---
library_name: transformers
license: apache-2.0
base_model: facebook/deit-small-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
- recall
model-index:
- name: deit_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: 0.9758620689655172
    - name: Recall
      type: recall
      value: 0.9806022408963586
---

<!-- 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. -->

# deit_fold_3

This model is a fine-tuned version of [facebook/deit-small-patch16-224](https://huggingface.co/facebook/deit-small-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0647
- Accuracy: 0.9759
- F1 Score: 0.9781
- Recall: 0.9806

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:------:|
| 2.8115        | 1.0   | 19   | 2.7735          | 0.3034   | 0.2529   | 0.2630 |
| 2.7100        | 2.0   | 38   | 2.6285          | 0.4069   | 0.2911   | 0.3284 |
| 2.5177        | 3.0   | 57   | 2.4014          | 0.5207   | 0.4125   | 0.4375 |
| 2.2202        | 4.0   | 76   | 2.0460          | 0.7069   | 0.7150   | 0.6830 |
| 1.7906        | 5.0   | 95   | 1.6558          | 0.8414   | 0.8552   | 0.8490 |
| 1.4703        | 6.0   | 114  | 1.4065          | 0.8724   | 0.8851   | 0.8883 |
| 1.2977        | 7.0   | 133  | 1.3043          | 0.9138   | 0.9200   | 0.9203 |
| 1.2124        | 8.0   | 152  | 1.2551          | 0.9345   | 0.9395   | 0.9427 |
| 1.1651        | 9.0   | 171  | 1.2009          | 0.9448   | 0.9490   | 0.9512 |
| 1.1434        | 10.0  | 190  | 1.1668          | 0.9483   | 0.9520   | 0.9536 |
| 1.1184        | 11.0  | 209  | 1.1541          | 0.9586   | 0.9611   | 0.9623 |
| 1.0736        | 12.0  | 228  | 1.1619          | 0.9517   | 0.9555   | 0.9598 |
| 1.0636        | 13.0  | 247  | 1.1813          | 0.9448   | 0.9499   | 0.9561 |
| 1.0464        | 14.0  | 266  | 1.1243          | 0.9655   | 0.9686   | 0.9721 |
| 1.0363        | 15.0  | 285  | 1.1079          | 0.9586   | 0.9615   | 0.9621 |
| 1.0317        | 16.0  | 304  | 1.1095          | 0.9655   | 0.9675   | 0.9708 |
| 1.0205        | 17.0  | 323  | 1.1498          | 0.9552   | 0.9593   | 0.9648 |
| 1.0146        | 18.0  | 342  | 1.1132          | 0.9655   | 0.9686   | 0.9721 |
| 1.0132        | 19.0  | 361  | 1.1042          | 0.9552   | 0.9586   | 0.9569 |
| 1.0060        | 20.0  | 380  | 1.0980          | 0.9552   | 0.9594   | 0.9549 |
| 0.9965        | 21.0  | 399  | 1.0731          | 0.9759   | 0.9780   | 0.9780 |
| 0.9954        | 22.0  | 418  | 1.0879          | 0.9621   | 0.9654   | 0.9631 |
| 1.0041        | 23.0  | 437  | 1.1282          | 0.9621   | 0.9656   | 0.9697 |
| 0.9945        | 24.0  | 456  | 1.0968          | 0.9655   | 0.9686   | 0.9721 |
| 0.9823        | 25.0  | 475  | 1.1093          | 0.9621   | 0.9652   | 0.9697 |
| 0.9811        | 26.0  | 494  | 1.0782          | 0.9690   | 0.9715   | 0.9746 |
| 0.9701        | 27.0  | 513  | 1.0829          | 0.9586   | 0.9615   | 0.9621 |
| 0.9695        | 28.0  | 532  | 1.0792          | 0.9724   | 0.9751   | 0.9782 |
| 0.9779        | 29.0  | 551  | 1.0625          | 0.9655   | 0.9684   | 0.9699 |
| 0.9825        | 30.0  | 570  | 1.0647          | 0.9759   | 0.9781   | 0.9806 |
| 0.9718        | 31.0  | 589  | 1.0718          | 0.9724   | 0.9750   | 0.9769 |
| 0.9798        | 32.0  | 608  | 1.0673          | 0.9759   | 0.9781   | 0.9806 |
| 0.9833        | 33.0  | 627  | 1.0644          | 0.9724   | 0.9750   | 0.9769 |
| 0.9665        | 34.0  | 646  | 1.0789          | 0.9724   | 0.9741   | 0.9770 |
| 0.9802        | 35.0  | 665  | 1.0593          | 0.9759   | 0.9781   | 0.9793 |
| 0.9624        | 36.0  | 684  | 1.0595          | 0.9759   | 0.9776   | 0.9806 |
| 0.9674        | 37.0  | 703  | 1.0814          | 0.9655   | 0.9681   | 0.9721 |
| 0.9723        | 38.0  | 722  | 1.0604          | 0.9759   | 0.9781   | 0.9806 |
| 0.9589        | 39.0  | 741  | 1.0768          | 0.9621   | 0.9655   | 0.9686 |
| 0.9655        | 40.0  | 760  | 1.0548          | 0.9655   | 0.9688   | 0.9694 |
| 0.9814        | 41.0  | 779  | 1.0676          | 0.9724   | 0.9751   | 0.9782 |
| 0.9627        | 42.0  | 798  | 1.0547          | 0.9759   | 0.9781   | 0.9806 |
| 0.9588        | 43.0  | 817  | 1.1152          | 0.9586   | 0.9626   | 0.9672 |
| 0.9665        | 44.0  | 836  | 1.0859          | 0.9690   | 0.9721   | 0.9757 |
| 0.9627        | 45.0  | 855  | 1.0683          | 0.9690   | 0.9721   | 0.9757 |
| 0.9576        | 46.0  | 874  | 1.0634          | 0.9759   | 0.9776   | 0.9806 |
| 0.9559        | 47.0  | 893  | 1.0620          | 0.9690   | 0.9718   | 0.9719 |
| 0.9642        | 48.0  | 912  | 1.0653          | 0.9724   | 0.9750   | 0.9756 |
| 0.9751        | 49.0  | 931  | 1.0574          | 0.9759   | 0.9781   | 0.9793 |
| 0.9688        | 50.0  | 950  | 1.0704          | 0.9690   | 0.9720   | 0.9744 |
| 0.9596        | 51.0  | 969  | 1.0635          | 0.9724   | 0.9750   | 0.9769 |
| 0.9716        | 52.0  | 988  | 1.0674          | 0.9759   | 0.9776   | 0.9806 |


### Framework versions

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