---
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- image-classification
- generated_from_trainer
datasets:
- cifar10-lt
metrics:
- accuracy
- f1
model-index:
- name: cifar10-lt
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: cifar10-lt
      type: cifar10-lt
      config: r-10
      split: test
      args: r-10
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9659
    - name: F1
      type: f1
      value: 0.9660399066727052
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# cifar10-lt

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the cifar10-lt dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1132
- Accuracy: 0.9659
- F1: 0.9660

## 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: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results



### Framework versions

- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3