---
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_fold2
  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: 0.2222222222222222
---

<!-- 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_fold2

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: 1.7073
- Accuracy: 0.2222

## 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    | 1.7237          | 0.2222   |
| 1.719         | 2.0   | 12   | 1.7228          | 0.2222   |
| 1.719         | 3.0   | 18   | 1.7220          | 0.2222   |
| 1.7128        | 4.0   | 24   | 1.7212          | 0.2222   |
| 1.7405        | 5.0   | 30   | 1.7204          | 0.2222   |
| 1.7405        | 6.0   | 36   | 1.7197          | 0.2222   |
| 1.6943        | 7.0   | 42   | 1.7190          | 0.2222   |
| 1.6943        | 8.0   | 48   | 1.7183          | 0.2222   |
| 1.6759        | 9.0   | 54   | 1.7176          | 0.2222   |
| 1.7158        | 10.0  | 60   | 1.7169          | 0.2222   |
| 1.7158        | 11.0  | 66   | 1.7162          | 0.2222   |
| 1.7024        | 12.0  | 72   | 1.7156          | 0.2222   |
| 1.7024        | 13.0  | 78   | 1.7150          | 0.2222   |
| 1.7744        | 14.0  | 84   | 1.7144          | 0.2222   |
| 1.7251        | 15.0  | 90   | 1.7139          | 0.2222   |
| 1.7251        | 16.0  | 96   | 1.7134          | 0.2222   |
| 1.6942        | 17.0  | 102  | 1.7129          | 0.2222   |
| 1.6942        | 18.0  | 108  | 1.7124          | 0.2222   |
| 1.7154        | 19.0  | 114  | 1.7120          | 0.2222   |
| 1.6829        | 20.0  | 120  | 1.7115          | 0.2222   |
| 1.6829        | 21.0  | 126  | 1.7111          | 0.2222   |
| 1.6559        | 22.0  | 132  | 1.7107          | 0.2222   |
| 1.6559        | 23.0  | 138  | 1.7104          | 0.2222   |
| 1.7194        | 24.0  | 144  | 1.7100          | 0.2222   |
| 1.6925        | 25.0  | 150  | 1.7097          | 0.2222   |
| 1.6925        | 26.0  | 156  | 1.7094          | 0.2222   |
| 1.6919        | 27.0  | 162  | 1.7091          | 0.2222   |
| 1.6919        | 28.0  | 168  | 1.7089          | 0.2222   |
| 1.6948        | 29.0  | 174  | 1.7086          | 0.2222   |
| 1.7059        | 30.0  | 180  | 1.7084          | 0.2222   |
| 1.7059        | 31.0  | 186  | 1.7082          | 0.2222   |
| 1.7337        | 32.0  | 192  | 1.7080          | 0.2222   |
| 1.7337        | 33.0  | 198  | 1.7079          | 0.2222   |
| 1.6587        | 34.0  | 204  | 1.7077          | 0.2222   |
| 1.7172        | 35.0  | 210  | 1.7076          | 0.2222   |
| 1.7172        | 36.0  | 216  | 1.7075          | 0.2222   |
| 1.7051        | 37.0  | 222  | 1.7075          | 0.2222   |
| 1.7051        | 38.0  | 228  | 1.7074          | 0.2222   |
| 1.6141        | 39.0  | 234  | 1.7074          | 0.2222   |
| 1.6784        | 40.0  | 240  | 1.7073          | 0.2222   |
| 1.6784        | 41.0  | 246  | 1.7073          | 0.2222   |
| 1.6991        | 42.0  | 252  | 1.7073          | 0.2222   |
| 1.6991        | 43.0  | 258  | 1.7073          | 0.2222   |
| 1.7247        | 44.0  | 264  | 1.7073          | 0.2222   |
| 1.6773        | 45.0  | 270  | 1.7073          | 0.2222   |
| 1.6773        | 46.0  | 276  | 1.7073          | 0.2222   |
| 1.6939        | 47.0  | 282  | 1.7073          | 0.2222   |
| 1.6939        | 48.0  | 288  | 1.7073          | 0.2222   |
| 1.6622        | 49.0  | 294  | 1.7073          | 0.2222   |
| 1.7192        | 50.0  | 300  | 1.7073          | 0.2222   |


### Framework versions

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