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dhmeltzer/
sagemaker-ViT-CIFAR10

Name: sagemaker-ViT-CIFAR10
Availability: InStock

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sagemaker-ViT-CIFAR10

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

Loss: 0.2966
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
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	313	1.4582	0.9325
1.6494	2.0	626	0.4472	0.9665
1.6494	3.0	939	0.2966	0.972

Framework versions

Transformers 4.26.0
Pytorch 1.13.1+cu117
Datasets 2.9.0
Tokenizers 0.13.2

dhmeltzer/sagemaker-ViT-CIFAR10

sagemaker-ViT-CIFAR10

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

dhmeltzer/
sagemaker-ViT-CIFAR10