---
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_rms_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: 0.9302325581395349
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# hushem_40x_deit_tiny_rms_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: 0.4488
- Accuracy: 0.9302

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.0843        | 1.0   | 217   | 0.4280          | 0.8837   |
| 0.0143        | 2.0   | 434   | 0.2889          | 0.9302   |
| 0.0172        | 3.0   | 651   | 0.5423          | 0.9070   |
| 0.0189        | 4.0   | 868   | 1.1419          | 0.7907   |
| 0.0003        | 5.0   | 1085  | 0.4120          | 0.9302   |
| 0.0           | 6.0   | 1302  | 0.4870          | 0.9302   |
| 0.0           | 7.0   | 1519  | 0.5568          | 0.9070   |
| 0.0           | 8.0   | 1736  | 0.5757          | 0.8837   |
| 0.0           | 9.0   | 1953  | 0.6076          | 0.8837   |
| 0.0           | 10.0  | 2170  | 0.6516          | 0.8837   |
| 0.0           | 11.0  | 2387  | 0.6056          | 0.8837   |
| 0.0           | 12.0  | 2604  | 0.6691          | 0.8837   |
| 0.0           | 13.0  | 2821  | 0.6559          | 0.8837   |
| 0.0           | 14.0  | 3038  | 0.7098          | 0.9070   |
| 0.0           | 15.0  | 3255  | 0.6515          | 0.9070   |
| 0.0157        | 16.0  | 3472  | 0.6215          | 0.8837   |
| 0.0           | 17.0  | 3689  | 0.6307          | 0.8837   |
| 0.0           | 18.0  | 3906  | 0.7467          | 0.8837   |
| 0.0           | 19.0  | 4123  | 0.7677          | 0.8837   |
| 0.0           | 20.0  | 4340  | 0.7998          | 0.8605   |
| 0.0           | 21.0  | 4557  | 0.8197          | 0.8605   |
| 0.0           | 22.0  | 4774  | 0.8507          | 0.8605   |
| 0.0           | 23.0  | 4991  | 0.8634          | 0.8605   |
| 0.0           | 24.0  | 5208  | 0.8853          | 0.8605   |
| 0.0           | 25.0  | 5425  | 0.7783          | 0.9070   |
| 0.0           | 26.0  | 5642  | 0.7092          | 0.9302   |
| 0.0           | 27.0  | 5859  | 0.6309          | 0.9302   |
| 0.0           | 28.0  | 6076  | 0.6509          | 0.9302   |
| 0.0           | 29.0  | 6293  | 0.5569          | 0.9070   |
| 0.0           | 30.0  | 6510  | 0.5554          | 0.9302   |
| 0.0           | 31.0  | 6727  | 0.5595          | 0.9070   |
| 0.0           | 32.0  | 6944  | 0.5154          | 0.9302   |
| 0.0           | 33.0  | 7161  | 0.5043          | 0.9070   |
| 0.0           | 34.0  | 7378  | 0.5110          | 0.9535   |
| 0.0           | 35.0  | 7595  | 0.4416          | 0.9302   |
| 0.0           | 36.0  | 7812  | 0.4610          | 0.9535   |
| 0.0           | 37.0  | 8029  | 0.5159          | 0.9302   |
| 0.0           | 38.0  | 8246  | 0.5232          | 0.9302   |
| 0.0           | 39.0  | 8463  | 0.5109          | 0.9302   |
| 0.0           | 40.0  | 8680  | 0.4511          | 0.9535   |
| 0.0           | 41.0  | 8897  | 0.4620          | 0.9302   |
| 0.0           | 42.0  | 9114  | 0.4370          | 0.9302   |
| 0.0           | 43.0  | 9331  | 0.4660          | 0.9302   |
| 0.0           | 44.0  | 9548  | 0.4561          | 0.9302   |
| 0.0           | 45.0  | 9765  | 0.4386          | 0.9302   |
| 0.0           | 46.0  | 9982  | 0.4625          | 0.9302   |
| 0.0           | 47.0  | 10199 | 0.4505          | 0.9302   |
| 0.0           | 48.0  | 10416 | 0.4377          | 0.9302   |
| 0.0           | 49.0  | 10633 | 0.4484          | 0.9302   |
| 0.0           | 50.0  | 10850 | 0.4488          | 0.9302   |


### Framework versions

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