---
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_00001_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: 0.2857142857142857
---

<!-- 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_00001_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: 1.6751
- Accuracy: 0.2857

## 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    | 1.6974          | 0.2857   |
| 1.71          | 2.0   | 12   | 1.6962          | 0.2857   |
| 1.71          | 3.0   | 18   | 1.6951          | 0.2857   |
| 1.7036        | 4.0   | 24   | 1.6940          | 0.2857   |
| 1.7465        | 5.0   | 30   | 1.6930          | 0.2857   |
| 1.7465        | 6.0   | 36   | 1.6921          | 0.2857   |
| 1.709         | 7.0   | 42   | 1.6911          | 0.2857   |
| 1.709         | 8.0   | 48   | 1.6901          | 0.2857   |
| 1.712         | 9.0   | 54   | 1.6892          | 0.2857   |
| 1.7048        | 10.0  | 60   | 1.6882          | 0.2857   |
| 1.7048        | 11.0  | 66   | 1.6874          | 0.2857   |
| 1.6828        | 12.0  | 72   | 1.6866          | 0.2857   |
| 1.6828        | 13.0  | 78   | 1.6858          | 0.2857   |
| 1.7139        | 14.0  | 84   | 1.6850          | 0.2857   |
| 1.719         | 15.0  | 90   | 1.6842          | 0.2857   |
| 1.719         | 16.0  | 96   | 1.6835          | 0.2857   |
| 1.6904        | 17.0  | 102  | 1.6828          | 0.2857   |
| 1.6904        | 18.0  | 108  | 1.6821          | 0.2857   |
| 1.7154        | 19.0  | 114  | 1.6815          | 0.2857   |
| 1.7326        | 20.0  | 120  | 1.6809          | 0.2857   |
| 1.7326        | 21.0  | 126  | 1.6804          | 0.2857   |
| 1.6942        | 22.0  | 132  | 1.6799          | 0.2857   |
| 1.6942        | 23.0  | 138  | 1.6794          | 0.2857   |
| 1.6945        | 24.0  | 144  | 1.6789          | 0.2857   |
| 1.728         | 25.0  | 150  | 1.6784          | 0.2857   |
| 1.728         | 26.0  | 156  | 1.6780          | 0.2857   |
| 1.7026        | 27.0  | 162  | 1.6776          | 0.2857   |
| 1.7026        | 28.0  | 168  | 1.6772          | 0.2857   |
| 1.7403        | 29.0  | 174  | 1.6769          | 0.2857   |
| 1.6716        | 30.0  | 180  | 1.6766          | 0.2857   |
| 1.6716        | 31.0  | 186  | 1.6764          | 0.2857   |
| 1.6806        | 32.0  | 192  | 1.6761          | 0.2857   |
| 1.6806        | 33.0  | 198  | 1.6759          | 0.2857   |
| 1.6988        | 34.0  | 204  | 1.6757          | 0.2857   |
| 1.6893        | 35.0  | 210  | 1.6755          | 0.2857   |
| 1.6893        | 36.0  | 216  | 1.6754          | 0.2857   |
| 1.6718        | 37.0  | 222  | 1.6753          | 0.2857   |
| 1.6718        | 38.0  | 228  | 1.6752          | 0.2857   |
| 1.7279        | 39.0  | 234  | 1.6751          | 0.2857   |
| 1.6803        | 40.0  | 240  | 1.6751          | 0.2857   |
| 1.6803        | 41.0  | 246  | 1.6751          | 0.2857   |
| 1.6785        | 42.0  | 252  | 1.6751          | 0.2857   |
| 1.6785        | 43.0  | 258  | 1.6751          | 0.2857   |
| 1.7169        | 44.0  | 264  | 1.6751          | 0.2857   |
| 1.6924        | 45.0  | 270  | 1.6751          | 0.2857   |
| 1.6924        | 46.0  | 276  | 1.6751          | 0.2857   |
| 1.6961        | 47.0  | 282  | 1.6751          | 0.2857   |
| 1.6961        | 48.0  | 288  | 1.6751          | 0.2857   |
| 1.7415        | 49.0  | 294  | 1.6751          | 0.2857   |
| 1.681         | 50.0  | 300  | 1.6751          | 0.2857   |


### Framework versions

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