---
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_adamax_001_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: 0.8935108153078203
---

<!-- 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_adamax_001_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: 0.8198
- Accuracy: 0.8935

## 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: 0.001
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6145        | 1.0   | 75   | 0.5428          | 0.7970   |
| 0.3766        | 2.0   | 150  | 0.5726          | 0.7720   |
| 0.4048        | 3.0   | 225  | 0.6119          | 0.7920   |
| 0.3699        | 4.0   | 300  | 0.3532          | 0.8619   |
| 0.3283        | 5.0   | 375  | 0.4734          | 0.8270   |
| 0.2617        | 6.0   | 450  | 0.5747          | 0.8053   |
| 0.2131        | 7.0   | 525  | 0.4492          | 0.8486   |
| 0.1731        | 8.0   | 600  | 0.4339          | 0.8686   |
| 0.1832        | 9.0   | 675  | 0.5654          | 0.8336   |
| 0.1286        | 10.0  | 750  | 1.0166          | 0.7704   |
| 0.0921        | 11.0  | 825  | 0.5592          | 0.8519   |
| 0.0818        | 12.0  | 900  | 0.6074          | 0.8486   |
| 0.1315        | 13.0  | 975  | 0.7091          | 0.8369   |
| 0.0851        | 14.0  | 1050 | 0.6304          | 0.8436   |
| 0.0354        | 15.0  | 1125 | 0.8000          | 0.8469   |
| 0.0659        | 16.0  | 1200 | 0.7712          | 0.8586   |
| 0.0297        | 17.0  | 1275 | 0.8136          | 0.8686   |
| 0.058         | 18.0  | 1350 | 0.7968          | 0.8536   |
| 0.0096        | 19.0  | 1425 | 0.7312          | 0.8719   |
| 0.0206        | 20.0  | 1500 | 0.7618          | 0.8453   |
| 0.0111        | 21.0  | 1575 | 1.0098          | 0.8336   |
| 0.0053        | 22.0  | 1650 | 0.8487          | 0.8502   |
| 0.0105        | 23.0  | 1725 | 0.7386          | 0.8702   |
| 0.0094        | 24.0  | 1800 | 0.8515          | 0.8419   |
| 0.0004        | 25.0  | 1875 | 0.8080          | 0.8636   |
| 0.0177        | 26.0  | 1950 | 0.6472          | 0.8819   |
| 0.0321        | 27.0  | 2025 | 0.6905          | 0.8785   |
| 0.0096        | 28.0  | 2100 | 0.6932          | 0.8852   |
| 0.0091        | 29.0  | 2175 | 0.7066          | 0.8869   |
| 0.0059        | 30.0  | 2250 | 0.7159          | 0.8819   |
| 0.0056        | 31.0  | 2325 | 0.7490          | 0.8869   |
| 0.0           | 32.0  | 2400 | 0.7569          | 0.8885   |
| 0.0           | 33.0  | 2475 | 0.7589          | 0.8869   |
| 0.0003        | 34.0  | 2550 | 0.7519          | 0.8935   |
| 0.01          | 35.0  | 2625 | 0.7808          | 0.8902   |
| 0.0           | 36.0  | 2700 | 0.7653          | 0.8918   |
| 0.0001        | 37.0  | 2775 | 0.7709          | 0.8902   |
| 0.0           | 38.0  | 2850 | 0.7835          | 0.8885   |
| 0.0016        | 39.0  | 2925 | 0.7996          | 0.8935   |
| 0.0           | 40.0  | 3000 | 0.7825          | 0.8918   |
| 0.0036        | 41.0  | 3075 | 0.7879          | 0.8918   |
| 0.0           | 42.0  | 3150 | 0.7990          | 0.8935   |
| 0.003         | 43.0  | 3225 | 0.8020          | 0.8935   |
| 0.0034        | 44.0  | 3300 | 0.8080          | 0.8935   |
| 0.0           | 45.0  | 3375 | 0.8073          | 0.8935   |
| 0.0           | 46.0  | 3450 | 0.8161          | 0.8935   |
| 0.0029        | 47.0  | 3525 | 0.8235          | 0.8918   |
| 0.0           | 48.0  | 3600 | 0.8195          | 0.8935   |
| 0.0023        | 49.0  | 3675 | 0.8192          | 0.8935   |
| 0.0022        | 50.0  | 3750 | 0.8198          | 0.8935   |


### Framework versions

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