---
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: smids_1x_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: 0.8631051752921536
---

<!-- 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_1x_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: 0.8877
- Accuracy: 0.8631

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4093        | 1.0   | 76   | 0.4066          | 0.8264   |
| 0.3822        | 2.0   | 152  | 0.3553          | 0.8614   |
| 0.1979        | 3.0   | 228  | 0.3399          | 0.8631   |
| 0.1648        | 4.0   | 304  | 0.3252          | 0.8815   |
| 0.0965        | 5.0   | 380  | 0.3551          | 0.8531   |
| 0.072         | 6.0   | 456  | 0.4036          | 0.8631   |
| 0.0292        | 7.0   | 532  | 0.4208          | 0.8598   |
| 0.0237        | 8.0   | 608  | 0.5314          | 0.8497   |
| 0.0407        | 9.0   | 684  | 0.5484          | 0.8497   |
| 0.0074        | 10.0  | 760  | 0.5780          | 0.8715   |
| 0.0366        | 11.0  | 836  | 0.5799          | 0.8631   |
| 0.0022        | 12.0  | 912  | 0.8054          | 0.8414   |
| 0.0514        | 13.0  | 988  | 0.5849          | 0.8748   |
| 0.0003        | 14.0  | 1064 | 0.6713          | 0.8664   |
| 0.0448        | 15.0  | 1140 | 0.6921          | 0.8715   |
| 0.0014        | 16.0  | 1216 | 0.6848          | 0.8631   |
| 0.0001        | 17.0  | 1292 | 0.7084          | 0.8648   |
| 0.0152        | 18.0  | 1368 | 0.8109          | 0.8681   |
| 0.0001        | 19.0  | 1444 | 0.7361          | 0.8698   |
| 0.004         | 20.0  | 1520 | 0.7743          | 0.8664   |
| 0.0035        | 21.0  | 1596 | 0.7272          | 0.8748   |
| 0.0282        | 22.0  | 1672 | 0.7515          | 0.8731   |
| 0.0001        | 23.0  | 1748 | 0.8060          | 0.8581   |
| 0.0001        | 24.0  | 1824 | 0.7763          | 0.8581   |
| 0.0156        | 25.0  | 1900 | 0.7302          | 0.8831   |
| 0.0068        | 26.0  | 1976 | 0.8763          | 0.8514   |
| 0.0045        | 27.0  | 2052 | 0.8144          | 0.8664   |
| 0.0058        | 28.0  | 2128 | 0.7716          | 0.8614   |
| 0.009         | 29.0  | 2204 | 0.8016          | 0.8664   |
| 0.0           | 30.0  | 2280 | 0.8234          | 0.8631   |
| 0.0087        | 31.0  | 2356 | 0.8420          | 0.8631   |
| 0.0102        | 32.0  | 2432 | 0.8218          | 0.8698   |
| 0.0           | 33.0  | 2508 | 0.8439          | 0.8564   |
| 0.0           | 34.0  | 2584 | 0.8448          | 0.8598   |
| 0.0154        | 35.0  | 2660 | 0.8638          | 0.8631   |
| 0.0044        | 36.0  | 2736 | 0.8664          | 0.8715   |
| 0.0088        | 37.0  | 2812 | 0.8649          | 0.8598   |
| 0.0           | 38.0  | 2888 | 0.8771          | 0.8598   |
| 0.0028        | 39.0  | 2964 | 0.8789          | 0.8631   |
| 0.0           | 40.0  | 3040 | 0.8645          | 0.8648   |
| 0.0044        | 41.0  | 3116 | 0.8681          | 0.8664   |
| 0.0           | 42.0  | 3192 | 0.8746          | 0.8631   |
| 0.0056        | 43.0  | 3268 | 0.8786          | 0.8664   |
| 0.0           | 44.0  | 3344 | 0.8858          | 0.8648   |
| 0.0           | 45.0  | 3420 | 0.8848          | 0.8648   |
| 0.0           | 46.0  | 3496 | 0.8858          | 0.8648   |
| 0.0           | 47.0  | 3572 | 0.8868          | 0.8631   |
| 0.0023        | 48.0  | 3648 | 0.8879          | 0.8631   |
| 0.0           | 49.0  | 3724 | 0.8884          | 0.8631   |
| 0.0           | 50.0  | 3800 | 0.8877          | 0.8631   |


### Framework versions

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