---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: car-countries-classification
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.29411764705882354
---

<!-- 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. -->

# car-countries-classification

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4039
- Accuracy: 0.2941

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| No log        | 0.9231 | 3    | 1.5830          | 0.3137   |
| No log        | 1.8462 | 6    | 1.5342          | 0.2941   |
| No log        | 2.7692 | 9    | 1.4845          | 0.2941   |
| 1.5308        | 4.0    | 13   | 1.4705          | 0.2745   |
| 1.5308        | 4.9231 | 16   | 1.4534          | 0.3137   |
| 1.5308        | 5.8462 | 19   | 1.4583          | 0.2745   |
| 1.3601        | 6.7692 | 22   | 1.4218          | 0.2941   |
| 1.3601        | 8.0    | 26   | 1.4283          | 0.2745   |
| 1.3601        | 8.9231 | 29   | 1.3973          | 0.3137   |
| 1.2778        | 9.2308 | 30   | 1.4039          | 0.2941   |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1