---
license: apache-2.0
base_model: google/vit-base-patch16-384
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: test-2-geoguessr-55
  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. -->

# test-2-geoguessr-55

This model is a fine-tuned version of [google/vit-base-patch16-384](https://huggingface.co./google/vit-base-patch16-384) on [marcelomoreno26/geoguessr](https://huggingface.co./datasets/marcelomoreno26/geoguessr) dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4296
- Accuracy: 0.3881
- F1: 0.1440

## 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: 2e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 394  | 3.3218          | 0.1603   | 0.0292 |
| 3.5132        | 2.0   | 788  | 3.1195          | 0.2243   | 0.0494 |
| 3.1361        | 3.0   | 1182 | 2.9820          | 0.2587   | 0.0657 |
| 2.9576        | 4.0   | 1576 | 2.8774          | 0.2906   | 0.0816 |
| 2.9576        | 5.0   | 1970 | 2.7940          | 0.3125   | 0.0950 |
| 2.8298        | 6.0   | 2364 | 2.7271          | 0.3250   | 0.1042 |
| 2.7378        | 7.0   | 2758 | 2.6721          | 0.3366   | 0.1112 |
| 2.6526        | 8.0   | 3152 | 2.6268          | 0.3466   | 0.1156 |
| 2.5971        | 9.0   | 3546 | 2.5882          | 0.3546   | 0.1220 |
| 2.5971        | 10.0  | 3940 | 2.5558          | 0.3630   | 0.1269 |
| 2.5468        | 11.0  | 4334 | 2.5286          | 0.3699   | 0.1321 |
| 2.519         | 12.0  | 4728 | 2.5057          | 0.3721   | 0.1337 |
| 2.4769        | 13.0  | 5122 | 2.4865          | 0.3760   | 0.1359 |
| 2.4528        | 14.0  | 5516 | 2.4706          | 0.3805   | 0.1387 |
| 2.4528        | 15.0  | 5910 | 2.4577          | 0.3820   | 0.1391 |
| 2.4307        | 16.0  | 6304 | 2.4473          | 0.3840   | 0.1410 |
| 2.4207        | 17.0  | 6698 | 2.4395          | 0.3863   | 0.1428 |
| 2.4114        | 18.0  | 7092 | 2.4340          | 0.3874   | 0.1437 |
| 2.4114        | 19.0  | 7486 | 2.4307          | 0.3883   | 0.1440 |
| 2.4           | 20.0  | 7880 | 2.4296          | 0.3881   | 0.1440 |


### Framework versions

- Transformers 4.39.1
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.15.2