---
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_fold4
  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: 0.8571428571428571
---

<!-- 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_fold4

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: 0.4549
- Accuracy: 0.8571

## 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    | 1.4075          | 0.2857   |
| 1.4145        | 2.0   | 12   | 1.3443          | 0.3571   |
| 1.4145        | 3.0   | 18   | 0.8612          | 0.6667   |
| 0.7818        | 4.0   | 24   | 0.9127          | 0.6190   |
| 0.3833        | 5.0   | 30   | 0.5998          | 0.8810   |
| 0.3833        | 6.0   | 36   | 0.5796          | 0.7857   |
| 0.1457        | 7.0   | 42   | 0.5756          | 0.8333   |
| 0.1457        | 8.0   | 48   | 0.5188          | 0.7857   |
| 0.0559        | 9.0   | 54   | 0.5146          | 0.8571   |
| 0.0198        | 10.0  | 60   | 0.5290          | 0.7857   |
| 0.0198        | 11.0  | 66   | 0.4513          | 0.8571   |
| 0.007         | 12.0  | 72   | 0.4696          | 0.8571   |
| 0.007         | 13.0  | 78   | 0.4668          | 0.8333   |
| 0.0039        | 14.0  | 84   | 0.4642          | 0.8333   |
| 0.0028        | 15.0  | 90   | 0.4519          | 0.8571   |
| 0.0028        | 16.0  | 96   | 0.4562          | 0.8333   |
| 0.0022        | 17.0  | 102  | 0.4543          | 0.8571   |
| 0.0022        | 18.0  | 108  | 0.4588          | 0.8571   |
| 0.0018        | 19.0  | 114  | 0.4546          | 0.8571   |
| 0.0016        | 20.0  | 120  | 0.4551          | 0.8333   |
| 0.0016        | 21.0  | 126  | 0.4570          | 0.8333   |
| 0.0013        | 22.0  | 132  | 0.4556          | 0.8333   |
| 0.0013        | 23.0  | 138  | 0.4547          | 0.8333   |
| 0.0012        | 24.0  | 144  | 0.4556          | 0.8571   |
| 0.0011        | 25.0  | 150  | 0.4547          | 0.8571   |
| 0.0011        | 26.0  | 156  | 0.4538          | 0.8571   |
| 0.001         | 27.0  | 162  | 0.4593          | 0.8333   |
| 0.001         | 28.0  | 168  | 0.4560          | 0.8333   |
| 0.0009        | 29.0  | 174  | 0.4555          | 0.8333   |
| 0.0009        | 30.0  | 180  | 0.4554          | 0.8333   |
| 0.0009        | 31.0  | 186  | 0.4563          | 0.8333   |
| 0.0008        | 32.0  | 192  | 0.4547          | 0.8571   |
| 0.0008        | 33.0  | 198  | 0.4545          | 0.8571   |
| 0.0008        | 34.0  | 204  | 0.4547          | 0.8571   |
| 0.0007        | 35.0  | 210  | 0.4541          | 0.8571   |
| 0.0007        | 36.0  | 216  | 0.4545          | 0.8571   |
| 0.0007        | 37.0  | 222  | 0.4550          | 0.8571   |
| 0.0007        | 38.0  | 228  | 0.4547          | 0.8571   |
| 0.0007        | 39.0  | 234  | 0.4549          | 0.8571   |
| 0.0007        | 40.0  | 240  | 0.4549          | 0.8571   |
| 0.0007        | 41.0  | 246  | 0.4549          | 0.8571   |
| 0.0007        | 42.0  | 252  | 0.4549          | 0.8571   |
| 0.0007        | 43.0  | 258  | 0.4549          | 0.8571   |
| 0.0007        | 44.0  | 264  | 0.4549          | 0.8571   |
| 0.0007        | 45.0  | 270  | 0.4549          | 0.8571   |
| 0.0007        | 46.0  | 276  | 0.4549          | 0.8571   |
| 0.0007        | 47.0  | 282  | 0.4549          | 0.8571   |
| 0.0007        | 48.0  | 288  | 0.4549          | 0.8571   |
| 0.0007        | 49.0  | 294  | 0.4549          | 0.8571   |
| 0.0007        | 50.0  | 300  | 0.4549          | 0.8571   |


### Framework versions

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