---
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_adamax_001_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: 0.8566666666666667
---

<!-- 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_adamax_001_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: 1.1786
- Accuracy: 0.8567

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6005        | 1.0   | 75   | 0.4146          | 0.83     |
| 0.4739        | 2.0   | 150  | 0.5214          | 0.7783   |
| 0.3159        | 3.0   | 225  | 0.3979          | 0.8467   |
| 0.3044        | 4.0   | 300  | 0.4320          | 0.845    |
| 0.3525        | 5.0   | 375  | 0.3215          | 0.8817   |
| 0.1872        | 6.0   | 450  | 0.4978          | 0.8267   |
| 0.2467        | 7.0   | 525  | 0.5551          | 0.8      |
| 0.1504        | 8.0   | 600  | 0.5301          | 0.8367   |
| 0.1309        | 9.0   | 675  | 0.5781          | 0.84     |
| 0.2177        | 10.0  | 750  | 0.5269          | 0.865    |
| 0.0844        | 11.0  | 825  | 0.5112          | 0.865    |
| 0.0758        | 12.0  | 900  | 0.6543          | 0.8617   |
| 0.1176        | 13.0  | 975  | 0.5860          | 0.855    |
| 0.0455        | 14.0  | 1050 | 0.7995          | 0.8317   |
| 0.0687        | 15.0  | 1125 | 0.6395          | 0.8633   |
| 0.0296        | 16.0  | 1200 | 0.8580          | 0.8517   |
| 0.0214        | 17.0  | 1275 | 0.9274          | 0.85     |
| 0.0164        | 18.0  | 1350 | 0.8318          | 0.8733   |
| 0.0192        | 19.0  | 1425 | 0.9491          | 0.8567   |
| 0.0338        | 20.0  | 1500 | 0.7653          | 0.8567   |
| 0.0007        | 21.0  | 1575 | 0.9985          | 0.8517   |
| 0.0001        | 22.0  | 1650 | 0.9967          | 0.87     |
| 0.0156        | 23.0  | 1725 | 1.1459          | 0.85     |
| 0.0033        | 24.0  | 1800 | 1.1111          | 0.8517   |
| 0.005         | 25.0  | 1875 | 1.1114          | 0.8467   |
| 0.0195        | 26.0  | 1950 | 1.0184          | 0.8617   |
| 0.0001        | 27.0  | 2025 | 1.0582          | 0.8567   |
| 0.0022        | 28.0  | 2100 | 1.1162          | 0.86     |
| 0.0           | 29.0  | 2175 | 1.1193          | 0.86     |
| 0.0           | 30.0  | 2250 | 1.1254          | 0.8567   |
| 0.0           | 31.0  | 2325 | 1.1372          | 0.86     |
| 0.0016        | 32.0  | 2400 | 1.1758          | 0.8583   |
| 0.0051        | 33.0  | 2475 | 1.1778          | 0.845    |
| 0.0047        | 34.0  | 2550 | 1.0600          | 0.8667   |
| 0.01          | 35.0  | 2625 | 1.1195          | 0.855    |
| 0.0037        | 36.0  | 2700 | 1.1381          | 0.8533   |
| 0.0025        | 37.0  | 2775 | 1.1434          | 0.855    |
| 0.0           | 38.0  | 2850 | 1.1612          | 0.8583   |
| 0.0           | 39.0  | 2925 | 1.1652          | 0.8567   |
| 0.0           | 40.0  | 3000 | 1.1711          | 0.855    |
| 0.0           | 41.0  | 3075 | 1.1589          | 0.86     |
| 0.0028        | 42.0  | 3150 | 1.1617          | 0.8617   |
| 0.0032        | 43.0  | 3225 | 1.1622          | 0.86     |
| 0.0           | 44.0  | 3300 | 1.1672          | 0.86     |
| 0.0027        | 45.0  | 3375 | 1.1668          | 0.86     |
| 0.0026        | 46.0  | 3450 | 1.1710          | 0.86     |
| 0.0057        | 47.0  | 3525 | 1.1686          | 0.86     |
| 0.0           | 48.0  | 3600 | 1.1767          | 0.8567   |
| 0.0           | 49.0  | 3675 | 1.1760          | 0.8583   |
| 0.0044        | 50.0  | 3750 | 1.1786          | 0.8567   |


### Framework versions

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