transformers pytorch 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_40x_deit_small_sgd_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: 0.28888888888888886
---

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# hushem_40x_deit_small_sgd_00001_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: 1.4445
- Accuracy: 0.2889

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.9592        | 1.0   | 215   | 1.6375          | 0.2444   |
| 1.9589        | 2.0   | 430   | 1.6244          | 0.2444   |
| 1.9405        | 3.0   | 645   | 1.6119          | 0.2444   |
| 1.8111        | 4.0   | 860   | 1.6000          | 0.2444   |
| 1.7854        | 5.0   | 1075  | 1.5888          | 0.2444   |
| 1.7837        | 6.0   | 1290  | 1.5782          | 0.2444   |
| 1.8329        | 7.0   | 1505  | 1.5681          | 0.2444   |
| 1.808         | 8.0   | 1720  | 1.5587          | 0.2444   |
| 1.8135        | 9.0   | 1935  | 1.5499          | 0.2444   |
| 1.7532        | 10.0  | 2150  | 1.5416          | 0.2444   |
| 1.7679        | 11.0  | 2365  | 1.5338          | 0.2667   |
| 1.6698        | 12.0  | 2580  | 1.5266          | 0.2667   |
| 1.7071        | 13.0  | 2795  | 1.5198          | 0.2667   |
| 1.7064        | 14.0  | 3010  | 1.5135          | 0.2667   |
| 1.6474        | 15.0  | 3225  | 1.5077          | 0.2667   |
| 1.6795        | 16.0  | 3440  | 1.5023          | 0.2667   |
| 1.6509        | 17.0  | 3655  | 1.4973          | 0.2444   |
| 1.6571        | 18.0  | 3870  | 1.4927          | 0.2444   |
| 1.6903        | 19.0  | 4085  | 1.4885          | 0.2444   |
| 1.594         | 20.0  | 4300  | 1.4845          | 0.2444   |
| 1.6043        | 21.0  | 4515  | 1.4809          | 0.2444   |
| 1.5781        | 22.0  | 4730  | 1.4775          | 0.2667   |
| 1.6042        | 23.0  | 4945  | 1.4744          | 0.2667   |
| 1.6585        | 24.0  | 5160  | 1.4716          | 0.2667   |
| 1.6133        | 25.0  | 5375  | 1.4689          | 0.2667   |
| 1.5503        | 26.0  | 5590  | 1.4665          | 0.2667   |
| 1.559         | 27.0  | 5805  | 1.4642          | 0.2889   |
| 1.5271        | 28.0  | 6020  | 1.4621          | 0.3111   |
| 1.5368        | 29.0  | 6235  | 1.4602          | 0.3111   |
| 1.5411        | 30.0  | 6450  | 1.4584          | 0.3111   |
| 1.6163        | 31.0  | 6665  | 1.4568          | 0.3111   |
| 1.5496        | 32.0  | 6880  | 1.4553          | 0.3111   |
| 1.5517        | 33.0  | 7095  | 1.4539          | 0.3111   |
| 1.5789        | 34.0  | 7310  | 1.4526          | 0.3111   |
| 1.5768        | 35.0  | 7525  | 1.4515          | 0.3111   |
| 1.5496        | 36.0  | 7740  | 1.4505          | 0.3111   |
| 1.5074        | 37.0  | 7955  | 1.4495          | 0.3111   |
| 1.5918        | 38.0  | 8170  | 1.4487          | 0.3111   |
| 1.5751        | 39.0  | 8385  | 1.4479          | 0.3111   |
| 1.5533        | 40.0  | 8600  | 1.4472          | 0.3111   |
| 1.5217        | 41.0  | 8815  | 1.4467          | 0.3111   |
| 1.5477        | 42.0  | 9030  | 1.4461          | 0.3111   |
| 1.5219        | 43.0  | 9245  | 1.4457          | 0.3111   |
| 1.5414        | 44.0  | 9460  | 1.4453          | 0.3111   |
| 1.5697        | 45.0  | 9675  | 1.4450          | 0.3111   |
| 1.5331        | 46.0  | 9890  | 1.4448          | 0.3111   |
| 1.5195        | 47.0  | 10105 | 1.4446          | 0.3111   |
| 1.5072        | 48.0  | 10320 | 1.4445          | 0.2889   |
| 1.5469        | 49.0  | 10535 | 1.4445          | 0.2889   |
| 1.5351        | 50.0  | 10750 | 1.4445          | 0.2889   |


### Framework versions

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