---
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: smids_5x_deit_tiny_rms_00001_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: 0.8981636060100167
---

<!-- 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_tiny_rms_00001_fold1

This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co./facebook/deit-tiny-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9495
- Accuracy: 0.8982

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.2593        | 1.0   | 376   | 0.3151          | 0.8765   |
| 0.1718        | 2.0   | 752   | 0.2623          | 0.8998   |
| 0.1615        | 3.0   | 1128  | 0.2861          | 0.8965   |
| 0.0982        | 4.0   | 1504  | 0.3444          | 0.8881   |
| 0.0553        | 5.0   | 1880  | 0.3784          | 0.9098   |
| 0.0747        | 6.0   | 2256  | 0.5204          | 0.8881   |
| 0.0183        | 7.0   | 2632  | 0.5683          | 0.8948   |
| 0.0068        | 8.0   | 3008  | 0.6428          | 0.8998   |
| 0.0727        | 9.0   | 3384  | 0.7962          | 0.8815   |
| 0.0001        | 10.0  | 3760  | 0.7940          | 0.8965   |
| 0.001         | 11.0  | 4136  | 0.9819          | 0.8681   |
| 0.0           | 12.0  | 4512  | 0.8908          | 0.8848   |
| 0.0018        | 13.0  | 4888  | 0.8621          | 0.8865   |
| 0.0198        | 14.0  | 5264  | 0.8948          | 0.8881   |
| 0.0291        | 15.0  | 5640  | 0.9361          | 0.8915   |
| 0.0001        | 16.0  | 6016  | 0.7825          | 0.8948   |
| 0.0           | 17.0  | 6392  | 0.8996          | 0.8815   |
| 0.0001        | 18.0  | 6768  | 0.8212          | 0.8948   |
| 0.0026        | 19.0  | 7144  | 0.8543          | 0.8831   |
| 0.0145        | 20.0  | 7520  | 0.8936          | 0.8881   |
| 0.004         | 21.0  | 7896  | 0.9825          | 0.8815   |
| 0.0           | 22.0  | 8272  | 0.9004          | 0.8932   |
| 0.0001        | 23.0  | 8648  | 0.8961          | 0.8965   |
| 0.0           | 24.0  | 9024  | 1.0000          | 0.8915   |
| 0.0           | 25.0  | 9400  | 0.9507          | 0.8865   |
| 0.079         | 26.0  | 9776  | 1.0040          | 0.8865   |
| 0.0           | 27.0  | 10152 | 0.9365          | 0.8998   |
| 0.0           | 28.0  | 10528 | 0.9689          | 0.8815   |
| 0.0089        | 29.0  | 10904 | 0.9542          | 0.8898   |
| 0.0105        | 30.0  | 11280 | 0.9853          | 0.8898   |
| 0.0           | 31.0  | 11656 | 0.9962          | 0.8965   |
| 0.0           | 32.0  | 12032 | 0.9324          | 0.8982   |
| 0.0           | 33.0  | 12408 | 1.0542          | 0.8881   |
| 0.0           | 34.0  | 12784 | 0.9887          | 0.8932   |
| 0.0           | 35.0  | 13160 | 0.8827          | 0.9082   |
| 0.0           | 36.0  | 13536 | 0.8957          | 0.8982   |
| 0.0           | 37.0  | 13912 | 0.9316          | 0.8932   |
| 0.0           | 38.0  | 14288 | 0.9562          | 0.8915   |
| 0.0           | 39.0  | 14664 | 0.9229          | 0.8982   |
| 0.0           | 40.0  | 15040 | 0.9352          | 0.8932   |
| 0.0           | 41.0  | 15416 | 0.9221          | 0.8915   |
| 0.0           | 42.0  | 15792 | 0.9253          | 0.8965   |
| 0.0           | 43.0  | 16168 | 0.9330          | 0.8881   |
| 0.0           | 44.0  | 16544 | 0.9447          | 0.8965   |
| 0.0           | 45.0  | 16920 | 0.9432          | 0.8965   |
| 0.0047        | 46.0  | 17296 | 0.9445          | 0.8965   |
| 0.0           | 47.0  | 17672 | 0.9464          | 0.8948   |
| 0.0           | 48.0  | 18048 | 0.9465          | 0.8948   |
| 0.0           | 49.0  | 18424 | 0.9475          | 0.8982   |
| 0.0039        | 50.0  | 18800 | 0.9495          | 0.8982   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.1+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2