---
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: smids_10x_deit_tiny_adamax_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: 0.9181969949916527
---

<!-- 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_10x_deit_tiny_adamax_0001_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: 0.7859
- Accuracy: 0.9182

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.2608        | 1.0   | 751   | 0.2844          | 0.8898   |
| 0.1304        | 2.0   | 1502  | 0.3294          | 0.8765   |
| 0.111         | 3.0   | 2253  | 0.3516          | 0.9015   |
| 0.1003        | 4.0   | 3004  | 0.4446          | 0.8932   |
| 0.034         | 5.0   | 3755  | 0.5205          | 0.8982   |
| 0.0067        | 6.0   | 4506  | 0.6326          | 0.9015   |
| 0.0227        | 7.0   | 5257  | 0.8411          | 0.8815   |
| 0.0262        | 8.0   | 6008  | 0.8754          | 0.8865   |
| 0.0488        | 9.0   | 6759  | 0.7139          | 0.9098   |
| 0.0361        | 10.0  | 7510  | 0.7866          | 0.8948   |
| 0.0107        | 11.0  | 8261  | 0.8081          | 0.9048   |
| 0.0056        | 12.0  | 9012  | 0.7555          | 0.8998   |
| 0.0           | 13.0  | 9763  | 0.8196          | 0.9015   |
| 0.0016        | 14.0  | 10514 | 0.8589          | 0.9032   |
| 0.0           | 15.0  | 11265 | 0.8346          | 0.9098   |
| 0.0           | 16.0  | 12016 | 0.7703          | 0.9115   |
| 0.0           | 17.0  | 12767 | 0.8587          | 0.9032   |
| 0.0           | 18.0  | 13518 | 0.8122          | 0.9115   |
| 0.0           | 19.0  | 14269 | 0.8002          | 0.9048   |
| 0.0           | 20.0  | 15020 | 0.8446          | 0.9115   |
| 0.0           | 21.0  | 15771 | 0.8926          | 0.9048   |
| 0.0           | 22.0  | 16522 | 0.8190          | 0.9065   |
| 0.0           | 23.0  | 17273 | 0.7943          | 0.9098   |
| 0.0           | 24.0  | 18024 | 0.7616          | 0.9098   |
| 0.0           | 25.0  | 18775 | 0.7566          | 0.9149   |
| 0.0           | 26.0  | 19526 | 0.7309          | 0.9149   |
| 0.0           | 27.0  | 20277 | 0.7760          | 0.9032   |
| 0.0           | 28.0  | 21028 | 0.7849          | 0.9132   |
| 0.008         | 29.0  | 21779 | 0.7826          | 0.9149   |
| 0.0           | 30.0  | 22530 | 0.7666          | 0.9199   |
| 0.0           | 31.0  | 23281 | 0.7402          | 0.9199   |
| 0.0           | 32.0  | 24032 | 0.7484          | 0.9199   |
| 0.0           | 33.0  | 24783 | 0.7616          | 0.9165   |
| 0.0           | 34.0  | 25534 | 0.7803          | 0.9149   |
| 0.0           | 35.0  | 26285 | 0.7685          | 0.9199   |
| 0.0           | 36.0  | 27036 | 0.7685          | 0.9165   |
| 0.0           | 37.0  | 27787 | 0.7687          | 0.9199   |
| 0.0           | 38.0  | 28538 | 0.7876          | 0.9199   |
| 0.0           | 39.0  | 29289 | 0.7749          | 0.9215   |
| 0.0           | 40.0  | 30040 | 0.7734          | 0.9165   |
| 0.0           | 41.0  | 30791 | 0.7803          | 0.9199   |
| 0.0           | 42.0  | 31542 | 0.7799          | 0.9182   |
| 0.0           | 43.0  | 32293 | 0.7798          | 0.9182   |
| 0.0           | 44.0  | 33044 | 0.7789          | 0.9182   |
| 0.0           | 45.0  | 33795 | 0.7827          | 0.9199   |
| 0.0           | 46.0  | 34546 | 0.7810          | 0.9182   |
| 0.0           | 47.0  | 35297 | 0.7840          | 0.9182   |
| 0.0           | 48.0  | 36048 | 0.7837          | 0.9199   |
| 0.0           | 49.0  | 36799 | 0.7839          | 0.9199   |
| 0.0           | 50.0  | 37550 | 0.7859          | 0.9182   |


### Framework versions

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