---
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_00001_fold3
  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: 0.27906976744186046
---

<!-- 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_00001_fold3

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: 1.6587
- Accuracy: 0.2791

## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.5526        | 1.0   | 28   | 1.7069          | 0.2791   |
| 1.5173        | 2.0   | 56   | 1.7047          | 0.2791   |
| 1.5161        | 3.0   | 84   | 1.7025          | 0.2791   |
| 1.5055        | 4.0   | 112  | 1.7004          | 0.2791   |
| 1.4587        | 5.0   | 140  | 1.6983          | 0.2791   |
| 1.5199        | 6.0   | 168  | 1.6963          | 0.2791   |
| 1.5621        | 7.0   | 196  | 1.6943          | 0.2791   |
| 1.5165        | 8.0   | 224  | 1.6925          | 0.2791   |
| 1.5226        | 9.0   | 252  | 1.6906          | 0.2791   |
| 1.4955        | 10.0  | 280  | 1.6889          | 0.2791   |
| 1.5136        | 11.0  | 308  | 1.6873          | 0.2791   |
| 1.5328        | 12.0  | 336  | 1.6856          | 0.2791   |
| 1.4996        | 13.0  | 364  | 1.6840          | 0.2791   |
| 1.5073        | 14.0  | 392  | 1.6824          | 0.2791   |
| 1.566         | 15.0  | 420  | 1.6809          | 0.2791   |
| 1.501         | 16.0  | 448  | 1.6795          | 0.2791   |
| 1.4781        | 17.0  | 476  | 1.6780          | 0.2791   |
| 1.5327        | 18.0  | 504  | 1.6766          | 0.2791   |
| 1.4922        | 19.0  | 532  | 1.6753          | 0.2791   |
| 1.5682        | 20.0  | 560  | 1.6741          | 0.2791   |
| 1.4804        | 21.0  | 588  | 1.6729          | 0.2791   |
| 1.4661        | 22.0  | 616  | 1.6719          | 0.2791   |
| 1.5385        | 23.0  | 644  | 1.6708          | 0.2791   |
| 1.4844        | 24.0  | 672  | 1.6698          | 0.2791   |
| 1.583         | 25.0  | 700  | 1.6688          | 0.2791   |
| 1.4741        | 26.0  | 728  | 1.6678          | 0.2791   |
| 1.4816        | 27.0  | 756  | 1.6669          | 0.2791   |
| 1.4922        | 28.0  | 784  | 1.6662          | 0.2791   |
| 1.5132        | 29.0  | 812  | 1.6654          | 0.2791   |
| 1.4828        | 30.0  | 840  | 1.6647          | 0.2791   |
| 1.4775        | 31.0  | 868  | 1.6640          | 0.2791   |
| 1.4969        | 32.0  | 896  | 1.6634          | 0.2791   |
| 1.5111        | 33.0  | 924  | 1.6627          | 0.2791   |
| 1.4897        | 34.0  | 952  | 1.6621          | 0.2791   |
| 1.485         | 35.0  | 980  | 1.6616          | 0.2791   |
| 1.5295        | 36.0  | 1008 | 1.6612          | 0.2791   |
| 1.4993        | 37.0  | 1036 | 1.6607          | 0.2791   |
| 1.4874        | 38.0  | 1064 | 1.6603          | 0.2791   |
| 1.5091        | 39.0  | 1092 | 1.6600          | 0.2791   |
| 1.4861        | 40.0  | 1120 | 1.6597          | 0.2791   |
| 1.5191        | 41.0  | 1148 | 1.6595          | 0.2791   |
| 1.4786        | 42.0  | 1176 | 1.6593          | 0.2791   |
| 1.4918        | 43.0  | 1204 | 1.6591          | 0.2791   |
| 1.5394        | 44.0  | 1232 | 1.6589          | 0.2791   |
| 1.4962        | 45.0  | 1260 | 1.6588          | 0.2791   |
| 1.4846        | 46.0  | 1288 | 1.6588          | 0.2791   |
| 1.4732        | 47.0  | 1316 | 1.6587          | 0.2791   |
| 1.4909        | 48.0  | 1344 | 1.6587          | 0.2791   |
| 1.4794        | 49.0  | 1372 | 1.6587          | 0.2791   |
| 1.4677        | 50.0  | 1400 | 1.6587          | 0.2791   |


### Framework versions

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