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_001_fold4
  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: 0.9285714285714286
---

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# hushem_40x_deit_base_sgd_001_fold4

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: 0.2186
- Accuracy: 0.9286

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.2742        | 1.0   | 219   | 1.3421          | 0.4286   |
| 1.1364        | 2.0   | 438   | 1.2693          | 0.4048   |
| 0.9912        | 3.0   | 657   | 1.1701          | 0.5238   |
| 0.8292        | 4.0   | 876   | 1.0493          | 0.6429   |
| 0.7771        | 5.0   | 1095  | 0.9148          | 0.7143   |
| 0.6956        | 6.0   | 1314  | 0.8048          | 0.7381   |
| 0.519         | 7.0   | 1533  | 0.7062          | 0.8095   |
| 0.5042        | 8.0   | 1752  | 0.6401          | 0.7857   |
| 0.4397        | 9.0   | 1971  | 0.5785          | 0.8333   |
| 0.3933        | 10.0  | 2190  | 0.5338          | 0.8571   |
| 0.341         | 11.0  | 2409  | 0.4959          | 0.8810   |
| 0.3345        | 12.0  | 2628  | 0.4569          | 0.8810   |
| 0.2949        | 13.0  | 2847  | 0.4265          | 0.9048   |
| 0.2608        | 14.0  | 3066  | 0.3999          | 0.9286   |
| 0.2368        | 15.0  | 3285  | 0.3796          | 0.9286   |
| 0.2257        | 16.0  | 3504  | 0.3614          | 0.9286   |
| 0.232         | 17.0  | 3723  | 0.3430          | 0.9286   |
| 0.1928        | 18.0  | 3942  | 0.3249          | 0.9286   |
| 0.1804        | 19.0  | 4161  | 0.3144          | 0.9286   |
| 0.1542        | 20.0  | 4380  | 0.3019          | 0.9048   |
| 0.1333        | 21.0  | 4599  | 0.2915          | 0.9286   |
| 0.1333        | 22.0  | 4818  | 0.2894          | 0.9048   |
| 0.1178        | 23.0  | 5037  | 0.2746          | 0.9286   |
| 0.1098        | 24.0  | 5256  | 0.2771          | 0.9048   |
| 0.1099        | 25.0  | 5475  | 0.2649          | 0.9048   |
| 0.0836        | 26.0  | 5694  | 0.2732          | 0.9048   |
| 0.0751        | 27.0  | 5913  | 0.2625          | 0.9048   |
| 0.0745        | 28.0  | 6132  | 0.2608          | 0.9048   |
| 0.0826        | 29.0  | 6351  | 0.2526          | 0.9048   |
| 0.079         | 30.0  | 6570  | 0.2463          | 0.9286   |
| 0.0659        | 31.0  | 6789  | 0.2439          | 0.9048   |
| 0.0738        | 32.0  | 7008  | 0.2422          | 0.9286   |
| 0.0683        | 33.0  | 7227  | 0.2335          | 0.9286   |
| 0.0674        | 34.0  | 7446  | 0.2343          | 0.9048   |
| 0.0633        | 35.0  | 7665  | 0.2311          | 0.9048   |
| 0.0608        | 36.0  | 7884  | 0.2259          | 0.9286   |
| 0.0543        | 37.0  | 8103  | 0.2239          | 0.9286   |
| 0.0444        | 38.0  | 8322  | 0.2256          | 0.9286   |
| 0.0496        | 39.0  | 8541  | 0.2255          | 0.9286   |
| 0.0513        | 40.0  | 8760  | 0.2253          | 0.9286   |
| 0.0449        | 41.0  | 8979  | 0.2226          | 0.9286   |
| 0.0449        | 42.0  | 9198  | 0.2216          | 0.9286   |
| 0.0549        | 43.0  | 9417  | 0.2202          | 0.9286   |
| 0.0488        | 44.0  | 9636  | 0.2213          | 0.9286   |
| 0.0437        | 45.0  | 9855  | 0.2208          | 0.9286   |
| 0.0362        | 46.0  | 10074 | 0.2201          | 0.9286   |
| 0.0622        | 47.0  | 10293 | 0.2188          | 0.9286   |
| 0.0546        | 48.0  | 10512 | 0.2185          | 0.9286   |
| 0.0472        | 49.0  | 10731 | 0.2186          | 0.9286   |
| 0.0581        | 50.0  | 10950 | 0.2186          | 0.9286   |


### Framework versions

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