---
license: apache-2.0
base_model: 02shanky/vit-finetuned-cifar10
tags:
- generated_from_trainer
datasets:
- cifar10
metrics:
- accuracy
model-index:
- name: vit-finetuned-vanilla-cifar10-0
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: cifar10
      type: cifar10
      config: plain_text
      split: train
      args: plain_text
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.992
---

<!-- 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-finetuned-vanilla-cifar10-0

This model is a fine-tuned version of [02shanky/vit-finetuned-cifar10](https://huggingface.co/02shanky/vit-finetuned-cifar10) on the cifar10 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0306
- Accuracy: 0.992

## 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: 0.0001
- 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
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 316  | 0.0619          | 0.9836   |
| 0.2651        | 2.0   | 633  | 0.0460          | 0.9867   |
| 0.2651        | 3.0   | 949  | 0.0415          | 0.9878   |
| 0.1967        | 4.0   | 1266 | 0.0326          | 0.9916   |
| 0.1552        | 4.99  | 1580 | 0.0306          | 0.992    |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1