transformers pytorch vit image-classification generated_from_trainer dataset:imagefolder base_model:facebook/deit-tiny-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_40x_deit_tiny_sgd_00001_fold3
  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: 0.27906976744186046
---

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# hushem_40x_deit_tiny_sgd_00001_fold3

This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4228
- Accuracy: 0.2791

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.4808        | 1.0   | 217   | 1.4816          | 0.2791   |
| 1.4823        | 2.0   | 434   | 1.4791          | 0.2791   |
| 1.4134        | 3.0   | 651   | 1.4766          | 0.2791   |
| 1.4759        | 4.0   | 868   | 1.4742          | 0.2791   |
| 1.4883        | 5.0   | 1085  | 1.4718          | 0.2791   |
| 1.4518        | 6.0   | 1302  | 1.4695          | 0.3023   |
| 1.4499        | 7.0   | 1519  | 1.4671          | 0.2791   |
| 1.4363        | 8.0   | 1736  | 1.4648          | 0.2791   |
| 1.4639        | 9.0   | 1953  | 1.4626          | 0.2791   |
| 1.447         | 10.0  | 2170  | 1.4604          | 0.2791   |
| 1.4636        | 11.0  | 2387  | 1.4583          | 0.3023   |
| 1.4249        | 12.0  | 2604  | 1.4562          | 0.3023   |
| 1.4551        | 13.0  | 2821  | 1.4542          | 0.3023   |
| 1.4299        | 14.0  | 3038  | 1.4523          | 0.2791   |
| 1.4254        | 15.0  | 3255  | 1.4505          | 0.2791   |
| 1.3712        | 16.0  | 3472  | 1.4487          | 0.2791   |
| 1.4294        | 17.0  | 3689  | 1.4469          | 0.2791   |
| 1.3982        | 18.0  | 3906  | 1.4452          | 0.2791   |
| 1.39          | 19.0  | 4123  | 1.4437          | 0.2791   |
| 1.3895        | 20.0  | 4340  | 1.4422          | 0.2791   |
| 1.3897        | 21.0  | 4557  | 1.4407          | 0.2791   |
| 1.381         | 22.0  | 4774  | 1.4393          | 0.2791   |
| 1.3878        | 23.0  | 4991  | 1.4380          | 0.2791   |
| 1.4255        | 24.0  | 5208  | 1.4367          | 0.2791   |
| 1.397         | 25.0  | 5425  | 1.4355          | 0.2791   |
| 1.3946        | 26.0  | 5642  | 1.4344          | 0.2791   |
| 1.4141        | 27.0  | 5859  | 1.4334          | 0.2791   |
| 1.391         | 28.0  | 6076  | 1.4324          | 0.2791   |
| 1.3772        | 29.0  | 6293  | 1.4314          | 0.2791   |
| 1.4053        | 30.0  | 6510  | 1.4305          | 0.2791   |
| 1.3414        | 31.0  | 6727  | 1.4297          | 0.2791   |
| 1.368         | 32.0  | 6944  | 1.4288          | 0.2791   |
| 1.3993        | 33.0  | 7161  | 1.4281          | 0.2791   |
| 1.3039        | 34.0  | 7378  | 1.4274          | 0.2791   |
| 1.3467        | 35.0  | 7595  | 1.4268          | 0.2791   |
| 1.3754        | 36.0  | 7812  | 1.4262          | 0.2791   |
| 1.3681        | 37.0  | 8029  | 1.4257          | 0.2791   |
| 1.3927        | 38.0  | 8246  | 1.4252          | 0.2791   |
| 1.3307        | 39.0  | 8463  | 1.4248          | 0.2791   |
| 1.3625        | 40.0  | 8680  | 1.4244          | 0.2791   |
| 1.3775        | 41.0  | 8897  | 1.4240          | 0.2791   |
| 1.3411        | 42.0  | 9114  | 1.4237          | 0.2791   |
| 1.3645        | 43.0  | 9331  | 1.4235          | 0.2791   |
| 1.3775        | 44.0  | 9548  | 1.4233          | 0.2791   |
| 1.3259        | 45.0  | 9765  | 1.4231          | 0.2791   |
| 1.3653        | 46.0  | 9982  | 1.4230          | 0.2791   |
| 1.3629        | 47.0  | 10199 | 1.4229          | 0.2791   |
| 1.3538        | 48.0  | 10416 | 1.4229          | 0.2791   |
| 1.3676        | 49.0  | 10633 | 1.4228          | 0.2791   |
| 1.357         | 50.0  | 10850 | 1.4228          | 0.2791   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.1+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2
