---
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 unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.9213
- Train Accuracy: 0.7869
- Validation Loss: 0.8231
- Validation Accuracy: 0.7869
- Epoch: 9

## 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': 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}
- training_precision: float32

### Training results

| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 1.6070     | 0.3770         | 1.5670          | 0.3770              | 0     |
| 1.5299     | 0.6557         | 1.4816          | 0.6557              | 1     |
| 1.4347     | 0.6066         | 1.3838          | 0.6066              | 2     |
| 1.3535     | 0.6885         | 1.2822          | 0.6885              | 3     |
| 1.2562     | 0.6885         | 1.1766          | 0.6885              | 4     |
| 1.1829     | 0.7705         | 1.0732          | 0.7705              | 5     |
| 1.1037     | 0.8033         | 0.9889          | 0.8033              | 6     |
| 1.0444     | 0.8525         | 0.9204          | 0.8525              | 7     |
| 0.9640     | 0.8197         | 0.8722          | 0.8197              | 8     |
| 0.9213     | 0.7869         | 0.8231          | 0.7869              | 9     |


### Framework versions

- Transformers 4.35.1
- TensorFlow 2.14.0
- Datasets 2.14.6
- Tokenizers 0.14.1