---
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vit-base-patch16-224-mascotas
  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-mascotas

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5660
- 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: 5.5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 40

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6192        | 0.99  | 52   | 0.5660          | 1.0      |
| 0.2794        | 2.0   | 105  | 0.1524          | 1.0      |
| 0.2006        | 2.99  | 157  | 0.1143          | 0.9474   |
| 0.2106        | 4.0   | 210  | 0.0506          | 1.0      |
| 0.1077        | 4.99  | 262  | 0.0339          | 1.0      |
| 0.1379        | 6.0   | 315  | 0.1391          | 0.9474   |
| 0.1387        | 6.99  | 367  | 0.0711          | 0.9474   |
| 0.1342        | 8.0   | 420  | 0.0231          | 1.0      |
| 0.0803        | 8.99  | 472  | 0.0475          | 1.0      |
| 0.097         | 10.0  | 525  | 0.0190          | 1.0      |
| 0.0888        | 10.99 | 577  | 0.0220          | 1.0      |
| 0.0668        | 12.0  | 630  | 0.0078          | 1.0      |
| 0.0559        | 12.99 | 682  | 0.0073          | 1.0      |
| 0.0759        | 14.0  | 735  | 0.0055          | 1.0      |
| 0.081         | 14.99 | 787  | 0.0058          | 1.0      |
| 0.0806        | 16.0  | 840  | 0.0102          | 1.0      |
| 0.0568        | 16.99 | 892  | 0.0164          | 1.0      |
| 0.0696        | 18.0  | 945  | 0.0049          | 1.0      |
| 0.0692        | 18.99 | 997  | 0.0040          | 1.0      |
| 0.0929        | 20.0  | 1050 | 0.0030          | 1.0      |
| 0.1169        | 20.99 | 1102 | 0.0183          | 1.0      |
| 0.0385        | 22.0  | 1155 | 0.0576          | 0.9474   |
| 0.0564        | 22.99 | 1207 | 0.0512          | 0.9474   |
| 0.0206        | 24.0  | 1260 | 0.0025          | 1.0      |
| 0.0984        | 24.99 | 1312 | 0.0028          | 1.0      |
| 0.0368        | 26.0  | 1365 | 0.0037          | 1.0      |
| 0.0436        | 26.99 | 1417 | 0.0609          | 0.9474   |
| 0.0896        | 28.0  | 1470 | 0.0154          | 1.0      |
| 0.079         | 28.99 | 1522 | 0.0026          | 1.0      |
| 0.0211        | 30.0  | 1575 | 0.0045          | 1.0      |
| 0.0499        | 30.99 | 1627 | 0.0042          | 1.0      |
| 0.0137        | 32.0  | 1680 | 0.0043          | 1.0      |
| 0.0711        | 32.99 | 1732 | 0.0019          | 1.0      |
| 0.0369        | 34.0  | 1785 | 0.0021          | 1.0      |
| 0.0382        | 34.99 | 1837 | 0.0031          | 1.0      |
| 0.0785        | 36.0  | 1890 | 0.0029          | 1.0      |
| 0.0575        | 36.99 | 1942 | 0.0020          | 1.0      |
| 0.0158        | 38.0  | 1995 | 0.0019          | 1.0      |
| 0.0489        | 38.99 | 2047 | 0.0022          | 1.0      |
| 0.0511        | 39.62 | 2080 | 0.0023          | 1.0      |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0