---
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_fold4
  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: 0.8783333333333333
---

<!-- 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_fold4

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: 1.4112
- Accuracy: 0.8783

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.2498        | 1.0   | 375   | 0.3750          | 0.8583   |
| 0.2126        | 2.0   | 750   | 0.3946          | 0.8617   |
| 0.0815        | 3.0   | 1125  | 0.3928          | 0.8817   |
| 0.1183        | 4.0   | 1500  | 0.4272          | 0.8733   |
| 0.1029        | 5.0   | 1875  | 0.5782          | 0.8833   |
| 0.0245        | 6.0   | 2250  | 0.6426          | 0.8867   |
| 0.0551        | 7.0   | 2625  | 0.8096          | 0.8733   |
| 0.0319        | 8.0   | 3000  | 0.8011          | 0.8733   |
| 0.0533        | 9.0   | 3375  | 0.8429          | 0.875    |
| 0.0056        | 10.0  | 3750  | 0.9672          | 0.8617   |
| 0.0136        | 11.0  | 4125  | 1.0120          | 0.8667   |
| 0.0031        | 12.0  | 4500  | 0.9881          | 0.87     |
| 0.0176        | 13.0  | 4875  | 1.1184          | 0.8767   |
| 0.0127        | 14.0  | 5250  | 1.1325          | 0.8583   |
| 0.0003        | 15.0  | 5625  | 1.2848          | 0.8683   |
| 0.0058        | 16.0  | 6000  | 1.1232          | 0.87     |
| 0.0002        | 17.0  | 6375  | 1.0571          | 0.8817   |
| 0.0421        | 18.0  | 6750  | 1.2079          | 0.8717   |
| 0.0004        | 19.0  | 7125  | 1.2753          | 0.87     |
| 0.0001        | 20.0  | 7500  | 1.3783          | 0.86     |
| 0.0           | 21.0  | 7875  | 1.3177          | 0.865    |
| 0.002         | 22.0  | 8250  | 1.3637          | 0.8633   |
| 0.0002        | 23.0  | 8625  | 1.4459          | 0.87     |
| 0.0005        | 24.0  | 9000  | 1.2813          | 0.875    |
| 0.0           | 25.0  | 9375  | 1.2487          | 0.88     |
| 0.0           | 26.0  | 9750  | 1.2405          | 0.875    |
| 0.0008        | 27.0  | 10125 | 1.3345          | 0.885    |
| 0.0001        | 28.0  | 10500 | 1.5106          | 0.865    |
| 0.0           | 29.0  | 10875 | 1.2765          | 0.8733   |
| 0.0           | 30.0  | 11250 | 1.2626          | 0.875    |
| 0.0332        | 31.0  | 11625 | 1.3653          | 0.8667   |
| 0.0           | 32.0  | 12000 | 1.3469          | 0.8683   |
| 0.0           | 33.0  | 12375 | 1.2524          | 0.8817   |
| 0.0           | 34.0  | 12750 | 1.2947          | 0.8767   |
| 0.0           | 35.0  | 13125 | 1.2962          | 0.8733   |
| 0.0           | 36.0  | 13500 | 1.3559          | 0.8783   |
| 0.0           | 37.0  | 13875 | 1.3878          | 0.8817   |
| 0.0033        | 38.0  | 14250 | 1.3553          | 0.8767   |
| 0.0           | 39.0  | 14625 | 1.4121          | 0.875    |
| 0.0           | 40.0  | 15000 | 1.4174          | 0.875    |
| 0.0           | 41.0  | 15375 | 1.4132          | 0.875    |
| 0.0           | 42.0  | 15750 | 1.4182          | 0.8767   |
| 0.0           | 43.0  | 16125 | 1.4186          | 0.8767   |
| 0.0           | 44.0  | 16500 | 1.4200          | 0.8767   |
| 0.0           | 45.0  | 16875 | 1.4125          | 0.8783   |
| 0.0           | 46.0  | 17250 | 1.4134          | 0.88     |
| 0.0           | 47.0  | 17625 | 1.4114          | 0.8783   |
| 0.0           | 48.0  | 18000 | 1.4108          | 0.8783   |
| 0.0           | 49.0  | 18375 | 1.4113          | 0.8783   |
| 0.0           | 50.0  | 18750 | 1.4112          | 0.8783   |


### Framework versions

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