---
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_fold3
  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: 0.38333333333333336
---

<!-- 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_fold3

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: 1.2082
- Accuracy: 0.3833

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3468        | 1.0   | 75   | 1.3684          | 0.345    |
| 1.2941        | 2.0   | 150  | 1.3595          | 0.3433   |
| 1.2835        | 3.0   | 225  | 1.3508          | 0.3433   |
| 1.3718        | 4.0   | 300  | 1.3426          | 0.345    |
| 1.2334        | 5.0   | 375  | 1.3348          | 0.345    |
| 1.2846        | 6.0   | 450  | 1.3274          | 0.3467   |
| 1.2876        | 7.0   | 525  | 1.3202          | 0.3483   |
| 1.2894        | 8.0   | 600  | 1.3134          | 0.3483   |
| 1.3322        | 9.0   | 675  | 1.3070          | 0.3483   |
| 1.3642        | 10.0  | 750  | 1.3007          | 0.35     |
| 1.2885        | 11.0  | 825  | 1.2947          | 0.3517   |
| 1.2098        | 12.0  | 900  | 1.2891          | 0.3517   |
| 1.2493        | 13.0  | 975  | 1.2838          | 0.35     |
| 1.2305        | 14.0  | 1050 | 1.2787          | 0.3517   |
| 1.2559        | 15.0  | 1125 | 1.2739          | 0.355    |
| 1.216         | 16.0  | 1200 | 1.2692          | 0.3567   |
| 1.2252        | 17.0  | 1275 | 1.2648          | 0.3583   |
| 1.2555        | 18.0  | 1350 | 1.2606          | 0.36     |
| 1.207         | 19.0  | 1425 | 1.2567          | 0.3583   |
| 1.163         | 20.0  | 1500 | 1.2528          | 0.3583   |
| 1.2799        | 21.0  | 1575 | 1.2493          | 0.3617   |
| 1.2576        | 22.0  | 1650 | 1.2460          | 0.3633   |
| 1.259         | 23.0  | 1725 | 1.2428          | 0.3617   |
| 1.2102        | 24.0  | 1800 | 1.2399          | 0.365    |
| 1.206         | 25.0  | 1875 | 1.2370          | 0.3633   |
| 1.2525        | 26.0  | 1950 | 1.2343          | 0.3683   |
| 1.2063        | 27.0  | 2025 | 1.2318          | 0.3683   |
| 1.2191        | 28.0  | 2100 | 1.2294          | 0.3683   |
| 1.2117        | 29.0  | 2175 | 1.2273          | 0.3683   |
| 1.2241        | 30.0  | 2250 | 1.2252          | 0.37     |
| 1.2256        | 31.0  | 2325 | 1.2233          | 0.3733   |
| 1.123         | 32.0  | 2400 | 1.2215          | 0.3767   |
| 1.1778        | 33.0  | 2475 | 1.2198          | 0.3767   |
| 1.2098        | 34.0  | 2550 | 1.2183          | 0.3817   |
| 1.1496        | 35.0  | 2625 | 1.2169          | 0.3783   |
| 1.2108        | 36.0  | 2700 | 1.2156          | 0.3833   |
| 1.2173        | 37.0  | 2775 | 1.2145          | 0.3817   |
| 1.177         | 38.0  | 2850 | 1.2134          | 0.38     |
| 1.1989        | 39.0  | 2925 | 1.2125          | 0.3783   |
| 1.2161        | 40.0  | 3000 | 1.2116          | 0.3783   |
| 1.2506        | 41.0  | 3075 | 1.2109          | 0.3783   |
| 1.2753        | 42.0  | 3150 | 1.2102          | 0.38     |
| 1.215         | 43.0  | 3225 | 1.2097          | 0.38     |
| 1.196         | 44.0  | 3300 | 1.2092          | 0.38     |
| 1.1971        | 45.0  | 3375 | 1.2089          | 0.3817   |
| 1.1869        | 46.0  | 3450 | 1.2086          | 0.3833   |
| 1.1695        | 47.0  | 3525 | 1.2084          | 0.3833   |
| 1.19          | 48.0  | 3600 | 1.2083          | 0.3833   |
| 1.1265        | 49.0  | 3675 | 1.2082          | 0.3833   |
| 1.1801        | 50.0  | 3750 | 1.2082          | 0.3833   |


### Framework versions

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