---
license: apache-2.0
base_model: facebook/deit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: smids_5x_deit_base_rms_0001_fold1
  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: 0.9081803005008348
---

<!-- 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. -->

# smids_5x_deit_base_rms_0001_fold1

This model is a fine-tuned version of [facebook/deit-base-patch16-224](https://huggingface.co/facebook/deit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8795
- Accuracy: 0.9082

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.232         | 1.0   | 376   | 0.3558          | 0.8531   |
| 0.1372        | 2.0   | 752   | 0.3215          | 0.8898   |
| 0.1203        | 3.0   | 1128  | 0.3886          | 0.8881   |
| 0.0697        | 4.0   | 1504  | 0.4340          | 0.8765   |
| 0.0324        | 5.0   | 1880  | 0.5132          | 0.8865   |
| 0.0728        | 6.0   | 2256  | 0.5310          | 0.8881   |
| 0.0495        | 7.0   | 2632  | 0.6186          | 0.8781   |
| 0.0797        | 8.0   | 3008  | 0.5758          | 0.8881   |
| 0.0121        | 9.0   | 3384  | 0.5420          | 0.8998   |
| 0.0399        | 10.0  | 3760  | 0.6888          | 0.8815   |
| 0.0293        | 11.0  | 4136  | 0.5816          | 0.9065   |
| 0.0382        | 12.0  | 4512  | 0.6430          | 0.8781   |
| 0.0148        | 13.0  | 4888  | 0.8464          | 0.8781   |
| 0.0249        | 14.0  | 5264  | 0.5972          | 0.8848   |
| 0.0008        | 15.0  | 5640  | 0.6413          | 0.8965   |
| 0.0409        | 16.0  | 6016  | 0.7158          | 0.8798   |
| 0.0202        | 17.0  | 6392  | 0.7167          | 0.8815   |
| 0.0253        | 18.0  | 6768  | 0.6005          | 0.8998   |
| 0.0002        | 19.0  | 7144  | 0.6775          | 0.8948   |
| 0.0275        | 20.0  | 7520  | 0.7685          | 0.8948   |
| 0.0272        | 21.0  | 7896  | 0.6847          | 0.8965   |
| 0.0003        | 22.0  | 8272  | 0.7613          | 0.8915   |
| 0.0008        | 23.0  | 8648  | 0.7342          | 0.8865   |
| 0.0001        | 24.0  | 9024  | 0.7590          | 0.8698   |
| 0.0           | 25.0  | 9400  | 0.7885          | 0.8898   |
| 0.0032        | 26.0  | 9776  | 0.6867          | 0.8982   |
| 0.0           | 27.0  | 10152 | 0.7507          | 0.8948   |
| 0.0003        | 28.0  | 10528 | 0.7142          | 0.8848   |
| 0.0043        | 29.0  | 10904 | 0.6904          | 0.8881   |
| 0.0066        | 30.0  | 11280 | 0.7736          | 0.8898   |
| 0.0007        | 31.0  | 11656 | 0.7358          | 0.8998   |
| 0.0006        | 32.0  | 12032 | 1.0875          | 0.8598   |
| 0.0           | 33.0  | 12408 | 0.7340          | 0.9015   |
| 0.0           | 34.0  | 12784 | 0.7139          | 0.8982   |
| 0.0           | 35.0  | 13160 | 0.7525          | 0.9115   |
| 0.0002        | 36.0  | 13536 | 0.7504          | 0.8982   |
| 0.0           | 37.0  | 13912 | 0.8006          | 0.8982   |
| 0.0           | 38.0  | 14288 | 0.7615          | 0.9015   |
| 0.0           | 39.0  | 14664 | 0.7609          | 0.9115   |
| 0.0           | 40.0  | 15040 | 0.8059          | 0.9015   |
| 0.0           | 41.0  | 15416 | 0.8037          | 0.9032   |
| 0.0           | 42.0  | 15792 | 0.8697          | 0.9048   |
| 0.0           | 43.0  | 16168 | 0.8414          | 0.9115   |
| 0.0           | 44.0  | 16544 | 0.8687          | 0.9098   |
| 0.0           | 45.0  | 16920 | 0.8833          | 0.9065   |
| 0.0031        | 46.0  | 17296 | 0.8963          | 0.9065   |
| 0.0           | 47.0  | 17672 | 0.8765          | 0.9082   |
| 0.0           | 48.0  | 18048 | 0.8724          | 0.9082   |
| 0.0           | 49.0  | 18424 | 0.8783          | 0.9082   |
| 0.0025        | 50.0  | 18800 | 0.8795          | 0.9082   |


### Framework versions

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