---
license: apache-2.0
base_model: facebook/deit-small-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: smids_3x_deit_small_adamax_001_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: 0.8818635607321131
---

<!-- 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_3x_deit_small_adamax_001_fold2

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: 1.0171
- Accuracy: 0.8819

## 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: 0.001
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.4401        | 1.0   | 225   | 0.3048          | 0.8735   |
| 0.2924        | 2.0   | 450   | 0.3208          | 0.8702   |
| 0.2562        | 3.0   | 675   | 0.3212          | 0.8702   |
| 0.2244        | 4.0   | 900   | 0.3324          | 0.8735   |
| 0.2012        | 5.0   | 1125  | 0.4267          | 0.8602   |
| 0.1372        | 6.0   | 1350  | 0.5512          | 0.8353   |
| 0.1267        | 7.0   | 1575  | 0.3624          | 0.8869   |
| 0.0899        | 8.0   | 1800  | 0.5724          | 0.8436   |
| 0.0839        | 9.0   | 2025  | 0.5571          | 0.8702   |
| 0.0466        | 10.0  | 2250  | 0.5349          | 0.8569   |
| 0.0801        | 11.0  | 2475  | 0.5913          | 0.8502   |
| 0.0671        | 12.0  | 2700  | 0.5854          | 0.8752   |
| 0.0348        | 13.0  | 2925  | 0.6837          | 0.8552   |
| 0.0379        | 14.0  | 3150  | 0.5712          | 0.8752   |
| 0.0439        | 15.0  | 3375  | 0.6348          | 0.8702   |
| 0.003         | 16.0  | 3600  | 0.7977          | 0.8686   |
| 0.0261        | 17.0  | 3825  | 0.6729          | 0.8735   |
| 0.002         | 18.0  | 4050  | 0.7795          | 0.8636   |
| 0.001         | 19.0  | 4275  | 0.6782          | 0.8852   |
| 0.0058        | 20.0  | 4500  | 0.6727          | 0.8918   |
| 0.0166        | 21.0  | 4725  | 0.6389          | 0.8835   |
| 0.0009        | 22.0  | 4950  | 0.7419          | 0.8752   |
| 0.0138        | 23.0  | 5175  | 0.7956          | 0.8769   |
| 0.0224        | 24.0  | 5400  | 0.7981          | 0.8735   |
| 0.0076        | 25.0  | 5625  | 0.7548          | 0.8802   |
| 0.0182        | 26.0  | 5850  | 0.8476          | 0.8586   |
| 0.0001        | 27.0  | 6075  | 0.8394          | 0.8669   |
| 0.0           | 28.0  | 6300  | 0.7756          | 0.8802   |
| 0.0001        | 29.0  | 6525  | 0.8666          | 0.8752   |
| 0.0033        | 30.0  | 6750  | 0.8769          | 0.8935   |
| 0.0046        | 31.0  | 6975  | 0.8571          | 0.8835   |
| 0.0           | 32.0  | 7200  | 0.8804          | 0.8802   |
| 0.0022        | 33.0  | 7425  | 0.8723          | 0.8902   |
| 0.0           | 34.0  | 7650  | 0.8812          | 0.8869   |
| 0.0           | 35.0  | 7875  | 0.9182          | 0.8819   |
| 0.0032        | 36.0  | 8100  | 0.9012          | 0.8869   |
| 0.0           | 37.0  | 8325  | 0.9270          | 0.8885   |
| 0.0           | 38.0  | 8550  | 0.8810          | 0.8902   |
| 0.0032        | 39.0  | 8775  | 0.9223          | 0.8918   |
| 0.0           | 40.0  | 9000  | 0.9755          | 0.8918   |
| 0.0003        | 41.0  | 9225  | 0.9917          | 0.8885   |
| 0.0           | 42.0  | 9450  | 0.9880          | 0.8869   |
| 0.0           | 43.0  | 9675  | 0.9953          | 0.8869   |
| 0.0           | 44.0  | 9900  | 0.9968          | 0.8869   |
| 0.0           | 45.0  | 10125 | 1.0016          | 0.8869   |
| 0.0           | 46.0  | 10350 | 1.0040          | 0.8852   |
| 0.0           | 47.0  | 10575 | 1.0063          | 0.8835   |
| 0.0           | 48.0  | 10800 | 1.0129          | 0.8835   |
| 0.0023        | 49.0  | 11025 | 1.0163          | 0.8819   |
| 0.0023        | 50.0  | 11250 | 1.0171          | 0.8819   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.0+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2