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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 [Felidae Dataset](https://huggingface.co./datasets/aditnnda/Felidae). |
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It achieves the following results on the evaluation set: |
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- Train Loss: 0.5782 |
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- Train Accuracy: 0.8361 |
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- Validation Loss: 0.5283 |
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- Validation Accuracy: 0.8361 |
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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': 3640, '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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| 1.5945 | 0.5574 | 1.5482 | 0.5574 | 0 | |
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| 1.5213 | 0.7541 | 1.4625 | 0.7541 | 1 | |
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| 1.4429 | 0.7049 | 1.3574 | 0.7049 | 2 | |
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| 1.3399 | 0.7869 | 1.2390 | 0.7869 | 3 | |
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| 1.2264 | 0.6721 | 1.1328 | 0.6721 | 4 | |
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| 1.1660 | 0.7869 | 1.0287 | 0.7869 | 5 | |
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| 1.0825 | 0.7377 | 0.9690 | 0.7377 | 6 | |
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| 1.0005 | 0.8197 | 0.8654 | 0.8197 | 7 | |
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| 0.9121 | 0.7869 | 0.8303 | 0.7869 | 8 | |
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| 0.8530 | 0.8525 | 0.7590 | 0.8525 | 9 | |
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| 0.8602 | 0.8361 | 0.7169 | 0.8361 | 10 | |
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| 0.8420 | 0.8197 | 0.6993 | 0.8197 | 11 | |
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| 0.7772 | 0.8689 | 0.6347 | 0.8689 | 12 | |
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| 0.7447 | 0.8689 | 0.6023 | 0.8689 | 13 | |
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| 0.7253 | 0.8197 | 0.6458 | 0.8197 | 14 | |
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| 0.6994 | 0.8361 | 0.6045 | 0.8361 | 15 | |
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| 0.6761 | 0.8361 | 0.6030 | 0.8361 | 16 | |
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| 0.5814 | 0.8197 | 0.5523 | 0.8197 | 17 | |
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| 0.5939 | 0.8689 | 0.5456 | 0.8689 | 18 | |
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| 0.5782 | 0.8361 | 0.5283 | 0.8361 | 19 | |
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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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