---
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_adamax_0001_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: 0.8948247078464107
---

<!-- 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_adamax_0001_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: 0.7139
- Accuracy: 0.8948

## 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: 0.0001
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5342        | 1.0   | 76   | 0.3575          | 0.8581   |
| 0.3487        | 2.0   | 152  | 0.2939          | 0.8898   |
| 0.1948        | 3.0   | 228  | 0.3052          | 0.8781   |
| 0.1604        | 4.0   | 304  | 0.3458          | 0.8798   |
| 0.0971        | 5.0   | 380  | 0.3617          | 0.8781   |
| 0.0708        | 6.0   | 456  | 0.5383          | 0.8664   |
| 0.0188        | 7.0   | 532  | 0.4843          | 0.8815   |
| 0.0379        | 8.0   | 608  | 0.6406          | 0.8848   |
| 0.0764        | 9.0   | 684  | 0.6359          | 0.8531   |
| 0.0087        | 10.0  | 760  | 0.6100          | 0.8798   |
| 0.0487        | 11.0  | 836  | 0.7711          | 0.8748   |
| 0.0123        | 12.0  | 912  | 0.6958          | 0.8815   |
| 0.011         | 13.0  | 988  | 0.7079          | 0.8781   |
| 0.0004        | 14.0  | 1064 | 0.6722          | 0.8898   |
| 0.0173        | 15.0  | 1140 | 0.7341          | 0.8698   |
| 0.0003        | 16.0  | 1216 | 0.6822          | 0.8932   |
| 0.0001        | 17.0  | 1292 | 0.6501          | 0.8881   |
| 0.0148        | 18.0  | 1368 | 0.7815          | 0.8631   |
| 0.0031        | 19.0  | 1444 | 0.7055          | 0.8831   |
| 0.0045        | 20.0  | 1520 | 0.8049          | 0.8831   |
| 0.0073        | 21.0  | 1596 | 0.7920          | 0.8715   |
| 0.0063        | 22.0  | 1672 | 0.7465          | 0.8715   |
| 0.0001        | 23.0  | 1748 | 0.8004          | 0.8781   |
| 0.0088        | 24.0  | 1824 | 0.7851          | 0.8748   |
| 0.0101        | 25.0  | 1900 | 0.7887          | 0.8831   |
| 0.0047        | 26.0  | 1976 | 0.8827          | 0.8614   |
| 0.0049        | 27.0  | 2052 | 0.7414          | 0.8881   |
| 0.0051        | 28.0  | 2128 | 0.7159          | 0.8915   |
| 0.0063        | 29.0  | 2204 | 0.6956          | 0.8815   |
| 0.0           | 30.0  | 2280 | 0.7029          | 0.8915   |
| 0.0047        | 31.0  | 2356 | 0.7051          | 0.8932   |
| 0.0086        | 32.0  | 2432 | 0.7051          | 0.8948   |
| 0.0           | 33.0  | 2508 | 0.7127          | 0.8865   |
| 0.0           | 34.0  | 2584 | 0.7124          | 0.8948   |
| 0.0109        | 35.0  | 2660 | 0.7099          | 0.8965   |
| 0.0034        | 36.0  | 2736 | 0.7067          | 0.8965   |
| 0.0066        | 37.0  | 2812 | 0.7137          | 0.8881   |
| 0.0           | 38.0  | 2888 | 0.7098          | 0.8915   |
| 0.0038        | 39.0  | 2964 | 0.7130          | 0.8932   |
| 0.0           | 40.0  | 3040 | 0.7175          | 0.8932   |
| 0.0028        | 41.0  | 3116 | 0.7128          | 0.8898   |
| 0.0           | 42.0  | 3192 | 0.7109          | 0.8915   |
| 0.0048        | 43.0  | 3268 | 0.7105          | 0.8915   |
| 0.0           | 44.0  | 3344 | 0.7293          | 0.8881   |
| 0.0           | 45.0  | 3420 | 0.7138          | 0.8932   |
| 0.0           | 46.0  | 3496 | 0.7167          | 0.8948   |
| 0.0           | 47.0  | 3572 | 0.7158          | 0.8948   |
| 0.0024        | 48.0  | 3648 | 0.7140          | 0.8948   |
| 0.0           | 49.0  | 3724 | 0.7139          | 0.8948   |
| 0.0           | 50.0  | 3800 | 0.7139          | 0.8948   |


### Framework versions

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