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: hushem_40x_deit_tiny_sgd_001_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: 0.6888888888888889
---

<!-- 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. -->

# hushem_40x_deit_tiny_sgd_001_fold2

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: 1.0440
- Accuracy: 0.6889

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.0975        | 1.0   | 215   | 1.3370          | 0.3778   |
| 0.8761        | 2.0   | 430   | 1.2895          | 0.4444   |
| 0.7359        | 3.0   | 645   | 1.2565          | 0.4889   |
| 0.6277        | 4.0   | 860   | 1.2398          | 0.5556   |
| 0.5094        | 5.0   | 1075  | 1.2052          | 0.5556   |
| 0.4187        | 6.0   | 1290  | 1.1950          | 0.5778   |
| 0.3909        | 7.0   | 1505  | 1.1310          | 0.6      |
| 0.3137        | 8.0   | 1720  | 1.1412          | 0.5556   |
| 0.2817        | 9.0   | 1935  | 1.0706          | 0.5778   |
| 0.2108        | 10.0  | 2150  | 1.0537          | 0.6      |
| 0.1785        | 11.0  | 2365  | 1.0606          | 0.5778   |
| 0.1677        | 12.0  | 2580  | 1.0202          | 0.5778   |
| 0.1602        | 13.0  | 2795  | 1.0251          | 0.5778   |
| 0.1355        | 14.0  | 3010  | 1.0164          | 0.6      |
| 0.1234        | 15.0  | 3225  | 1.0019          | 0.5778   |
| 0.0937        | 16.0  | 3440  | 0.9960          | 0.6      |
| 0.0963        | 17.0  | 3655  | 0.9708          | 0.5778   |
| 0.0998        | 18.0  | 3870  | 0.9907          | 0.5778   |
| 0.0604        | 19.0  | 4085  | 0.9932          | 0.6      |
| 0.0724        | 20.0  | 4300  | 0.9792          | 0.5556   |
| 0.0616        | 21.0  | 4515  | 0.9528          | 0.5556   |
| 0.0591        | 22.0  | 4730  | 0.9741          | 0.5556   |
| 0.0433        | 23.0  | 4945  | 0.9824          | 0.5556   |
| 0.0476        | 24.0  | 5160  | 0.9907          | 0.5556   |
| 0.0326        | 25.0  | 5375  | 0.9714          | 0.5778   |
| 0.0325        | 26.0  | 5590  | 0.9834          | 0.6      |
| 0.0352        | 27.0  | 5805  | 0.9903          | 0.5778   |
| 0.0319        | 28.0  | 6020  | 0.9831          | 0.5778   |
| 0.0242        | 29.0  | 6235  | 0.9872          | 0.6      |
| 0.0238        | 30.0  | 6450  | 1.0027          | 0.6222   |
| 0.0166        | 31.0  | 6665  | 0.9985          | 0.5778   |
| 0.0151        | 32.0  | 6880  | 1.0088          | 0.6      |
| 0.0176        | 33.0  | 7095  | 1.0180          | 0.6      |
| 0.0221        | 34.0  | 7310  | 1.0038          | 0.6444   |
| 0.0159        | 35.0  | 7525  | 0.9868          | 0.6667   |
| 0.0115        | 36.0  | 7740  | 1.0104          | 0.6444   |
| 0.017         | 37.0  | 7955  | 1.0128          | 0.6889   |
| 0.0105        | 38.0  | 8170  | 1.0250          | 0.6444   |
| 0.0144        | 39.0  | 8385  | 1.0115          | 0.6889   |
| 0.0092        | 40.0  | 8600  | 1.0202          | 0.6667   |
| 0.0131        | 41.0  | 8815  | 1.0296          | 0.6444   |
| 0.0108        | 42.0  | 9030  | 1.0274          | 0.6889   |
| 0.0089        | 43.0  | 9245  | 1.0423          | 0.6889   |
| 0.0153        | 44.0  | 9460  | 1.0420          | 0.6889   |
| 0.0077        | 45.0  | 9675  | 1.0387          | 0.6667   |
| 0.0096        | 46.0  | 9890  | 1.0413          | 0.6889   |
| 0.0073        | 47.0  | 10105 | 1.0431          | 0.6889   |
| 0.0112        | 48.0  | 10320 | 1.0453          | 0.6889   |
| 0.0085        | 49.0  | 10535 | 1.0438          | 0.6889   |
| 0.01          | 50.0  | 10750 | 1.0440          | 0.6889   |


### Framework versions

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