---
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_1x_deit_tiny_sgd_lr00001_fold4
  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: 0.19047619047619047
---

<!-- 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_1x_deit_tiny_sgd_lr00001_fold4

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: 1.5565
- Accuracy: 0.1905

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 6    | 1.5632          | 0.1905   |
| 1.6067        | 2.0   | 12   | 1.5628          | 0.1905   |
| 1.6067        | 3.0   | 18   | 1.5625          | 0.1905   |
| 1.6234        | 4.0   | 24   | 1.5621          | 0.1905   |
| 1.6412        | 5.0   | 30   | 1.5618          | 0.1905   |
| 1.6412        | 6.0   | 36   | 1.5615          | 0.1905   |
| 1.6304        | 7.0   | 42   | 1.5612          | 0.1905   |
| 1.6304        | 8.0   | 48   | 1.5609          | 0.1905   |
| 1.6339        | 9.0   | 54   | 1.5606          | 0.1905   |
| 1.6208        | 10.0  | 60   | 1.5604          | 0.1905   |
| 1.6208        | 11.0  | 66   | 1.5601          | 0.1905   |
| 1.599         | 12.0  | 72   | 1.5598          | 0.1905   |
| 1.599         | 13.0  | 78   | 1.5596          | 0.1905   |
| 1.6454        | 14.0  | 84   | 1.5594          | 0.1905   |
| 1.5993        | 15.0  | 90   | 1.5591          | 0.1905   |
| 1.5993        | 16.0  | 96   | 1.5589          | 0.1905   |
| 1.6104        | 17.0  | 102  | 1.5587          | 0.1905   |
| 1.6104        | 18.0  | 108  | 1.5585          | 0.1905   |
| 1.5995        | 19.0  | 114  | 1.5584          | 0.1905   |
| 1.6359        | 20.0  | 120  | 1.5582          | 0.1905   |
| 1.6359        | 21.0  | 126  | 1.5580          | 0.1905   |
| 1.5868        | 22.0  | 132  | 1.5579          | 0.1905   |
| 1.5868        | 23.0  | 138  | 1.5577          | 0.1905   |
| 1.67          | 24.0  | 144  | 1.5576          | 0.1905   |
| 1.5662        | 25.0  | 150  | 1.5575          | 0.1905   |
| 1.5662        | 26.0  | 156  | 1.5573          | 0.1905   |
| 1.6118        | 27.0  | 162  | 1.5572          | 0.1905   |
| 1.6118        | 28.0  | 168  | 1.5571          | 0.1905   |
| 1.6163        | 29.0  | 174  | 1.5570          | 0.1905   |
| 1.6392        | 30.0  | 180  | 1.5569          | 0.1905   |
| 1.6392        | 31.0  | 186  | 1.5568          | 0.1905   |
| 1.6602        | 32.0  | 192  | 1.5568          | 0.1905   |
| 1.6602        | 33.0  | 198  | 1.5567          | 0.1905   |
| 1.5354        | 34.0  | 204  | 1.5567          | 0.1905   |
| 1.6205        | 35.0  | 210  | 1.5566          | 0.1905   |
| 1.6205        | 36.0  | 216  | 1.5566          | 0.1905   |
| 1.6201        | 37.0  | 222  | 1.5565          | 0.1905   |
| 1.6201        | 38.0  | 228  | 1.5565          | 0.1905   |
| 1.5923        | 39.0  | 234  | 1.5565          | 0.1905   |
| 1.6521        | 40.0  | 240  | 1.5565          | 0.1905   |
| 1.6521        | 41.0  | 246  | 1.5565          | 0.1905   |
| 1.6177        | 42.0  | 252  | 1.5565          | 0.1905   |
| 1.6177        | 43.0  | 258  | 1.5565          | 0.1905   |
| 1.6437        | 44.0  | 264  | 1.5565          | 0.1905   |
| 1.5948        | 45.0  | 270  | 1.5565          | 0.1905   |
| 1.5948        | 46.0  | 276  | 1.5565          | 0.1905   |
| 1.6236        | 47.0  | 282  | 1.5565          | 0.1905   |
| 1.6236        | 48.0  | 288  | 1.5565          | 0.1905   |
| 1.6168        | 49.0  | 294  | 1.5565          | 0.1905   |
| 1.6032        | 50.0  | 300  | 1.5565          | 0.1905   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1