---
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_adamax_001_fold2
  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: 0.8901830282861897
---

<!-- 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_adamax_001_fold2

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: 1.1513
- Accuracy: 0.8902

## 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: 0.001
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.3758        | 1.0   | 375   | 0.3275          | 0.8619   |
| 0.3244        | 2.0   | 750   | 0.4328          | 0.8403   |
| 0.3305        | 3.0   | 1125  | 0.3559          | 0.8586   |
| 0.2057        | 4.0   | 1500  | 0.3484          | 0.8752   |
| 0.2037        | 5.0   | 1875  | 0.3334          | 0.8918   |
| 0.109         | 6.0   | 2250  | 0.3396          | 0.8869   |
| 0.1296        | 7.0   | 2625  | 0.4274          | 0.8719   |
| 0.1447        | 8.0   | 3000  | 0.4555          | 0.8569   |
| 0.0656        | 9.0   | 3375  | 0.4650          | 0.8869   |
| 0.0303        | 10.0  | 3750  | 0.5987          | 0.8602   |
| 0.0379        | 11.0  | 4125  | 0.5753          | 0.8835   |
| 0.0368        | 12.0  | 4500  | 0.6264          | 0.8669   |
| 0.0495        | 13.0  | 4875  | 0.6979          | 0.8569   |
| 0.0376        | 14.0  | 5250  | 0.7442          | 0.8636   |
| 0.0604        | 15.0  | 5625  | 0.8422          | 0.8636   |
| 0.0353        | 16.0  | 6000  | 0.7521          | 0.8852   |
| 0.0761        | 17.0  | 6375  | 0.7920          | 0.8752   |
| 0.004         | 18.0  | 6750  | 1.0354          | 0.8702   |
| 0.0148        | 19.0  | 7125  | 0.7279          | 0.8785   |
| 0.0237        | 20.0  | 7500  | 0.7424          | 0.8735   |
| 0.0011        | 21.0  | 7875  | 0.7919          | 0.8802   |
| 0.0017        | 22.0  | 8250  | 0.8106          | 0.8918   |
| 0.0086        | 23.0  | 8625  | 0.8451          | 0.8735   |
| 0.0037        | 24.0  | 9000  | 0.8674          | 0.8735   |
| 0.0002        | 25.0  | 9375  | 0.8393          | 0.8869   |
| 0.0036        | 26.0  | 9750  | 0.8897          | 0.8902   |
| 0.0019        | 27.0  | 10125 | 0.8685          | 0.8885   |
| 0.0           | 28.0  | 10500 | 0.8366          | 0.8902   |
| 0.0007        | 29.0  | 10875 | 0.9524          | 0.8985   |
| 0.0002        | 30.0  | 11250 | 0.9036          | 0.8918   |
| 0.0073        | 31.0  | 11625 | 0.9747          | 0.8935   |
| 0.0057        | 32.0  | 12000 | 0.9823          | 0.8885   |
| 0.0116        | 33.0  | 12375 | 0.9806          | 0.8935   |
| 0.0           | 34.0  | 12750 | 1.0179          | 0.8885   |
| 0.0           | 35.0  | 13125 | 1.0978          | 0.8785   |
| 0.0           | 36.0  | 13500 | 0.9957          | 0.8852   |
| 0.0           | 37.0  | 13875 | 1.0261          | 0.8902   |
| 0.0           | 38.0  | 14250 | 1.0512          | 0.8885   |
| 0.0           | 39.0  | 14625 | 1.0513          | 0.8902   |
| 0.0035        | 40.0  | 15000 | 1.0782          | 0.8902   |
| 0.0           | 41.0  | 15375 | 1.0839          | 0.8885   |
| 0.0032        | 42.0  | 15750 | 1.1078          | 0.8885   |
| 0.0027        | 43.0  | 16125 | 1.1099          | 0.8902   |
| 0.0028        | 44.0  | 16500 | 1.1218          | 0.8902   |
| 0.0032        | 45.0  | 16875 | 1.1207          | 0.8885   |
| 0.0           | 46.0  | 17250 | 1.1330          | 0.8885   |
| 0.0059        | 47.0  | 17625 | 1.1405          | 0.8885   |
| 0.0           | 48.0  | 18000 | 1.1472          | 0.8885   |
| 0.0026        | 49.0  | 18375 | 1.1507          | 0.8885   |
| 0.0022        | 50.0  | 18750 | 1.1513          | 0.8902   |


### Framework versions

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