pytorch vit image-classification dataset:cifar10 transformers generated_from_trainer license:apache-2.0 model-index
---
license: apache-2.0
tags:
- image-classification
- generated_from_trainer
datasets:
- cifar10
model-index:
- name: vit-base-patch16-224-cifar10
  results:
  - task:
      type: image-classification
      name: Image Classification
    dataset:
      name: cifar10
      type: cifar10
      config: plain_text
      split: test
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.1004
      verified: true
    - name: Precision Macro
      type: precision
      value: 0.07725693204097324
      verified: true
    - name: Precision Micro
      type: precision
      value: 0.1004
      verified: true
    - name: Precision Weighted
      type: precision
      value: 0.07725693204097323
      verified: true
    - name: Recall Macro
      type: recall
      value: 0.1004
      verified: true
    - name: Recall Micro
      type: recall
      value: 0.1004
      verified: true
    - name: Recall Weighted
      type: recall
      value: 0.1004
      verified: true
    - name: F1 Macro
      type: f1
      value: 0.07942008420616108
      verified: true
    - name: F1 Micro
      type: f1
      value: 0.1004
      verified: true
    - name: F1 Weighted
      type: f1
      value: 0.07942008420616108
      verified: true
    - name: loss
      type: loss
      value: 2.3154706954956055
      verified: true
---

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# vit-base-patch16-224-cifar10

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 cifar10 dataset.

## 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: 8
- eval_batch_size: 8
- seed: 1337
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Framework versions

- Transformers 4.19.0.dev0
- Pytorch 1.10.1
- Datasets 2.1.0
- Tokenizers 0.12.1
