---
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_rms_0001_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: 0.7073170731707317
---

<!-- 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_rms_0001_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: 2.0948
- Accuracy: 0.7073

## 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: 0.0001
- 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    | 1.4454          | 0.2439   |
| 1.8172        | 2.0   | 12   | 1.4646          | 0.2439   |
| 1.8172        | 3.0   | 18   | 1.3798          | 0.2439   |
| 1.4754        | 4.0   | 24   | 1.4689          | 0.2439   |
| 1.3952        | 5.0   | 30   | 1.4002          | 0.2439   |
| 1.3952        | 6.0   | 36   | 1.4703          | 0.2439   |
| 1.3837        | 7.0   | 42   | 1.4402          | 0.4390   |
| 1.3837        | 8.0   | 48   | 1.1526          | 0.4146   |
| 1.379         | 9.0   | 54   | 0.9870          | 0.7317   |
| 1.2244        | 10.0  | 60   | 0.9071          | 0.7317   |
| 1.2244        | 11.0  | 66   | 0.8229          | 0.6829   |
| 1.0625        | 12.0  | 72   | 1.5587          | 0.6341   |
| 1.0625        | 13.0  | 78   | 0.6583          | 0.6829   |
| 0.8932        | 14.0  | 84   | 0.6538          | 0.7073   |
| 0.7639        | 15.0  | 90   | 1.3081          | 0.4878   |
| 0.7639        | 16.0  | 96   | 1.0570          | 0.6341   |
| 0.5943        | 17.0  | 102  | 1.2582          | 0.5854   |
| 0.5943        | 18.0  | 108  | 0.7216          | 0.7805   |
| 0.3924        | 19.0  | 114  | 1.9152          | 0.5366   |
| 0.287         | 20.0  | 120  | 1.2648          | 0.5854   |
| 0.287         | 21.0  | 126  | 1.2267          | 0.6829   |
| 0.1533        | 22.0  | 132  | 1.4758          | 0.6585   |
| 0.1533        | 23.0  | 138  | 1.4603          | 0.7561   |
| 0.0513        | 24.0  | 144  | 2.1352          | 0.6098   |
| 0.0125        | 25.0  | 150  | 2.3347          | 0.6829   |
| 0.0125        | 26.0  | 156  | 1.8507          | 0.7073   |
| 0.024         | 27.0  | 162  | 1.9066          | 0.7073   |
| 0.024         | 28.0  | 168  | 1.9502          | 0.7073   |
| 0.0005        | 29.0  | 174  | 1.9771          | 0.7073   |
| 0.0004        | 30.0  | 180  | 1.9991          | 0.7073   |
| 0.0004        | 31.0  | 186  | 2.0117          | 0.7073   |
| 0.0003        | 32.0  | 192  | 2.0299          | 0.7073   |
| 0.0003        | 33.0  | 198  | 2.0438          | 0.7073   |
| 0.0003        | 34.0  | 204  | 2.0584          | 0.7073   |
| 0.0003        | 35.0  | 210  | 2.0666          | 0.7073   |
| 0.0003        | 36.0  | 216  | 2.0751          | 0.7073   |
| 0.0003        | 37.0  | 222  | 2.0815          | 0.7073   |
| 0.0003        | 38.0  | 228  | 2.0862          | 0.7073   |
| 0.0003        | 39.0  | 234  | 2.0898          | 0.7073   |
| 0.0002        | 40.0  | 240  | 2.0927          | 0.7073   |
| 0.0002        | 41.0  | 246  | 2.0945          | 0.7073   |
| 0.0003        | 42.0  | 252  | 2.0948          | 0.7073   |
| 0.0003        | 43.0  | 258  | 2.0948          | 0.7073   |
| 0.0002        | 44.0  | 264  | 2.0948          | 0.7073   |
| 0.0003        | 45.0  | 270  | 2.0948          | 0.7073   |
| 0.0003        | 46.0  | 276  | 2.0948          | 0.7073   |
| 0.0002        | 47.0  | 282  | 2.0948          | 0.7073   |
| 0.0002        | 48.0  | 288  | 2.0948          | 0.7073   |
| 0.0002        | 49.0  | 294  | 2.0948          | 0.7073   |
| 0.0002        | 50.0  | 300  | 2.0948          | 0.7073   |


### Framework versions

- Transformers 4.35.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.7
- Tokenizers 0.14.1