---
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- image-classification
- animals
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vit-base-animals10
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# vit-base-animals10

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the Rapidata/Animals-10 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0784
- Accuracy: 0.9762

## 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: 5e-05
- train_batch_size: 8
- 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.0997        | 1.0   | 2356  | 0.0928          | 0.9732   |
| 0.0752        | 2.0   | 4712  | 0.0678          | 0.9809   |
| 0.0743        | 3.0   | 7068  | 0.0584          | 0.9839   |
| 0.0882        | 4.0   | 9424  | 0.0605          | 0.9792   |
| 0.0656        | 5.0   | 11780 | 0.0653          | 0.9813   |


### Framework versions

- Transformers 4.52.4
- Pytorch 2.7.0+cu128
- Datasets 3.6.0
- Tokenizers 0.21.1