transformers tensorboard safetensors 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: smids_1x_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: 0.47
---

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# smids_1x_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: 1.0491
- Accuracy: 0.47

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0941        | 1.0   | 75   | 1.0867          | 0.3867   |
| 1.1031        | 2.0   | 150  | 1.0847          | 0.3883   |
| 1.0678        | 3.0   | 225  | 1.0827          | 0.39     |
| 1.0493        | 4.0   | 300  | 1.0809          | 0.395    |
| 1.0783        | 5.0   | 375  | 1.0791          | 0.4017   |
| 1.0689        | 6.0   | 450  | 1.0774          | 0.4083   |
| 1.0606        | 7.0   | 525  | 1.0758          | 0.4117   |
| 1.0286        | 8.0   | 600  | 1.0743          | 0.4117   |
| 1.0504        | 9.0   | 675  | 1.0729          | 0.415    |
| 1.0349        | 10.0  | 750  | 1.0714          | 0.415    |
| 1.0372        | 11.0  | 825  | 1.0701          | 0.4167   |
| 1.0665        | 12.0  | 900  | 1.0688          | 0.4233   |
| 1.0542        | 13.0  | 975  | 1.0676          | 0.4233   |
| 1.0662        | 14.0  | 1050 | 1.0664          | 0.4267   |
| 1.0308        | 15.0  | 1125 | 1.0653          | 0.4283   |
| 1.0599        | 16.0  | 1200 | 1.0642          | 0.4283   |
| 1.0281        | 17.0  | 1275 | 1.0632          | 0.43     |
| 1.0433        | 18.0  | 1350 | 1.0622          | 0.4383   |
| 1.0474        | 19.0  | 1425 | 1.0612          | 0.4433   |
| 1.0662        | 20.0  | 1500 | 1.0603          | 0.4467   |
| 1.0359        | 21.0  | 1575 | 1.0595          | 0.4417   |
| 1.0248        | 22.0  | 1650 | 1.0587          | 0.4417   |
| 1.0401        | 23.0  | 1725 | 1.0579          | 0.445    |
| 1.0329        | 24.0  | 1800 | 1.0572          | 0.4467   |
| 1.053         | 25.0  | 1875 | 1.0565          | 0.4533   |
| 1.0305        | 26.0  | 1950 | 1.0558          | 0.4533   |
| 1.0308        | 27.0  | 2025 | 1.0552          | 0.455    |
| 1.0523        | 28.0  | 2100 | 1.0546          | 0.4567   |
| 1.0577        | 29.0  | 2175 | 1.0541          | 0.4583   |
| 1.0456        | 30.0  | 2250 | 1.0535          | 0.4583   |
| 1.0268        | 31.0  | 2325 | 1.0531          | 0.4583   |
| 1.0567        | 32.0  | 2400 | 1.0526          | 0.4617   |
| 1.0191        | 33.0  | 2475 | 1.0522          | 0.465    |
| 1.0381        | 34.0  | 2550 | 1.0518          | 0.47     |
| 1.0572        | 35.0  | 2625 | 1.0514          | 0.47     |
| 1.0481        | 36.0  | 2700 | 1.0511          | 0.47     |
| 1.022         | 37.0  | 2775 | 1.0508          | 0.4683   |
| 1.0366        | 38.0  | 2850 | 1.0505          | 0.4683   |
| 1.029         | 39.0  | 2925 | 1.0502          | 0.4683   |
| 1.0115        | 40.0  | 3000 | 1.0500          | 0.47     |
| 1.0512        | 41.0  | 3075 | 1.0498          | 0.47     |
| 1.0219        | 42.0  | 3150 | 1.0496          | 0.47     |
| 1.046         | 43.0  | 3225 | 1.0495          | 0.47     |
| 1.0476        | 44.0  | 3300 | 1.0494          | 0.47     |
| 1.0512        | 45.0  | 3375 | 1.0493          | 0.47     |
| 1.0286        | 46.0  | 3450 | 1.0492          | 0.47     |
| 1.0307        | 47.0  | 3525 | 1.0491          | 0.47     |
| 1.0266        | 48.0  | 3600 | 1.0491          | 0.47     |
| 1.0403        | 49.0  | 3675 | 1.0491          | 0.47     |
| 1.011         | 50.0  | 3750 | 1.0491          | 0.47     |


### Framework versions

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