---
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_fold2
  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: 0.3544093178036606
---

<!-- 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_fold2

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: 1.1866
- Accuracy: 0.3544

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3496        | 1.0   | 75   | 1.3448          | 0.3444   |
| 1.342         | 2.0   | 150  | 1.3359          | 0.3444   |
| 1.3049        | 3.0   | 225  | 1.3273          | 0.3428   |
| 1.3212        | 4.0   | 300  | 1.3189          | 0.3428   |
| 1.2683        | 5.0   | 375  | 1.3112          | 0.3394   |
| 1.3476        | 6.0   | 450  | 1.3037          | 0.3394   |
| 1.3281        | 7.0   | 525  | 1.2966          | 0.3378   |
| 1.2813        | 8.0   | 600  | 1.2897          | 0.3394   |
| 1.3177        | 9.0   | 675  | 1.2831          | 0.3394   |
| 1.2768        | 10.0  | 750  | 1.2769          | 0.3394   |
| 1.2973        | 11.0  | 825  | 1.2710          | 0.3394   |
| 1.2616        | 12.0  | 900  | 1.2654          | 0.3428   |
| 1.2694        | 13.0  | 975  | 1.2600          | 0.3428   |
| 1.1891        | 14.0  | 1050 | 1.2550          | 0.3361   |
| 1.2441        | 15.0  | 1125 | 1.2502          | 0.3411   |
| 1.211         | 16.0  | 1200 | 1.2456          | 0.3428   |
| 1.247         | 17.0  | 1275 | 1.2413          | 0.3411   |
| 1.2791        | 18.0  | 1350 | 1.2372          | 0.3411   |
| 1.2453        | 19.0  | 1425 | 1.2333          | 0.3428   |
| 1.2386        | 20.0  | 1500 | 1.2296          | 0.3444   |
| 1.2461        | 21.0  | 1575 | 1.2262          | 0.3461   |
| 1.2333        | 22.0  | 1650 | 1.2229          | 0.3461   |
| 1.2716        | 23.0  | 1725 | 1.2198          | 0.3478   |
| 1.2019        | 24.0  | 1800 | 1.2169          | 0.3461   |
| 1.1715        | 25.0  | 1875 | 1.2141          | 0.3444   |
| 1.1932        | 26.0  | 1950 | 1.2116          | 0.3461   |
| 1.2512        | 27.0  | 2025 | 1.2092          | 0.3444   |
| 1.1951        | 28.0  | 2100 | 1.2069          | 0.3444   |
| 1.2421        | 29.0  | 2175 | 1.2047          | 0.3461   |
| 1.1922        | 30.0  | 2250 | 1.2027          | 0.3478   |
| 1.2041        | 31.0  | 2325 | 1.2008          | 0.3478   |
| 1.2208        | 32.0  | 2400 | 1.1991          | 0.3478   |
| 1.1905        | 33.0  | 2475 | 1.1975          | 0.3478   |
| 1.1949        | 34.0  | 2550 | 1.1960          | 0.3478   |
| 1.1944        | 35.0  | 2625 | 1.1946          | 0.3527   |
| 1.1832        | 36.0  | 2700 | 1.1934          | 0.3561   |
| 1.2088        | 37.0  | 2775 | 1.1923          | 0.3577   |
| 1.2643        | 38.0  | 2850 | 1.1913          | 0.3594   |
| 1.2153        | 39.0  | 2925 | 1.1904          | 0.3561   |
| 1.2054        | 40.0  | 3000 | 1.1896          | 0.3561   |
| 1.188         | 41.0  | 3075 | 1.1889          | 0.3561   |
| 1.2171        | 42.0  | 3150 | 1.1883          | 0.3577   |
| 1.1949        | 43.0  | 3225 | 1.1878          | 0.3577   |
| 1.159         | 44.0  | 3300 | 1.1874          | 0.3561   |
| 1.1443        | 45.0  | 3375 | 1.1871          | 0.3544   |
| 1.1683        | 46.0  | 3450 | 1.1869          | 0.3544   |
| 1.2029        | 47.0  | 3525 | 1.1867          | 0.3544   |
| 1.1913        | 48.0  | 3600 | 1.1867          | 0.3544   |
| 1.1814        | 49.0  | 3675 | 1.1866          | 0.3544   |
| 1.1739        | 50.0  | 3750 | 1.1866          | 0.3544   |


### Framework versions

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