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: 0.1924 Accuracy: 0.9445 Model description This model is a fine tuned version of a pre trained Vision Transformer ( google/vit base patch16 224 ) for image classification on the Oxford IIIT Pet Dataset. It uses transfer learning to adapt a generic vision model to identify 37 different cat and dog breeds. The model head is adjusted to output the number of classes in the dataset, and it is trained end to end using standard classification loss. Intended uses & limitations Intended Uses: Educational demos on transfer learning and fine tuning vision models. Pet breed classification in structured datasets similar to Oxford Pets. Comparative analysis with zero shot models like CLIP. Limitations: May not generalize well to breeds outside of the Oxford IIIT dataset. Not suitable for real world medical or safety critical applications. Input images should be clear, centered, and close in style to the training data (cropped pet portraits). Training and evaluation data The model is trained and evaluated on th…
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