---
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vit-base-patch16-224-cifar10
  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-cifar10

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: 0.0506
- Accuracy: 0.9906

## 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: 128
- eval_batch_size: 64
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 0.1
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.0405        | 1.2788 | 500  | 0.0684          | 0.9801   |
| 0.0211        | 2.5575 | 1000 | 0.0913          | 0.9763   |
| 0.0107        | 3.8363 | 1500 | 0.0541          | 0.9864   |
| 0.0045        | 5.1151 | 2000 | 0.0534          | 0.9883   |
| 0.0022        | 6.3939 | 2500 | 0.0522          | 0.989    |
| 0.0009        | 7.6726 | 3000 | 0.0506          | 0.9906   |
| 0.0012        | 8.9514 | 3500 | 0.0487          | 0.9905   |


### Framework versions

- Transformers 5.3.0
- Pytorch 2.6.0+cu124
- Datasets 4.8.3
- Tokenizers 0.22.2