transformers tensorboard safetensors 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_5x_deit_base_sgd_0001_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: 0.16666666666666666
---

<!-- 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_5x_deit_base_sgd_0001_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: 1.3872
- Accuracy: 0.1667

## 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: 0.0001
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4331        | 1.0   | 28   | 1.4140          | 0.1429   |
| 1.407         | 2.0   | 56   | 1.4126          | 0.1667   |
| 1.4098        | 3.0   | 84   | 1.4112          | 0.1667   |
| 1.4223        | 4.0   | 112  | 1.4100          | 0.1905   |
| 1.4411        | 5.0   | 140  | 1.4087          | 0.1905   |
| 1.4173        | 6.0   | 168  | 1.4075          | 0.1905   |
| 1.4276        | 7.0   | 196  | 1.4064          | 0.1905   |
| 1.4071        | 8.0   | 224  | 1.4054          | 0.1905   |
| 1.3997        | 9.0   | 252  | 1.4043          | 0.1905   |
| 1.3965        | 10.0  | 280  | 1.4034          | 0.1905   |
| 1.3989        | 11.0  | 308  | 1.4024          | 0.1667   |
| 1.3964        | 12.0  | 336  | 1.4014          | 0.1667   |
| 1.3857        | 13.0  | 364  | 1.4005          | 0.1667   |
| 1.3798        | 14.0  | 392  | 1.3997          | 0.1667   |
| 1.3951        | 15.0  | 420  | 1.3990          | 0.1667   |
| 1.4132        | 16.0  | 448  | 1.3982          | 0.1667   |
| 1.4034        | 17.0  | 476  | 1.3975          | 0.1667   |
| 1.3759        | 18.0  | 504  | 1.3968          | 0.1667   |
| 1.3925        | 19.0  | 532  | 1.3961          | 0.1667   |
| 1.3819        | 20.0  | 560  | 1.3955          | 0.1667   |
| 1.3696        | 21.0  | 588  | 1.3949          | 0.1667   |
| 1.369         | 22.0  | 616  | 1.3944          | 0.1667   |
| 1.3858        | 23.0  | 644  | 1.3938          | 0.1667   |
| 1.3737        | 24.0  | 672  | 1.3933          | 0.1905   |
| 1.3918        | 25.0  | 700  | 1.3928          | 0.1905   |
| 1.383         | 26.0  | 728  | 1.3923          | 0.1905   |
| 1.3591        | 27.0  | 756  | 1.3919          | 0.1905   |
| 1.373         | 28.0  | 784  | 1.3914          | 0.1905   |
| 1.3774        | 29.0  | 812  | 1.3910          | 0.1905   |
| 1.4107        | 30.0  | 840  | 1.3906          | 0.1905   |
| 1.3774        | 31.0  | 868  | 1.3903          | 0.1905   |
| 1.372         | 32.0  | 896  | 1.3899          | 0.1905   |
| 1.3576        | 33.0  | 924  | 1.3896          | 0.1905   |
| 1.3584        | 34.0  | 952  | 1.3892          | 0.1905   |
| 1.3749        | 35.0  | 980  | 1.3889          | 0.1905   |
| 1.3548        | 36.0  | 1008 | 1.3887          | 0.1905   |
| 1.3718        | 37.0  | 1036 | 1.3884          | 0.1905   |
| 1.3762        | 38.0  | 1064 | 1.3882          | 0.1667   |
| 1.367         | 39.0  | 1092 | 1.3880          | 0.1667   |
| 1.3764        | 40.0  | 1120 | 1.3878          | 0.1667   |
| 1.3651        | 41.0  | 1148 | 1.3877          | 0.1667   |
| 1.3606        | 42.0  | 1176 | 1.3876          | 0.1667   |
| 1.3658        | 43.0  | 1204 | 1.3874          | 0.1667   |
| 1.3704        | 44.0  | 1232 | 1.3874          | 0.1667   |
| 1.3557        | 45.0  | 1260 | 1.3873          | 0.1667   |
| 1.3731        | 46.0  | 1288 | 1.3872          | 0.1667   |
| 1.3663        | 47.0  | 1316 | 1.3872          | 0.1667   |
| 1.3426        | 48.0  | 1344 | 1.3872          | 0.1667   |
| 1.3656        | 49.0  | 1372 | 1.3872          | 0.1667   |
| 1.3695        | 50.0  | 1400 | 1.3872          | 0.1667   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
