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franciscoafy/
vit-base-patch16-224-franciscoflores-classification

Name: vit-base-patch16-224-franciscoflores-classification
Availability: InStock

generated_from_trainer

google/vit-base-patch16-224-in21k

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vit-base-patch16-224-franciscoflores-classification

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

Loss: 0.0071
accuracy : 0.9988

Model description

Transfer learning from a pre-trained image classification model determines which images are of a dog and which ones are of food

Intended uses & limitations

More information needed

Training and evaluation data

This model was trained using the "sasha/dog-food"

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 0.0002
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss
0.0618	1.9	500	0.0146
0.0062	3.8	1000	0.0071

Framework versions

Transformers 4.33.1
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.13.3

franciscoafy/vit-base-patch16-224-franciscoflores-classification