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# vit-base-oxford-iiit-pets

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the pcuenq/oxford-pets dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1977
- Accuracy: 0.9445

## 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

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3582        | 1.0   | 370  | 0.2997          | 0.9256   |
| 0.2125        | 2.0   | 740  | 0.2200          | 0.9418   |
| 0.1573        | 3.0   | 1110 | 0.1966          | 0.9405   |
| 0.1472        | 4.0   | 1480 | 0.1884          | 0.9445   |
| 0.1338        | 5.0   | 1850 | 0.1865          | 0.9472   |


### Framework versions

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



Results:

- Accuracy: 0.8800
- Precision: 0.8768
- Recall: 0.8800

Zusätzlich aus Interesse erstellt:
F1-Score (weighted): 0.8605
F1-Score (micro): 0.8800 
F1-Score (macro): 0.8605



siamese birman shiba inu staffordshire bull terrier basset hound bombay japanese chin chihuahua german shorthaired pomeranian beagle english cocker spaniel american pit bull terrier ragdoll persian egyptian mau miniature pinscher sphynx maine coon keeshond yorkshire terrier havanese leonberger wheaten terrier american bulldog english setter boxer newfoundland bengal samoyed british shorthair great pyrenees abyssinian pug saint bernard russian blue scottish terrier