---
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_00001_fold5
  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: 0.8933333333333333
---

<!-- 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_00001_fold5

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: 0.8918
- Accuracy: 0.8933

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.3356        | 1.0   | 375   | 0.3637          | 0.8583   |
| 0.2941        | 2.0   | 750   | 0.2859          | 0.8917   |
| 0.2173        | 3.0   | 1125  | 0.2723          | 0.8933   |
| 0.2107        | 4.0   | 1500  | 0.2619          | 0.9017   |
| 0.1256        | 5.0   | 1875  | 0.3096          | 0.8767   |
| 0.0844        | 6.0   | 2250  | 0.2740          | 0.8983   |
| 0.0863        | 7.0   | 2625  | 0.3155          | 0.895    |
| 0.0472        | 8.0   | 3000  | 0.3497          | 0.895    |
| 0.0763        | 9.0   | 3375  | 0.3686          | 0.895    |
| 0.0335        | 10.0  | 3750  | 0.4149          | 0.8967   |
| 0.0338        | 11.0  | 4125  | 0.4756          | 0.8933   |
| 0.0184        | 12.0  | 4500  | 0.5125          | 0.89     |
| 0.0027        | 13.0  | 4875  | 0.6023          | 0.8767   |
| 0.0397        | 14.0  | 5250  | 0.6231          | 0.885    |
| 0.0014        | 15.0  | 5625  | 0.7069          | 0.8733   |
| 0.0003        | 16.0  | 6000  | 0.6770          | 0.8983   |
| 0.0258        | 17.0  | 6375  | 0.7038          | 0.895    |
| 0.0256        | 18.0  | 6750  | 0.7293          | 0.89     |
| 0.0002        | 19.0  | 7125  | 0.7746          | 0.8833   |
| 0.0001        | 20.0  | 7500  | 0.7738          | 0.8917   |
| 0.0001        | 21.0  | 7875  | 0.8059          | 0.8833   |
| 0.026         | 22.0  | 8250  | 0.8287          | 0.8933   |
| 0.0138        | 23.0  | 8625  | 0.8293          | 0.8867   |
| 0.0           | 24.0  | 9000  | 0.8289          | 0.88     |
| 0.0           | 25.0  | 9375  | 0.8428          | 0.8933   |
| 0.0001        | 26.0  | 9750  | 0.8343          | 0.8917   |
| 0.0016        | 27.0  | 10125 | 0.8455          | 0.89     |
| 0.0           | 28.0  | 10500 | 0.8478          | 0.89     |
| 0.0001        | 29.0  | 10875 | 0.8508          | 0.8917   |
| 0.0173        | 30.0  | 11250 | 0.8741          | 0.8917   |
| 0.0           | 31.0  | 11625 | 0.8677          | 0.8933   |
| 0.0           | 32.0  | 12000 | 0.8682          | 0.8933   |
| 0.0           | 33.0  | 12375 | 0.8819          | 0.8917   |
| 0.0           | 34.0  | 12750 | 0.8684          | 0.8917   |
| 0.0           | 35.0  | 13125 | 0.8910          | 0.8933   |
| 0.0           | 36.0  | 13500 | 0.8845          | 0.8933   |
| 0.0           | 37.0  | 13875 | 0.8700          | 0.8917   |
| 0.0072        | 38.0  | 14250 | 0.8781          | 0.8917   |
| 0.0           | 39.0  | 14625 | 0.8840          | 0.8933   |
| 0.0           | 40.0  | 15000 | 0.8993          | 0.895    |
| 0.0           | 41.0  | 15375 | 0.8767          | 0.8883   |
| 0.0           | 42.0  | 15750 | 0.8820          | 0.8967   |
| 0.0           | 43.0  | 16125 | 0.8803          | 0.8983   |
| 0.0           | 44.0  | 16500 | 0.8853          | 0.895    |
| 0.0           | 45.0  | 16875 | 0.8969          | 0.8917   |
| 0.0           | 46.0  | 17250 | 0.8999          | 0.8917   |
| 0.0073        | 47.0  | 17625 | 0.8921          | 0.895    |
| 0.0           | 48.0  | 18000 | 0.8943          | 0.8917   |
| 0.0           | 49.0  | 18375 | 0.8940          | 0.8933   |
| 0.0065        | 50.0  | 18750 | 0.8918          | 0.8933   |


### Framework versions

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