---
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_lr0001_fold1
  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: 0.5777777777777777
---

<!-- 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_lr0001_fold1

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: 3.0724
- Accuracy: 0.5778

## 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    | 1.7581          | 0.2444   |
| 2.2176        | 2.0   | 12   | 1.4575          | 0.2444   |
| 2.2176        | 3.0   | 18   | 1.4070          | 0.2444   |
| 1.4625        | 4.0   | 24   | 1.4089          | 0.2444   |
| 1.4303        | 5.0   | 30   | 1.4530          | 0.2667   |
| 1.4303        | 6.0   | 36   | 1.3605          | 0.3778   |
| 1.3759        | 7.0   | 42   | 1.4068          | 0.3778   |
| 1.3759        | 8.0   | 48   | 1.3279          | 0.2889   |
| 1.3199        | 9.0   | 54   | 1.5997          | 0.2444   |
| 1.2335        | 10.0  | 60   | 1.5834          | 0.2444   |
| 1.2335        | 11.0  | 66   | 1.6144          | 0.3333   |
| 1.0406        | 12.0  | 72   | 1.1266          | 0.5111   |
| 1.0406        | 13.0  | 78   | 1.6894          | 0.3556   |
| 0.851         | 14.0  | 84   | 1.8080          | 0.4444   |
| 0.5856        | 15.0  | 90   | 2.0552          | 0.3778   |
| 0.5856        | 16.0  | 96   | 1.3379          | 0.4889   |
| 0.3402        | 17.0  | 102  | 1.4787          | 0.4889   |
| 0.3402        | 18.0  | 108  | 2.2439          | 0.4222   |
| 0.233         | 19.0  | 114  | 1.7239          | 0.4889   |
| 0.1016        | 20.0  | 120  | 2.5401          | 0.4222   |
| 0.1016        | 21.0  | 126  | 1.5433          | 0.5778   |
| 0.0994        | 22.0  | 132  | 1.8891          | 0.5333   |
| 0.0994        | 23.0  | 138  | 1.9405          | 0.4889   |
| 0.0839        | 24.0  | 144  | 1.5418          | 0.5778   |
| 0.0282        | 25.0  | 150  | 2.4010          | 0.5778   |
| 0.0282        | 26.0  | 156  | 2.6175          | 0.5778   |
| 0.0011        | 27.0  | 162  | 2.7024          | 0.5778   |
| 0.0011        | 28.0  | 168  | 2.7954          | 0.5778   |
| 0.0007        | 29.0  | 174  | 2.8362          | 0.5778   |
| 0.0006        | 30.0  | 180  | 2.8852          | 0.5778   |
| 0.0006        | 31.0  | 186  | 2.9050          | 0.5778   |
| 0.0005        | 32.0  | 192  | 2.9414          | 0.5778   |
| 0.0005        | 33.0  | 198  | 2.9746          | 0.5778   |
| 0.0005        | 34.0  | 204  | 2.9947          | 0.5778   |
| 0.0004        | 35.0  | 210  | 3.0141          | 0.5778   |
| 0.0004        | 36.0  | 216  | 3.0300          | 0.5778   |
| 0.0004        | 37.0  | 222  | 3.0447          | 0.5778   |
| 0.0004        | 38.0  | 228  | 3.0565          | 0.5778   |
| 0.0003        | 39.0  | 234  | 3.0642          | 0.5778   |
| 0.0003        | 40.0  | 240  | 3.0696          | 0.5778   |
| 0.0003        | 41.0  | 246  | 3.0717          | 0.5778   |
| 0.0003        | 42.0  | 252  | 3.0724          | 0.5778   |
| 0.0003        | 43.0  | 258  | 3.0724          | 0.5778   |
| 0.0003        | 44.0  | 264  | 3.0724          | 0.5778   |
| 0.0003        | 45.0  | 270  | 3.0724          | 0.5778   |
| 0.0003        | 46.0  | 276  | 3.0724          | 0.5778   |
| 0.0003        | 47.0  | 282  | 3.0724          | 0.5778   |
| 0.0003        | 48.0  | 288  | 3.0724          | 0.5778   |
| 0.0003        | 49.0  | 294  | 3.0724          | 0.5778   |
| 0.0003        | 50.0  | 300  | 3.0724          | 0.5778   |


### Framework versions

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