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: hushem_5x_deit_small_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: 0.4444444444444444
---

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# hushem_5x_deit_small_sgd_001_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: 1.3629
- Accuracy: 0.4444

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4659        | 1.0   | 27   | 1.4409          | 0.2889   |
| 1.3866        | 2.0   | 54   | 1.4026          | 0.3556   |
| 1.3486        | 3.0   | 81   | 1.3816          | 0.3333   |
| 1.3477        | 4.0   | 108  | 1.3676          | 0.3111   |
| 1.2816        | 5.0   | 135  | 1.3557          | 0.3333   |
| 1.2558        | 6.0   | 162  | 1.3444          | 0.3556   |
| 1.2259        | 7.0   | 189  | 1.3343          | 0.3556   |
| 1.2042        | 8.0   | 216  | 1.3245          | 0.3556   |
| 1.1683        | 9.0   | 243  | 1.3158          | 0.4      |
| 1.1515        | 10.0  | 270  | 1.3086          | 0.4222   |
| 1.1156        | 11.0  | 297  | 1.3037          | 0.4222   |
| 1.1061        | 12.0  | 324  | 1.2999          | 0.4444   |
| 1.0903        | 13.0  | 351  | 1.3002          | 0.4444   |
| 1.0661        | 14.0  | 378  | 1.3028          | 0.4444   |
| 1.0598        | 15.0  | 405  | 1.3085          | 0.4444   |
| 1.0378        | 16.0  | 432  | 1.3130          | 0.4444   |
| 1.0191        | 17.0  | 459  | 1.3179          | 0.4444   |
| 0.9884        | 18.0  | 486  | 1.3238          | 0.4444   |
| 0.9629        | 19.0  | 513  | 1.3282          | 0.4444   |
| 0.9575        | 20.0  | 540  | 1.3319          | 0.4222   |
| 0.9397        | 21.0  | 567  | 1.3353          | 0.4222   |
| 0.9296        | 22.0  | 594  | 1.3380          | 0.4222   |
| 0.9149        | 23.0  | 621  | 1.3408          | 0.4222   |
| 0.9023        | 24.0  | 648  | 1.3446          | 0.4222   |
| 0.8747        | 25.0  | 675  | 1.3454          | 0.4667   |
| 0.9184        | 26.0  | 702  | 1.3472          | 0.4444   |
| 0.8454        | 27.0  | 729  | 1.3479          | 0.4444   |
| 0.8505        | 28.0  | 756  | 1.3510          | 0.4444   |
| 0.8567        | 29.0  | 783  | 1.3517          | 0.4444   |
| 0.8854        | 30.0  | 810  | 1.3544          | 0.4667   |
| 0.834         | 31.0  | 837  | 1.3546          | 0.4444   |
| 0.8438        | 32.0  | 864  | 1.3560          | 0.4444   |
| 0.8236        | 33.0  | 891  | 1.3564          | 0.4444   |
| 0.8208        | 34.0  | 918  | 1.3570          | 0.4444   |
| 0.8066        | 35.0  | 945  | 1.3589          | 0.4444   |
| 0.8073        | 36.0  | 972  | 1.3591          | 0.4444   |
| 0.8089        | 37.0  | 999  | 1.3595          | 0.4444   |
| 0.777         | 38.0  | 1026 | 1.3599          | 0.4444   |
| 0.7828        | 39.0  | 1053 | 1.3610          | 0.4444   |
| 0.787         | 40.0  | 1080 | 1.3609          | 0.4444   |
| 0.8016        | 41.0  | 1107 | 1.3612          | 0.4444   |
| 0.7822        | 42.0  | 1134 | 1.3619          | 0.4444   |
| 0.8105        | 43.0  | 1161 | 1.3621          | 0.4444   |
| 0.7646        | 44.0  | 1188 | 1.3622          | 0.4444   |
| 0.7928        | 45.0  | 1215 | 1.3624          | 0.4444   |
| 0.7714        | 46.0  | 1242 | 1.3625          | 0.4444   |
| 0.7741        | 47.0  | 1269 | 1.3627          | 0.4444   |
| 0.7688        | 48.0  | 1296 | 1.3629          | 0.4444   |
| 0.834         | 49.0  | 1323 | 1.3629          | 0.4444   |
| 0.7751        | 50.0  | 1350 | 1.3629          | 0.4444   |


### Framework versions

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