transformers pytorch vit image-classification generated_from_trainer dataset:imagefolder base_model:facebook/deit-base-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: facebook/deit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_40x_deit_base_sgd_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: 0.2682926829268293
---

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# hushem_40x_deit_base_sgd_00001_fold5

This model is a fine-tuned version of [facebook/deit-base-patch16-224](https://huggingface.co/facebook/deit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3600
- Accuracy: 0.2683

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.4054        | 1.0   | 220   | 1.3726          | 0.2683   |
| 1.4058        | 2.0   | 440   | 1.3720          | 0.2683   |
| 1.4165        | 3.0   | 660   | 1.3713          | 0.2683   |
| 1.3927        | 4.0   | 880   | 1.3707          | 0.2683   |
| 1.4116        | 5.0   | 1100  | 1.3701          | 0.2683   |
| 1.3812        | 6.0   | 1320  | 1.3696          | 0.2683   |
| 1.4048        | 7.0   | 1540  | 1.3690          | 0.2683   |
| 1.3591        | 8.0   | 1760  | 1.3685          | 0.2683   |
| 1.4052        | 9.0   | 1980  | 1.3680          | 0.2683   |
| 1.3882        | 10.0  | 2200  | 1.3676          | 0.2683   |
| 1.3863        | 11.0  | 2420  | 1.3671          | 0.2683   |
| 1.3965        | 12.0  | 2640  | 1.3667          | 0.2683   |
| 1.4035        | 13.0  | 2860  | 1.3663          | 0.2683   |
| 1.3813        | 14.0  | 3080  | 1.3659          | 0.2683   |
| 1.3758        | 15.0  | 3300  | 1.3655          | 0.2683   |
| 1.3822        | 16.0  | 3520  | 1.3651          | 0.2683   |
| 1.3951        | 17.0  | 3740  | 1.3648          | 0.2683   |
| 1.3934        | 18.0  | 3960  | 1.3645          | 0.2683   |
| 1.3858        | 19.0  | 4180  | 1.3642          | 0.2683   |
| 1.3848        | 20.0  | 4400  | 1.3639          | 0.2683   |
| 1.379         | 21.0  | 4620  | 1.3636          | 0.2683   |
| 1.3756        | 22.0  | 4840  | 1.3633          | 0.2683   |
| 1.3759        | 23.0  | 5060  | 1.3630          | 0.2683   |
| 1.3873        | 24.0  | 5280  | 1.3628          | 0.2683   |
| 1.3701        | 25.0  | 5500  | 1.3626          | 0.2683   |
| 1.3779        | 26.0  | 5720  | 1.3623          | 0.2683   |
| 1.3916        | 27.0  | 5940  | 1.3621          | 0.2683   |
| 1.3605        | 28.0  | 6160  | 1.3619          | 0.2927   |
| 1.3832        | 29.0  | 6380  | 1.3617          | 0.2927   |
| 1.3641        | 30.0  | 6600  | 1.3616          | 0.2927   |
| 1.3806        | 31.0  | 6820  | 1.3614          | 0.2927   |
| 1.3762        | 32.0  | 7040  | 1.3612          | 0.2927   |
| 1.3671        | 33.0  | 7260  | 1.3611          | 0.2683   |
| 1.3772        | 34.0  | 7480  | 1.3610          | 0.2683   |
| 1.3577        | 35.0  | 7700  | 1.3608          | 0.2683   |
| 1.3486        | 36.0  | 7920  | 1.3607          | 0.2683   |
| 1.3611        | 37.0  | 8140  | 1.3606          | 0.2683   |
| 1.355         | 38.0  | 8360  | 1.3605          | 0.2683   |
| 1.3682        | 39.0  | 8580  | 1.3604          | 0.2683   |
| 1.3669        | 40.0  | 8800  | 1.3603          | 0.2683   |
| 1.3585        | 41.0  | 9020  | 1.3603          | 0.2683   |
| 1.3549        | 42.0  | 9240  | 1.3602          | 0.2683   |
| 1.3669        | 43.0  | 9460  | 1.3602          | 0.2683   |
| 1.353         | 44.0  | 9680  | 1.3601          | 0.2683   |
| 1.3499        | 45.0  | 9900  | 1.3601          | 0.2683   |
| 1.3573        | 46.0  | 10120 | 1.3600          | 0.2683   |
| 1.384         | 47.0  | 10340 | 1.3600          | 0.2683   |
| 1.367         | 48.0  | 10560 | 1.3600          | 0.2683   |
| 1.3753        | 49.0  | 10780 | 1.3600          | 0.2683   |
| 1.3687        | 50.0  | 11000 | 1.3600          | 0.2683   |


### Framework versions

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