---
license: apache-2.0
base_model: facebook/deit-small-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_5x_deit_small_sgd_00001_fold1
  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_5x_deit_small_sgd_00001_fold1

This model is a fine-tuned version of [facebook/deit-small-patch16-224](https://huggingface.co/facebook/deit-small-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6074
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4194        | 1.0   | 27   | 1.6162          | 0.2222   |
| 1.4315        | 2.0   | 54   | 1.6158          | 0.2222   |
| 1.4532        | 3.0   | 81   | 1.6154          | 0.2222   |
| 1.4652        | 4.0   | 108  | 1.6150          | 0.2222   |
| 1.4244        | 5.0   | 135  | 1.6147          | 0.2222   |
| 1.4622        | 6.0   | 162  | 1.6143          | 0.2222   |
| 1.4528        | 7.0   | 189  | 1.6140          | 0.2222   |
| 1.4262        | 8.0   | 216  | 1.6136          | 0.2222   |
| 1.4181        | 9.0   | 243  | 1.6133          | 0.2222   |
| 1.4163        | 10.0  | 270  | 1.6130          | 0.2222   |
| 1.4463        | 11.0  | 297  | 1.6127          | 0.2222   |
| 1.4137        | 12.0  | 324  | 1.6124          | 0.2222   |
| 1.4131        | 13.0  | 351  | 1.6121          | 0.2222   |
| 1.4148        | 14.0  | 378  | 1.6118          | 0.2222   |
| 1.444         | 15.0  | 405  | 1.6115          | 0.2222   |
| 1.4135        | 16.0  | 432  | 1.6113          | 0.2222   |
| 1.4356        | 17.0  | 459  | 1.6110          | 0.2222   |
| 1.4146        | 18.0  | 486  | 1.6108          | 0.2222   |
| 1.4096        | 19.0  | 513  | 1.6105          | 0.2222   |
| 1.4038        | 20.0  | 540  | 1.6103          | 0.2222   |
| 1.3926        | 21.0  | 567  | 1.6101          | 0.2222   |
| 1.4332        | 22.0  | 594  | 1.6099          | 0.2222   |
| 1.4214        | 23.0  | 621  | 1.6097          | 0.2222   |
| 1.4083        | 24.0  | 648  | 1.6095          | 0.2222   |
| 1.4271        | 25.0  | 675  | 1.6093          | 0.2222   |
| 1.4496        | 26.0  | 702  | 1.6091          | 0.2222   |
| 1.4117        | 27.0  | 729  | 1.6090          | 0.2222   |
| 1.403         | 28.0  | 756  | 1.6088          | 0.2222   |
| 1.3913        | 29.0  | 783  | 1.6087          | 0.2222   |
| 1.4302        | 30.0  | 810  | 1.6085          | 0.2222   |
| 1.4037        | 31.0  | 837  | 1.6084          | 0.2222   |
| 1.4442        | 32.0  | 864  | 1.6083          | 0.2222   |
| 1.4272        | 33.0  | 891  | 1.6082          | 0.2222   |
| 1.4095        | 34.0  | 918  | 1.6080          | 0.2222   |
| 1.4234        | 35.0  | 945  | 1.6079          | 0.2222   |
| 1.4343        | 36.0  | 972  | 1.6079          | 0.2222   |
| 1.4253        | 37.0  | 999  | 1.6078          | 0.2222   |
| 1.4109        | 38.0  | 1026 | 1.6077          | 0.2222   |
| 1.4096        | 39.0  | 1053 | 1.6076          | 0.2222   |
| 1.3772        | 40.0  | 1080 | 1.6076          | 0.2222   |
| 1.4046        | 41.0  | 1107 | 1.6075          | 0.2222   |
| 1.384         | 42.0  | 1134 | 1.6075          | 0.2222   |
| 1.4202        | 43.0  | 1161 | 1.6075          | 0.2222   |
| 1.3963        | 44.0  | 1188 | 1.6074          | 0.2222   |
| 1.4183        | 45.0  | 1215 | 1.6074          | 0.2222   |
| 1.3888        | 46.0  | 1242 | 1.6074          | 0.2222   |
| 1.4088        | 47.0  | 1269 | 1.6074          | 0.2222   |
| 1.393         | 48.0  | 1296 | 1.6074          | 0.2222   |
| 1.4397        | 49.0  | 1323 | 1.6074          | 0.2222   |
| 1.4472        | 50.0  | 1350 | 1.6074          | 0.2222   |


### Framework versions

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