base

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DeiT-base-DatasetDict({

train: Dataset({
    features: ['img', 'fine_label', 'coarse_label'],
    num_rows: 50000
})
test: Dataset({
    features: ['img', 'fine_label', 'coarse_label'],
    num_rows: 10000
})
validation: Dataset({
    features: ['img', 'fine_label', 'coarse_label'],
    num_rows: 10000
})

})

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

• Loss: 0.3054
• Accuracy: 0.906

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: 5e-05
• train_batch_size: 64
• eval_batch_size: 1
• seed: 777
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 10

Training results

Framework versions

• Transformers 4.38.1
• Pytorch 2.1.0+cu121
• Datasets 2.18.0
• Tokenizers 0.15.2