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---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_keras_callback
model-index:
- name: aditnnda/felidae_klasifikasi
results: []
---
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# aditnnda/felidae_klasifikasi
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).
It achieves the following results on the evaluation set:
- Train Loss: 0.5782
- Train Accuracy: 0.8361
- Validation Loss: 0.5283
- Validation Accuracy: 0.8361
- Epoch: 19
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- 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}
- training_precision: float32
### Training results
| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 1.5945 | 0.5574 | 1.5482 | 0.5574 | 0 |
| 1.5213 | 0.7541 | 1.4625 | 0.7541 | 1 |
| 1.4429 | 0.7049 | 1.3574 | 0.7049 | 2 |
| 1.3399 | 0.7869 | 1.2390 | 0.7869 | 3 |
| 1.2264 | 0.6721 | 1.1328 | 0.6721 | 4 |
| 1.1660 | 0.7869 | 1.0287 | 0.7869 | 5 |
| 1.0825 | 0.7377 | 0.9690 | 0.7377 | 6 |
| 1.0005 | 0.8197 | 0.8654 | 0.8197 | 7 |
| 0.9121 | 0.7869 | 0.8303 | 0.7869 | 8 |
| 0.8530 | 0.8525 | 0.7590 | 0.8525 | 9 |
| 0.8602 | 0.8361 | 0.7169 | 0.8361 | 10 |
| 0.8420 | 0.8197 | 0.6993 | 0.8197 | 11 |
| 0.7772 | 0.8689 | 0.6347 | 0.8689 | 12 |
| 0.7447 | 0.8689 | 0.6023 | 0.8689 | 13 |
| 0.7253 | 0.8197 | 0.6458 | 0.8197 | 14 |
| 0.6994 | 0.8361 | 0.6045 | 0.8361 | 15 |
| 0.6761 | 0.8361 | 0.6030 | 0.8361 | 16 |
| 0.5814 | 0.8197 | 0.5523 | 0.8197 | 17 |
| 0.5939 | 0.8689 | 0.5456 | 0.8689 | 18 |
| 0.5782 | 0.8361 | 0.5283 | 0.8361 | 19 |
### Framework versions
- Transformers 4.35.1
- TensorFlow 2.14.0
- Datasets 2.14.6
- Tokenizers 0.14.1
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