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_fold2
  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: 0.3111111111111111
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# hushem_40x_deit_base_sgd_00001_fold2

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: 1.3898
- Accuracy: 0.3111

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.4168        | 1.0   | 215   | 1.4077          | 0.2444   |
| 1.3843        | 2.0   | 430   | 1.4068          | 0.2444   |
| 1.4045        | 3.0   | 645   | 1.4059          | 0.2444   |
| 1.3944        | 4.0   | 860   | 1.4051          | 0.2444   |
| 1.3979        | 5.0   | 1075  | 1.4043          | 0.2444   |
| 1.4212        | 6.0   | 1290  | 1.4036          | 0.2667   |
| 1.4197        | 7.0   | 1505  | 1.4029          | 0.2667   |
| 1.369         | 8.0   | 1720  | 1.4022          | 0.2667   |
| 1.3853        | 9.0   | 1935  | 1.4015          | 0.2667   |
| 1.4053        | 10.0  | 2150  | 1.4008          | 0.2667   |
| 1.3723        | 11.0  | 2365  | 1.4002          | 0.2667   |
| 1.3571        | 12.0  | 2580  | 1.3996          | 0.2667   |
| 1.3936        | 13.0  | 2795  | 1.3990          | 0.2667   |
| 1.3779        | 14.0  | 3010  | 1.3985          | 0.2667   |
| 1.3861        | 15.0  | 3225  | 1.3979          | 0.2667   |
| 1.4005        | 16.0  | 3440  | 1.3974          | 0.2889   |
| 1.3769        | 17.0  | 3655  | 1.3969          | 0.2889   |
| 1.3909        | 18.0  | 3870  | 1.3964          | 0.2889   |
| 1.3834        | 19.0  | 4085  | 1.3960          | 0.2889   |
| 1.3642        | 20.0  | 4300  | 1.3956          | 0.2889   |
| 1.3863        | 21.0  | 4515  | 1.3951          | 0.2889   |
| 1.3863        | 22.0  | 4730  | 1.3947          | 0.2889   |
| 1.3703        | 23.0  | 4945  | 1.3944          | 0.2889   |
| 1.3733        | 24.0  | 5160  | 1.3940          | 0.2889   |
| 1.3751        | 25.0  | 5375  | 1.3937          | 0.3111   |
| 1.3799        | 26.0  | 5590  | 1.3933          | 0.3111   |
| 1.3637        | 27.0  | 5805  | 1.3930          | 0.3111   |
| 1.3658        | 28.0  | 6020  | 1.3927          | 0.3111   |
| 1.3837        | 29.0  | 6235  | 1.3924          | 0.3111   |
| 1.3573        | 30.0  | 6450  | 1.3922          | 0.3111   |
| 1.3483        | 31.0  | 6665  | 1.3919          | 0.3111   |
| 1.3737        | 32.0  | 6880  | 1.3917          | 0.3111   |
| 1.3567        | 33.0  | 7095  | 1.3915          | 0.3111   |
| 1.3764        | 34.0  | 7310  | 1.3913          | 0.3111   |
| 1.3646        | 35.0  | 7525  | 1.3911          | 0.3111   |
| 1.3557        | 36.0  | 7740  | 1.3909          | 0.3111   |
| 1.3829        | 37.0  | 7955  | 1.3907          | 0.3111   |
| 1.3713        | 38.0  | 8170  | 1.3906          | 0.3111   |
| 1.3468        | 39.0  | 8385  | 1.3905          | 0.3111   |
| 1.3527        | 40.0  | 8600  | 1.3903          | 0.3111   |
| 1.3629        | 41.0  | 8815  | 1.3902          | 0.3111   |
| 1.3464        | 42.0  | 9030  | 1.3901          | 0.3111   |
| 1.3709        | 43.0  | 9245  | 1.3901          | 0.3111   |
| 1.3524        | 44.0  | 9460  | 1.3900          | 0.3111   |
| 1.3532        | 45.0  | 9675  | 1.3899          | 0.3111   |
| 1.3657        | 46.0  | 9890  | 1.3899          | 0.3111   |
| 1.3891        | 47.0  | 10105 | 1.3899          | 0.3111   |
| 1.3666        | 48.0  | 10320 | 1.3898          | 0.3111   |
| 1.3713        | 49.0  | 10535 | 1.3898          | 0.3111   |
| 1.3614        | 50.0  | 10750 | 1.3898          | 0.3111   |


### Framework versions

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