philschmid / vit-base-patch16-224-in21k-image-classification-sagemaker

huggingface.co
Total runs: 9
24-hour runs: 1
7-day runs: -23
30-day runs: -19
Model's Last Updated: June 09 2021
image-classification

Introduction of vit-base-patch16-224-in21k-image-classification-sagemaker

Model Details of vit-base-patch16-224-in21k-image-classification-sagemaker

vit-base-patch16-224-in21k-image-classification-sagemaker

This model is a fine-tuned version of vit-base-patch16-224-in21k on the cifar10 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3033
  • Accuracy: 0.972
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: 16
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 3
Training results
Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 313 1.4603 0.936
1.6548 2.0 626 0.4451 0.966
1.6548 3.0 939 0.3033 0.972
Framework versions
  • Transformers 4.6.1
  • Pytorch 1.7.1
  • Datasets 1.6.2
  • Tokenizers 0.10.3

Runs of philschmid vit-base-patch16-224-in21k-image-classification-sagemaker on huggingface.co

9
Total runs
1
24-hour runs
1
3-day runs
-23
7-day runs
-19
30-day runs

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vit-base-patch16-224-in21k-image-classification-sagemaker install

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philschmid
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