---
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: smids_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: 0.8569051580698835
---

<!-- 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. -->

# smids_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: 1.4112
- Accuracy: 0.8569

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.8146        | 1.0   | 75   | 0.7861          | 0.5524   |
| 0.5727        | 2.0   | 150  | 0.4984          | 0.8103   |
| 0.5359        | 3.0   | 225  | 0.4227          | 0.8286   |
| 0.4099        | 4.0   | 300  | 0.4531          | 0.8270   |
| 0.3762        | 5.0   | 375  | 0.4703          | 0.8236   |
| 0.2518        | 6.0   | 450  | 0.5236          | 0.8453   |
| 0.2143        | 7.0   | 525  | 0.5529          | 0.8353   |
| 0.1716        | 8.0   | 600  | 0.6424          | 0.8519   |
| 0.1064        | 9.0   | 675  | 1.0458          | 0.7987   |
| 0.1362        | 10.0  | 750  | 0.7319          | 0.8336   |
| 0.1448        | 11.0  | 825  | 0.9729          | 0.8236   |
| 0.0254        | 12.0  | 900  | 0.9267          | 0.8436   |
| 0.0822        | 13.0  | 975  | 1.0041          | 0.8336   |
| 0.0792        | 14.0  | 1050 | 1.1093          | 0.8220   |
| 0.0861        | 15.0  | 1125 | 1.1399          | 0.8153   |
| 0.049         | 16.0  | 1200 | 1.3759          | 0.8103   |
| 0.0209        | 17.0  | 1275 | 1.1868          | 0.8303   |
| 0.0314        | 18.0  | 1350 | 1.3024          | 0.8353   |
| 0.0371        | 19.0  | 1425 | 1.1958          | 0.8303   |
| 0.0408        | 20.0  | 1500 | 1.0595          | 0.8469   |
| 0.0443        | 21.0  | 1575 | 1.2918          | 0.8353   |
| 0.0161        | 22.0  | 1650 | 1.3270          | 0.8270   |
| 0.002         | 23.0  | 1725 | 1.3561          | 0.8369   |
| 0.0119        | 24.0  | 1800 | 1.3471          | 0.8353   |
| 0.021         | 25.0  | 1875 | 1.3114          | 0.8403   |
| 0.0001        | 26.0  | 1950 | 1.2789          | 0.8453   |
| 0.0215        | 27.0  | 2025 | 1.3801          | 0.8253   |
| 0.0117        | 28.0  | 2100 | 1.3311          | 0.8353   |
| 0.0064        | 29.0  | 2175 | 1.5354          | 0.8153   |
| 0.0497        | 30.0  | 2250 | 1.2007          | 0.8419   |
| 0.0245        | 31.0  | 2325 | 1.2452          | 0.8586   |
| 0.0           | 32.0  | 2400 | 1.2980          | 0.8586   |
| 0.0           | 33.0  | 2475 | 1.3038          | 0.8586   |
| 0.0           | 34.0  | 2550 | 1.3062          | 0.8552   |
| 0.0104        | 35.0  | 2625 | 1.3421          | 0.8519   |
| 0.0001        | 36.0  | 2700 | 1.3682          | 0.8369   |
| 0.0027        | 37.0  | 2775 | 1.4409          | 0.8419   |
| 0.0           | 38.0  | 2850 | 1.3923          | 0.8519   |
| 0.0017        | 39.0  | 2925 | 1.4064          | 0.8536   |
| 0.0           | 40.0  | 3000 | 1.4003          | 0.8519   |
| 0.0027        | 41.0  | 3075 | 1.4111          | 0.8519   |
| 0.0           | 42.0  | 3150 | 1.4021          | 0.8519   |
| 0.0025        | 43.0  | 3225 | 1.4193          | 0.8519   |
| 0.0029        | 44.0  | 3300 | 1.3989          | 0.8552   |
| 0.0           | 45.0  | 3375 | 1.4257          | 0.8536   |
| 0.0           | 46.0  | 3450 | 1.4244          | 0.8536   |
| 0.0027        | 47.0  | 3525 | 1.4185          | 0.8536   |
| 0.0           | 48.0  | 3600 | 1.4177          | 0.8569   |
| 0.0023        | 49.0  | 3675 | 1.4124          | 0.8569   |
| 0.0021        | 50.0  | 3750 | 1.4112          | 0.8569   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0