracy | Validation Loss | Validation Accuracy | Epoch | |
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|:----------:|:--------------:|:---------------:|:-------------------:|:-----:| |
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| 1.6070 | 0.3770 | 1.5670 | 0.3770 | 0 | |
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| 1.5299 | 0.6557 | 1.4816 | 0.6557 | 1 | |
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| 1.4347 | 0.6066 | 1.3838 | 0.6066 | 2 | |
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| 1.3535 | 0.6885 | 1.2822 | 0.6885 | 3 | |
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| 1.2562 | 0.6885 | 1.1766 | 0.6885 | 4 | |
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| 1.1829 | 0.7705 | 1.0732 | 0.7705 | 5 | |
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| 1.1037 | 0.8033 | 0.9889 | 0.8033 | 6 | |
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| 1.0444 | 0.8525 | 0.9204 | 0.8525 | 7 | |
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| 0.9640 | 0.8197 | 0.8722 | 0.8197 | 8 | |
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| 0.9213 | 0.7869 | 0.8231 | 0.7869 | 9 | |
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### Framework versions |
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- Transformers 4.35.1 |
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- TensorFlow 2.14.0 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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