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---
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_fold1
  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: 0.26666666666666666
---

<!-- 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_fold1

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: 1.6650
- Accuracy: 0.2667

## 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    | 1.6807          | 0.2667   |
| 1.7256        | 2.0   | 12   | 1.6798          | 0.2667   |
| 1.7256        | 3.0   | 18   | 1.6790          | 0.2667   |
| 1.715         | 4.0   | 24   | 1.6783          | 0.2667   |
| 1.7579        | 5.0   | 30   | 1.6775          | 0.2667   |
| 1.7579        | 6.0   | 36   | 1.6768          | 0.2667   |
| 1.7037        | 7.0   | 42   | 1.6761          | 0.2667   |
| 1.7037        | 8.0   | 48   | 1.6755          | 0.2667   |
| 1.6916        | 9.0   | 54   | 1.6748          | 0.2667   |
| 1.7402        | 10.0  | 60   | 1.6742          | 0.2667   |
| 1.7402        | 11.0  | 66   | 1.6736          | 0.2667   |
| 1.7036        | 12.0  | 72   | 1.6730          | 0.2667   |
| 1.7036        | 13.0  | 78   | 1.6724          | 0.2667   |
| 1.8164        | 14.0  | 84   | 1.6718          | 0.2667   |
| 1.7198        | 15.0  | 90   | 1.6713          | 0.2667   |
| 1.7198        | 16.0  | 96   | 1.6708          | 0.2667   |
| 1.7047        | 17.0  | 102  | 1.6704          | 0.2667   |
| 1.7047        | 18.0  | 108  | 1.6699          | 0.2667   |
| 1.7105        | 19.0  | 114  | 1.6695          | 0.2667   |
| 1.6839        | 20.0  | 120  | 1.6691          | 0.2667   |
| 1.6839        | 21.0  | 126  | 1.6687          | 0.2667   |
| 1.6768        | 22.0  | 132  | 1.6683          | 0.2667   |
| 1.6768        | 23.0  | 138  | 1.6679          | 0.2667   |
| 1.7332        | 24.0  | 144  | 1.6676          | 0.2667   |
| 1.69          | 25.0  | 150  | 1.6673          | 0.2667   |
| 1.69          | 26.0  | 156  | 1.6670          | 0.2667   |
| 1.6919        | 27.0  | 162  | 1.6668          | 0.2667   |
| 1.6919        | 28.0  | 168  | 1.6665          | 0.2667   |
| 1.713         | 29.0  | 174  | 1.6663          | 0.2667   |
| 1.7082        | 30.0  | 180  | 1.6661          | 0.2667   |
| 1.7082        | 31.0  | 186  | 1.6659          | 0.2667   |
| 1.7547        | 32.0  | 192  | 1.6657          | 0.2667   |
| 1.7547        | 33.0  | 198  | 1.6656          | 0.2667   |
| 1.6513        | 34.0  | 204  | 1.6654          | 0.2667   |
| 1.7419        | 35.0  | 210  | 1.6653          | 0.2667   |
| 1.7419        | 36.0  | 216  | 1.6652          | 0.2667   |
| 1.7087        | 37.0  | 222  | 1.6652          | 0.2667   |
| 1.7087        | 38.0  | 228  | 1.6651          | 0.2667   |
| 1.6162        | 39.0  | 234  | 1.6651          | 0.2667   |
| 1.6974        | 40.0  | 240  | 1.6651          | 0.2667   |
| 1.6974        | 41.0  | 246  | 1.6650          | 0.2667   |
| 1.7234        | 42.0  | 252  | 1.6650          | 0.2667   |
| 1.7234        | 43.0  | 258  | 1.6650          | 0.2667   |
| 1.7326        | 44.0  | 264  | 1.6650          | 0.2667   |
| 1.6725        | 45.0  | 270  | 1.6650          | 0.2667   |
| 1.6725        | 46.0  | 276  | 1.6650          | 0.2667   |
| 1.6993        | 47.0  | 282  | 1.6650          | 0.2667   |
| 1.6993        | 48.0  | 288  | 1.6650          | 0.2667   |
| 1.6816        | 49.0  | 294  | 1.6650          | 0.2667   |
| 1.7255        | 50.0  | 300  | 1.6650          | 0.2667   |


### Framework versions

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