---
license: apache-2.0
base_model: WinKawaks/vit-tiny-patch16-224
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: vit-tiny-patch16-224-finetuned-RESISC45_01
  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-tiny-patch16-224-finetuned-RESISC45_01

This model is a fine-tuned version of [WinKawaks/vit-tiny-patch16-224](https://huggingface.co/WinKawaks/vit-tiny-patch16-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2402
- Accuracy: 0.9302
- Precision: 0.9317
- Recall: 0.9302
- F1: 0.9301

## 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: 0.0001
- train_batch_size: 512
- eval_batch_size: 512
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 3.9864        | 1.0   | 37   | 2.0458          | 0.643    | 0.6573    | 0.643  | 0.6131 |
| 0.8947        | 2.0   | 74   | 0.5364          | 0.873    | 0.8821    | 0.873  | 0.8720 |
| 0.5981        | 3.0   | 111  | 0.3644          | 0.907    | 0.9137    | 0.907  | 0.9068 |
| 0.46          | 4.0   | 148  | 0.2821          | 0.914    | 0.9209    | 0.914  | 0.9130 |
| 0.3936        | 5.0   | 185  | 0.2343          | 0.929    | 0.9331    | 0.929  | 0.9289 |
| 0.3629        | 6.0   | 222  | 0.2191          | 0.935    | 0.9404    | 0.935  | 0.9351 |
| 0.3154        | 7.0   | 259  | 0.2000          | 0.939    | 0.9424    | 0.939  | 0.9388 |
| 0.317         | 8.0   | 296  | 0.1736          | 0.952    | 0.9548    | 0.952  | 0.9520 |
| 0.2921        | 9.0   | 333  | 0.1725          | 0.952    | 0.9545    | 0.952  | 0.9519 |
| 0.2922        | 10.0  | 370  | 0.1738          | 0.945    | 0.9481    | 0.945  | 0.9449 |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1