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_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: 0.7555555555555555
---

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# hushem_40x_deit_base_sgd_001_fold1

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: 0.7430
- Accuracy: 0.7556

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.2392        | 1.0   | 215   | 1.3895          | 0.2667   |
| 1.1003        | 2.0   | 430   | 1.3294          | 0.3333   |
| 1.0196        | 3.0   | 645   | 1.2624          | 0.4444   |
| 0.8639        | 4.0   | 860   | 1.1946          | 0.4889   |
| 0.731         | 5.0   | 1075  | 1.1313          | 0.5111   |
| 0.6646        | 6.0   | 1290  | 1.0718          | 0.5556   |
| 0.545         | 7.0   | 1505  | 1.0254          | 0.6      |
| 0.4701        | 8.0   | 1720  | 0.9800          | 0.6444   |
| 0.4065        | 9.0   | 1935  | 0.9495          | 0.6222   |
| 0.3851        | 10.0  | 2150  | 0.9148          | 0.6667   |
| 0.3271        | 11.0  | 2365  | 0.8947          | 0.6667   |
| 0.2977        | 12.0  | 2580  | 0.8732          | 0.6889   |
| 0.2671        | 13.0  | 2795  | 0.8416          | 0.7111   |
| 0.2428        | 14.0  | 3010  | 0.8450          | 0.6889   |
| 0.2387        | 15.0  | 3225  | 0.8270          | 0.7111   |
| 0.1988        | 16.0  | 3440  | 0.8218          | 0.7111   |
| 0.1804        | 17.0  | 3655  | 0.8107          | 0.7333   |
| 0.1681        | 18.0  | 3870  | 0.8058          | 0.7333   |
| 0.1475        | 19.0  | 4085  | 0.7968          | 0.7333   |
| 0.1494        | 20.0  | 4300  | 0.7851          | 0.7556   |
| 0.1288        | 21.0  | 4515  | 0.7807          | 0.7556   |
| 0.1265        | 22.0  | 4730  | 0.7751          | 0.7556   |
| 0.1136        | 23.0  | 4945  | 0.7744          | 0.7556   |
| 0.094         | 24.0  | 5160  | 0.7654          | 0.7556   |
| 0.0987        | 25.0  | 5375  | 0.7661          | 0.7556   |
| 0.096         | 26.0  | 5590  | 0.7527          | 0.7556   |
| 0.084         | 27.0  | 5805  | 0.7535          | 0.7556   |
| 0.069         | 28.0  | 6020  | 0.7589          | 0.7556   |
| 0.0764        | 29.0  | 6235  | 0.7612          | 0.7556   |
| 0.067         | 30.0  | 6450  | 0.7558          | 0.7556   |
| 0.0458        | 31.0  | 6665  | 0.7531          | 0.7333   |
| 0.0687        | 32.0  | 6880  | 0.7463          | 0.7556   |
| 0.0414        | 33.0  | 7095  | 0.7445          | 0.7556   |
| 0.0522        | 34.0  | 7310  | 0.7378          | 0.7556   |
| 0.0521        | 35.0  | 7525  | 0.7477          | 0.7556   |
| 0.0458        | 36.0  | 7740  | 0.7370          | 0.7556   |
| 0.0586        | 37.0  | 7955  | 0.7425          | 0.7556   |
| 0.0551        | 38.0  | 8170  | 0.7441          | 0.7556   |
| 0.0389        | 39.0  | 8385  | 0.7437          | 0.7556   |
| 0.0335        | 40.0  | 8600  | 0.7446          | 0.7556   |
| 0.0337        | 41.0  | 8815  | 0.7439          | 0.7556   |
| 0.0431        | 42.0  | 9030  | 0.7421          | 0.7556   |
| 0.0392        | 43.0  | 9245  | 0.7439          | 0.7556   |
| 0.03          | 44.0  | 9460  | 0.7447          | 0.7556   |
| 0.0402        | 45.0  | 9675  | 0.7426          | 0.7556   |
| 0.0313        | 46.0  | 9890  | 0.7416          | 0.7556   |
| 0.0341        | 47.0  | 10105 | 0.7428          | 0.7556   |
| 0.0375        | 48.0  | 10320 | 0.7420          | 0.7556   |
| 0.0432        | 49.0  | 10535 | 0.7428          | 0.7556   |
| 0.0389        | 50.0  | 10750 | 0.7430          | 0.7556   |


### Framework versions

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