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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: 0.2048
- Accuracy: 0.9432

## 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: 32
- eval_batch_size: 16
- 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 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.7025        | 1.0   | 185  | 0.3849          | 0.9242   |
| 0.2944        | 2.0   | 370  | 0.2704          | 0.9337   |
| 0.2129        | 3.0   | 555  | 0.2417          | 0.9378   |
| 0.1761        | 4.0   | 740  | 0.2305          | 0.9350   |
| 0.157         | 5.0   | 925  | 0.2281          | 0.9378   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.14.1

{"license": "apache-2.0", "tags": ["image-classification", "generated_from_trainer"], "datasets": ["pcuenq/oxford-pets"], "metrics": ["accuracy"], "base_model": "google/vit-base-patch16-224", "model-index": [{"name": "vit-base-oxford-iiit-pets", "results": []}]}
transformers tensorboard safetensors vit image-classification generated_from_trainer dataset:pcuenq/oxford-pets base_model:google/vit-base-patch16-224 license:apache-2.0 autotrain_compatible endpoints_compatible has_space region:us