---
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_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_1x_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: 1.6900
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 6    | 1.7081          | 0.2791   |
| 1.7325        | 2.0   | 12   | 1.7072          | 0.2791   |
| 1.7325        | 3.0   | 18   | 1.7063          | 0.2791   |
| 1.7152        | 4.0   | 24   | 1.7055          | 0.2791   |
| 1.6813        | 5.0   | 30   | 1.7046          | 0.2791   |
| 1.6813        | 6.0   | 36   | 1.7038          | 0.2791   |
| 1.6984        | 7.0   | 42   | 1.7030          | 0.2791   |
| 1.6984        | 8.0   | 48   | 1.7022          | 0.2791   |
| 1.7131        | 9.0   | 54   | 1.7014          | 0.2791   |
| 1.7337        | 10.0  | 60   | 1.7007          | 0.2791   |
| 1.7337        | 11.0  | 66   | 1.7000          | 0.2791   |
| 1.7143        | 12.0  | 72   | 1.6993          | 0.2791   |
| 1.7143        | 13.0  | 78   | 1.6987          | 0.2791   |
| 1.6884        | 14.0  | 84   | 1.6981          | 0.2791   |
| 1.7252        | 15.0  | 90   | 1.6975          | 0.2791   |
| 1.7252        | 16.0  | 96   | 1.6969          | 0.2791   |
| 1.7269        | 17.0  | 102  | 1.6963          | 0.2791   |
| 1.7269        | 18.0  | 108  | 1.6958          | 0.2791   |
| 1.6858        | 19.0  | 114  | 1.6953          | 0.2791   |
| 1.7013        | 20.0  | 120  | 1.6948          | 0.2791   |
| 1.7013        | 21.0  | 126  | 1.6943          | 0.2791   |
| 1.7051        | 22.0  | 132  | 1.6939          | 0.2791   |
| 1.7051        | 23.0  | 138  | 1.6935          | 0.2791   |
| 1.6834        | 24.0  | 144  | 1.6931          | 0.2791   |
| 1.6977        | 25.0  | 150  | 1.6927          | 0.2791   |
| 1.6977        | 26.0  | 156  | 1.6924          | 0.2791   |
| 1.7016        | 27.0  | 162  | 1.6920          | 0.2791   |
| 1.7016        | 28.0  | 168  | 1.6917          | 0.2791   |
| 1.7242        | 29.0  | 174  | 1.6915          | 0.2791   |
| 1.6808        | 30.0  | 180  | 1.6912          | 0.2791   |
| 1.6808        | 31.0  | 186  | 1.6910          | 0.2791   |
| 1.7032        | 32.0  | 192  | 1.6908          | 0.2791   |
| 1.7032        | 33.0  | 198  | 1.6906          | 0.2791   |
| 1.6261        | 34.0  | 204  | 1.6905          | 0.2791   |
| 1.7412        | 35.0  | 210  | 1.6903          | 0.2791   |
| 1.7412        | 36.0  | 216  | 1.6902          | 0.2791   |
| 1.6899        | 37.0  | 222  | 1.6901          | 0.2791   |
| 1.6899        | 38.0  | 228  | 1.6901          | 0.2791   |
| 1.6944        | 39.0  | 234  | 1.6900          | 0.2791   |
| 1.6965        | 40.0  | 240  | 1.6900          | 0.2791   |
| 1.6965        | 41.0  | 246  | 1.6900          | 0.2791   |
| 1.6787        | 42.0  | 252  | 1.6900          | 0.2791   |
| 1.6787        | 43.0  | 258  | 1.6900          | 0.2791   |
| 1.6617        | 44.0  | 264  | 1.6900          | 0.2791   |
| 1.7215        | 45.0  | 270  | 1.6900          | 0.2791   |
| 1.7215        | 46.0  | 276  | 1.6900          | 0.2791   |
| 1.6881        | 47.0  | 282  | 1.6900          | 0.2791   |
| 1.6881        | 48.0  | 288  | 1.6900          | 0.2791   |
| 1.6823        | 49.0  | 294  | 1.6900          | 0.2791   |
| 1.7275        | 50.0  | 300  | 1.6900          | 0.2791   |


### Framework versions

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