---
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_1x_deit_tiny_sgd_0001_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: 0.24390243902439024
---

<!-- 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_1x_deit_tiny_sgd_0001_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: 1.5523
- Accuracy: 0.2439

## 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: 0.0001
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 6    | 1.7547          | 0.2439   |
| 1.7078        | 2.0   | 12   | 1.7422          | 0.2439   |
| 1.7078        | 3.0   | 18   | 1.7303          | 0.2439   |
| 1.6827        | 4.0   | 24   | 1.7187          | 0.2439   |
| 1.6676        | 5.0   | 30   | 1.7076          | 0.2439   |
| 1.6676        | 6.0   | 36   | 1.6970          | 0.2439   |
| 1.6669        | 7.0   | 42   | 1.6882          | 0.2439   |
| 1.6669        | 8.0   | 48   | 1.6793          | 0.2439   |
| 1.5935        | 9.0   | 54   | 1.6701          | 0.2439   |
| 1.6316        | 10.0  | 60   | 1.6617          | 0.2439   |
| 1.6316        | 11.0  | 66   | 1.6538          | 0.2439   |
| 1.6324        | 12.0  | 72   | 1.6460          | 0.2439   |
| 1.6324        | 13.0  | 78   | 1.6387          | 0.2439   |
| 1.5842        | 14.0  | 84   | 1.6318          | 0.2439   |
| 1.5897        | 15.0  | 90   | 1.6256          | 0.2439   |
| 1.5897        | 16.0  | 96   | 1.6199          | 0.2439   |
| 1.5943        | 17.0  | 102  | 1.6144          | 0.2439   |
| 1.5943        | 18.0  | 108  | 1.6092          | 0.2195   |
| 1.5586        | 19.0  | 114  | 1.6040          | 0.2195   |
| 1.5924        | 20.0  | 120  | 1.5990          | 0.2195   |
| 1.5924        | 21.0  | 126  | 1.5945          | 0.2195   |
| 1.5676        | 22.0  | 132  | 1.5902          | 0.2195   |
| 1.5676        | 23.0  | 138  | 1.5862          | 0.2195   |
| 1.5352        | 24.0  | 144  | 1.5823          | 0.2195   |
| 1.5842        | 25.0  | 150  | 1.5786          | 0.2195   |
| 1.5842        | 26.0  | 156  | 1.5752          | 0.2195   |
| 1.5461        | 27.0  | 162  | 1.5723          | 0.2195   |
| 1.5461        | 28.0  | 168  | 1.5695          | 0.2195   |
| 1.551         | 29.0  | 174  | 1.5671          | 0.2439   |
| 1.5549        | 30.0  | 180  | 1.5649          | 0.2439   |
| 1.5549        | 31.0  | 186  | 1.5628          | 0.2439   |
| 1.5532        | 32.0  | 192  | 1.5610          | 0.2439   |
| 1.5532        | 33.0  | 198  | 1.5594          | 0.2439   |
| 1.5006        | 34.0  | 204  | 1.5578          | 0.2439   |
| 1.5134        | 35.0  | 210  | 1.5565          | 0.2439   |
| 1.5134        | 36.0  | 216  | 1.5553          | 0.2439   |
| 1.5386        | 37.0  | 222  | 1.5543          | 0.2439   |
| 1.5386        | 38.0  | 228  | 1.5536          | 0.2439   |
| 1.5372        | 39.0  | 234  | 1.5530          | 0.2439   |
| 1.528         | 40.0  | 240  | 1.5526          | 0.2439   |
| 1.528         | 41.0  | 246  | 1.5524          | 0.2439   |
| 1.5555        | 42.0  | 252  | 1.5523          | 0.2439   |
| 1.5555        | 43.0  | 258  | 1.5523          | 0.2439   |
| 1.509         | 44.0  | 264  | 1.5523          | 0.2439   |
| 1.5379        | 45.0  | 270  | 1.5523          | 0.2439   |
| 1.5379        | 46.0  | 276  | 1.5523          | 0.2439   |
| 1.5588        | 47.0  | 282  | 1.5523          | 0.2439   |
| 1.5588        | 48.0  | 288  | 1.5523          | 0.2439   |
| 1.509         | 49.0  | 294  | 1.5523          | 0.2439   |
| 1.5414        | 50.0  | 300  | 1.5523          | 0.2439   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1