transformers pytorch vit image-classification generated_from_trainer dataset:imagefolder base_model:facebook/deit-small-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: facebook/deit-small-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_40x_deit_small_sgd_00001_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: 0.32558139534883723
---

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# hushem_40x_deit_small_sgd_00001_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: 1.3703
- Accuracy: 0.3256

## 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: 1e-05
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.8914        | 1.0   | 217   | 1.5805          | 0.2558   |
| 2.0178        | 2.0   | 434   | 1.5654          | 0.2558   |
| 2.0179        | 3.0   | 651   | 1.5510          | 0.2558   |
| 1.8888        | 4.0   | 868   | 1.5374          | 0.2558   |
| 1.872         | 5.0   | 1085  | 1.5245          | 0.2558   |
| 1.7831        | 6.0   | 1302  | 1.5124          | 0.2558   |
| 1.836         | 7.0   | 1519  | 1.5009          | 0.2558   |
| 1.8178        | 8.0   | 1736  | 1.4901          | 0.2558   |
| 1.7694        | 9.0   | 1953  | 1.4801          | 0.2326   |
| 1.7678        | 10.0  | 2170  | 1.4706          | 0.2326   |
| 1.659         | 11.0  | 2387  | 1.4618          | 0.2326   |
| 1.6239        | 12.0  | 2604  | 1.4536          | 0.2558   |
| 1.6882        | 13.0  | 2821  | 1.4460          | 0.2558   |
| 1.6748        | 14.0  | 3038  | 1.4391          | 0.2558   |
| 1.6892        | 15.0  | 3255  | 1.4327          | 0.2791   |
| 1.725         | 16.0  | 3472  | 1.4268          | 0.2791   |
| 1.6371        | 17.0  | 3689  | 1.4214          | 0.2791   |
| 1.6193        | 18.0  | 3906  | 1.4164          | 0.3256   |
| 1.6512        | 19.0  | 4123  | 1.4119          | 0.3256   |
| 1.6188        | 20.0  | 4340  | 1.4078          | 0.3256   |
| 1.643         | 21.0  | 4557  | 1.4041          | 0.3256   |
| 1.5803        | 22.0  | 4774  | 1.4006          | 0.3256   |
| 1.592         | 23.0  | 4991  | 1.3975          | 0.3256   |
| 1.5987        | 24.0  | 5208  | 1.3946          | 0.3256   |
| 1.566         | 25.0  | 5425  | 1.3921          | 0.3488   |
| 1.5574        | 26.0  | 5642  | 1.3897          | 0.3488   |
| 1.4978        | 27.0  | 5859  | 1.3876          | 0.3488   |
| 1.524         | 28.0  | 6076  | 1.3857          | 0.3488   |
| 1.5682        | 29.0  | 6293  | 1.3839          | 0.3488   |
| 1.5042        | 30.0  | 6510  | 1.3823          | 0.3488   |
| 1.5589        | 31.0  | 6727  | 1.3808          | 0.3023   |
| 1.5347        | 32.0  | 6944  | 1.3795          | 0.3023   |
| 1.5403        | 33.0  | 7161  | 1.3783          | 0.3023   |
| 1.5548        | 34.0  | 7378  | 1.3772          | 0.3023   |
| 1.5321        | 35.0  | 7595  | 1.3762          | 0.3023   |
| 1.5015        | 36.0  | 7812  | 1.3753          | 0.3023   |
| 1.4993        | 37.0  | 8029  | 1.3745          | 0.3023   |
| 1.4844        | 38.0  | 8246  | 1.3738          | 0.3023   |
| 1.5191        | 39.0  | 8463  | 1.3732          | 0.3023   |
| 1.515         | 40.0  | 8680  | 1.3726          | 0.3256   |
| 1.4957        | 41.0  | 8897  | 1.3721          | 0.3256   |
| 1.5585        | 42.0  | 9114  | 1.3717          | 0.3256   |
| 1.5037        | 43.0  | 9331  | 1.3713          | 0.3256   |
| 1.4828        | 44.0  | 9548  | 1.3710          | 0.3256   |
| 1.4967        | 45.0  | 9765  | 1.3708          | 0.3256   |
| 1.5387        | 46.0  | 9982  | 1.3706          | 0.3256   |
| 1.5118        | 47.0  | 10199 | 1.3705          | 0.3256   |
| 1.5073        | 48.0  | 10416 | 1.3704          | 0.3256   |
| 1.5166        | 49.0  | 10633 | 1.3703          | 0.3256   |
| 1.4994        | 50.0  | 10850 | 1.3703          | 0.3256   |


### Framework versions

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