---
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_3
  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: 0.9827586206896551
    - name: Recall
      type: recall
      value: 0.9827835611856683
---

<!-- 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_3

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: 1.0408
- Accuracy: 0.9828
- F1 Score: 0.9839
- Recall: 0.9828

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:------:|
| 2.8990        | 1.0   | 19   | 2.8243          | 0.3      | 0.1902   | 0.2394 |
| 2.6775        | 2.0   | 38   | 2.5749          | 0.3759   | 0.2813   | 0.3098 |
| 2.3450        | 3.0   | 57   | 2.2350          | 0.5931   | 0.5678   | 0.5485 |
| 1.9329        | 4.0   | 76   | 1.8672          | 0.7828   | 0.7860   | 0.7689 |
| 1.5705        | 5.0   | 95   | 1.5231          | 0.8931   | 0.9009   | 0.8963 |
| 1.3488        | 6.0   | 114  | 1.3058          | 0.9379   | 0.9421   | 0.9399 |
| 1.1881        | 7.0   | 133  | 1.2164          | 0.9379   | 0.9429   | 0.9400 |
| 1.1692        | 8.0   | 152  | 1.1655          | 0.9483   | 0.9521   | 0.9498 |
| 1.1013        | 9.0   | 171  | 1.1383          | 0.9621   | 0.9654   | 0.9620 |
| 1.0939        | 10.0  | 190  | 1.1244          | 0.9586   | 0.9621   | 0.9570 |
| 1.0743        | 11.0  | 209  | 1.1158          | 0.9690   | 0.9716   | 0.9682 |
| 1.0535        | 12.0  | 228  | 1.0974          | 0.9655   | 0.9687   | 0.9670 |
| 1.0468        | 13.0  | 247  | 1.0882          | 0.9655   | 0.9683   | 0.9683 |
| 1.0113        | 14.0  | 266  | 1.0735          | 0.9759   | 0.9778   | 0.9766 |
| 1.0041        | 15.0  | 285  | 1.0831          | 0.9724   | 0.9753   | 0.9717 |
| 1.0087        | 16.0  | 304  | 1.0676          | 0.9724   | 0.9749   | 0.9754 |
| 1.0055        | 17.0  | 323  | 1.0714          | 0.9655   | 0.9689   | 0.9705 |
| 0.9963        | 18.0  | 342  | 1.0680          | 0.9690   | 0.9719   | 0.9730 |
| 0.9857        | 19.0  | 361  | 1.0630          | 0.9759   | 0.9776   | 0.9753 |
| 0.9784        | 20.0  | 380  | 1.0617          | 0.9724   | 0.9748   | 0.9754 |
| 0.9790        | 21.0  | 399  | 1.0653          | 0.9724   | 0.9748   | 0.9754 |
| 0.9791        | 22.0  | 418  | 1.0574          | 0.9724   | 0.9749   | 0.9754 |
| 0.9900        | 23.0  | 437  | 1.0858          | 0.9690   | 0.9720   | 0.9768 |
| 0.9790        | 24.0  | 456  | 1.0520          | 0.9759   | 0.9776   | 0.9753 |
| 0.9708        | 25.0  | 475  | 1.0499          | 0.9724   | 0.9749   | 0.9754 |
| 0.9708        | 26.0  | 494  | 1.0448          | 0.9793   | 0.9809   | 0.9803 |
| 0.9707        | 27.0  | 513  | 1.0459          | 0.9793   | 0.9809   | 0.9803 |
| 0.9729        | 28.0  | 532  | 1.0549          | 0.9690   | 0.9719   | 0.9730 |
| 0.9845        | 29.0  | 551  | 1.0451          | 0.9793   | 0.9809   | 0.9803 |
| 0.9771        | 30.0  | 570  | 1.0502          | 0.9759   | 0.9778   | 0.9766 |
| 0.9716        | 31.0  | 589  | 1.0507          | 0.9759   | 0.9779   | 0.9779 |
| 0.9669        | 32.0  | 608  | 1.0457          | 0.9793   | 0.9809   | 0.9803 |
| 0.9761        | 33.0  | 627  | 1.0483          | 0.9793   | 0.9808   | 0.9791 |
| 0.9627        | 34.0  | 646  | 1.0437          | 0.9724   | 0.9743   | 0.9743 |
| 0.9738        | 35.0  | 665  | 1.0431          | 0.9759   | 0.9779   | 0.9779 |
| 0.9666        | 36.0  | 684  | 1.0413          | 0.9759   | 0.9779   | 0.9779 |
| 0.9657        | 37.0  | 703  | 1.0452          | 0.9724   | 0.9743   | 0.9743 |
| 0.9649        | 38.0  | 722  | 1.0440          | 0.9793   | 0.9809   | 0.9803 |
| 0.9607        | 39.0  | 741  | 1.0389          | 0.9759   | 0.9774   | 0.9780 |
| 0.9693        | 40.0  | 760  | 1.0408          | 0.9828   | 0.9839   | 0.9828 |
| 0.9692        | 41.0  | 779  | 1.0374          | 0.9793   | 0.9809   | 0.9803 |
| 0.9599        | 42.0  | 798  | 1.0390          | 0.9793   | 0.9809   | 0.9803 |
| 0.9601        | 43.0  | 817  | 1.0372          | 0.9793   | 0.9810   | 0.9816 |
| 0.9642        | 44.0  | 836  | 1.0432          | 0.9793   | 0.9809   | 0.9803 |
| 0.9624        | 45.0  | 855  | 1.0412          | 0.9759   | 0.9779   | 0.9779 |
| 0.9598        | 46.0  | 874  | 1.0395          | 0.9793   | 0.9809   | 0.9803 |
| 0.9567        | 47.0  | 893  | 1.0414          | 0.9793   | 0.9809   | 0.9803 |
| 0.9634        | 48.0  | 912  | 1.0416          | 0.9759   | 0.9779   | 0.9779 |
| 0.9662        | 49.0  | 931  | 1.0416          | 0.9759   | 0.9779   | 0.9779 |
| 0.9652        | 50.0  | 950  | 1.0457          | 0.9759   | 0.9779   | 0.9779 |
| 0.9597        | 51.0  | 969  | 1.0418          | 0.9724   | 0.9748   | 0.9754 |
| 0.9675        | 52.0  | 988  | 1.0403          | 0.9724   | 0.9748   | 0.9754 |
| 0.9615        | 53.0  | 1007 | 1.0389          | 0.9724   | 0.9749   | 0.9754 |


### Framework versions

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