---
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: results
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# Dog Breeds Classification

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on 71 Dog Breeds-Image Data Set (Kaggle).
It achieves the following results on the evaluation set:
- Loss: 0.0763
- Accuracy: 0.9743

## Model description

This Model is a Transfer Learning-based model and trained with the size of 224x224 pixels. This model can predict dog with 71 classes of breeds.

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4379        | 1.0   | 249  | 0.2430          | 0.93     |
| 0.1998        | 2.0   | 498  | 0.1380          | 0.9514   |
| 0.0739        | 3.0   | 747  | 0.1008          | 0.9614   |
| 0.0135        | 4.0   | 996  | 0.0834          | 0.9671   |
| 0.0036        | 5.0   | 1245 | 0.0763          | 0.9743   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1