---
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_fold1
  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: 0.3111111111111111
---

<!-- 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_fold1

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: 1.4305
- Accuracy: 0.3111

## 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    | 1.6118          | 0.1778   |
| 1.6924        | 2.0   | 12   | 1.5735          | 0.2222   |
| 1.6924        | 3.0   | 18   | 1.5416          | 0.2222   |
| 1.5478        | 4.0   | 24   | 1.5201          | 0.2444   |
| 1.5093        | 5.0   | 30   | 1.4995          | 0.2889   |
| 1.5093        | 6.0   | 36   | 1.4836          | 0.2889   |
| 1.4614        | 7.0   | 42   | 1.4737          | 0.2889   |
| 1.4614        | 8.0   | 48   | 1.4656          | 0.2889   |
| 1.3895        | 9.0   | 54   | 1.4578          | 0.2222   |
| 1.4002        | 10.0  | 60   | 1.4519          | 0.2667   |
| 1.4002        | 11.0  | 66   | 1.4464          | 0.2667   |
| 1.3595        | 12.0  | 72   | 1.4429          | 0.2667   |
| 1.3595        | 13.0  | 78   | 1.4392          | 0.2667   |
| 1.3506        | 14.0  | 84   | 1.4366          | 0.2222   |
| 1.2804        | 15.0  | 90   | 1.4347          | 0.2      |
| 1.2804        | 16.0  | 96   | 1.4330          | 0.2      |
| 1.2746        | 17.0  | 102  | 1.4333          | 0.2667   |
| 1.2746        | 18.0  | 108  | 1.4332          | 0.2667   |
| 1.2774        | 19.0  | 114  | 1.4327          | 0.2667   |
| 1.2547        | 20.0  | 120  | 1.4313          | 0.2667   |
| 1.2547        | 21.0  | 126  | 1.4295          | 0.2667   |
| 1.2313        | 22.0  | 132  | 1.4282          | 0.2889   |
| 1.2313        | 23.0  | 138  | 1.4285          | 0.2889   |
| 1.2194        | 24.0  | 144  | 1.4285          | 0.2889   |
| 1.2083        | 25.0  | 150  | 1.4272          | 0.2889   |
| 1.2083        | 26.0  | 156  | 1.4286          | 0.3111   |
| 1.1973        | 27.0  | 162  | 1.4278          | 0.3111   |
| 1.1973        | 28.0  | 168  | 1.4278          | 0.3111   |
| 1.1964        | 29.0  | 174  | 1.4276          | 0.3111   |
| 1.2006        | 30.0  | 180  | 1.4293          | 0.3111   |
| 1.2006        | 31.0  | 186  | 1.4290          | 0.3111   |
| 1.1662        | 32.0  | 192  | 1.4295          | 0.3111   |
| 1.1662        | 33.0  | 198  | 1.4297          | 0.3111   |
| 1.1889        | 34.0  | 204  | 1.4294          | 0.3111   |
| 1.1683        | 35.0  | 210  | 1.4293          | 0.3111   |
| 1.1683        | 36.0  | 216  | 1.4299          | 0.3111   |
| 1.1652        | 37.0  | 222  | 1.4302          | 0.3111   |
| 1.1652        | 38.0  | 228  | 1.4307          | 0.3111   |
| 1.1321        | 39.0  | 234  | 1.4308          | 0.3111   |
| 1.1584        | 40.0  | 240  | 1.4306          | 0.3111   |
| 1.1584        | 41.0  | 246  | 1.4304          | 0.3111   |
| 1.1553        | 42.0  | 252  | 1.4305          | 0.3111   |
| 1.1553        | 43.0  | 258  | 1.4305          | 0.3111   |
| 1.168         | 44.0  | 264  | 1.4305          | 0.3111   |
| 1.1533        | 45.0  | 270  | 1.4305          | 0.3111   |
| 1.1533        | 46.0  | 276  | 1.4305          | 0.3111   |
| 1.1682        | 47.0  | 282  | 1.4305          | 0.3111   |
| 1.1682        | 48.0  | 288  | 1.4305          | 0.3111   |
| 1.1255        | 49.0  | 294  | 1.4305          | 0.3111   |
| 1.1698        | 50.0  | 300  | 1.4305          | 0.3111   |


### Framework versions

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