---
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_0001_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: 0.5555555555555556
---

<!-- 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_0001_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: 3.1133
- Accuracy: 0.5556

## 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: 0.0001
- 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    | 1.9323          | 0.2444   |
| 2.0865        | 2.0   | 12   | 1.4427          | 0.2444   |
| 2.0865        | 3.0   | 18   | 1.4293          | 0.2444   |
| 1.4431        | 4.0   | 24   | 1.3952          | 0.4667   |
| 1.4003        | 5.0   | 30   | 1.2967          | 0.4      |
| 1.4003        | 6.0   | 36   | 1.4719          | 0.2444   |
| 1.3496        | 7.0   | 42   | 1.3224          | 0.3556   |
| 1.3496        | 8.0   | 48   | 1.4673          | 0.3778   |
| 1.2064        | 9.0   | 54   | 1.4551          | 0.2667   |
| 1.1859        | 10.0  | 60   | 1.3687          | 0.3111   |
| 1.1859        | 11.0  | 66   | 1.2313          | 0.4444   |
| 1.0817        | 12.0  | 72   | 1.1514          | 0.4444   |
| 1.0817        | 13.0  | 78   | 1.1701          | 0.4444   |
| 1.0144        | 14.0  | 84   | 1.2204          | 0.4222   |
| 0.8578        | 15.0  | 90   | 1.1603          | 0.4889   |
| 0.8578        | 16.0  | 96   | 1.0987          | 0.5111   |
| 0.8063        | 17.0  | 102  | 0.9277          | 0.5111   |
| 0.8063        | 18.0  | 108  | 1.2038          | 0.5333   |
| 0.601         | 19.0  | 114  | 0.9886          | 0.6      |
| 0.465         | 20.0  | 120  | 1.5667          | 0.5111   |
| 0.465         | 21.0  | 126  | 1.8238          | 0.4889   |
| 0.2956        | 22.0  | 132  | 1.6043          | 0.4222   |
| 0.2956        | 23.0  | 138  | 1.2746          | 0.4889   |
| 0.3513        | 24.0  | 144  | 1.6389          | 0.5556   |
| 0.2137        | 25.0  | 150  | 1.6350          | 0.4889   |
| 0.2137        | 26.0  | 156  | 1.5926          | 0.4667   |
| 0.191         | 27.0  | 162  | 1.8516          | 0.4889   |
| 0.191         | 28.0  | 168  | 2.3628          | 0.4889   |
| 0.0581        | 29.0  | 174  | 2.3998          | 0.4889   |
| 0.0517        | 30.0  | 180  | 2.3913          | 0.5333   |
| 0.0517        | 31.0  | 186  | 2.7108          | 0.5556   |
| 0.005         | 32.0  | 192  | 2.8104          | 0.5556   |
| 0.005         | 33.0  | 198  | 2.8829          | 0.5556   |
| 0.0008        | 34.0  | 204  | 2.9326          | 0.5333   |
| 0.0006        | 35.0  | 210  | 2.9793          | 0.5556   |
| 0.0006        | 36.0  | 216  | 3.0150          | 0.5556   |
| 0.0005        | 37.0  | 222  | 3.0520          | 0.5556   |
| 0.0005        | 38.0  | 228  | 3.0772          | 0.5556   |
| 0.0004        | 39.0  | 234  | 3.0948          | 0.5556   |
| 0.0004        | 40.0  | 240  | 3.1038          | 0.5556   |
| 0.0004        | 41.0  | 246  | 3.1116          | 0.5556   |
| 0.0004        | 42.0  | 252  | 3.1133          | 0.5556   |
| 0.0004        | 43.0  | 258  | 3.1133          | 0.5556   |
| 0.0004        | 44.0  | 264  | 3.1133          | 0.5556   |
| 0.0004        | 45.0  | 270  | 3.1133          | 0.5556   |
| 0.0004        | 46.0  | 276  | 3.1133          | 0.5556   |
| 0.0004        | 47.0  | 282  | 3.1133          | 0.5556   |
| 0.0004        | 48.0  | 288  | 3.1133          | 0.5556   |
| 0.0004        | 49.0  | 294  | 3.1133          | 0.5556   |
| 0.0004        | 50.0  | 300  | 3.1133          | 0.5556   |


### Framework versions

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