---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: turcoins-classifier
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: hsyntemiz--turcoins
      split: test
      args: hsyntemiz--turcoins
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9548611111111112
---

<!-- 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. -->

# turcoins-classifier

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: 0.1763
- Accuracy: 0.9549

## 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: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.9277        | 1.0   | 146  | 1.9660          | 0.7726   |
| 1.6627        | 2.0   | 292  | 1.7154          | 0.7917   |
| 1.4071        | 2.99  | 438  | 1.4120          | 0.8079   |
| 1.09          | 4.0   | 585  | 1.1225          | 0.8362   |
| 0.8086        | 5.0   | 731  | 0.8917          | 0.8675   |
| 0.7636        | 6.0   | 877  | 0.7596          | 0.8709   |
| 0.611         | 6.99  | 1023 | 0.6493          | 0.8883   |
| 0.4605        | 8.0   | 1170 | 0.5899          | 0.8872   |
| 0.37          | 9.0   | 1316 | 0.4978          | 0.9045   |
| 0.3882        | 10.0  | 1462 | 0.4424          | 0.9132   |
| 0.3139        | 10.99 | 1608 | 0.3969          | 0.9115   |
| 0.3178        | 12.0  | 1755 | 0.3525          | 0.9294   |
| 0.2796        | 13.0  | 1901 | 0.3552          | 0.9161   |
| 0.2571        | 14.0  | 2047 | 0.3189          | 0.9265   |
| 0.2481        | 14.99 | 2193 | 0.2945          | 0.9358   |
| 0.1875        | 16.0  | 2340 | 0.2647          | 0.9392   |
| 0.1861        | 17.0  | 2486 | 0.2404          | 0.9410   |
| 0.1839        | 18.0  | 2632 | 0.2556          | 0.9421   |
| 0.173         | 18.99 | 2778 | 0.2387          | 0.9462   |
| 0.1837        | 20.0  | 2925 | 0.2049          | 0.9485   |
| 0.1724        | 21.0  | 3071 | 0.2065          | 0.9525   |
| 0.1399        | 22.0  | 3217 | 0.2089          | 0.9404   |
| 0.1696        | 22.99 | 3363 | 0.1957          | 0.9497   |
| 0.1405        | 24.0  | 3510 | 0.1848          | 0.9554   |
| 0.1009        | 25.0  | 3656 | 0.1912          | 0.9520   |
| 0.1126        | 26.0  | 3802 | 0.1717          | 0.9560   |
| 0.1336        | 26.99 | 3948 | 0.1699          | 0.9589   |
| 0.1046        | 28.0  | 4095 | 0.1600          | 0.9601   |
| 0.126         | 29.0  | 4241 | 0.1839          | 0.9520   |
| 0.0882        | 29.95 | 4380 | 0.1763          | 0.9549   |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3