metadata

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

vit-base-cifar10

This model is a fine-tuned version of 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