---
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_5x_deit_tiny_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: 0.24390243902439024
---

<!-- 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_tiny_sgd_00001_fold5

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: 1.7062
- Accuracy: 0.2439

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.53          | 1.0   | 28   | 1.7652          | 0.2439   |
| 1.4658        | 2.0   | 56   | 1.7625          | 0.2439   |
| 1.4749        | 3.0   | 84   | 1.7598          | 0.2439   |
| 1.4869        | 4.0   | 112  | 1.7572          | 0.2439   |
| 1.4859        | 5.0   | 140  | 1.7548          | 0.2439   |
| 1.5155        | 6.0   | 168  | 1.7523          | 0.2439   |
| 1.4632        | 7.0   | 196  | 1.7499          | 0.2439   |
| 1.4958        | 8.0   | 224  | 1.7475          | 0.2439   |
| 1.538         | 9.0   | 252  | 1.7452          | 0.2439   |
| 1.5008        | 10.0  | 280  | 1.7432          | 0.2439   |
| 1.4793        | 11.0  | 308  | 1.7411          | 0.2439   |
| 1.483         | 12.0  | 336  | 1.7391          | 0.2439   |
| 1.4966        | 13.0  | 364  | 1.7374          | 0.2439   |
| 1.5231        | 14.0  | 392  | 1.7355          | 0.2439   |
| 1.5038        | 15.0  | 420  | 1.7337          | 0.2439   |
| 1.4896        | 16.0  | 448  | 1.7319          | 0.2439   |
| 1.5043        | 17.0  | 476  | 1.7303          | 0.2439   |
| 1.4967        | 18.0  | 504  | 1.7286          | 0.2439   |
| 1.5162        | 19.0  | 532  | 1.7269          | 0.2439   |
| 1.5126        | 20.0  | 560  | 1.7254          | 0.2439   |
| 1.4809        | 21.0  | 588  | 1.7239          | 0.2439   |
| 1.4877        | 22.0  | 616  | 1.7225          | 0.2439   |
| 1.5048        | 23.0  | 644  | 1.7212          | 0.2439   |
| 1.4932        | 24.0  | 672  | 1.7199          | 0.2439   |
| 1.4898        | 25.0  | 700  | 1.7187          | 0.2439   |
| 1.4408        | 26.0  | 728  | 1.7176          | 0.2439   |
| 1.5027        | 27.0  | 756  | 1.7165          | 0.2439   |
| 1.4716        | 28.0  | 784  | 1.7154          | 0.2439   |
| 1.5167        | 29.0  | 812  | 1.7145          | 0.2439   |
| 1.4795        | 30.0  | 840  | 1.7136          | 0.2439   |
| 1.5126        | 31.0  | 868  | 1.7127          | 0.2439   |
| 1.4908        | 32.0  | 896  | 1.7119          | 0.2439   |
| 1.4785        | 33.0  | 924  | 1.7111          | 0.2439   |
| 1.4672        | 34.0  | 952  | 1.7104          | 0.2439   |
| 1.4938        | 35.0  | 980  | 1.7097          | 0.2439   |
| 1.4756        | 36.0  | 1008 | 1.7092          | 0.2439   |
| 1.4385        | 37.0  | 1036 | 1.7087          | 0.2439   |
| 1.5268        | 38.0  | 1064 | 1.7082          | 0.2439   |
| 1.4939        | 39.0  | 1092 | 1.7078          | 0.2439   |
| 1.4888        | 40.0  | 1120 | 1.7074          | 0.2439   |
| 1.4584        | 41.0  | 1148 | 1.7071          | 0.2439   |
| 1.5033        | 42.0  | 1176 | 1.7068          | 0.2439   |
| 1.5098        | 43.0  | 1204 | 1.7066          | 0.2439   |
| 1.485         | 44.0  | 1232 | 1.7064          | 0.2439   |
| 1.4705        | 45.0  | 1260 | 1.7063          | 0.2439   |
| 1.4946        | 46.0  | 1288 | 1.7062          | 0.2439   |
| 1.4654        | 47.0  | 1316 | 1.7062          | 0.2439   |
| 1.5055        | 48.0  | 1344 | 1.7062          | 0.2439   |
| 1.4868        | 49.0  | 1372 | 1.7062          | 0.2439   |
| 1.489         | 50.0  | 1400 | 1.7062          | 0.2439   |


### Framework versions

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