---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vit-base-patch16-224-in21k-shiba-inu-detector
  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. -->

# vit-base-patch16-224-in21k-shiba-inu-detector

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on dataset with 4 dog types including Shiba Inu.

It achieves the following results on the evaluation set:
- Loss: 0.6511
- Accuracy: 1.0

## 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:
- learning_rate: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.94  | 4    | 1.3875          | 0.1667   |
| No log        | 1.94  | 8    | 1.2712          | 0.7833   |
| 1.4176        | 2.94  | 12   | 1.0972          | 0.9      |
| 1.4176        | 3.94  | 16   | 0.9365          | 0.95     |
| 1.0144        | 4.94  | 20   | 0.7836          | 0.9833   |
| 1.0144        | 5.94  | 24   | 0.6511          | 1.0      |
| 1.0144        | 6.94  | 28   | 0.5329          | 1.0      |
| 0.6329        | 7.94  | 32   | 0.4403          | 1.0      |
| 0.6329        | 8.94  | 36   | 0.3777          | 1.0      |
| 0.3821        | 9.94  | 40   | 0.3273          | 1.0      |
| 0.3821        | 10.94 | 44   | 0.2886          | 1.0      |
| 0.3821        | 11.94 | 48   | 0.2622          | 1.0      |
| 0.2655        | 12.94 | 52   | 0.2397          | 1.0      |
| 0.2655        | 13.94 | 56   | 0.2250          | 1.0      |
| 0.202         | 14.94 | 60   | 0.2152          | 1.0      |
| 0.202         | 15.94 | 64   | 0.2074          | 1.0      |
| 0.202         | 16.94 | 68   | 0.2003          | 1.0      |
| 0.1785        | 17.94 | 72   | 0.1960          | 1.0      |
| 0.1785        | 18.94 | 76   | 0.1936          | 1.0      |
| 0.1618        | 19.94 | 80   | 0.1930          | 1.0      |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.11.0+cu113
- Datasets 2.0.0
- Tokenizers 0.11.6