vit-base-cifar10 / README.md
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---
license: apache-2.0
tags:
- image-classification
- generated_from_trainer
model-index:
- name: vit-base-cifar10
results: []
---
<!-- 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-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