---
license: apache-2.0
base_model: facebook/deit-small-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: smids_1x_deit_small_rms_0001_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: 0.8683333333333333
---

<!-- 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_small_rms_0001_fold3

This model is a fine-tuned version of [facebook/deit-small-patch16-224](https://huggingface.co/facebook/deit-small-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1062
- Accuracy: 0.8683

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.9975        | 1.0   | 75   | 0.8496          | 0.5467   |
| 0.5061        | 2.0   | 150  | 0.5223          | 0.8067   |
| 0.3795        | 3.0   | 225  | 0.4405          | 0.8267   |
| 0.3892        | 4.0   | 300  | 0.3713          | 0.8533   |
| 0.1768        | 5.0   | 375  | 0.3582          | 0.88     |
| 0.1554        | 6.0   | 450  | 0.4330          | 0.8733   |
| 0.1428        | 7.0   | 525  | 0.4207          | 0.8567   |
| 0.0674        | 8.0   | 600  | 0.6040          | 0.8567   |
| 0.0307        | 9.0   | 675  | 0.7767          | 0.8317   |
| 0.0367        | 10.0  | 750  | 0.6480          | 0.8567   |
| 0.0581        | 11.0  | 825  | 0.6494          | 0.87     |
| 0.0608        | 12.0  | 900  | 0.5071          | 0.8667   |
| 0.0462        | 13.0  | 975  | 0.7332          | 0.855    |
| 0.0198        | 14.0  | 1050 | 0.7960          | 0.8633   |
| 0.0291        | 15.0  | 1125 | 0.7675          | 0.8683   |
| 0.0004        | 16.0  | 1200 | 0.8666          | 0.8567   |
| 0.0394        | 17.0  | 1275 | 0.8320          | 0.8667   |
| 0.0137        | 18.0  | 1350 | 0.8206          | 0.86     |
| 0.0055        | 19.0  | 1425 | 0.9665          | 0.8583   |
| 0.029         | 20.0  | 1500 | 0.8497          | 0.8683   |
| 0.0429        | 21.0  | 1575 | 0.9318          | 0.8717   |
| 0.0315        | 22.0  | 1650 | 0.9188          | 0.8567   |
| 0.0182        | 23.0  | 1725 | 0.8073          | 0.875    |
| 0.0239        | 24.0  | 1800 | 0.9607          | 0.8683   |
| 0.0057        | 25.0  | 1875 | 0.8991          | 0.8767   |
| 0.004         | 26.0  | 1950 | 0.8719          | 0.8633   |
| 0.0226        | 27.0  | 2025 | 0.8720          | 0.8533   |
| 0.0534        | 28.0  | 2100 | 0.8637          | 0.8633   |
| 0.0299        | 29.0  | 2175 | 0.9839          | 0.865    |
| 0.0001        | 30.0  | 2250 | 0.9564          | 0.8667   |
| 0.0001        | 31.0  | 2325 | 0.9281          | 0.8783   |
| 0.0024        | 32.0  | 2400 | 0.9454          | 0.875    |
| 0.0023        | 33.0  | 2475 | 0.9716          | 0.875    |
| 0.0055        | 34.0  | 2550 | 0.9822          | 0.875    |
| 0.009         | 35.0  | 2625 | 0.9930          | 0.865    |
| 0.0029        | 36.0  | 2700 | 1.0435          | 0.8717   |
| 0.0019        | 37.0  | 2775 | 1.0502          | 0.8683   |
| 0.0           | 38.0  | 2850 | 1.0112          | 0.87     |
| 0.0           | 39.0  | 2925 | 1.0171          | 0.8733   |
| 0.0           | 40.0  | 3000 | 1.0381          | 0.8733   |
| 0.0           | 41.0  | 3075 | 1.0120          | 0.8667   |
| 0.0026        | 42.0  | 3150 | 1.0208          | 0.8667   |
| 0.0025        | 43.0  | 3225 | 1.0419          | 0.8683   |
| 0.0           | 44.0  | 3300 | 1.0612          | 0.87     |
| 0.0025        | 45.0  | 3375 | 1.0735          | 0.8633   |
| 0.0025        | 46.0  | 3450 | 1.0868          | 0.8667   |
| 0.0049        | 47.0  | 3525 | 1.0931          | 0.87     |
| 0.0           | 48.0  | 3600 | 1.0992          | 0.8683   |
| 0.0           | 49.0  | 3675 | 1.1039          | 0.87     |
| 0.0045        | 50.0  | 3750 | 1.1062          | 0.8683   |


### Framework versions

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