---
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_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: 0.36833333333333335
---

<!-- 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_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: 1.1969
- Accuracy: 0.3683

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2818        | 1.0   | 75   | 1.3526          | 0.35     |
| 1.2881        | 2.0   | 150  | 1.3438          | 0.35     |
| 1.2902        | 3.0   | 225  | 1.3353          | 0.3533   |
| 1.3491        | 4.0   | 300  | 1.3273          | 0.3517   |
| 1.2508        | 5.0   | 375  | 1.3195          | 0.355    |
| 1.2901        | 6.0   | 450  | 1.3122          | 0.355    |
| 1.2792        | 7.0   | 525  | 1.3053          | 0.3583   |
| 1.2973        | 8.0   | 600  | 1.2988          | 0.3583   |
| 1.3051        | 9.0   | 675  | 1.2924          | 0.3583   |
| 1.3668        | 10.0  | 750  | 1.2863          | 0.3583   |
| 1.2982        | 11.0  | 825  | 1.2805          | 0.3633   |
| 1.1991        | 12.0  | 900  | 1.2750          | 0.3617   |
| 1.2833        | 13.0  | 975  | 1.2699          | 0.3617   |
| 1.2768        | 14.0  | 1050 | 1.2648          | 0.36     |
| 1.2691        | 15.0  | 1125 | 1.2602          | 0.36     |
| 1.2029        | 16.0  | 1200 | 1.2557          | 0.3617   |
| 1.2189        | 17.0  | 1275 | 1.2513          | 0.3667   |
| 1.2814        | 18.0  | 1350 | 1.2472          | 0.3683   |
| 1.1777        | 19.0  | 1425 | 1.2435          | 0.37     |
| 1.2006        | 20.0  | 1500 | 1.2398          | 0.3683   |
| 1.3016        | 21.0  | 1575 | 1.2363          | 0.3717   |
| 1.2664        | 22.0  | 1650 | 1.2331          | 0.3683   |
| 1.1963        | 23.0  | 1725 | 1.2301          | 0.37     |
| 1.2239        | 24.0  | 1800 | 1.2272          | 0.37     |
| 1.1881        | 25.0  | 1875 | 1.2244          | 0.37     |
| 1.2397        | 26.0  | 1950 | 1.2219          | 0.3717   |
| 1.1817        | 27.0  | 2025 | 1.2194          | 0.3717   |
| 1.2303        | 28.0  | 2100 | 1.2172          | 0.3733   |
| 1.253         | 29.0  | 2175 | 1.2151          | 0.3733   |
| 1.1936        | 30.0  | 2250 | 1.2131          | 0.3733   |
| 1.2173        | 31.0  | 2325 | 1.2113          | 0.3733   |
| 1.153         | 32.0  | 2400 | 1.2096          | 0.3733   |
| 1.2175        | 33.0  | 2475 | 1.2080          | 0.3733   |
| 1.2243        | 34.0  | 2550 | 1.2065          | 0.3733   |
| 1.1302        | 35.0  | 2625 | 1.2052          | 0.3717   |
| 1.1855        | 36.0  | 2700 | 1.2040          | 0.37     |
| 1.1832        | 37.0  | 2775 | 1.2029          | 0.37     |
| 1.1866        | 38.0  | 2850 | 1.2019          | 0.365    |
| 1.2112        | 39.0  | 2925 | 1.2010          | 0.365    |
| 1.199         | 40.0  | 3000 | 1.2002          | 0.3667   |
| 1.1826        | 41.0  | 3075 | 1.1995          | 0.3667   |
| 1.2211        | 42.0  | 3150 | 1.1988          | 0.3683   |
| 1.2093        | 43.0  | 3225 | 1.1983          | 0.3683   |
| 1.2039        | 44.0  | 3300 | 1.1979          | 0.3683   |
| 1.1848        | 45.0  | 3375 | 1.1975          | 0.3683   |
| 1.2445        | 46.0  | 3450 | 1.1973          | 0.3683   |
| 1.1786        | 47.0  | 3525 | 1.1971          | 0.3683   |
| 1.1742        | 48.0  | 3600 | 1.1970          | 0.3683   |
| 1.1159        | 49.0  | 3675 | 1.1969          | 0.3683   |
| 1.1807        | 50.0  | 3750 | 1.1969          | 0.3683   |


### Framework versions

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