---
license: apache-2.0
base_model: facebook/deit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_5x_deit_base_sgd_00001_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: 0.17073170731707318
---

<!-- 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_base_sgd_00001_fold5

This model is a fine-tuned version of [facebook/deit-base-patch16-224](https://huggingface.co/facebook/deit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3712
- Accuracy: 0.1707

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4308        | 1.0   | 28   | 1.3745          | 0.2195   |
| 1.4381        | 2.0   | 56   | 1.3744          | 0.1951   |
| 1.4303        | 3.0   | 84   | 1.3742          | 0.1951   |
| 1.4196        | 4.0   | 112  | 1.3741          | 0.1951   |
| 1.4462        | 5.0   | 140  | 1.3739          | 0.1951   |
| 1.4289        | 6.0   | 168  | 1.3738          | 0.1951   |
| 1.4513        | 7.0   | 196  | 1.3737          | 0.1951   |
| 1.454         | 8.0   | 224  | 1.3736          | 0.1951   |
| 1.4395        | 9.0   | 252  | 1.3734          | 0.1951   |
| 1.4245        | 10.0  | 280  | 1.3733          | 0.1951   |
| 1.4477        | 11.0  | 308  | 1.3732          | 0.1951   |
| 1.4479        | 12.0  | 336  | 1.3731          | 0.1951   |
| 1.4264        | 13.0  | 364  | 1.3730          | 0.1951   |
| 1.4179        | 14.0  | 392  | 1.3729          | 0.1951   |
| 1.4497        | 15.0  | 420  | 1.3728          | 0.1951   |
| 1.4379        | 16.0  | 448  | 1.3727          | 0.1951   |
| 1.4414        | 17.0  | 476  | 1.3726          | 0.1951   |
| 1.452         | 18.0  | 504  | 1.3725          | 0.1951   |
| 1.4605        | 19.0  | 532  | 1.3724          | 0.1951   |
| 1.4508        | 20.0  | 560  | 1.3723          | 0.1951   |
| 1.4355        | 21.0  | 588  | 1.3722          | 0.1951   |
| 1.4232        | 22.0  | 616  | 1.3721          | 0.1951   |
| 1.4314        | 23.0  | 644  | 1.3721          | 0.1951   |
| 1.4464        | 24.0  | 672  | 1.3720          | 0.1951   |
| 1.4347        | 25.0  | 700  | 1.3719          | 0.1951   |
| 1.4331        | 26.0  | 728  | 1.3719          | 0.1707   |
| 1.4315        | 27.0  | 756  | 1.3718          | 0.1707   |
| 1.4463        | 28.0  | 784  | 1.3717          | 0.1707   |
| 1.4461        | 29.0  | 812  | 1.3717          | 0.1707   |
| 1.4576        | 30.0  | 840  | 1.3716          | 0.1707   |
| 1.4346        | 31.0  | 868  | 1.3716          | 0.1707   |
| 1.4439        | 32.0  | 896  | 1.3715          | 0.1707   |
| 1.4382        | 33.0  | 924  | 1.3715          | 0.1707   |
| 1.4458        | 34.0  | 952  | 1.3715          | 0.1707   |
| 1.4323        | 35.0  | 980  | 1.3714          | 0.1707   |
| 1.4333        | 36.0  | 1008 | 1.3714          | 0.1707   |
| 1.4238        | 37.0  | 1036 | 1.3714          | 0.1707   |
| 1.4188        | 38.0  | 1064 | 1.3713          | 0.1707   |
| 1.4355        | 39.0  | 1092 | 1.3713          | 0.1707   |
| 1.4499        | 40.0  | 1120 | 1.3713          | 0.1707   |
| 1.4289        | 41.0  | 1148 | 1.3713          | 0.1707   |
| 1.4376        | 42.0  | 1176 | 1.3712          | 0.1707   |
| 1.4427        | 43.0  | 1204 | 1.3712          | 0.1707   |
| 1.4421        | 44.0  | 1232 | 1.3712          | 0.1707   |
| 1.4536        | 45.0  | 1260 | 1.3712          | 0.1707   |
| 1.4126        | 46.0  | 1288 | 1.3712          | 0.1707   |
| 1.4355        | 47.0  | 1316 | 1.3712          | 0.1707   |
| 1.4384        | 48.0  | 1344 | 1.3712          | 0.1707   |
| 1.431         | 49.0  | 1372 | 1.3712          | 0.1707   |
| 1.4525        | 50.0  | 1400 | 1.3712          | 0.1707   |


### Framework versions

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