---
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_rms_001_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: 0.6585365853658537
---

<!-- 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_rms_001_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: 1.2275
- Accuracy: 0.6585

## 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: 0.001
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.7524        | 1.0   | 28   | 1.5298          | 0.2439   |
| 1.4312        | 2.0   | 56   | 1.4291          | 0.2683   |
| 1.3924        | 3.0   | 84   | 1.4059          | 0.2927   |
| 1.4173        | 4.0   | 112  | 1.3938          | 0.2683   |
| 1.3939        | 5.0   | 140  | 1.3790          | 0.2683   |
| 1.3863        | 6.0   | 168  | 1.4164          | 0.2439   |
| 1.3865        | 7.0   | 196  | 1.3790          | 0.2683   |
| 1.394         | 8.0   | 224  | 1.3790          | 0.2683   |
| 1.3883        | 9.0   | 252  | 1.4097          | 0.2683   |
| 1.3472        | 10.0  | 280  | 1.2478          | 0.4390   |
| 1.3905        | 11.0  | 308  | 1.2068          | 0.3902   |
| 1.1031        | 12.0  | 336  | 1.2038          | 0.4390   |
| 1.1503        | 13.0  | 364  | 1.0846          | 0.4634   |
| 1.2064        | 14.0  | 392  | 1.1395          | 0.4146   |
| 1.1249        | 15.0  | 420  | 1.1544          | 0.4146   |
| 1.1285        | 16.0  | 448  | 1.0714          | 0.4634   |
| 1.1149        | 17.0  | 476  | 0.9771          | 0.6098   |
| 1.0493        | 18.0  | 504  | 0.9974          | 0.4634   |
| 0.9938        | 19.0  | 532  | 0.9792          | 0.5366   |
| 1.0212        | 20.0  | 560  | 0.9949          | 0.5854   |
| 0.9943        | 21.0  | 588  | 1.0078          | 0.5366   |
| 1.0044        | 22.0  | 616  | 0.9007          | 0.5366   |
| 1.0661        | 23.0  | 644  | 1.2742          | 0.4878   |
| 0.9523        | 24.0  | 672  | 0.9851          | 0.6829   |
| 0.8733        | 25.0  | 700  | 0.9430          | 0.5854   |
| 0.8075        | 26.0  | 728  | 0.9660          | 0.6585   |
| 0.9128        | 27.0  | 756  | 0.9161          | 0.7561   |
| 0.8898        | 28.0  | 784  | 0.8767          | 0.7073   |
| 0.8051        | 29.0  | 812  | 0.8174          | 0.6829   |
| 0.8328        | 30.0  | 840  | 0.8077          | 0.6585   |
| 0.81          | 31.0  | 868  | 0.7911          | 0.6585   |
| 0.7372        | 32.0  | 896  | 1.0262          | 0.6585   |
| 0.7641        | 33.0  | 924  | 1.0698          | 0.5854   |
| 0.7745        | 34.0  | 952  | 0.8530          | 0.6829   |
| 0.7037        | 35.0  | 980  | 1.0106          | 0.6585   |
| 0.7449        | 36.0  | 1008 | 0.8975          | 0.7073   |
| 0.7391        | 37.0  | 1036 | 0.9607          | 0.6829   |
| 0.7447        | 38.0  | 1064 | 1.0096          | 0.6585   |
| 0.7043        | 39.0  | 1092 | 1.0986          | 0.7073   |
| 0.6379        | 40.0  | 1120 | 1.0787          | 0.6829   |
| 0.6476        | 41.0  | 1148 | 1.0057          | 0.6829   |
| 0.5799        | 42.0  | 1176 | 1.1714          | 0.6341   |
| 0.5954        | 43.0  | 1204 | 1.1356          | 0.6829   |
| 0.6189        | 44.0  | 1232 | 1.1609          | 0.6829   |
| 0.5672        | 45.0  | 1260 | 1.1726          | 0.6829   |
| 0.5115        | 46.0  | 1288 | 1.2388          | 0.6829   |
| 0.4522        | 47.0  | 1316 | 1.2273          | 0.6829   |
| 0.4728        | 48.0  | 1344 | 1.2290          | 0.6585   |
| 0.4195        | 49.0  | 1372 | 1.2275          | 0.6585   |
| 0.4871        | 50.0  | 1400 | 1.2275          | 0.6585   |


### Framework versions

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