transformers pytorch vit image-classification generated_from_trainer dataset:imagefolder base_model:facebook/deit-base-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: facebook/deit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_40x_deit_base_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: 0.7111111111111111
---

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# hushem_40x_deit_base_sgd_001_fold2

This model is a fine-tuned version of [facebook/deit-base-patch16-224](https://huggingface.co/facebook/deit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9714
- Accuracy: 0.7111

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.2707        | 1.0   | 215   | 1.3448          | 0.3333   |
| 1.0768        | 2.0   | 430   | 1.2879          | 0.3333   |
| 0.9642        | 3.0   | 645   | 1.2312          | 0.3556   |
| 0.8173        | 4.0   | 860   | 1.1793          | 0.4222   |
| 0.7029        | 5.0   | 1075  | 1.1361          | 0.4889   |
| 0.6404        | 6.0   | 1290  | 1.1006          | 0.5111   |
| 0.5591        | 7.0   | 1505  | 1.0646          | 0.5778   |
| 0.4274        | 8.0   | 1720  | 1.0467          | 0.5778   |
| 0.3944        | 9.0   | 1935  | 1.0267          | 0.6444   |
| 0.3254        | 10.0  | 2150  | 1.0079          | 0.6222   |
| 0.2604        | 11.0  | 2365  | 0.9958          | 0.6222   |
| 0.2631        | 12.0  | 2580  | 0.9759          | 0.6222   |
| 0.2337        | 13.0  | 2795  | 0.9617          | 0.6      |
| 0.1789        | 14.0  | 3010  | 0.9588          | 0.6222   |
| 0.1879        | 15.0  | 3225  | 0.9460          | 0.6222   |
| 0.1684        | 16.0  | 3440  | 0.9372          | 0.6222   |
| 0.1577        | 17.0  | 3655  | 0.9384          | 0.6444   |
| 0.14          | 18.0  | 3870  | 0.9410          | 0.6444   |
| 0.1197        | 19.0  | 4085  | 0.9384          | 0.6444   |
| 0.1254        | 20.0  | 4300  | 0.9412          | 0.6444   |
| 0.1072        | 21.0  | 4515  | 0.9296          | 0.6444   |
| 0.0973        | 22.0  | 4730  | 0.9322          | 0.6444   |
| 0.0821        | 23.0  | 4945  | 0.9340          | 0.6444   |
| 0.0927        | 24.0  | 5160  | 0.9345          | 0.6667   |
| 0.0715        | 25.0  | 5375  | 0.9358          | 0.6667   |
| 0.0724        | 26.0  | 5590  | 0.9414          | 0.6889   |
| 0.0815        | 27.0  | 5805  | 0.9356          | 0.6667   |
| 0.0671        | 28.0  | 6020  | 0.9387          | 0.6889   |
| 0.053         | 29.0  | 6235  | 0.9438          | 0.6889   |
| 0.0671        | 30.0  | 6450  | 0.9381          | 0.7111   |
| 0.0428        | 31.0  | 6665  | 0.9431          | 0.7111   |
| 0.041         | 32.0  | 6880  | 0.9407          | 0.7111   |
| 0.0371        | 33.0  | 7095  | 0.9476          | 0.7111   |
| 0.0372        | 34.0  | 7310  | 0.9501          | 0.7111   |
| 0.0416        | 35.0  | 7525  | 0.9484          | 0.7111   |
| 0.0375        | 36.0  | 7740  | 0.9551          | 0.7111   |
| 0.0443        | 37.0  | 7955  | 0.9530          | 0.7111   |
| 0.031         | 38.0  | 8170  | 0.9549          | 0.7111   |
| 0.0359        | 39.0  | 8385  | 0.9537          | 0.7111   |
| 0.0327        | 40.0  | 8600  | 0.9553          | 0.7111   |
| 0.0313        | 41.0  | 8815  | 0.9602          | 0.7111   |
| 0.0312        | 42.0  | 9030  | 0.9634          | 0.7111   |
| 0.0302        | 43.0  | 9245  | 0.9659          | 0.7111   |
| 0.0284        | 44.0  | 9460  | 0.9687          | 0.7111   |
| 0.0286        | 45.0  | 9675  | 0.9696          | 0.7111   |
| 0.0307        | 46.0  | 9890  | 0.9699          | 0.7111   |
| 0.0251        | 47.0  | 10105 | 0.9708          | 0.7111   |
| 0.0291        | 48.0  | 10320 | 0.9714          | 0.7111   |
| 0.0372        | 49.0  | 10535 | 0.9713          | 0.7111   |
| 0.0296        | 50.0  | 10750 | 0.9714          | 0.7111   |


### Framework versions

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