---
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_5x_deit_tiny_sgd_001_fold5
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: test
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.5121951219512195
---

<!-- 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. -->

# hushem_5x_deit_tiny_sgd_001_fold5

This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0480
- Accuracy: 0.5122

## 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: 0.001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4966        | 1.0   | 28   | 1.5748          | 0.2439   |
| 1.363         | 2.0   | 56   | 1.4510          | 0.2927   |
| 1.3445        | 3.0   | 84   | 1.3731          | 0.3902   |
| 1.2909        | 4.0   | 112  | 1.3148          | 0.3902   |
| 1.2782        | 5.0   | 140  | 1.2775          | 0.4146   |
| 1.2431        | 6.0   | 168  | 1.2527          | 0.4146   |
| 1.1698        | 7.0   | 196  | 1.2349          | 0.4634   |
| 1.1766        | 8.0   | 224  | 1.2144          | 0.4634   |
| 1.17          | 9.0   | 252  | 1.1948          | 0.4634   |
| 1.1062        | 10.0  | 280  | 1.1764          | 0.4390   |
| 1.0601        | 11.0  | 308  | 1.1840          | 0.4634   |
| 1.0566        | 12.0  | 336  | 1.1703          | 0.4634   |
| 1.0478        | 13.0  | 364  | 1.1443          | 0.4634   |
| 1.0482        | 14.0  | 392  | 1.1542          | 0.4634   |
| 1.0161        | 15.0  | 420  | 1.1465          | 0.4634   |
| 1.0335        | 16.0  | 448  | 1.1434          | 0.4634   |
| 0.9719        | 17.0  | 476  | 1.1475          | 0.4634   |
| 0.9588        | 18.0  | 504  | 1.1439          | 0.4634   |
| 1.0081        | 19.0  | 532  | 1.1431          | 0.4634   |
| 0.973         | 20.0  | 560  | 1.1304          | 0.4878   |
| 0.94          | 21.0  | 588  | 1.1093          | 0.4878   |
| 0.8982        | 22.0  | 616  | 1.1184          | 0.4878   |
| 0.9204        | 23.0  | 644  | 1.1332          | 0.4634   |
| 0.8435        | 24.0  | 672  | 1.1088          | 0.4878   |
| 0.8736        | 25.0  | 700  | 1.0913          | 0.4878   |
| 0.846         | 26.0  | 728  | 1.0897          | 0.4878   |
| 0.8446        | 27.0  | 756  | 1.0809          | 0.4878   |
| 0.8745        | 28.0  | 784  | 1.0794          | 0.4878   |
| 0.8251        | 29.0  | 812  | 1.0765          | 0.5122   |
| 0.8547        | 30.0  | 840  | 1.0870          | 0.4878   |
| 0.7939        | 31.0  | 868  | 1.0770          | 0.4878   |
| 0.7828        | 32.0  | 896  | 1.0780          | 0.4878   |
| 0.8106        | 33.0  | 924  | 1.0700          | 0.5122   |
| 0.784         | 34.0  | 952  | 1.0593          | 0.5122   |
| 0.7795        | 35.0  | 980  | 1.0615          | 0.4878   |
| 0.8007        | 36.0  | 1008 | 1.0592          | 0.4878   |
| 0.726         | 37.0  | 1036 | 1.0594          | 0.4878   |
| 0.7657        | 38.0  | 1064 | 1.0523          | 0.4878   |
| 0.7942        | 39.0  | 1092 | 1.0544          | 0.4878   |
| 0.7485        | 40.0  | 1120 | 1.0497          | 0.5122   |
| 0.7752        | 41.0  | 1148 | 1.0549          | 0.5122   |
| 0.7115        | 42.0  | 1176 | 1.0535          | 0.4878   |
| 0.7477        | 43.0  | 1204 | 1.0497          | 0.5122   |
| 0.769         | 44.0  | 1232 | 1.0484          | 0.5122   |
| 0.7292        | 45.0  | 1260 | 1.0496          | 0.5122   |
| 0.7475        | 46.0  | 1288 | 1.0482          | 0.5122   |
| 0.7629        | 47.0  | 1316 | 1.0480          | 0.5122   |
| 0.8           | 48.0  | 1344 | 1.0480          | 0.5122   |
| 0.7301        | 49.0  | 1372 | 1.0480          | 0.5122   |
| 0.738         | 50.0  | 1400 | 1.0480          | 0.5122   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0