---
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: smids_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: 0.38898163606010017
---

<!-- 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. -->

# smids_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: 1.1750
- Accuracy: 0.3890

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3532        | 1.0   | 76   | 1.3243          | 0.3506   |
| 1.4232        | 2.0   | 152  | 1.3155          | 0.3489   |
| 1.3221        | 3.0   | 228  | 1.3073          | 0.3489   |
| 1.3312        | 4.0   | 304  | 1.2992          | 0.3489   |
| 1.2834        | 5.0   | 380  | 1.2918          | 0.3539   |
| 1.3512        | 6.0   | 456  | 1.2848          | 0.3573   |
| 1.3029        | 7.0   | 532  | 1.2778          | 0.3573   |
| 1.3216        | 8.0   | 608  | 1.2712          | 0.3606   |
| 1.2731        | 9.0   | 684  | 1.2652          | 0.3656   |
| 1.2932        | 10.0  | 760  | 1.2593          | 0.3639   |
| 1.3065        | 11.0  | 836  | 1.2537          | 0.3606   |
| 1.2874        | 12.0  | 912  | 1.2484          | 0.3606   |
| 1.2669        | 13.0  | 988  | 1.2434          | 0.3623   |
| 1.2861        | 14.0  | 1064 | 1.2386          | 0.3639   |
| 1.3203        | 15.0  | 1140 | 1.2340          | 0.3639   |
| 1.3343        | 16.0  | 1216 | 1.2296          | 0.3639   |
| 1.3239        | 17.0  | 1292 | 1.2256          | 0.3656   |
| 1.2639        | 18.0  | 1368 | 1.2217          | 0.3639   |
| 1.2169        | 19.0  | 1444 | 1.2180          | 0.3673   |
| 1.1959        | 20.0  | 1520 | 1.2146          | 0.3689   |
| 1.2012        | 21.0  | 1596 | 1.2114          | 0.3723   |
| 1.1569        | 22.0  | 1672 | 1.2083          | 0.3706   |
| 1.2377        | 23.0  | 1748 | 1.2054          | 0.3656   |
| 1.2417        | 24.0  | 1824 | 1.2027          | 0.3673   |
| 1.2459        | 25.0  | 1900 | 1.2001          | 0.3689   |
| 1.2355        | 26.0  | 1976 | 1.1977          | 0.3673   |
| 1.2821        | 27.0  | 2052 | 1.1955          | 0.3656   |
| 1.2546        | 28.0  | 2128 | 1.1935          | 0.3706   |
| 1.2602        | 29.0  | 2204 | 1.1915          | 0.3689   |
| 1.1654        | 30.0  | 2280 | 1.1896          | 0.3723   |
| 1.2138        | 31.0  | 2356 | 1.1879          | 0.3740   |
| 1.2289        | 32.0  | 2432 | 1.1863          | 0.3756   |
| 1.1744        | 33.0  | 2508 | 1.1849          | 0.3756   |
| 1.2018        | 34.0  | 2584 | 1.1835          | 0.3756   |
| 1.2411        | 35.0  | 2660 | 1.1823          | 0.3773   |
| 1.2021        | 36.0  | 2736 | 1.1812          | 0.3840   |
| 1.172         | 37.0  | 2812 | 1.1802          | 0.3840   |
| 1.2015        | 38.0  | 2888 | 1.1792          | 0.3840   |
| 1.2305        | 39.0  | 2964 | 1.1784          | 0.3840   |
| 1.1165        | 40.0  | 3040 | 1.1777          | 0.3840   |
| 1.2641        | 41.0  | 3116 | 1.1771          | 0.3856   |
| 1.2228        | 42.0  | 3192 | 1.1765          | 0.3856   |
| 1.1905        | 43.0  | 3268 | 1.1761          | 0.3856   |
| 1.1893        | 44.0  | 3344 | 1.1757          | 0.3873   |
| 1.2905        | 45.0  | 3420 | 1.1755          | 0.3873   |
| 1.194         | 46.0  | 3496 | 1.1753          | 0.3873   |
| 1.1805        | 47.0  | 3572 | 1.1751          | 0.3873   |
| 1.1703        | 48.0  | 3648 | 1.1750          | 0.3873   |
| 1.2028        | 49.0  | 3724 | 1.1750          | 0.3890   |
| 1.2474        | 50.0  | 3800 | 1.1750          | 0.3890   |


### Framework versions

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