transformers pytorch vit image-classification generated_from_trainer dataset:imagefolder base_model:facebook/deit-tiny-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: smids_3x_deit_tiny_adamax_0001_fold1
  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: 0.8981636060100167
---

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# smids_3x_deit_tiny_adamax_0001_fold1

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: 0.8020
- Accuracy: 0.8982

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.3976        | 1.0   | 226   | 0.3057          | 0.8848   |
| 0.2433        | 2.0   | 452   | 0.3108          | 0.8698   |
| 0.1348        | 3.0   | 678   | 0.3373          | 0.8982   |
| 0.1034        | 4.0   | 904   | 0.3559          | 0.9032   |
| 0.1083        | 5.0   | 1130  | 0.4835          | 0.8648   |
| 0.066         | 6.0   | 1356  | 0.5085          | 0.8881   |
| 0.0304        | 7.0   | 1582  | 0.5167          | 0.8982   |
| 0.0203        | 8.0   | 1808  | 0.4920          | 0.8915   |
| 0.0411        | 9.0   | 2034  | 0.6349          | 0.8948   |
| 0.0001        | 10.0  | 2260  | 0.5499          | 0.9015   |
| 0.0005        | 11.0  | 2486  | 0.8482          | 0.8715   |
| 0.0006        | 12.0  | 2712  | 0.6367          | 0.9082   |
| 0.0001        | 13.0  | 2938  | 0.6540          | 0.9082   |
| 0.0145        | 14.0  | 3164  | 0.7445          | 0.8848   |
| 0.0002        | 15.0  | 3390  | 0.7327          | 0.8948   |
| 0.0002        | 16.0  | 3616  | 0.7425          | 0.8898   |
| 0.0076        | 17.0  | 3842  | 0.8300          | 0.8881   |
| 0.0           | 18.0  | 4068  | 0.8281          | 0.8898   |
| 0.0117        | 19.0  | 4294  | 0.8348          | 0.8865   |
| 0.0           | 20.0  | 4520  | 0.7762          | 0.8932   |
| 0.0101        | 21.0  | 4746  | 0.8545          | 0.8781   |
| 0.0102        | 22.0  | 4972  | 0.6911          | 0.9048   |
| 0.0118        | 23.0  | 5198  | 0.7788          | 0.8965   |
| 0.0134        | 24.0  | 5424  | 0.8281          | 0.8898   |
| 0.0           | 25.0  | 5650  | 0.8580          | 0.8865   |
| 0.0002        | 26.0  | 5876  | 0.8155          | 0.8965   |
| 0.0           | 27.0  | 6102  | 0.7810          | 0.8982   |
| 0.0           | 28.0  | 6328  | 0.7738          | 0.9048   |
| 0.0           | 29.0  | 6554  | 0.7899          | 0.8915   |
| 0.0           | 30.0  | 6780  | 0.7800          | 0.9015   |
| 0.0           | 31.0  | 7006  | 0.7916          | 0.8982   |
| 0.0           | 32.0  | 7232  | 0.7756          | 0.8965   |
| 0.0037        | 33.0  | 7458  | 0.7754          | 0.9015   |
| 0.0           | 34.0  | 7684  | 0.7805          | 0.8982   |
| 0.0           | 35.0  | 7910  | 0.7846          | 0.8932   |
| 0.0           | 36.0  | 8136  | 0.8045          | 0.8932   |
| 0.0           | 37.0  | 8362  | 0.7958          | 0.8948   |
| 0.0           | 38.0  | 8588  | 0.7780          | 0.8965   |
| 0.0           | 39.0  | 8814  | 0.7869          | 0.8998   |
| 0.0           | 40.0  | 9040  | 0.7801          | 0.8965   |
| 0.0031        | 41.0  | 9266  | 0.7806          | 0.9032   |
| 0.0032        | 42.0  | 9492  | 0.8019          | 0.8982   |
| 0.0           | 43.0  | 9718  | 0.7990          | 0.8982   |
| 0.0           | 44.0  | 9944  | 0.8009          | 0.8965   |
| 0.0           | 45.0  | 10170 | 0.8036          | 0.8982   |
| 0.0           | 46.0  | 10396 | 0.8034          | 0.8982   |
| 0.0           | 47.0  | 10622 | 0.8034          | 0.8982   |
| 0.0           | 48.0  | 10848 | 0.8001          | 0.8982   |
| 0.0           | 49.0  | 11074 | 0.8018          | 0.8982   |
| 0.0           | 50.0  | 11300 | 0.8020          | 0.8982   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.1+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2
