---
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
- recall
model-index:
- name: fold_4
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: None
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9653979238754326
    - name: Recall
      type: recall
      value: 0.9683506090481117
---

<!-- 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. -->

# fold_4

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1328
- Accuracy: 0.9654
- F1 Score: 0.9688
- Recall: 0.9684

## 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: 1e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 150
- num_epochs: 100
- label_smoothing_factor: 0.15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Score | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:------:|
| 2.7279        | 1.0   | 19   | 2.6961          | 0.3287   | 0.3257   | 0.3264 |
| 2.6497        | 2.0   | 38   | 2.5197          | 0.4775   | 0.4752   | 0.4600 |
| 2.3856        | 3.0   | 57   | 2.2554          | 0.6574   | 0.6632   | 0.6472 |
| 2.0467        | 4.0   | 76   | 1.9435          | 0.8062   | 0.8186   | 0.8137 |
| 1.6696        | 5.0   | 95   | 1.6132          | 0.8720   | 0.8800   | 0.8750 |
| 1.3967        | 6.0   | 114  | 1.3746          | 0.9170   | 0.9249   | 0.9244 |
| 1.2758        | 7.0   | 133  | 1.2437          | 0.9412   | 0.9473   | 0.9422 |
| 1.1517        | 8.0   | 152  | 1.1767          | 0.9550   | 0.9593   | 0.9559 |
| 1.1069        | 9.0   | 171  | 1.1511          | 0.9516   | 0.9556   | 0.9512 |
| 1.0847        | 10.0  | 190  | 1.1386          | 0.9550   | 0.9589   | 0.9584 |
| 1.0566        | 11.0  | 209  | 1.1328          | 0.9654   | 0.9688   | 0.9684 |
| 1.0535        | 12.0  | 228  | 1.1346          | 0.9550   | 0.9597   | 0.9609 |
| 1.0154        | 13.0  | 247  | 1.1250          | 0.9550   | 0.9595   | 0.9595 |
| 1.0196        | 14.0  | 266  | 1.1252          | 0.9585   | 0.9625   | 0.9609 |
| 1.0003        | 15.0  | 285  | 1.1256          | 0.9481   | 0.9529   | 0.9524 |
| 0.9951        | 16.0  | 304  | 1.1191          | 0.9619   | 0.9653   | 0.9659 |
| 0.9877        | 17.0  | 323  | 1.1133          | 0.9619   | 0.9651   | 0.9646 |
| 0.9841        | 18.0  | 342  | 1.1038          | 0.9619   | 0.9651   | 0.9646 |
| 0.9887        | 19.0  | 361  | 1.1080          | 0.9619   | 0.9650   | 0.9635 |
| 0.9794        | 20.0  | 380  | 1.1105          | 0.9619   | 0.9651   | 0.9646 |
| 0.9786        | 21.0  | 399  | 1.1086          | 0.9654   | 0.9681   | 0.9671 |
| 0.9719        | 22.0  | 418  | 1.1084          | 0.9550   | 0.9591   | 0.9597 |
| 0.9723        | 23.0  | 437  | 1.1242          | 0.9516   | 0.9562   | 0.9584 |
| 0.9813        | 24.0  | 456  | 1.0986          | 0.9654   | 0.9681   | 0.9671 |
| 0.9682        | 25.0  | 475  | 1.0959          | 0.9654   | 0.9681   | 0.9671 |
| 0.9750        | 26.0  | 494  | 1.0990          | 0.9654   | 0.9681   | 0.9671 |
| 0.9716        | 27.0  | 513  | 1.0995          | 0.9619   | 0.9651   | 0.9646 |
| 0.9701        | 28.0  | 532  | 1.0949          | 0.9654   | 0.9681   | 0.9671 |
| 0.9694        | 29.0  | 551  | 1.0997          | 0.9654   | 0.9681   | 0.9671 |
| 0.9637        | 30.0  | 570  | 1.1002          | 0.9654   | 0.9681   | 0.9671 |
| 0.9647        | 31.0  | 589  | 1.0992          | 0.9654   | 0.9681   | 0.9671 |
| 0.9658        | 32.0  | 608  | 1.1084          | 0.9619   | 0.9650   | 0.9635 |
| 0.9686        | 33.0  | 627  | 1.1156          | 0.9619   | 0.9652   | 0.9659 |
| 0.9632        | 34.0  | 646  | 1.1068          | 0.9619   | 0.9650   | 0.9634 |
| 0.9630        | 35.0  | 665  | 1.1040          | 0.9619   | 0.9650   | 0.9634 |
| 0.9680        | 36.0  | 684  | 1.1131          | 0.9619   | 0.9650   | 0.9634 |
| 0.9579        | 37.0  | 703  | 1.1063          | 0.9619   | 0.9650   | 0.9634 |
| 0.9615        | 38.0  | 722  | 1.1063          | 0.9619   | 0.9650   | 0.9634 |


### Framework versions

- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 5.0.0
- Tokenizers 0.22.2