---
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_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: 0.8735440931780366
---

<!-- 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_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: 0.8884
- Accuracy: 0.8735

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4433        | 1.0   | 75   | 0.4087          | 0.8136   |
| 0.2718        | 2.0   | 150  | 0.3393          | 0.8636   |
| 0.1523        | 3.0   | 225  | 0.3549          | 0.8602   |
| 0.1126        | 4.0   | 300  | 0.4203          | 0.8785   |
| 0.1857        | 5.0   | 375  | 0.5016          | 0.8702   |
| 0.1676        | 6.0   | 450  | 0.6812          | 0.8403   |
| 0.0685        | 7.0   | 525  | 0.6011          | 0.8719   |
| 0.0238        | 8.0   | 600  | 0.6670          | 0.8686   |
| 0.0519        | 9.0   | 675  | 0.6013          | 0.8686   |
| 0.0386        | 10.0  | 750  | 0.7008          | 0.8719   |
| 0.0148        | 11.0  | 825  | 0.7193          | 0.8619   |
| 0.0007        | 12.0  | 900  | 0.7563          | 0.8752   |
| 0.0241        | 13.0  | 975  | 0.7693          | 0.8636   |
| 0.0307        | 14.0  | 1050 | 0.8760          | 0.8636   |
| 0.0115        | 15.0  | 1125 | 0.7808          | 0.8719   |
| 0.0035        | 16.0  | 1200 | 0.7588          | 0.8669   |
| 0.0001        | 17.0  | 1275 | 0.8971          | 0.8619   |
| 0.0102        | 18.0  | 1350 | 0.7909          | 0.8719   |
| 0.0001        | 19.0  | 1425 | 0.7984          | 0.8636   |
| 0.004         | 20.0  | 1500 | 0.8206          | 0.8669   |
| 0.0001        | 21.0  | 1575 | 0.8515          | 0.8752   |
| 0.0           | 22.0  | 1650 | 0.7887          | 0.8752   |
| 0.0           | 23.0  | 1725 | 0.9036          | 0.8719   |
| 0.0001        | 24.0  | 1800 | 0.8151          | 0.8735   |
| 0.0           | 25.0  | 1875 | 0.8674          | 0.8669   |
| 0.0           | 26.0  | 1950 | 0.8463          | 0.8702   |
| 0.0044        | 27.0  | 2025 | 0.8541          | 0.8669   |
| 0.0043        | 28.0  | 2100 | 0.8322          | 0.8669   |
| 0.002         | 29.0  | 2175 | 0.8405          | 0.8686   |
| 0.0043        | 30.0  | 2250 | 0.8433          | 0.8686   |
| 0.0034        | 31.0  | 2325 | 0.8353          | 0.8752   |
| 0.0           | 32.0  | 2400 | 0.8744          | 0.8702   |
| 0.0           | 33.0  | 2475 | 0.8688          | 0.8669   |
| 0.0           | 34.0  | 2550 | 0.8557          | 0.8669   |
| 0.0091        | 35.0  | 2625 | 0.8746          | 0.8669   |
| 0.0           | 36.0  | 2700 | 0.8586          | 0.8686   |
| 0.0           | 37.0  | 2775 | 0.8715          | 0.8702   |
| 0.0           | 38.0  | 2850 | 0.8844          | 0.8719   |
| 0.0019        | 39.0  | 2925 | 0.8957          | 0.8735   |
| 0.0           | 40.0  | 3000 | 0.8803          | 0.8752   |
| 0.0031        | 41.0  | 3075 | 0.8802          | 0.8752   |
| 0.0           | 42.0  | 3150 | 0.8828          | 0.8752   |
| 0.0026        | 43.0  | 3225 | 0.8803          | 0.8735   |
| 0.003         | 44.0  | 3300 | 0.8878          | 0.8752   |
| 0.0           | 45.0  | 3375 | 0.8894          | 0.8702   |
| 0.0           | 46.0  | 3450 | 0.8874          | 0.8735   |
| 0.0024        | 47.0  | 3525 | 0.8958          | 0.8752   |
| 0.0           | 48.0  | 3600 | 0.8893          | 0.8735   |
| 0.0023        | 49.0  | 3675 | 0.8880          | 0.8735   |
| 0.0021        | 50.0  | 3750 | 0.8884          | 0.8735   |


### Framework versions

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