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---
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- image-classification
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vit-base-oxford-iiit-pets
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# 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: 0.1992
- Accuracy: 0.9350
## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3808 | 1.0 | 370 | 0.2939 | 0.9229 |
| 0.2337 | 2.0 | 740 | 0.2166 | 0.9432 |
| 0.1762 | 3.0 | 1110 | 0.2010 | 0.9459 |
| 0.1414 | 4.0 | 1480 | 0.1922 | 0.9513 |
| 0.136 | 5.0 | 1850 | 0.1895 | 0.9499 |
### Framework versions
- Transformers 4.41.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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