---
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_5
  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: 0.9515570934256056
    - name: Recall
      type: recall
      value: 0.955763200802709
---

<!-- 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_5

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: 1.1556
- Accuracy: 0.9516
- F1 Score: 0.9547
- Recall: 0.9558

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:------:|
| 3.0831        | 1.0   | 19   | 2.9877          | 0.1834   | 0.1506   | 0.1750 |
| 2.9160        | 2.0   | 38   | 2.7975          | 0.2734   | 0.2517   | 0.2583 |
| 2.5816        | 3.0   | 57   | 2.5431          | 0.4671   | 0.4271   | 0.4325 |
| 2.1999        | 4.0   | 76   | 2.2368          | 0.6263   | 0.6019   | 0.6120 |
| 1.8110        | 5.0   | 95   | 1.9213          | 0.7301   | 0.7278   | 0.7223 |
| 1.4822        | 6.0   | 114  | 1.6147          | 0.8304   | 0.8407   | 0.8357 |
| 1.2515        | 7.0   | 133  | 1.4442          | 0.8581   | 0.8646   | 0.8541 |
| 1.1471        | 8.0   | 152  | 1.3540          | 0.8789   | 0.8857   | 0.8784 |
| 1.0819        | 9.0   | 171  | 1.2801          | 0.8962   | 0.9021   | 0.8978 |
| 1.0613        | 10.0  | 190  | 1.2465          | 0.9100   | 0.9142   | 0.9124 |
| 1.0395        | 11.0  | 209  | 1.2235          | 0.9343   | 0.9386   | 0.9387 |
| 1.0240        | 12.0  | 228  | 1.2106          | 0.9377   | 0.9410   | 0.9397 |
| 1.0257        | 13.0  | 247  | 1.1934          | 0.9308   | 0.9358   | 0.9361 |
| 1.0162        | 14.0  | 266  | 1.1946          | 0.9377   | 0.9402   | 0.9384 |
| 0.9940        | 15.0  | 285  | 1.1879          | 0.9377   | 0.9411   | 0.9397 |
| 1.0097        | 16.0  | 304  | 1.1848          | 0.9412   | 0.9449   | 0.9423 |
| 0.9937        | 17.0  | 323  | 1.1863          | 0.9377   | 0.9408   | 0.9384 |
| 0.9864        | 18.0  | 342  | 1.1935          | 0.9446   | 0.9471   | 0.9446 |
| 0.9830        | 19.0  | 361  | 1.1802          | 0.9446   | 0.9474   | 0.9459 |
| 0.9825        | 20.0  | 380  | 1.1508          | 0.9446   | 0.9490   | 0.9485 |
| 0.9733        | 21.0  | 399  | 1.1568          | 0.9343   | 0.9385   | 0.9385 |
| 0.9778        | 22.0  | 418  | 1.1570          | 0.9412   | 0.9455   | 0.9460 |
| 0.9657        | 23.0  | 437  | 1.1588          | 0.9446   | 0.9487   | 0.9497 |
| 0.9771        | 24.0  | 456  | 1.1637          | 0.9446   | 0.9495   | 0.9510 |
| 0.9647        | 25.0  | 475  | 1.1640          | 0.9481   | 0.9509   | 0.9509 |
| 0.9649        | 26.0  | 494  | 1.1572          | 0.9516   | 0.9546   | 0.9546 |
| 0.9686        | 27.0  | 513  | 1.1667          | 0.9377   | 0.9411   | 0.9397 |
| 0.9681        | 28.0  | 532  | 1.1614          | 0.9377   | 0.9417   | 0.9423 |
| 0.9642        | 29.0  | 551  | 1.1599          | 0.9412   | 0.9444   | 0.9434 |
| 0.9677        | 30.0  | 570  | 1.1556          | 0.9516   | 0.9547   | 0.9558 |


### Framework versions

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