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: smids_1x_deit_small_sgd_00001_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: 0.4774624373956594
---

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# smids_1x_deit_small_sgd_00001_fold1

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: 1.0403
- Accuracy: 0.4775

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0855        | 1.0   | 76   | 1.0750          | 0.4424   |
| 1.0478        | 2.0   | 152  | 1.0731          | 0.4391   |
| 1.0766        | 3.0   | 228  | 1.0714          | 0.4391   |
| 1.0629        | 4.0   | 304  | 1.0697          | 0.4357   |
| 1.094         | 5.0   | 380  | 1.0680          | 0.4341   |
| 1.0477        | 6.0   | 456  | 1.0665          | 0.4391   |
| 1.0623        | 7.0   | 532  | 1.0650          | 0.4441   |
| 1.0732        | 8.0   | 608  | 1.0636          | 0.4457   |
| 1.0667        | 9.0   | 684  | 1.0622          | 0.4491   |
| 1.0551        | 10.0  | 760  | 1.0610          | 0.4491   |
| 1.0356        | 11.0  | 836  | 1.0597          | 0.4491   |
| 1.0548        | 12.0  | 912  | 1.0586          | 0.4508   |
| 1.0615        | 13.0  | 988  | 1.0574          | 0.4591   |
| 1.0286        | 14.0  | 1064 | 1.0564          | 0.4574   |
| 1.0112        | 15.0  | 1140 | 1.0553          | 0.4558   |
| 1.0377        | 16.0  | 1216 | 1.0543          | 0.4574   |
| 1.0367        | 17.0  | 1292 | 1.0534          | 0.4608   |
| 1.0315        | 18.0  | 1368 | 1.0524          | 0.4608   |
| 1.0307        | 19.0  | 1444 | 1.0516          | 0.4608   |
| 1.0759        | 20.0  | 1520 | 1.0507          | 0.4658   |
| 1.0618        | 21.0  | 1596 | 1.0499          | 0.4674   |
| 1.0607        | 22.0  | 1672 | 1.0492          | 0.4691   |
| 1.0436        | 23.0  | 1748 | 1.0485          | 0.4741   |
| 1.0498        | 24.0  | 1824 | 1.0478          | 0.4758   |
| 1.0615        | 25.0  | 1900 | 1.0471          | 0.4741   |
| 1.0688        | 26.0  | 1976 | 1.0465          | 0.4741   |
| 1.0336        | 27.0  | 2052 | 1.0459          | 0.4741   |
| 1.0515        | 28.0  | 2128 | 1.0454          | 0.4741   |
| 1.042         | 29.0  | 2204 | 1.0449          | 0.4775   |
| 1.0112        | 30.0  | 2280 | 1.0444          | 0.4791   |
| 1.0359        | 31.0  | 2356 | 1.0439          | 0.4791   |
| 1.0424        | 32.0  | 2432 | 1.0435          | 0.4791   |
| 1.0133        | 33.0  | 2508 | 1.0431          | 0.4808   |
| 1.0411        | 34.0  | 2584 | 1.0427          | 0.4791   |
| 1.0158        | 35.0  | 2660 | 1.0424          | 0.4775   |
| 1.0378        | 36.0  | 2736 | 1.0421          | 0.4775   |
| 1.0599        | 37.0  | 2812 | 1.0418          | 0.4791   |
| 1.0074        | 38.0  | 2888 | 1.0416          | 0.4775   |
| 1.0149        | 39.0  | 2964 | 1.0413          | 0.4775   |
| 1.0618        | 40.0  | 3040 | 1.0411          | 0.4775   |
| 1.0242        | 41.0  | 3116 | 1.0409          | 0.4775   |
| 1.0268        | 42.0  | 3192 | 1.0408          | 0.4775   |
| 1.0441        | 43.0  | 3268 | 1.0407          | 0.4758   |
| 1.0356        | 44.0  | 3344 | 1.0406          | 0.4775   |
| 1.0273        | 45.0  | 3420 | 1.0405          | 0.4775   |
| 1.0473        | 46.0  | 3496 | 1.0404          | 0.4775   |
| 1.0225        | 47.0  | 3572 | 1.0404          | 0.4775   |
| 1.0411        | 48.0  | 3648 | 1.0404          | 0.4775   |
| 1.0464        | 49.0  | 3724 | 1.0403          | 0.4775   |
| 1.0229        | 50.0  | 3800 | 1.0403          | 0.4775   |


### Framework versions

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