transformers pytorch 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_3x_deit_small_sgd_001_fold3
  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: 0.885
---

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# smids_3x_deit_small_sgd_001_fold3

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: 0.2981
- Accuracy: 0.885

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.8586        | 1.0   | 225   | 0.8598          | 0.645    |
| 0.6573        | 2.0   | 450   | 0.6819          | 0.745    |
| 0.5284        | 3.0   | 675   | 0.5681          | 0.79     |
| 0.4678        | 4.0   | 900   | 0.5034          | 0.82     |
| 0.4555        | 5.0   | 1125  | 0.4634          | 0.835    |
| 0.3848        | 6.0   | 1350  | 0.4333          | 0.8467   |
| 0.3445        | 7.0   | 1575  | 0.4134          | 0.85     |
| 0.3821        | 8.0   | 1800  | 0.3974          | 0.8533   |
| 0.3848        | 9.0   | 2025  | 0.3892          | 0.86     |
| 0.352         | 10.0  | 2250  | 0.3850          | 0.8483   |
| 0.3444        | 11.0  | 2475  | 0.3683          | 0.86     |
| 0.3393        | 12.0  | 2700  | 0.3678          | 0.8583   |
| 0.3465        | 13.0  | 2925  | 0.3528          | 0.865    |
| 0.3329        | 14.0  | 3150  | 0.3471          | 0.865    |
| 0.2839        | 15.0  | 3375  | 0.3437          | 0.865    |
| 0.3134        | 16.0  | 3600  | 0.3375          | 0.865    |
| 0.3254        | 17.0  | 3825  | 0.3357          | 0.865    |
| 0.2941        | 18.0  | 4050  | 0.3300          | 0.8717   |
| 0.2779        | 19.0  | 4275  | 0.3259          | 0.8767   |
| 0.2907        | 20.0  | 4500  | 0.3243          | 0.88     |
| 0.2541        | 21.0  | 4725  | 0.3245          | 0.875    |
| 0.2729        | 22.0  | 4950  | 0.3234          | 0.8717   |
| 0.2394        | 23.0  | 5175  | 0.3164          | 0.8867   |
| 0.24          | 24.0  | 5400  | 0.3164          | 0.8767   |
| 0.2295        | 25.0  | 5625  | 0.3132          | 0.8783   |
| 0.2317        | 26.0  | 5850  | 0.3134          | 0.8767   |
| 0.2077        | 27.0  | 6075  | 0.3127          | 0.875    |
| 0.2292        | 28.0  | 6300  | 0.3093          | 0.885    |
| 0.2441        | 29.0  | 6525  | 0.3091          | 0.885    |
| 0.2145        | 30.0  | 6750  | 0.3086          | 0.8767   |
| 0.2324        | 31.0  | 6975  | 0.3048          | 0.8833   |
| 0.2227        | 32.0  | 7200  | 0.3048          | 0.8817   |
| 0.245         | 33.0  | 7425  | 0.3041          | 0.8833   |
| 0.214         | 34.0  | 7650  | 0.3030          | 0.8833   |
| 0.1813        | 35.0  | 7875  | 0.3036          | 0.8817   |
| 0.2664        | 36.0  | 8100  | 0.3024          | 0.8833   |
| 0.1941        | 37.0  | 8325  | 0.3004          | 0.8883   |
| 0.2199        | 38.0  | 8550  | 0.3022          | 0.8833   |
| 0.2069        | 39.0  | 8775  | 0.2984          | 0.885    |
| 0.1869        | 40.0  | 9000  | 0.2998          | 0.8833   |
| 0.2101        | 41.0  | 9225  | 0.2995          | 0.8833   |
| 0.2258        | 42.0  | 9450  | 0.2989          | 0.8883   |
| 0.2128        | 43.0  | 9675  | 0.2987          | 0.8867   |
| 0.2283        | 44.0  | 9900  | 0.2982          | 0.8867   |
| 0.2441        | 45.0  | 10125 | 0.2992          | 0.8833   |
| 0.1971        | 46.0  | 10350 | 0.2984          | 0.885    |
| 0.221         | 47.0  | 10575 | 0.2978          | 0.8867   |
| 0.2053        | 48.0  | 10800 | 0.2980          | 0.885    |
| 0.2465        | 49.0  | 11025 | 0.2980          | 0.885    |
| 0.2188        | 50.0  | 11250 | 0.2981          | 0.885    |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.0+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2
