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_001_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: 0.8372093023255814
---

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# hushem_40x_deit_tiny_sgd_001_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: 0.4899
- Accuracy: 0.8372

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.1798        | 1.0   | 217   | 1.2889          | 0.4186   |
| 1.0098        | 2.0   | 434   | 1.1067          | 0.6047   |
| 0.7827        | 3.0   | 651   | 0.9427          | 0.6977   |
| 0.6326        | 4.0   | 868   | 0.7917          | 0.6977   |
| 0.5443        | 5.0   | 1085  | 0.6647          | 0.7907   |
| 0.4438        | 6.0   | 1302  | 0.5810          | 0.8140   |
| 0.3761        | 7.0   | 1519  | 0.5185          | 0.8372   |
| 0.3386        | 8.0   | 1736  | 0.4778          | 0.8140   |
| 0.2796        | 9.0   | 1953  | 0.4431          | 0.8605   |
| 0.2037        | 10.0  | 2170  | 0.4372          | 0.8605   |
| 0.1624        | 11.0  | 2387  | 0.3943          | 0.8837   |
| 0.1477        | 12.0  | 2604  | 0.4019          | 0.8605   |
| 0.1485        | 13.0  | 2821  | 0.3856          | 0.8605   |
| 0.1192        | 14.0  | 3038  | 0.3686          | 0.8605   |
| 0.1115        | 15.0  | 3255  | 0.3722          | 0.8605   |
| 0.0891        | 16.0  | 3472  | 0.3567          | 0.8837   |
| 0.0776        | 17.0  | 3689  | 0.3631          | 0.8605   |
| 0.1039        | 18.0  | 3906  | 0.3600          | 0.8605   |
| 0.0608        | 19.0  | 4123  | 0.3514          | 0.8605   |
| 0.0639        | 20.0  | 4340  | 0.3706          | 0.8605   |
| 0.0555        | 21.0  | 4557  | 0.3773          | 0.8605   |
| 0.0552        | 22.0  | 4774  | 0.3713          | 0.8372   |
| 0.0457        | 23.0  | 4991  | 0.3749          | 0.8372   |
| 0.0383        | 24.0  | 5208  | 0.3901          | 0.8372   |
| 0.0332        | 25.0  | 5425  | 0.3933          | 0.8372   |
| 0.0322        | 26.0  | 5642  | 0.3995          | 0.8372   |
| 0.0278        | 27.0  | 5859  | 0.4012          | 0.8372   |
| 0.0212        | 28.0  | 6076  | 0.3938          | 0.8372   |
| 0.0224        | 29.0  | 6293  | 0.4080          | 0.8372   |
| 0.0218        | 30.0  | 6510  | 0.4237          | 0.8372   |
| 0.0278        | 31.0  | 6727  | 0.4231          | 0.8372   |
| 0.0212        | 32.0  | 6944  | 0.4330          | 0.8372   |
| 0.021         | 33.0  | 7161  | 0.4507          | 0.8372   |
| 0.0127        | 34.0  | 7378  | 0.4390          | 0.8372   |
| 0.0158        | 35.0  | 7595  | 0.4566          | 0.8372   |
| 0.0178        | 36.0  | 7812  | 0.4594          | 0.8372   |
| 0.0109        | 37.0  | 8029  | 0.4570          | 0.8372   |
| 0.0096        | 38.0  | 8246  | 0.4635          | 0.8372   |
| 0.0113        | 39.0  | 8463  | 0.4700          | 0.8372   |
| 0.0149        | 40.0  | 8680  | 0.4815          | 0.8372   |
| 0.0111        | 41.0  | 8897  | 0.4769          | 0.8372   |
| 0.0075        | 42.0  | 9114  | 0.4756          | 0.8372   |
| 0.0093        | 43.0  | 9331  | 0.4800          | 0.8372   |
| 0.009         | 44.0  | 9548  | 0.4851          | 0.8372   |
| 0.0065        | 45.0  | 9765  | 0.4808          | 0.8372   |
| 0.011         | 46.0  | 9982  | 0.4835          | 0.8372   |
| 0.0064        | 47.0  | 10199 | 0.4871          | 0.8372   |
| 0.0093        | 48.0  | 10416 | 0.4902          | 0.8372   |
| 0.0136        | 49.0  | 10633 | 0.4899          | 0.8372   |
| 0.0058        | 50.0  | 10850 | 0.4899          | 0.8372   |


### Framework versions

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