---
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_2
  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: 0.9586206896551724
    - name: Recall
      type: recall
      value: 0.9621148459383753
---

<!-- 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_2

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: 1.1405
- Accuracy: 0.9586
- F1 Score: 0.9620
- Recall: 0.9621

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:------:|
| 2.8182        | 1.0   | 19   | 2.7982          | 0.2966   | 0.2243   | 0.2444 |
| 2.7152        | 2.0   | 38   | 2.6468          | 0.3793   | 0.2689   | 0.3032 |
| 2.5094        | 3.0   | 57   | 2.4150          | 0.5241   | 0.4335   | 0.4481 |
| 2.1993        | 4.0   | 76   | 2.0760          | 0.7172   | 0.7150   | 0.6964 |
| 1.7513        | 5.0   | 95   | 1.7070          | 0.8069   | 0.8177   | 0.8141 |
| 1.4469        | 6.0   | 114  | 1.4631          | 0.8586   | 0.8728   | 0.8742 |
| 1.2482        | 7.0   | 133  | 1.3515          | 0.8759   | 0.8882   | 0.8890 |
| 1.2058        | 8.0   | 152  | 1.3018          | 0.8897   | 0.8990   | 0.8998 |
| 1.1470        | 9.0   | 171  | 1.2735          | 0.9069   | 0.9141   | 0.9169 |
| 1.0887        | 10.0  | 190  | 1.2533          | 0.9207   | 0.9291   | 0.9306 |
| 1.0903        | 11.0  | 209  | 1.2413          | 0.9103   | 0.9182   | 0.9159 |
| 1.0576        | 12.0  | 228  | 1.2260          | 0.9207   | 0.9286   | 0.9317 |
| 1.0231        | 13.0  | 247  | 1.2594          | 0.9207   | 0.9278   | 0.9303 |
| 1.0264        | 14.0  | 266  | 1.2164          | 0.9276   | 0.9339   | 0.9305 |
| 1.0175        | 15.0  | 285  | 1.2294          | 0.9241   | 0.9301   | 0.9267 |
| 1.0135        | 16.0  | 304  | 1.2143          | 0.9345   | 0.9406   | 0.9402 |
| 1.0178        | 17.0  | 323  | 1.2314          | 0.9276   | 0.9351   | 0.9380 |
| 0.9823        | 18.0  | 342  | 1.2160          | 0.9310   | 0.9373   | 0.9365 |
| 0.9965        | 19.0  | 361  | 1.2154          | 0.9172   | 0.9232   | 0.9206 |
| 0.9854        | 20.0  | 380  | 1.1846          | 0.9345   | 0.9411   | 0.9415 |
| 0.9807        | 21.0  | 399  | 1.2096          | 0.9345   | 0.9414   | 0.9414 |
| 0.9860        | 22.0  | 418  | 1.1996          | 0.9276   | 0.9338   | 0.9316 |
| 0.9796        | 23.0  | 437  | 1.1967          | 0.9310   | 0.9365   | 0.9317 |
| 0.9826        | 24.0  | 456  | 1.2180          | 0.9172   | 0.9239   | 0.9183 |
| 0.9809        | 25.0  | 475  | 1.2030          | 0.9345   | 0.9405   | 0.9378 |
| 0.9803        | 26.0  | 494  | 1.1866          | 0.9345   | 0.9403   | 0.9389 |
| 0.9748        | 27.0  | 513  | 1.1626          | 0.9448   | 0.9497   | 0.9487 |
| 0.9659        | 28.0  | 532  | 1.1405          | 0.9586   | 0.9620   | 0.9621 |
| 0.9718        | 29.0  | 551  | 1.1410          | 0.9483   | 0.9525   | 0.9525 |
| 0.9668        | 30.0  | 570  | 1.1485          | 0.9552   | 0.9589   | 0.9584 |
| 0.9715        | 31.0  | 589  | 1.1423          | 0.9448   | 0.9499   | 0.9502 |
| 0.9729        | 32.0  | 608  | 1.1560          | 0.9483   | 0.9535   | 0.9550 |
| 0.9766        | 33.0  | 627  | 1.1721          | 0.9483   | 0.9541   | 0.9561 |
| 0.9687        | 34.0  | 646  | 1.1706          | 0.9448   | 0.9509   | 0.9524 |
| 0.9769        | 35.0  | 665  | 1.1539          | 0.9345   | 0.9410   | 0.9403 |
| 0.9609        | 36.0  | 684  | 1.1552          | 0.9483   | 0.9539   | 0.9549 |
| 0.9587        | 37.0  | 703  | 1.1565          | 0.9517   | 0.9569   | 0.9597 |
| 0.9673        | 38.0  | 722  | 1.1675          | 0.9483   | 0.9537   | 0.9562 |


### Framework versions

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