---
license: apache-2.0
base_model: facebook/deit-small-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_5x_deit_small_rms_0001_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: 0.9302325581395349
---

<!-- 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_5x_deit_small_rms_0001_fold3

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: 0.6867
- Accuracy: 0.9302

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.8625        | 1.0   | 28   | 0.7655          | 0.7442   |
| 0.213         | 2.0   | 56   | 0.3346          | 0.9070   |
| 0.0427        | 3.0   | 84   | 0.3169          | 0.8837   |
| 0.0088        | 4.0   | 112  | 0.2583          | 0.9070   |
| 0.0019        | 5.0   | 140  | 0.3591          | 0.9070   |
| 0.0013        | 6.0   | 168  | 0.3828          | 0.8837   |
| 0.0008        | 7.0   | 196  | 0.3548          | 0.9070   |
| 0.0007        | 8.0   | 224  | 0.3758          | 0.9302   |
| 0.0005        | 9.0   | 252  | 0.4221          | 0.9070   |
| 0.0004        | 10.0  | 280  | 0.4042          | 0.9302   |
| 0.0004        | 11.0  | 308  | 0.4067          | 0.9302   |
| 0.0003        | 12.0  | 336  | 0.4099          | 0.9302   |
| 0.0002        | 13.0  | 364  | 0.4211          | 0.9302   |
| 0.0002        | 14.0  | 392  | 0.4323          | 0.9302   |
| 0.0002        | 15.0  | 420  | 0.4463          | 0.9302   |
| 0.0002        | 16.0  | 448  | 0.4550          | 0.9302   |
| 0.0001        | 17.0  | 476  | 0.4114          | 0.9302   |
| 0.0001        | 18.0  | 504  | 0.4747          | 0.9302   |
| 0.0001        | 19.0  | 532  | 0.4880          | 0.9302   |
| 0.0001        | 20.0  | 560  | 0.4798          | 0.9302   |
| 0.0001        | 21.0  | 588  | 0.5078          | 0.9302   |
| 0.0001        | 22.0  | 616  | 0.5161          | 0.9302   |
| 0.0001        | 23.0  | 644  | 0.5322          | 0.9302   |
| 0.0001        | 24.0  | 672  | 0.5391          | 0.9302   |
| 0.0           | 25.0  | 700  | 0.5387          | 0.9302   |
| 0.0           | 26.0  | 728  | 0.5518          | 0.9302   |
| 0.0           | 27.0  | 756  | 0.5912          | 0.9302   |
| 0.0           | 28.0  | 784  | 0.5723          | 0.9302   |
| 0.0           | 29.0  | 812  | 0.5780          | 0.9302   |
| 0.0           | 30.0  | 840  | 0.5909          | 0.9302   |
| 0.0           | 31.0  | 868  | 0.5963          | 0.9302   |
| 0.0           | 32.0  | 896  | 0.6068          | 0.9302   |
| 0.0           | 33.0  | 924  | 0.6067          | 0.9302   |
| 0.0           | 34.0  | 952  | 0.6107          | 0.9302   |
| 0.0           | 35.0  | 980  | 0.5868          | 0.9302   |
| 0.0           | 36.0  | 1008 | 0.6292          | 0.9302   |
| 0.0           | 37.0  | 1036 | 0.6428          | 0.9302   |
| 0.0           | 38.0  | 1064 | 0.6729          | 0.9070   |
| 0.0           | 39.0  | 1092 | 0.6601          | 0.9302   |
| 0.0           | 40.0  | 1120 | 0.6776          | 0.9070   |
| 0.0           | 41.0  | 1148 | 0.6683          | 0.9302   |
| 0.0           | 42.0  | 1176 | 0.6712          | 0.9302   |
| 0.0           | 43.0  | 1204 | 0.6721          | 0.9302   |
| 0.0           | 44.0  | 1232 | 0.6819          | 0.9302   |
| 0.0           | 45.0  | 1260 | 0.6829          | 0.9302   |
| 0.0           | 46.0  | 1288 | 0.6827          | 0.9302   |
| 0.0           | 47.0  | 1316 | 0.6864          | 0.9302   |
| 0.0           | 48.0  | 1344 | 0.6865          | 0.9302   |
| 0.0           | 49.0  | 1372 | 0.6867          | 0.9302   |
| 0.0           | 50.0  | 1400 | 0.6867          | 0.9302   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0