pytorch tensorboard vit image-classification transformers generated_from_trainer license:apache-2.0 model-index
---
license: apache-2.0
tags:
- image-classification
- generated_from_trainer
model-index:
- name: vit-base-cifar10
  results: []
---

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# vit-base-cifar10

This model is a fine-tuned version of [nateraw/vit-base-patch16-224-cifar10](https://huggingface.co/nateraw/vit-base-patch16-224-cifar10) on the cifar10-upside-down dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.2348
- eval_accuracy: 0.9134
- eval_runtime: 157.4172
- eval_samples_per_second: 127.051
- eval_steps_per_second: 1.988
- epoch: 0.02
- step: 26

## Model description

Vision Transformer

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP

### Framework versions

- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6
