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_adamax_00001_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: 0.7555555555555555
---

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# hushem_40x_deit_base_adamax_00001_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: 2.1410
- 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: 1e-05
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.1698        | 1.0   | 215   | 0.9036          | 0.6667   |
| 0.0086        | 2.0   | 430   | 0.8771          | 0.8      |
| 0.0023        | 3.0   | 645   | 0.9467          | 0.8      |
| 0.0009        | 4.0   | 860   | 1.0021          | 0.7778   |
| 0.0006        | 5.0   | 1075  | 1.0414          | 0.7556   |
| 0.0004        | 6.0   | 1290  | 1.0789          | 0.7556   |
| 0.0003        | 7.0   | 1505  | 1.0927          | 0.7778   |
| 0.0002        | 8.0   | 1720  | 1.1233          | 0.7778   |
| 0.0002        | 9.0   | 1935  | 1.1652          | 0.7778   |
| 0.0001        | 10.0  | 2150  | 1.1805          | 0.7778   |
| 0.0001        | 11.0  | 2365  | 1.2046          | 0.7778   |
| 0.0001        | 12.0  | 2580  | 1.2366          | 0.7778   |
| 0.0001        | 13.0  | 2795  | 1.2540          | 0.7778   |
| 0.0001        | 14.0  | 3010  | 1.2856          | 0.7778   |
| 0.0           | 15.0  | 3225  | 1.3104          | 0.7778   |
| 0.0           | 16.0  | 3440  | 1.3434          | 0.7778   |
| 0.0           | 17.0  | 3655  | 1.3705          | 0.7778   |
| 0.0           | 18.0  | 3870  | 1.3922          | 0.7778   |
| 0.0           | 19.0  | 4085  | 1.4221          | 0.7778   |
| 0.0           | 20.0  | 4300  | 1.4557          | 0.7778   |
| 0.0           | 21.0  | 4515  | 1.4854          | 0.7778   |
| 0.0           | 22.0  | 4730  | 1.5092          | 0.7778   |
| 0.0           | 23.0  | 4945  | 1.5343          | 0.7778   |
| 0.0           | 24.0  | 5160  | 1.5541          | 0.7778   |
| 0.0           | 25.0  | 5375  | 1.5830          | 0.7778   |
| 0.0           | 26.0  | 5590  | 1.6177          | 0.7778   |
| 0.0           | 27.0  | 5805  | 1.6474          | 0.7778   |
| 0.0           | 28.0  | 6020  | 1.6634          | 0.7778   |
| 0.0           | 29.0  | 6235  | 1.6875          | 0.7778   |
| 0.0           | 30.0  | 6450  | 1.7106          | 0.7778   |
| 0.0           | 31.0  | 6665  | 1.7484          | 0.7778   |
| 0.0           | 32.0  | 6880  | 1.7797          | 0.7778   |
| 0.0           | 33.0  | 7095  | 1.8167          | 0.7778   |
| 0.0           | 34.0  | 7310  | 1.8422          | 0.7778   |
| 0.0           | 35.0  | 7525  | 1.8678          | 0.7778   |
| 0.0           | 36.0  | 7740  | 1.8865          | 0.7778   |
| 0.0           | 37.0  | 7955  | 1.9143          | 0.7778   |
| 0.0           | 38.0  | 8170  | 1.9225          | 0.7778   |
| 0.0           | 39.0  | 8385  | 1.9621          | 0.7778   |
| 0.0           | 40.0  | 8600  | 1.9777          | 0.7556   |
| 0.0           | 41.0  | 8815  | 2.0240          | 0.7778   |
| 0.0           | 42.0  | 9030  | 2.0141          | 0.7556   |
| 0.0           | 43.0  | 9245  | 2.0463          | 0.7556   |
| 0.0           | 44.0  | 9460  | 2.0688          | 0.7556   |
| 0.0           | 45.0  | 9675  | 2.0919          | 0.7556   |
| 0.0           | 46.0  | 9890  | 2.1123          | 0.7556   |
| 0.0           | 47.0  | 10105 | 2.1294          | 0.7556   |
| 0.0           | 48.0  | 10320 | 2.1354          | 0.7556   |
| 0.0           | 49.0  | 10535 | 2.1448          | 0.7556   |
| 0.0           | 50.0  | 10750 | 2.1410          | 0.7556   |


### Framework versions

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