---
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_1x_deit_tiny_rms_00001_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: 0.6222222222222222
---

<!-- 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. -->

# hushem_1x_deit_tiny_rms_00001_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: 1.4676
- Accuracy: 0.6222

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 6    | 1.3067          | 0.4222   |
| 1.3733        | 2.0   | 12   | 1.3951          | 0.4444   |
| 1.3733        | 3.0   | 18   | 1.3740          | 0.4222   |
| 0.6558        | 4.0   | 24   | 1.2467          | 0.5333   |
| 0.3343        | 5.0   | 30   | 1.5107          | 0.4667   |
| 0.3343        | 6.0   | 36   | 1.6079          | 0.4444   |
| 0.1446        | 7.0   | 42   | 1.2227          | 0.5333   |
| 0.1446        | 8.0   | 48   | 1.2018          | 0.5333   |
| 0.0575        | 9.0   | 54   | 1.2408          | 0.5111   |
| 0.0237        | 10.0  | 60   | 1.2581          | 0.5111   |
| 0.0237        | 11.0  | 66   | 1.4007          | 0.6      |
| 0.0072        | 12.0  | 72   | 1.2676          | 0.6444   |
| 0.0072        | 13.0  | 78   | 1.2933          | 0.5778   |
| 0.0036        | 14.0  | 84   | 1.3326          | 0.6222   |
| 0.0025        | 15.0  | 90   | 1.3074          | 0.6444   |
| 0.0025        | 16.0  | 96   | 1.3484          | 0.6222   |
| 0.002         | 17.0  | 102  | 1.3984          | 0.6222   |
| 0.002         | 18.0  | 108  | 1.3916          | 0.6222   |
| 0.0017        | 19.0  | 114  | 1.3871          | 0.6222   |
| 0.0014        | 20.0  | 120  | 1.4171          | 0.6222   |
| 0.0014        | 21.0  | 126  | 1.4207          | 0.6222   |
| 0.0012        | 22.0  | 132  | 1.4218          | 0.6222   |
| 0.0012        | 23.0  | 138  | 1.4371          | 0.6222   |
| 0.0011        | 24.0  | 144  | 1.4404          | 0.6222   |
| 0.001         | 25.0  | 150  | 1.4321          | 0.6222   |
| 0.001         | 26.0  | 156  | 1.4218          | 0.6222   |
| 0.0009        | 27.0  | 162  | 1.4367          | 0.6222   |
| 0.0009        | 28.0  | 168  | 1.4359          | 0.6222   |
| 0.0008        | 29.0  | 174  | 1.4387          | 0.6222   |
| 0.0008        | 30.0  | 180  | 1.4566          | 0.6222   |
| 0.0008        | 31.0  | 186  | 1.4528          | 0.6222   |
| 0.0007        | 32.0  | 192  | 1.4517          | 0.6222   |
| 0.0007        | 33.0  | 198  | 1.4535          | 0.6222   |
| 0.0007        | 34.0  | 204  | 1.4488          | 0.6444   |
| 0.0007        | 35.0  | 210  | 1.4494          | 0.6444   |
| 0.0007        | 36.0  | 216  | 1.4561          | 0.6444   |
| 0.0007        | 37.0  | 222  | 1.4595          | 0.6444   |
| 0.0007        | 38.0  | 228  | 1.4667          | 0.6222   |
| 0.0006        | 39.0  | 234  | 1.4671          | 0.6222   |
| 0.0007        | 40.0  | 240  | 1.4686          | 0.6222   |
| 0.0007        | 41.0  | 246  | 1.4681          | 0.6222   |
| 0.0006        | 42.0  | 252  | 1.4676          | 0.6222   |
| 0.0006        | 43.0  | 258  | 1.4676          | 0.6222   |
| 0.0006        | 44.0  | 264  | 1.4676          | 0.6222   |
| 0.0006        | 45.0  | 270  | 1.4676          | 0.6222   |
| 0.0006        | 46.0  | 276  | 1.4676          | 0.6222   |
| 0.0006        | 47.0  | 282  | 1.4676          | 0.6222   |
| 0.0006        | 48.0  | 288  | 1.4676          | 0.6222   |
| 0.0006        | 49.0  | 294  | 1.4676          | 0.6222   |
| 0.0006        | 50.0  | 300  | 1.4676          | 0.6222   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1