---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_keras_callback
model-index:
- name: Alph0nse/vit-base-patch16-224-in21k_v2_breed_cls_v2
  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. -->

# Alph0nse/vit-base-patch16-224-in21k_v2_breed_cls_v2

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: 0.8190
- Train Accuracy: 0.9248
- Train Top-3-accuracy: 0.9777
- Validation Loss: 0.9820
- Validation Accuracy: 0.9308
- Validation Top-3-accuracy: 0.9799
- Epoch: 4

## 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': 560, '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 | Train Top-3-accuracy | Validation Loss | Validation Accuracy | Validation Top-3-accuracy | Epoch |
|:----------:|:--------------:|:--------------------:|:---------------:|:-------------------:|:-------------------------:|:-----:|
| 2.4175     | 0.5263         | 0.7190               | 1.9955          | 0.7702              | 0.9039                    | 0     |
| 1.5487     | 0.8270         | 0.9344               | 1.4502          | 0.8624              | 0.9519                    | 1     |
| 1.1223     | 0.8829         | 0.9609               | 1.1583          | 0.8982              | 0.9674                    | 2     |
| 0.9127     | 0.9094         | 0.9718               | 1.0461          | 0.9181              | 0.9753                    | 3     |
| 0.8190     | 0.9248         | 0.9777               | 0.9820          | 0.9308              | 0.9799                    | 4     |


### Framework versions

- Transformers 4.38.2
- TensorFlow 2.15.0
- Datasets 2.18.0
- Tokenizers 0.15.2