---
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_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: 0.6585365853658537
---

<!-- 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_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: 1.1280
- Accuracy: 0.6585

## 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    | 1.2888          | 0.4390   |
| 1.3565        | 2.0   | 12   | 1.0130          | 0.5366   |
| 1.3565        | 3.0   | 18   | 0.9361          | 0.5366   |
| 0.667         | 4.0   | 24   | 0.8831          | 0.6585   |
| 0.2929        | 5.0   | 30   | 0.8739          | 0.5854   |
| 0.2929        | 6.0   | 36   | 0.9329          | 0.5854   |
| 0.1055        | 7.0   | 42   | 0.9159          | 0.6585   |
| 0.1055        | 8.0   | 48   | 1.0700          | 0.5854   |
| 0.04          | 9.0   | 54   | 1.0357          | 0.5854   |
| 0.013         | 10.0  | 60   | 0.9379          | 0.6585   |
| 0.013         | 11.0  | 66   | 0.9964          | 0.6341   |
| 0.0046        | 12.0  | 72   | 1.0009          | 0.6585   |
| 0.0046        | 13.0  | 78   | 0.9889          | 0.6585   |
| 0.0029        | 14.0  | 84   | 1.0074          | 0.6585   |
| 0.0023        | 15.0  | 90   | 1.0258          | 0.6585   |
| 0.0023        | 16.0  | 96   | 1.0330          | 0.6585   |
| 0.0018        | 17.0  | 102  | 1.0391          | 0.6585   |
| 0.0018        | 18.0  | 108  | 1.0476          | 0.6585   |
| 0.0015        | 19.0  | 114  | 1.0552          | 0.6585   |
| 0.0013        | 20.0  | 120  | 1.0615          | 0.6585   |
| 0.0013        | 21.0  | 126  | 1.0642          | 0.6585   |
| 0.0011        | 22.0  | 132  | 1.0600          | 0.6585   |
| 0.0011        | 23.0  | 138  | 1.0791          | 0.6341   |
| 0.001         | 24.0  | 144  | 1.0890          | 0.6585   |
| 0.001         | 25.0  | 150  | 1.0948          | 0.6585   |
| 0.001         | 26.0  | 156  | 1.1067          | 0.6585   |
| 0.0008        | 27.0  | 162  | 1.0949          | 0.6585   |
| 0.0008        | 28.0  | 168  | 1.1017          | 0.6585   |
| 0.0008        | 29.0  | 174  | 1.1094          | 0.6585   |
| 0.0007        | 30.0  | 180  | 1.1105          | 0.6585   |
| 0.0007        | 31.0  | 186  | 1.1156          | 0.6585   |
| 0.0007        | 32.0  | 192  | 1.1158          | 0.6585   |
| 0.0007        | 33.0  | 198  | 1.1174          | 0.6585   |
| 0.0007        | 34.0  | 204  | 1.1167          | 0.6585   |
| 0.0006        | 35.0  | 210  | 1.1206          | 0.6585   |
| 0.0006        | 36.0  | 216  | 1.1224          | 0.6585   |
| 0.0006        | 37.0  | 222  | 1.1230          | 0.6585   |
| 0.0006        | 38.0  | 228  | 1.1253          | 0.6585   |
| 0.0006        | 39.0  | 234  | 1.1272          | 0.6585   |
| 0.0006        | 40.0  | 240  | 1.1276          | 0.6585   |
| 0.0006        | 41.0  | 246  | 1.1278          | 0.6585   |
| 0.0006        | 42.0  | 252  | 1.1280          | 0.6585   |
| 0.0006        | 43.0  | 258  | 1.1280          | 0.6585   |
| 0.0006        | 44.0  | 264  | 1.1280          | 0.6585   |
| 0.0006        | 45.0  | 270  | 1.1280          | 0.6585   |
| 0.0006        | 46.0  | 276  | 1.1280          | 0.6585   |
| 0.0006        | 47.0  | 282  | 1.1280          | 0.6585   |
| 0.0006        | 48.0  | 288  | 1.1280          | 0.6585   |
| 0.0006        | 49.0  | 294  | 1.1280          | 0.6585   |
| 0.0006        | 50.0  | 300  | 1.1280          | 0.6585   |


### Framework versions

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