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vit-cifar100-cifar100

Image Classification
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vit-cifar100-cifar100 / README.md
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metadata
base_model: google/vit-base-patch16-224-in21k
library_name: peft
license: apache-2.0
metrics:
  - accuracy
tags:
  - image-classification
  - vision
  - generated_from_trainer
model-index:
  - name: vit-cifar100-cifar100
    results: []

vit-cifar100-cifar100

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the cifar100 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2550
  • Accuracy: 0.9236

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: 0.0005
  • 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: 5.0

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.5206 1.0 5313 0.3323 0.9051
0.7608 2.0 10626 0.2929 0.9139
0.8691 3.0 15939 0.2725 0.9173
0.3582 4.0 21252 0.2581 0.9232
0.4711 5.0 26565 0.2550 0.9236

Framework versions

  • PEFT 0.12.0
  • Transformers 4.44.2
  • Pytorch 2.0.1+cu117
  • Datasets 3.0.0
  • Tokenizers 0.19.1