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: smids_3x_deit_small_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: 0.8768718801996672
---

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# smids_3x_deit_small_adamax_0001_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: 1.0636
- Accuracy: 0.8769

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.2927        | 1.0   | 225   | 0.3073          | 0.8686   |
| 0.1512        | 2.0   | 450   | 0.3158          | 0.8902   |
| 0.0739        | 3.0   | 675   | 0.4826          | 0.8602   |
| 0.0696        | 4.0   | 900   | 0.4520          | 0.8835   |
| 0.0095        | 5.0   | 1125  | 0.6442          | 0.8636   |
| 0.0162        | 6.0   | 1350  | 0.8340          | 0.8403   |
| 0.0336        | 7.0   | 1575  | 0.6936          | 0.8669   |
| 0.0025        | 8.0   | 1800  | 0.8353          | 0.8669   |
| 0.0105        | 9.0   | 2025  | 0.8036          | 0.8702   |
| 0.0025        | 10.0  | 2250  | 0.8245          | 0.8769   |
| 0.0004        | 11.0  | 2475  | 0.9095          | 0.8802   |
| 0.0003        | 12.0  | 2700  | 1.0840          | 0.8669   |
| 0.0001        | 13.0  | 2925  | 0.9475          | 0.8735   |
| 0.016         | 14.0  | 3150  | 0.9122          | 0.8835   |
| 0.0           | 15.0  | 3375  | 0.7790          | 0.8918   |
| 0.0           | 16.0  | 3600  | 0.7787          | 0.8785   |
| 0.0029        | 17.0  | 3825  | 0.8308          | 0.8918   |
| 0.0           | 18.0  | 4050  | 0.9812          | 0.8752   |
| 0.0006        | 19.0  | 4275  | 0.9540          | 0.8686   |
| 0.0           | 20.0  | 4500  | 0.9292          | 0.8785   |
| 0.0           | 21.0  | 4725  | 0.9652          | 0.8785   |
| 0.0           | 22.0  | 4950  | 0.9762          | 0.8802   |
| 0.0029        | 23.0  | 5175  | 0.9826          | 0.8702   |
| 0.0           | 24.0  | 5400  | 0.9763          | 0.8669   |
| 0.0047        | 25.0  | 5625  | 0.9733          | 0.8719   |
| 0.0           | 26.0  | 5850  | 0.9680          | 0.8686   |
| 0.0           | 27.0  | 6075  | 0.9775          | 0.8869   |
| 0.0           | 28.0  | 6300  | 0.9726          | 0.8769   |
| 0.0           | 29.0  | 6525  | 1.0293          | 0.8702   |
| 0.0036        | 30.0  | 6750  | 1.0029          | 0.8885   |
| 0.0           | 31.0  | 6975  | 0.9992          | 0.8686   |
| 0.0           | 32.0  | 7200  | 0.9937          | 0.8686   |
| 0.0           | 33.0  | 7425  | 0.9950          | 0.8802   |
| 0.0           | 34.0  | 7650  | 0.9997          | 0.8735   |
| 0.0           | 35.0  | 7875  | 1.0478          | 0.8769   |
| 0.0033        | 36.0  | 8100  | 1.0278          | 0.8686   |
| 0.0           | 37.0  | 8325  | 1.0247          | 0.8802   |
| 0.0           | 38.0  | 8550  | 1.0317          | 0.8785   |
| 0.0032        | 39.0  | 8775  | 1.0297          | 0.8819   |
| 0.0           | 40.0  | 9000  | 1.0396          | 0.8802   |
| 0.0           | 41.0  | 9225  | 1.0404          | 0.8752   |
| 0.0           | 42.0  | 9450  | 1.0476          | 0.8785   |
| 0.0           | 43.0  | 9675  | 1.0513          | 0.8802   |
| 0.0           | 44.0  | 9900  | 1.0502          | 0.8769   |
| 0.0           | 45.0  | 10125 | 1.0584          | 0.8752   |
| 0.0           | 46.0  | 10350 | 1.0568          | 0.8769   |
| 0.0           | 47.0  | 10575 | 1.0576          | 0.8785   |
| 0.0           | 48.0  | 10800 | 1.0616          | 0.8785   |
| 0.0023        | 49.0  | 11025 | 1.0626          | 0.8769   |
| 0.0023        | 50.0  | 11250 | 1.0636          | 0.8769   |


### Framework versions

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