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vit-base-patch16-224-in21k-image-classification-sagemaker – AI Model by philschmid | AlphaNeural AI
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philschmid
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vit-base-patch16-224-in21k-image-classification-sagemaker
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transformers
pytorch
vit
image-classification
autotrain_compatible
endpoints_compatible
us
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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
