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_00001_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: 0.8048780487804879
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# hushem_5x_deit_small_adamax_00001_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: 0.6350
- Accuracy: 0.8049

## 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: 1e-05
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.307         | 1.0   | 28   | 1.2048          | 0.4878   |
| 1.0055        | 2.0   | 56   | 1.0344          | 0.5366   |
| 0.7917        | 3.0   | 84   | 0.8814          | 0.6829   |
| 0.5612        | 4.0   | 112  | 0.7794          | 0.6585   |
| 0.4121        | 5.0   | 140  | 0.6731          | 0.7805   |
| 0.3453        | 6.0   | 168  | 0.6198          | 0.7561   |
| 0.2136        | 7.0   | 196  | 0.5552          | 0.7805   |
| 0.1402        | 8.0   | 224  | 0.5538          | 0.7805   |
| 0.1098        | 9.0   | 252  | 0.5179          | 0.8049   |
| 0.0661        | 10.0  | 280  | 0.4716          | 0.8293   |
| 0.0459        | 11.0  | 308  | 0.4940          | 0.8049   |
| 0.0201        | 12.0  | 336  | 0.4943          | 0.7805   |
| 0.0128        | 13.0  | 364  | 0.4835          | 0.8049   |
| 0.013         | 14.0  | 392  | 0.5177          | 0.8049   |
| 0.005         | 15.0  | 420  | 0.5313          | 0.7805   |
| 0.0049        | 16.0  | 448  | 0.5255          | 0.8293   |
| 0.0033        | 17.0  | 476  | 0.5525          | 0.8049   |
| 0.0027        | 18.0  | 504  | 0.5486          | 0.8049   |
| 0.0024        | 19.0  | 532  | 0.5501          | 0.8049   |
| 0.0021        | 20.0  | 560  | 0.5689          | 0.8049   |
| 0.0017        | 21.0  | 588  | 0.5750          | 0.8049   |
| 0.0016        | 22.0  | 616  | 0.5752          | 0.8049   |
| 0.0015        | 23.0  | 644  | 0.5846          | 0.8049   |
| 0.0013        | 24.0  | 672  | 0.5888          | 0.8049   |
| 0.0012        | 25.0  | 700  | 0.5919          | 0.8049   |
| 0.0012        | 26.0  | 728  | 0.5956          | 0.8049   |
| 0.0011        | 27.0  | 756  | 0.5988          | 0.8049   |
| 0.0011        | 28.0  | 784  | 0.6017          | 0.8049   |
| 0.001         | 29.0  | 812  | 0.6080          | 0.8049   |
| 0.0009        | 30.0  | 840  | 0.6107          | 0.8049   |
| 0.0009        | 31.0  | 868  | 0.6102          | 0.8049   |
| 0.0008        | 32.0  | 896  | 0.6145          | 0.8049   |
| 0.0008        | 33.0  | 924  | 0.6168          | 0.8049   |
| 0.0008        | 34.0  | 952  | 0.6219          | 0.8049   |
| 0.0008        | 35.0  | 980  | 0.6219          | 0.8049   |
| 0.0008        | 36.0  | 1008 | 0.6245          | 0.8049   |
| 0.0007        | 37.0  | 1036 | 0.6250          | 0.8049   |
| 0.0007        | 38.0  | 1064 | 0.6281          | 0.8049   |
| 0.0007        | 39.0  | 1092 | 0.6275          | 0.8049   |
| 0.0006        | 40.0  | 1120 | 0.6308          | 0.8049   |
| 0.0007        | 41.0  | 1148 | 0.6308          | 0.8049   |
| 0.0006        | 42.0  | 1176 | 0.6332          | 0.8049   |
| 0.0006        | 43.0  | 1204 | 0.6344          | 0.8049   |
| 0.0006        | 44.0  | 1232 | 0.6352          | 0.8049   |
| 0.0006        | 45.0  | 1260 | 0.6342          | 0.8049   |
| 0.0006        | 46.0  | 1288 | 0.6344          | 0.8049   |
| 0.0006        | 47.0  | 1316 | 0.6347          | 0.8049   |
| 0.0006        | 48.0  | 1344 | 0.6350          | 0.8049   |
| 0.0006        | 49.0  | 1372 | 0.6350          | 0.8049   |
| 0.0006        | 50.0  | 1400 | 0.6350          | 0.8049   |


### Framework versions

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