---
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