---
license: apache-2.0
base_model: facebook/deit-small-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_1x_deit_small_adamax_001_fold2
  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: 0.5777777777777777
---

<!-- 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_small_adamax_001_fold2

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: 3.0653
- Accuracy: 0.5778

## 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    | 1.5866          | 0.2444   |
| 1.9023        | 2.0   | 12   | 1.3764          | 0.2444   |
| 1.9023        | 3.0   | 18   | 1.3051          | 0.4222   |
| 1.349         | 4.0   | 24   | 1.1457          | 0.4889   |
| 1.2765        | 5.0   | 30   | 1.1296          | 0.5333   |
| 1.2765        | 6.0   | 36   | 1.0799          | 0.4667   |
| 0.9532        | 7.0   | 42   | 0.9251          | 0.5778   |
| 0.9532        | 8.0   | 48   | 0.9697          | 0.6      |
| 0.606         | 9.0   | 54   | 1.3926          | 0.4889   |
| 0.572         | 10.0  | 60   | 1.7732          | 0.5778   |
| 0.572         | 11.0  | 66   | 1.3882          | 0.5556   |
| 0.5961        | 12.0  | 72   | 1.7835          | 0.5333   |
| 0.5961        | 13.0  | 78   | 1.6876          | 0.5111   |
| 0.36          | 14.0  | 84   | 2.6292          | 0.5556   |
| 0.1021        | 15.0  | 90   | 3.3955          | 0.4444   |
| 0.1021        | 16.0  | 96   | 2.7199          | 0.5333   |
| 0.0705        | 17.0  | 102  | 3.2188          | 0.5778   |
| 0.0705        | 18.0  | 108  | 2.9572          | 0.5778   |
| 0.1408        | 19.0  | 114  | 3.4311          | 0.6222   |
| 0.0481        | 20.0  | 120  | 3.3680          | 0.5111   |
| 0.0481        | 21.0  | 126  | 3.9440          | 0.4889   |
| 0.0285        | 22.0  | 132  | 3.0805          | 0.5111   |
| 0.0285        | 23.0  | 138  | 3.2788          | 0.4889   |
| 0.0077        | 24.0  | 144  | 3.3798          | 0.5111   |
| 0.0144        | 25.0  | 150  | 3.3118          | 0.5333   |
| 0.0144        | 26.0  | 156  | 3.1251          | 0.5111   |
| 0.0005        | 27.0  | 162  | 2.9134          | 0.5778   |
| 0.0005        | 28.0  | 168  | 2.8352          | 0.6      |
| 0.0006        | 29.0  | 174  | 2.7529          | 0.5778   |
| 0.0002        | 30.0  | 180  | 2.8235          | 0.6      |
| 0.0002        | 31.0  | 186  | 2.8802          | 0.6      |
| 0.0001        | 32.0  | 192  | 2.9253          | 0.5778   |
| 0.0001        | 33.0  | 198  | 2.9651          | 0.5778   |
| 0.0001        | 34.0  | 204  | 2.9943          | 0.5778   |
| 0.0001        | 35.0  | 210  | 3.0146          | 0.5778   |
| 0.0001        | 36.0  | 216  | 3.0314          | 0.5778   |
| 0.0001        | 37.0  | 222  | 3.0446          | 0.5778   |
| 0.0001        | 38.0  | 228  | 3.0538          | 0.5778   |
| 0.0001        | 39.0  | 234  | 3.0596          | 0.5778   |
| 0.0001        | 40.0  | 240  | 3.0631          | 0.5778   |
| 0.0001        | 41.0  | 246  | 3.0649          | 0.5778   |
| 0.0001        | 42.0  | 252  | 3.0653          | 0.5778   |
| 0.0001        | 43.0  | 258  | 3.0653          | 0.5778   |
| 0.0001        | 44.0  | 264  | 3.0653          | 0.5778   |
| 0.0001        | 45.0  | 270  | 3.0653          | 0.5778   |
| 0.0001        | 46.0  | 276  | 3.0653          | 0.5778   |
| 0.0001        | 47.0  | 282  | 3.0653          | 0.5778   |
| 0.0001        | 48.0  | 288  | 3.0653          | 0.5778   |
| 0.0001        | 49.0  | 294  | 3.0653          | 0.5778   |
| 0.0001        | 50.0  | 300  | 3.0653          | 0.5778   |


### Framework versions

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