---
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_1x_deit_tiny_sgd_lr001_fold5
  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: 0.3902439024390244
---

<!-- 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_1x_deit_tiny_sgd_lr001_fold5

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: 1.3032
- Accuracy: 0.3902

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 6    | 1.6123          | 0.1220   |
| 1.5785        | 2.0   | 12   | 1.5813          | 0.1463   |
| 1.5785        | 3.0   | 18   | 1.5542          | 0.1463   |
| 1.5395        | 4.0   | 24   | 1.5297          | 0.1463   |
| 1.4749        | 5.0   | 30   | 1.5083          | 0.1951   |
| 1.4749        | 6.0   | 36   | 1.4884          | 0.1951   |
| 1.4296        | 7.0   | 42   | 1.4718          | 0.1707   |
| 1.4296        | 8.0   | 48   | 1.4578          | 0.1463   |
| 1.4059        | 9.0   | 54   | 1.4447          | 0.1463   |
| 1.3876        | 10.0  | 60   | 1.4316          | 0.2195   |
| 1.3876        | 11.0  | 66   | 1.4209          | 0.2195   |
| 1.3523        | 12.0  | 72   | 1.4102          | 0.2195   |
| 1.3523        | 13.0  | 78   | 1.4009          | 0.2439   |
| 1.3412        | 14.0  | 84   | 1.3926          | 0.2439   |
| 1.3216        | 15.0  | 90   | 1.3847          | 0.2927   |
| 1.3216        | 16.0  | 96   | 1.3782          | 0.3171   |
| 1.2923        | 17.0  | 102  | 1.3713          | 0.3415   |
| 1.2923        | 18.0  | 108  | 1.3652          | 0.3415   |
| 1.305         | 19.0  | 114  | 1.3592          | 0.3415   |
| 1.2722        | 20.0  | 120  | 1.3536          | 0.3415   |
| 1.2722        | 21.0  | 126  | 1.3490          | 0.3659   |
| 1.2479        | 22.0  | 132  | 1.3441          | 0.3659   |
| 1.2479        | 23.0  | 138  | 1.3399          | 0.3659   |
| 1.2818        | 24.0  | 144  | 1.3360          | 0.3659   |
| 1.2363        | 25.0  | 150  | 1.3318          | 0.3659   |
| 1.2363        | 26.0  | 156  | 1.3281          | 0.3659   |
| 1.2375        | 27.0  | 162  | 1.3249          | 0.3659   |
| 1.2375        | 28.0  | 168  | 1.3220          | 0.3659   |
| 1.2164        | 29.0  | 174  | 1.3194          | 0.3659   |
| 1.2359        | 30.0  | 180  | 1.3171          | 0.3902   |
| 1.2359        | 31.0  | 186  | 1.3148          | 0.3902   |
| 1.2121        | 32.0  | 192  | 1.3127          | 0.3902   |
| 1.2121        | 33.0  | 198  | 1.3110          | 0.3902   |
| 1.2131        | 34.0  | 204  | 1.3092          | 0.3902   |
| 1.1973        | 35.0  | 210  | 1.3077          | 0.3902   |
| 1.1973        | 36.0  | 216  | 1.3064          | 0.3902   |
| 1.1836        | 37.0  | 222  | 1.3054          | 0.3902   |
| 1.1836        | 38.0  | 228  | 1.3046          | 0.3902   |
| 1.2087        | 39.0  | 234  | 1.3039          | 0.3902   |
| 1.2019        | 40.0  | 240  | 1.3035          | 0.3902   |
| 1.2019        | 41.0  | 246  | 1.3033          | 0.3902   |
| 1.2033        | 42.0  | 252  | 1.3032          | 0.3902   |
| 1.2033        | 43.0  | 258  | 1.3032          | 0.3902   |
| 1.1754        | 44.0  | 264  | 1.3032          | 0.3902   |
| 1.1907        | 45.0  | 270  | 1.3032          | 0.3902   |
| 1.1907        | 46.0  | 276  | 1.3032          | 0.3902   |
| 1.2082        | 47.0  | 282  | 1.3032          | 0.3902   |
| 1.2082        | 48.0  | 288  | 1.3032          | 0.3902   |
| 1.1699        | 49.0  | 294  | 1.3032          | 0.3902   |
| 1.2038        | 50.0  | 300  | 1.3032          | 0.3902   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1