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_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: 0.28888888888888886
---

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# hushem_40x_deit_base_sgd_00001_fold1

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: 1.4455
- Accuracy: 0.2889

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.379         | 1.0   | 215   | 1.4681          | 0.2889   |
| 1.3967        | 2.0   | 430   | 1.4670          | 0.2889   |
| 1.423         | 3.0   | 645   | 1.4660          | 0.2889   |
| 1.4018        | 4.0   | 860   | 1.4650          | 0.2889   |
| 1.3899        | 5.0   | 1075  | 1.4640          | 0.2889   |
| 1.4076        | 6.0   | 1290  | 1.4631          | 0.2889   |
| 1.3743        | 7.0   | 1505  | 1.4622          | 0.2889   |
| 1.3724        | 8.0   | 1720  | 1.4613          | 0.2889   |
| 1.3757        | 9.0   | 1935  | 1.4604          | 0.2889   |
| 1.3783        | 10.0  | 2150  | 1.4596          | 0.2889   |
| 1.4141        | 11.0  | 2365  | 1.4589          | 0.2889   |
| 1.3702        | 12.0  | 2580  | 1.4581          | 0.2889   |
| 1.3842        | 13.0  | 2795  | 1.4574          | 0.2889   |
| 1.3926        | 14.0  | 3010  | 1.4567          | 0.2889   |
| 1.3764        | 15.0  | 3225  | 1.4560          | 0.2889   |
| 1.3955        | 16.0  | 3440  | 1.4553          | 0.2889   |
| 1.3752        | 17.0  | 3655  | 1.4547          | 0.2889   |
| 1.3872        | 18.0  | 3870  | 1.4541          | 0.2889   |
| 1.3795        | 19.0  | 4085  | 1.4535          | 0.2889   |
| 1.3768        | 20.0  | 4300  | 1.4530          | 0.2889   |
| 1.3609        | 21.0  | 4515  | 1.4524          | 0.2889   |
| 1.3552        | 22.0  | 4730  | 1.4519          | 0.2889   |
| 1.3869        | 23.0  | 4945  | 1.4514          | 0.2889   |
| 1.3741        | 24.0  | 5160  | 1.4510          | 0.2889   |
| 1.3721        | 25.0  | 5375  | 1.4505          | 0.2889   |
| 1.3593        | 26.0  | 5590  | 1.4501          | 0.2889   |
| 1.3536        | 27.0  | 5805  | 1.4497          | 0.2889   |
| 1.3543        | 28.0  | 6020  | 1.4493          | 0.2889   |
| 1.3589        | 29.0  | 6235  | 1.4489          | 0.2889   |
| 1.3445        | 30.0  | 6450  | 1.4486          | 0.2889   |
| 1.3539        | 31.0  | 6665  | 1.4483          | 0.2889   |
| 1.3535        | 32.0  | 6880  | 1.4480          | 0.2889   |
| 1.3498        | 33.0  | 7095  | 1.4477          | 0.2889   |
| 1.3497        | 34.0  | 7310  | 1.4474          | 0.2889   |
| 1.3582        | 35.0  | 7525  | 1.4472          | 0.2889   |
| 1.354         | 36.0  | 7740  | 1.4469          | 0.2889   |
| 1.3681        | 37.0  | 7955  | 1.4467          | 0.2889   |
| 1.346         | 38.0  | 8170  | 1.4465          | 0.2889   |
| 1.3468        | 39.0  | 8385  | 1.4463          | 0.2889   |
| 1.3488        | 40.0  | 8600  | 1.4462          | 0.2889   |
| 1.3542        | 41.0  | 8815  | 1.4460          | 0.2889   |
| 1.3813        | 42.0  | 9030  | 1.4459          | 0.2889   |
| 1.3585        | 43.0  | 9245  | 1.4458          | 0.2889   |
| 1.3347        | 44.0  | 9460  | 1.4457          | 0.2889   |
| 1.3527        | 45.0  | 9675  | 1.4456          | 0.2889   |
| 1.3601        | 46.0  | 9890  | 1.4456          | 0.2889   |
| 1.3484        | 47.0  | 10105 | 1.4455          | 0.2889   |
| 1.3543        | 48.0  | 10320 | 1.4455          | 0.2889   |
| 1.3639        | 49.0  | 10535 | 1.4455          | 0.2889   |
| 1.3697        | 50.0  | 10750 | 1.4455          | 0.2889   |


### Framework versions

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