---
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: test-cifar-10
  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. -->

# test-cifar-10

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9675
- Accuracy: 0.1471

## 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: 2e-05
- train_batch_size: 10
- eval_batch_size: 4
- 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: linear
- num_epochs: 12

### Training results

| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| No log        | 1.0   | 398  | 0.1078   | 2.4878          |
| 2.6367        | 2.0   | 796  | 0.1225   | 2.2750          |
| 2.0748        | 3.0   | 1194 | 0.1471   | 2.1435          |
| 1.9035        | 4.0   | 1592 | 0.1225   | 2.0770          |
| 1.9035        | 5.0   | 1990 | 0.1422   | 2.0976          |
| 1.8217        | 6.0   | 2388 | 0.1618   | 1.9768          |
| 1.7998        | 7.0   | 2786 | 2.0803   | 0.1275          |
| 1.7268        | 8.0   | 3184 | 1.9141   | 0.1569          |
| 1.6826        | 9.0   | 3582 | 1.7059   | 0.2010          |
| 1.6826        | 10.0  | 3980 | 2.0650   | 0.1127          |
| 1.6642        | 11.0  | 4378 | 1.9643   | 0.1520          |
| 1.6267        | 12.0  | 4776 | 1.9675   | 0.1471          |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3