vit-base-oxford-iiit-pets

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vit-base-oxford-iiit-pets

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

• Loss: 0.1900
• Accuracy: 0.9378

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: 0.0003
• train_batch_size: 16
• eval_batch_size: 8
• seed: 42
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 5

Training results

Framework versions

• Transformers 4.50.0
• Pytorch 2.6.0+cu124
• Datasets 3.4.1
• Tokenizers 0.21.1

Zero-Shot Evaluation

A comparison model was evaluated using openai/clip-vit-base-patch32 on the Oxford-IIIT Pet dataset.

Ergebnisse (Zero-Shot):

• Accuracy: 88.00%
• Precision (macro): 87.68%
• Recall (macro): 88.00%

Although the model was not trained on the dataset, it shows remarkable performance.