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_fold3
  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: 0.3488372093023256
---

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# hushem_5x_deit_base_sgd_0001_fold3

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: 1.3613
- Accuracy: 0.3488

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4194        | 1.0   | 28   | 1.3854          | 0.3721   |
| 1.4285        | 2.0   | 56   | 1.3841          | 0.3721   |
| 1.4355        | 3.0   | 84   | 1.3830          | 0.3721   |
| 1.435         | 4.0   | 112  | 1.3819          | 0.3721   |
| 1.3846        | 5.0   | 140  | 1.3808          | 0.3488   |
| 1.4335        | 6.0   | 168  | 1.3798          | 0.3488   |
| 1.4069        | 7.0   | 196  | 1.3789          | 0.3488   |
| 1.4319        | 8.0   | 224  | 1.3779          | 0.3488   |
| 1.4012        | 9.0   | 252  | 1.3769          | 0.3488   |
| 1.401         | 10.0  | 280  | 1.3761          | 0.3488   |
| 1.4013        | 11.0  | 308  | 1.3752          | 0.3488   |
| 1.4057        | 12.0  | 336  | 1.3744          | 0.3488   |
| 1.3918        | 13.0  | 364  | 1.3736          | 0.3488   |
| 1.3961        | 14.0  | 392  | 1.3729          | 0.3721   |
| 1.3654        | 15.0  | 420  | 1.3722          | 0.3721   |
| 1.3967        | 16.0  | 448  | 1.3715          | 0.3488   |
| 1.3921        | 17.0  | 476  | 1.3708          | 0.3488   |
| 1.3819        | 18.0  | 504  | 1.3702          | 0.3488   |
| 1.3847        | 19.0  | 532  | 1.3696          | 0.3488   |
| 1.402         | 20.0  | 560  | 1.3690          | 0.3488   |
| 1.3988        | 21.0  | 588  | 1.3684          | 0.3488   |
| 1.3796        | 22.0  | 616  | 1.3679          | 0.3488   |
| 1.3761        | 23.0  | 644  | 1.3674          | 0.3721   |
| 1.3729        | 24.0  | 672  | 1.3669          | 0.3721   |
| 1.3864        | 25.0  | 700  | 1.3664          | 0.3488   |
| 1.3808        | 26.0  | 728  | 1.3660          | 0.3488   |
| 1.3849        | 27.0  | 756  | 1.3656          | 0.3488   |
| 1.3863        | 28.0  | 784  | 1.3652          | 0.3488   |
| 1.3673        | 29.0  | 812  | 1.3648          | 0.3488   |
| 1.3797        | 30.0  | 840  | 1.3644          | 0.3488   |
| 1.3679        | 31.0  | 868  | 1.3641          | 0.3488   |
| 1.3844        | 32.0  | 896  | 1.3638          | 0.3488   |
| 1.3656        | 33.0  | 924  | 1.3634          | 0.3488   |
| 1.3701        | 34.0  | 952  | 1.3631          | 0.3488   |
| 1.363         | 35.0  | 980  | 1.3629          | 0.3488   |
| 1.386         | 36.0  | 1008 | 1.3627          | 0.3488   |
| 1.3733        | 37.0  | 1036 | 1.3624          | 0.3488   |
| 1.3666        | 38.0  | 1064 | 1.3622          | 0.3488   |
| 1.3489        | 39.0  | 1092 | 1.3620          | 0.3488   |
| 1.3854        | 40.0  | 1120 | 1.3619          | 0.3488   |
| 1.3831        | 41.0  | 1148 | 1.3617          | 0.3488   |
| 1.3627        | 42.0  | 1176 | 1.3616          | 0.3488   |
| 1.3753        | 43.0  | 1204 | 1.3615          | 0.3488   |
| 1.3596        | 44.0  | 1232 | 1.3614          | 0.3488   |
| 1.3572        | 45.0  | 1260 | 1.3614          | 0.3488   |
| 1.3678        | 46.0  | 1288 | 1.3613          | 0.3488   |
| 1.3744        | 47.0  | 1316 | 1.3613          | 0.3488   |
| 1.3693        | 48.0  | 1344 | 1.3613          | 0.3488   |
| 1.3589        | 49.0  | 1372 | 1.3613          | 0.3488   |
| 1.3662        | 50.0  | 1400 | 1.3613          | 0.3488   |


### Framework versions

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