---
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_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: 0.9619377162629758
    - name: Recall
      type: recall
      value: 0.9645564195827585
---

<!-- 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_5

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: 1.1404
- Accuracy: 0.9619
- F1 Score: 0.9640
- Recall: 0.9646

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:------:|
| 2.8530        | 1.0   | 19   | 2.8472          | 0.2457   | 0.1618   | 0.2585 |
| 2.7569        | 2.0   | 38   | 2.6803          | 0.3460   | 0.2744   | 0.3182 |
| 2.5095        | 3.0   | 57   | 2.4824          | 0.5329   | 0.4757   | 0.4751 |
| 2.2538        | 4.0   | 76   | 2.2623          | 0.6436   | 0.6377   | 0.6053 |
| 1.8808        | 5.0   | 95   | 1.9165          | 0.7855   | 0.7984   | 0.7868 |
| 1.5094        | 6.0   | 114  | 1.5722          | 0.8720   | 0.8806   | 0.8797 |
| 1.2994        | 7.0   | 133  | 1.3893          | 0.8927   | 0.8983   | 0.8981 |
| 1.1850        | 8.0   | 152  | 1.3009          | 0.9135   | 0.9173   | 0.9189 |
| 1.0969        | 9.0   | 171  | 1.2608          | 0.9239   | 0.9300   | 0.9365 |
| 1.0729        | 10.0  | 190  | 1.2305          | 0.9377   | 0.9417   | 0.9437 |
| 1.0772        | 11.0  | 209  | 1.2142          | 0.9412   | 0.9445   | 0.9474 |
| 1.0385        | 12.0  | 228  | 1.1961          | 0.9481   | 0.9508   | 0.9524 |
| 1.0451        | 13.0  | 247  | 1.1773          | 0.9481   | 0.9514   | 0.9524 |
| 1.0382        | 14.0  | 266  | 1.1736          | 0.9516   | 0.9550   | 0.9561 |
| 1.0027        | 15.0  | 285  | 1.1668          | 0.9446   | 0.9486   | 0.9512 |
| 1.0166        | 16.0  | 304  | 1.1624          | 0.9446   | 0.9489   | 0.9525 |
| 1.0117        | 17.0  | 323  | 1.1576          | 0.9481   | 0.9506   | 0.9511 |
| 0.9923        | 18.0  | 342  | 1.1607          | 0.9446   | 0.9481   | 0.9486 |
| 0.9858        | 19.0  | 361  | 1.1551          | 0.9446   | 0.9489   | 0.9499 |
| 0.9924        | 20.0  | 380  | 1.1926          | 0.9377   | 0.9414   | 0.9384 |
| 0.9967        | 21.0  | 399  | 1.1682          | 0.9481   | 0.9507   | 0.9496 |
| 0.9727        | 22.0  | 418  | 1.1736          | 0.9446   | 0.9482   | 0.9461 |
| 0.9704        | 23.0  | 437  | 1.1639          | 0.9516   | 0.9544   | 0.9522 |
| 0.9733        | 24.0  | 456  | 1.1616          | 0.9481   | 0.9516   | 0.9536 |
| 0.9721        | 25.0  | 475  | 1.1662          | 0.9446   | 0.9482   | 0.9461 |
| 0.9680        | 26.0  | 494  | 1.1546          | 0.9481   | 0.9516   | 0.9511 |
| 0.9649        | 27.0  | 513  | 1.1476          | 0.9550   | 0.9582   | 0.9571 |
| 0.9737        | 28.0  | 532  | 1.1391          | 0.9550   | 0.9584   | 0.9584 |
| 0.9751        | 29.0  | 551  | 1.1496          | 0.9550   | 0.9580   | 0.9558 |
| 0.9702        | 30.0  | 570  | 1.1402          | 0.9550   | 0.9581   | 0.9597 |
| 0.9657        | 31.0  | 589  | 1.1368          | 0.9585   | 0.9610   | 0.9621 |
| 0.9674        | 32.0  | 608  | 1.1334          | 0.9550   | 0.9581   | 0.9597 |
| 0.9623        | 33.0  | 627  | 1.1573          | 0.9550   | 0.9574   | 0.9558 |
| 0.9718        | 34.0  | 646  | 1.1462          | 0.9585   | 0.9606   | 0.9595 |
| 0.9699        | 35.0  | 665  | 1.1404          | 0.9619   | 0.9640   | 0.9646 |
| 0.9699        | 36.0  | 684  | 1.1588          | 0.9516   | 0.9551   | 0.9572 |
| 0.9673        | 37.0  | 703  | 1.1423          | 0.9585   | 0.9615   | 0.9621 |
| 0.9611        | 38.0  | 722  | 1.1642          | 0.9481   | 0.9518   | 0.9485 |
| 0.9566        | 39.0  | 741  | 1.1492          | 0.9550   | 0.9580   | 0.9585 |
| 0.9627        | 40.0  | 760  | 1.1508          | 0.9585   | 0.9610   | 0.9621 |
| 0.9546        | 41.0  | 779  | 1.1408          | 0.9619   | 0.9640   | 0.9646 |
| 0.9604        | 42.0  | 798  | 1.1421          | 0.9619   | 0.9640   | 0.9646 |


### Framework versions

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