---
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_001_fold4
  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: 0.4523809523809524
---

<!-- 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_001_fold4

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: 1.2335
- Accuracy: 0.4524

## 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    | 1.5918          | 0.2857   |
| 1.6404        | 2.0   | 12   | 1.5188          | 0.2857   |
| 1.6404        | 3.0   | 18   | 1.4665          | 0.2857   |
| 1.5241        | 4.0   | 24   | 1.4299          | 0.3333   |
| 1.4755        | 5.0   | 30   | 1.4106          | 0.3571   |
| 1.4755        | 6.0   | 36   | 1.3938          | 0.3095   |
| 1.4186        | 7.0   | 42   | 1.3803          | 0.2857   |
| 1.4186        | 8.0   | 48   | 1.3677          | 0.3810   |
| 1.3819        | 9.0   | 54   | 1.3558          | 0.3810   |
| 1.3541        | 10.0  | 60   | 1.3456          | 0.3810   |
| 1.3541        | 11.0  | 66   | 1.3370          | 0.3810   |
| 1.3363        | 12.0  | 72   | 1.3284          | 0.3810   |
| 1.3363        | 13.0  | 78   | 1.3193          | 0.3571   |
| 1.3168        | 14.0  | 84   | 1.3103          | 0.4048   |
| 1.2875        | 15.0  | 90   | 1.3032          | 0.4048   |
| 1.2875        | 16.0  | 96   | 1.2966          | 0.4048   |
| 1.2638        | 17.0  | 102  | 1.2902          | 0.4048   |
| 1.2638        | 18.0  | 108  | 1.2846          | 0.4048   |
| 1.2758        | 19.0  | 114  | 1.2805          | 0.4048   |
| 1.2611        | 20.0  | 120  | 1.2763          | 0.4048   |
| 1.2611        | 21.0  | 126  | 1.2724          | 0.4048   |
| 1.2411        | 22.0  | 132  | 1.2693          | 0.4048   |
| 1.2411        | 23.0  | 138  | 1.2666          | 0.4048   |
| 1.2357        | 24.0  | 144  | 1.2628          | 0.4048   |
| 1.231         | 25.0  | 150  | 1.2590          | 0.4048   |
| 1.231         | 26.0  | 156  | 1.2555          | 0.4048   |
| 1.2026        | 27.0  | 162  | 1.2531          | 0.4048   |
| 1.2026        | 28.0  | 168  | 1.2508          | 0.4048   |
| 1.2253        | 29.0  | 174  | 1.2482          | 0.4048   |
| 1.1949        | 30.0  | 180  | 1.2457          | 0.4048   |
| 1.1949        | 31.0  | 186  | 1.2436          | 0.4286   |
| 1.2025        | 32.0  | 192  | 1.2420          | 0.4286   |
| 1.2025        | 33.0  | 198  | 1.2406          | 0.4524   |
| 1.1709        | 34.0  | 204  | 1.2390          | 0.4524   |
| 1.1908        | 35.0  | 210  | 1.2376          | 0.4524   |
| 1.1908        | 36.0  | 216  | 1.2365          | 0.4524   |
| 1.1663        | 37.0  | 222  | 1.2358          | 0.4524   |
| 1.1663        | 38.0  | 228  | 1.2349          | 0.4524   |
| 1.1875        | 39.0  | 234  | 1.2342          | 0.4524   |
| 1.1799        | 40.0  | 240  | 1.2338          | 0.4524   |
| 1.1799        | 41.0  | 246  | 1.2336          | 0.4524   |
| 1.1658        | 42.0  | 252  | 1.2335          | 0.4524   |
| 1.1658        | 43.0  | 258  | 1.2335          | 0.4524   |
| 1.1875        | 44.0  | 264  | 1.2335          | 0.4524   |
| 1.1627        | 45.0  | 270  | 1.2335          | 0.4524   |
| 1.1627        | 46.0  | 276  | 1.2335          | 0.4524   |
| 1.1689        | 47.0  | 282  | 1.2335          | 0.4524   |
| 1.1689        | 48.0  | 288  | 1.2335          | 0.4524   |
| 1.1911        | 49.0  | 294  | 1.2335          | 0.4524   |
| 1.1557        | 50.0  | 300  | 1.2335          | 0.4524   |


### Framework versions

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