---
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_1
  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: 0.9655172413793104
    - name: Recall
      type: recall
      value: 0.9681372549019608
---

<!-- 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_1

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: 1.1170
- Accuracy: 0.9655
- F1 Score: 0.9681
- Recall: 0.9681

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:------:|
| 2.7052        | 1.0   | 19   | 2.6182          | 0.3897   | 0.2859   | 0.3210 |
| 2.6037        | 2.0   | 38   | 2.4936          | 0.4345   | 0.3591   | 0.3697 |
| 2.4310        | 3.0   | 57   | 2.2883          | 0.5552   | 0.5442   | 0.5290 |
| 2.1283        | 4.0   | 76   | 1.9885          | 0.7172   | 0.7322   | 0.7214 |
| 1.7269        | 5.0   | 95   | 1.6339          | 0.8172   | 0.8313   | 0.8241 |
| 1.4880        | 6.0   | 114  | 1.3974          | 0.8655   | 0.8730   | 0.8676 |
| 1.2856        | 7.0   | 133  | 1.2969          | 0.9      | 0.9069   | 0.9031 |
| 1.2589        | 8.0   | 152  | 1.2535          | 0.9069   | 0.9112   | 0.9057 |
| 1.1813        | 9.0   | 171  | 1.1953          | 0.9241   | 0.9300   | 0.9304 |
| 1.1441        | 10.0  | 190  | 1.1895          | 0.9379   | 0.9417   | 0.9389 |
| 1.1279        | 11.0  | 209  | 1.1635          | 0.9552   | 0.9589   | 0.9584 |
| 1.0956        | 12.0  | 228  | 1.1425          | 0.9483   | 0.9524   | 0.9511 |
| 1.0689        | 13.0  | 247  | 1.1503          | 0.9483   | 0.9511   | 0.9521 |
| 1.0613        | 14.0  | 266  | 1.1557          | 0.9552   | 0.9574   | 0.9571 |
| 1.0226        | 15.0  | 285  | 1.1592          | 0.9448   | 0.9478   | 0.9449 |
| 1.0242        | 16.0  | 304  | 1.1320          | 0.9483   | 0.9511   | 0.9510 |
| 1.0160        | 17.0  | 323  | 1.1371          | 0.9552   | 0.9584   | 0.9571 |
| 0.9991        | 18.0  | 342  | 1.1267          | 0.9621   | 0.9650   | 0.9657 |
| 1.0108        | 19.0  | 361  | 1.1350          | 0.9517   | 0.9551   | 0.9534 |
| 1.0175        | 20.0  | 380  | 1.1404          | 0.9586   | 0.9617   | 0.9608 |
| 0.9991        | 21.0  | 399  | 1.1422          | 0.9586   | 0.9614   | 0.9596 |
| 0.9951        | 22.0  | 418  | 1.1277          | 0.9552   | 0.9590   | 0.9608 |
| 0.9753        | 23.0  | 437  | 1.1113          | 0.9586   | 0.9620   | 0.9632 |
| 0.9748        | 24.0  | 456  | 1.1117          | 0.9552   | 0.9590   | 0.9608 |
| 0.9748        | 25.0  | 475  | 1.1086          | 0.9621   | 0.9648   | 0.9645 |
| 0.9704        | 26.0  | 494  | 1.1182          | 0.9586   | 0.9619   | 0.9620 |
| 0.9748        | 27.0  | 513  | 1.1061          | 0.9586   | 0.9620   | 0.9632 |
| 0.9637        | 28.0  | 532  | 1.0796          | 0.9621   | 0.9652   | 0.9669 |
| 0.9696        | 29.0  | 551  | 1.1170          | 0.9655   | 0.9681   | 0.9681 |
| 0.9656        | 30.0  | 570  | 1.0977          | 0.9621   | 0.9652   | 0.9669 |
| 0.9679        | 31.0  | 589  | 1.1275          | 0.9586   | 0.9621   | 0.9632 |
| 0.9699        | 32.0  | 608  | 1.0992          | 0.9586   | 0.9622   | 0.9645 |
| 0.9760        | 33.0  | 627  | 1.1147          | 0.9621   | 0.9647   | 0.9632 |
| 0.9595        | 34.0  | 646  | 1.0978          | 0.9621   | 0.9653   | 0.9681 |
| 0.9619        | 35.0  | 665  | 1.1000          | 0.9621   | 0.9648   | 0.9645 |
| 0.9634        | 36.0  | 684  | 1.1140          | 0.9655   | 0.9679   | 0.9669 |
| 0.9554        | 37.0  | 703  | 1.1082          | 0.9655   | 0.9679   | 0.9669 |
| 0.9644        | 38.0  | 722  | 1.1166          | 0.9655   | 0.9681   | 0.9681 |


### Framework versions

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