---
license: apache-2.0
base_model: facebook/deit-small-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_40x_deit_small_adamax_00001_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: 0.9024390243902439
---

<!-- 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_small_adamax_00001_fold5

This model is a fine-tuned version of [facebook/deit-small-patch16-224](https://huggingface.co/facebook/deit-small-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4380
- Accuracy: 0.9024

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.2763        | 1.0   | 220   | 0.4688          | 0.7561   |
| 0.0369        | 2.0   | 440   | 0.2296          | 0.9024   |
| 0.0054        | 3.0   | 660   | 0.3595          | 0.8537   |
| 0.0018        | 4.0   | 880   | 0.2500          | 0.9024   |
| 0.0006        | 5.0   | 1100  | 0.2205          | 0.9268   |
| 0.0003        | 6.0   | 1320  | 0.2552          | 0.9024   |
| 0.0003        | 7.0   | 1540  | 0.2520          | 0.9024   |
| 0.0002        | 8.0   | 1760  | 0.2923          | 0.8780   |
| 0.0001        | 9.0   | 1980  | 0.2754          | 0.8780   |
| 0.0001        | 10.0  | 2200  | 0.2945          | 0.8780   |
| 0.0001        | 11.0  | 2420  | 0.2841          | 0.9024   |
| 0.0001        | 12.0  | 2640  | 0.3077          | 0.9024   |
| 0.0001        | 13.0  | 2860  | 0.3076          | 0.8780   |
| 0.0           | 14.0  | 3080  | 0.3160          | 0.8780   |
| 0.0           | 15.0  | 3300  | 0.2918          | 0.9024   |
| 0.0           | 16.0  | 3520  | 0.3305          | 0.8780   |
| 0.0           | 17.0  | 3740  | 0.3206          | 0.8780   |
| 0.0           | 18.0  | 3960  | 0.3174          | 0.8780   |
| 0.0           | 19.0  | 4180  | 0.3189          | 0.8780   |
| 0.0           | 20.0  | 4400  | 0.3130          | 0.9024   |
| 0.0           | 21.0  | 4620  | 0.3383          | 0.8780   |
| 0.0           | 22.0  | 4840  | 0.3473          | 0.8780   |
| 0.0           | 23.0  | 5060  | 0.3548          | 0.8780   |
| 0.0           | 24.0  | 5280  | 0.3221          | 0.8780   |
| 0.0           | 25.0  | 5500  | 0.3554          | 0.8780   |
| 0.0           | 26.0  | 5720  | 0.3715          | 0.8780   |
| 0.0           | 27.0  | 5940  | 0.3690          | 0.8780   |
| 0.0           | 28.0  | 6160  | 0.3648          | 0.8780   |
| 0.0           | 29.0  | 6380  | 0.3806          | 0.8780   |
| 0.0           | 30.0  | 6600  | 0.3725          | 0.8780   |
| 0.0           | 31.0  | 6820  | 0.4022          | 0.8780   |
| 0.0           | 32.0  | 7040  | 0.3871          | 0.8780   |
| 0.0           | 33.0  | 7260  | 0.4133          | 0.8780   |
| 0.0           | 34.0  | 7480  | 0.4117          | 0.8780   |
| 0.0           | 35.0  | 7700  | 0.3832          | 0.8780   |
| 0.0           | 36.0  | 7920  | 0.3977          | 0.8780   |
| 0.0           | 37.0  | 8140  | 0.3959          | 0.8780   |
| 0.0           | 38.0  | 8360  | 0.4687          | 0.8780   |
| 0.0           | 39.0  | 8580  | 0.4404          | 0.8780   |
| 0.0           | 40.0  | 8800  | 0.3819          | 0.9024   |
| 0.0           | 41.0  | 9020  | 0.4514          | 0.8780   |
| 0.0           | 42.0  | 9240  | 0.4623          | 0.8780   |
| 0.0           | 43.0  | 9460  | 0.4136          | 0.9024   |
| 0.0           | 44.0  | 9680  | 0.4401          | 0.9024   |
| 0.0           | 45.0  | 9900  | 0.4714          | 0.9024   |
| 0.0           | 46.0  | 10120 | 0.4588          | 0.9024   |
| 0.0           | 47.0  | 10340 | 0.4584          | 0.9024   |
| 0.0           | 48.0  | 10560 | 0.4588          | 0.9024   |
| 0.0           | 49.0  | 10780 | 0.4430          | 0.9024   |
| 0.0           | 50.0  | 11000 | 0.4380          | 0.9024   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.0+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2