---
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_adamax_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: 0.5581395348837209
---

<!-- 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_adamax_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: 0.8253
- Accuracy: 0.5581

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 6    | 1.4425          | 0.2791   |
| 1.416         | 2.0   | 12   | 1.3728          | 0.3023   |
| 1.416         | 3.0   | 18   | 1.3124          | 0.3488   |
| 1.2388        | 4.0   | 24   | 1.2509          | 0.3721   |
| 1.1051        | 5.0   | 30   | 1.1962          | 0.3488   |
| 1.1051        | 6.0   | 36   | 1.1517          | 0.3721   |
| 0.9682        | 7.0   | 42   | 1.1212          | 0.3721   |
| 0.9682        | 8.0   | 48   | 1.0990          | 0.4186   |
| 0.8769        | 9.0   | 54   | 1.0709          | 0.4884   |
| 0.7643        | 10.0  | 60   | 1.0587          | 0.5116   |
| 0.7643        | 11.0  | 66   | 1.0451          | 0.4884   |
| 0.6717        | 12.0  | 72   | 1.0399          | 0.5581   |
| 0.6717        | 13.0  | 78   | 1.0224          | 0.5349   |
| 0.5988        | 14.0  | 84   | 1.0021          | 0.4884   |
| 0.5291        | 15.0  | 90   | 0.9852          | 0.4884   |
| 0.5291        | 16.0  | 96   | 0.9774          | 0.5116   |
| 0.4581        | 17.0  | 102  | 0.9701          | 0.5116   |
| 0.4581        | 18.0  | 108  | 0.9598          | 0.5116   |
| 0.3895        | 19.0  | 114  | 0.9410          | 0.5814   |
| 0.3415        | 20.0  | 120  | 0.9223          | 0.5581   |
| 0.3415        | 21.0  | 126  | 0.9172          | 0.5349   |
| 0.3044        | 22.0  | 132  | 0.9106          | 0.5349   |
| 0.3044        | 23.0  | 138  | 0.9037          | 0.5581   |
| 0.2632        | 24.0  | 144  | 0.8935          | 0.5581   |
| 0.2425        | 25.0  | 150  | 0.8847          | 0.5814   |
| 0.2425        | 26.0  | 156  | 0.8721          | 0.5581   |
| 0.2102        | 27.0  | 162  | 0.8625          | 0.5581   |
| 0.2102        | 28.0  | 168  | 0.8546          | 0.5581   |
| 0.189         | 29.0  | 174  | 0.8540          | 0.5814   |
| 0.1637        | 30.0  | 180  | 0.8496          | 0.6047   |
| 0.1637        | 31.0  | 186  | 0.8464          | 0.6047   |
| 0.1512        | 32.0  | 192  | 0.8420          | 0.5581   |
| 0.1512        | 33.0  | 198  | 0.8380          | 0.5581   |
| 0.1374        | 34.0  | 204  | 0.8346          | 0.5581   |
| 0.1287        | 35.0  | 210  | 0.8327          | 0.5581   |
| 0.1287        | 36.0  | 216  | 0.8290          | 0.5581   |
| 0.124         | 37.0  | 222  | 0.8276          | 0.5581   |
| 0.124         | 38.0  | 228  | 0.8271          | 0.5581   |
| 0.1186        | 39.0  | 234  | 0.8265          | 0.5581   |
| 0.1159        | 40.0  | 240  | 0.8255          | 0.5581   |
| 0.1159        | 41.0  | 246  | 0.8253          | 0.5581   |
| 0.1139        | 42.0  | 252  | 0.8253          | 0.5581   |
| 0.1139        | 43.0  | 258  | 0.8253          | 0.5581   |
| 0.1142        | 44.0  | 264  | 0.8253          | 0.5581   |
| 0.1107        | 45.0  | 270  | 0.8253          | 0.5581   |
| 0.1107        | 46.0  | 276  | 0.8253          | 0.5581   |
| 0.1118        | 47.0  | 282  | 0.8253          | 0.5581   |
| 0.1118        | 48.0  | 288  | 0.8253          | 0.5581   |
| 0.1159        | 49.0  | 294  | 0.8253          | 0.5581   |
| 0.1095        | 50.0  | 300  | 0.8253          | 0.5581   |


### Framework versions

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