---
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_v3
  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: 0.9519230769230769
    - name: Recall
      type: recall
      value: 0.9579300074460163
---

<!-- 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_v3

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: 1.1298
- Accuracy: 0.9519
- F1 Score: 0.9537
- Recall: 0.9579

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:------:|
| 2.8252        | 1.0   | 20   | 2.8294          | 0.2532   | 0.1757   | 0.2799 |
| 2.6170        | 2.0   | 40   | 2.6009          | 0.4231   | 0.3643   | 0.4176 |
| 2.3206        | 3.0   | 60   | 2.3003          | 0.6282   | 0.6023   | 0.6150 |
| 1.9316        | 4.0   | 80   | 1.9340          | 0.7468   | 0.7536   | 0.7418 |
| 1.6434        | 5.0   | 100  | 1.6591          | 0.8301   | 0.8350   | 0.8313 |
| 1.4153        | 6.0   | 120  | 1.4709          | 0.8718   | 0.8757   | 0.8768 |
| 1.2545        | 7.0   | 140  | 1.3896          | 0.8846   | 0.8842   | 0.8805 |
| 1.2233        | 8.0   | 160  | 1.3060          | 0.9006   | 0.9020   | 0.8985 |
| 1.1294        | 9.0   | 180  | 1.2383          | 0.9295   | 0.9305   | 0.9327 |
| 1.1183        | 10.0  | 200  | 1.2321          | 0.9167   | 0.9188   | 0.9187 |
| 1.1030        | 11.0  | 220  | 1.2141          | 0.9263   | 0.9277   | 0.9273 |
| 1.0461        | 12.0  | 240  | 1.1977          | 0.9327   | 0.9341   | 0.9346 |
| 1.0356        | 13.0  | 260  | 1.1742          | 0.9327   | 0.9345   | 0.9359 |
| 1.0387        | 14.0  | 280  | 1.1660          | 0.9295   | 0.9322   | 0.9366 |
| 1.0136        | 15.0  | 300  | 1.1681          | 0.9295   | 0.9318   | 0.9359 |
| 1.0312        | 16.0  | 320  | 1.1628          | 0.9295   | 0.9316   | 0.9346 |
| 1.0127        | 17.0  | 340  | 1.1365          | 0.9391   | 0.9409   | 0.9420 |
| 1.0043        | 18.0  | 360  | 1.1322          | 0.9423   | 0.9439   | 0.9444 |
| 0.9970        | 19.0  | 380  | 1.1653          | 0.9455   | 0.9473   | 0.9532 |
| 1.0022        | 20.0  | 400  | 1.1536          | 0.9359   | 0.9380   | 0.9415 |
| 1.0002        | 21.0  | 420  | 1.1603          | 0.9391   | 0.9412   | 0.9469 |
| 1.0062        | 22.0  | 440  | 1.1409          | 0.9455   | 0.9470   | 0.9518 |
| 0.9826        | 23.0  | 460  | 1.1523          | 0.9423   | 0.9437   | 0.9415 |
| 0.9858        | 24.0  | 480  | 1.1611          | 0.9455   | 0.9472   | 0.9513 |
| 0.9753        | 25.0  | 500  | 1.1412          | 0.9455   | 0.9472   | 0.9506 |
| 0.9730        | 26.0  | 520  | 1.1605          | 0.9423   | 0.9441   | 0.9427 |
| 0.9833        | 27.0  | 540  | 1.1281          | 0.9519   | 0.9531   | 0.9555 |
| 0.9765        | 28.0  | 560  | 1.1411          | 0.9487   | 0.9503   | 0.9501 |
| 0.9791        | 29.0  | 580  | 1.1365          | 0.9487   | 0.9511   | 0.9555 |
| 0.9748        | 30.0  | 600  | 1.1481          | 0.9391   | 0.9415   | 0.9450 |
| 0.9725        | 31.0  | 620  | 1.1567          | 0.9359   | 0.9370   | 0.9366 |
| 0.9645        | 32.0  | 640  | 1.1298          | 0.9519   | 0.9537   | 0.9579 |
| 0.9599        | 33.0  | 660  | 1.1275          | 0.9487   | 0.9500   | 0.9518 |
| 0.9701        | 34.0  | 680  | 1.1281          | 0.9519   | 0.9530   | 0.9543 |
| 0.9785        | 35.0  | 700  | 1.1293          | 0.9455   | 0.9472   | 0.9506 |
| 0.9714        | 36.0  | 720  | 1.1466          | 0.9455   | 0.9473   | 0.9513 |
| 0.9687        | 37.0  | 740  | 1.1502          | 0.9423   | 0.9447   | 0.9501 |
| 0.9581        | 38.0  | 760  | 1.1606          | 0.9391   | 0.9415   | 0.9464 |
| 0.9675        | 39.0  | 780  | 1.1502          | 0.9423   | 0.9442   | 0.9462 |
| 0.9697        | 40.0  | 800  | 1.1641          | 0.9391   | 0.9414   | 0.9476 |
| 0.9664        | 41.0  | 820  | 1.1442          | 0.9455   | 0.9475   | 0.9523 |
| 0.9567        | 42.0  | 840  | 1.1395          | 0.9423   | 0.9441   | 0.9462 |
| 0.9716        | 43.0  | 860  | 1.1537          | 0.9359   | 0.9380   | 0.9415 |


### Framework versions

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