transformers tensorboard safetensors vit image-classification generated_from_trainer dataset:imagefolder base_model:facebook/deit-small-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: facebook/deit-small-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_5x_deit_small_adamax_001_fold5
  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: 0.7560975609756098
---

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# hushem_5x_deit_small_adamax_001_fold5

This model is a fine-tuned version of [facebook/deit-small-patch16-224](https://huggingface.co/facebook/deit-small-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9978
- Accuracy: 0.7561

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4105        | 1.0   | 28   | 1.2401          | 0.4878   |
| 1.1305        | 2.0   | 56   | 1.2429          | 0.4634   |
| 0.8883        | 3.0   | 84   | 1.0090          | 0.5366   |
| 0.7137        | 4.0   | 112  | 0.7064          | 0.7317   |
| 0.4682        | 5.0   | 140  | 0.8445          | 0.7073   |
| 0.5286        | 6.0   | 168  | 1.1652          | 0.5854   |
| 0.3742        | 7.0   | 196  | 0.6789          | 0.8049   |
| 0.3573        | 8.0   | 224  | 0.7278          | 0.7317   |
| 0.272         | 9.0   | 252  | 0.8849          | 0.7561   |
| 0.1472        | 10.0  | 280  | 1.2627          | 0.6829   |
| 0.1837        | 11.0  | 308  | 1.1712          | 0.7317   |
| 0.0937        | 12.0  | 336  | 1.4720          | 0.7073   |
| 0.1467        | 13.0  | 364  | 1.7992          | 0.6585   |
| 0.1394        | 14.0  | 392  | 1.7959          | 0.5854   |
| 0.0985        | 15.0  | 420  | 1.4497          | 0.7317   |
| 0.0548        | 16.0  | 448  | 1.4327          | 0.7561   |
| 0.0354        | 17.0  | 476  | 1.5157          | 0.7317   |
| 0.0897        | 18.0  | 504  | 1.9967          | 0.7561   |
| 0.0783        | 19.0  | 532  | 1.8000          | 0.6829   |
| 0.0872        | 20.0  | 560  | 2.1630          | 0.7073   |
| 0.0467        | 21.0  | 588  | 1.7971          | 0.7073   |
| 0.0024        | 22.0  | 616  | 1.1519          | 0.8049   |
| 0.001         | 23.0  | 644  | 1.4688          | 0.7805   |
| 0.0101        | 24.0  | 672  | 1.1822          | 0.8293   |
| 0.005         | 25.0  | 700  | 1.2237          | 0.8293   |
| 0.0001        | 26.0  | 728  | 1.7234          | 0.7317   |
| 0.0025        | 27.0  | 756  | 1.4712          | 0.7561   |
| 0.0001        | 28.0  | 784  | 2.0676          | 0.7805   |
| 0.0003        | 29.0  | 812  | 2.0101          | 0.7317   |
| 0.0           | 30.0  | 840  | 2.0010          | 0.7561   |
| 0.0           | 31.0  | 868  | 1.9976          | 0.7561   |
| 0.0           | 32.0  | 896  | 1.9954          | 0.7561   |
| 0.0           | 33.0  | 924  | 1.9948          | 0.7561   |
| 0.0           | 34.0  | 952  | 1.9948          | 0.7561   |
| 0.0           | 35.0  | 980  | 1.9948          | 0.7561   |
| 0.0           | 36.0  | 1008 | 1.9942          | 0.7561   |
| 0.0           | 37.0  | 1036 | 1.9944          | 0.7561   |
| 0.0           | 38.0  | 1064 | 1.9949          | 0.7561   |
| 0.0           | 39.0  | 1092 | 1.9951          | 0.7561   |
| 0.0           | 40.0  | 1120 | 1.9957          | 0.7561   |
| 0.0           | 41.0  | 1148 | 1.9963          | 0.7561   |
| 0.0           | 42.0  | 1176 | 1.9964          | 0.7561   |
| 0.0           | 43.0  | 1204 | 1.9969          | 0.7561   |
| 0.0           | 44.0  | 1232 | 1.9973          | 0.7561   |
| 0.0           | 45.0  | 1260 | 1.9974          | 0.7561   |
| 0.0           | 46.0  | 1288 | 1.9976          | 0.7561   |
| 0.0           | 47.0  | 1316 | 1.9978          | 0.7561   |
| 0.0           | 48.0  | 1344 | 1.9978          | 0.7561   |
| 0.0           | 49.0  | 1372 | 1.9978          | 0.7561   |
| 0.0           | 50.0  | 1400 | 1.9978          | 0.7561   |


### Framework versions

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