---
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_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: 0.2682926829268293
---

<!-- 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_0001_fold5

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: 1.3702
- Accuracy: 0.2683

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.5914        | 1.0   | 28   | 1.5102          | 0.2195   |
| 1.502         | 2.0   | 56   | 1.4998          | 0.2439   |
| 1.5359        | 3.0   | 84   | 1.4897          | 0.2439   |
| 1.4953        | 4.0   | 112  | 1.4806          | 0.2195   |
| 1.505         | 5.0   | 140  | 1.4721          | 0.2439   |
| 1.5366        | 6.0   | 168  | 1.4645          | 0.2439   |
| 1.5251        | 7.0   | 196  | 1.4572          | 0.2439   |
| 1.4698        | 8.0   | 224  | 1.4506          | 0.2439   |
| 1.4915        | 9.0   | 252  | 1.4443          | 0.2439   |
| 1.4618        | 10.0  | 280  | 1.4384          | 0.2439   |
| 1.4473        | 11.0  | 308  | 1.4329          | 0.2439   |
| 1.4682        | 12.0  | 336  | 1.4279          | 0.2439   |
| 1.4426        | 13.0  | 364  | 1.4233          | 0.2439   |
| 1.4128        | 14.0  | 392  | 1.4190          | 0.2683   |
| 1.4363        | 15.0  | 420  | 1.4150          | 0.2683   |
| 1.4383        | 16.0  | 448  | 1.4113          | 0.2683   |
| 1.4168        | 17.0  | 476  | 1.4079          | 0.2683   |
| 1.4317        | 18.0  | 504  | 1.4047          | 0.2683   |
| 1.4208        | 19.0  | 532  | 1.4016          | 0.2927   |
| 1.4021        | 20.0  | 560  | 1.3989          | 0.2927   |
| 1.4325        | 21.0  | 588  | 1.3963          | 0.2927   |
| 1.4072        | 22.0  | 616  | 1.3940          | 0.2927   |
| 1.3729        | 23.0  | 644  | 1.3918          | 0.2927   |
| 1.3955        | 24.0  | 672  | 1.3898          | 0.2927   |
| 1.3868        | 25.0  | 700  | 1.3879          | 0.2927   |
| 1.3985        | 26.0  | 728  | 1.3861          | 0.2683   |
| 1.3854        | 27.0  | 756  | 1.3845          | 0.2683   |
| 1.3968        | 28.0  | 784  | 1.3830          | 0.2683   |
| 1.3689        | 29.0  | 812  | 1.3816          | 0.2683   |
| 1.4069        | 30.0  | 840  | 1.3803          | 0.2683   |
| 1.387         | 31.0  | 868  | 1.3791          | 0.2683   |
| 1.3786        | 32.0  | 896  | 1.3780          | 0.2683   |
| 1.3773        | 33.0  | 924  | 1.3769          | 0.2683   |
| 1.3779        | 34.0  | 952  | 1.3760          | 0.2683   |
| 1.3797        | 35.0  | 980  | 1.3751          | 0.2683   |
| 1.3671        | 36.0  | 1008 | 1.3744          | 0.2683   |
| 1.3638        | 37.0  | 1036 | 1.3737          | 0.2683   |
| 1.3614        | 38.0  | 1064 | 1.3731          | 0.2683   |
| 1.3646        | 39.0  | 1092 | 1.3725          | 0.2683   |
| 1.3609        | 40.0  | 1120 | 1.3720          | 0.2683   |
| 1.3899        | 41.0  | 1148 | 1.3716          | 0.2683   |
| 1.3896        | 42.0  | 1176 | 1.3712          | 0.2683   |
| 1.3725        | 43.0  | 1204 | 1.3709          | 0.2683   |
| 1.3896        | 44.0  | 1232 | 1.3706          | 0.2683   |
| 1.3695        | 45.0  | 1260 | 1.3704          | 0.2683   |
| 1.3698        | 46.0  | 1288 | 1.3703          | 0.2683   |
| 1.3813        | 47.0  | 1316 | 1.3702          | 0.2683   |
| 1.3636        | 48.0  | 1344 | 1.3702          | 0.2683   |
| 1.3528        | 49.0  | 1372 | 1.3702          | 0.2683   |
| 1.3747        | 50.0  | 1400 | 1.3702          | 0.2683   |


### Framework versions

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