transformers pytorch vit image-classification generated_from_trainer dataset:imagefolder base_model:facebook/deit-small-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: facebook/deit-small-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_40x_deit_small_adamax_00001_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_small_adamax_00001_fold4

This model is a fine-tuned version of [facebook/deit-small-patch16-224](https://huggingface.co/facebook/deit-small-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4871
- 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: 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.3231        | 1.0   | 219   | 0.5052          | 0.8333   |
| 0.0379        | 2.0   | 438   | 0.1942          | 0.9524   |
| 0.0035        | 3.0   | 657   | 0.1985          | 0.9524   |
| 0.0013        | 4.0   | 876   | 0.1951          | 0.9524   |
| 0.0011        | 5.0   | 1095  | 0.2264          | 0.9524   |
| 0.0004        | 6.0   | 1314  | 0.2512          | 0.9286   |
| 0.0002        | 7.0   | 1533  | 0.2460          | 0.9286   |
| 0.0002        | 8.0   | 1752  | 0.2596          | 0.9286   |
| 0.0001        | 9.0   | 1971  | 0.2767          | 0.9286   |
| 0.0001        | 10.0  | 2190  | 0.2928          | 0.9286   |
| 0.0001        | 11.0  | 2409  | 0.2970          | 0.9286   |
| 0.0001        | 12.0  | 2628  | 0.2820          | 0.9286   |
| 0.0001        | 13.0  | 2847  | 0.3043          | 0.9286   |
| 0.0           | 14.0  | 3066  | 0.3118          | 0.9286   |
| 0.0           | 15.0  | 3285  | 0.3261          | 0.9286   |
| 0.0           | 16.0  | 3504  | 0.3432          | 0.9286   |
| 0.0           | 17.0  | 3723  | 0.3644          | 0.9286   |
| 0.0           | 18.0  | 3942  | 0.3650          | 0.9286   |
| 0.0           | 19.0  | 4161  | 0.3445          | 0.9286   |
| 0.0           | 20.0  | 4380  | 0.3724          | 0.9286   |
| 0.0           | 21.0  | 4599  | 0.3804          | 0.9286   |
| 0.0           | 22.0  | 4818  | 0.3614          | 0.9286   |
| 0.0           | 23.0  | 5037  | 0.3623          | 0.9286   |
| 0.0           | 24.0  | 5256  | 0.3788          | 0.9286   |
| 0.0           | 25.0  | 5475  | 0.3915          | 0.9286   |
| 0.0           | 26.0  | 5694  | 0.3845          | 0.9286   |
| 0.0           | 27.0  | 5913  | 0.4164          | 0.9286   |
| 0.0           | 28.0  | 6132  | 0.4005          | 0.9286   |
| 0.0           | 29.0  | 6351  | 0.4219          | 0.9286   |
| 0.0           | 30.0  | 6570  | 0.4046          | 0.9286   |
| 0.0           | 31.0  | 6789  | 0.4132          | 0.9286   |
| 0.0           | 32.0  | 7008  | 0.4320          | 0.9286   |
| 0.0           | 33.0  | 7227  | 0.4247          | 0.9286   |
| 0.0           | 34.0  | 7446  | 0.4486          | 0.9286   |
| 0.0           | 35.0  | 7665  | 0.4281          | 0.9286   |
| 0.0           | 36.0  | 7884  | 0.4371          | 0.9286   |
| 0.0           | 37.0  | 8103  | 0.4603          | 0.9286   |
| 0.0           | 38.0  | 8322  | 0.4397          | 0.9286   |
| 0.0           | 39.0  | 8541  | 0.4445          | 0.9286   |
| 0.0           | 40.0  | 8760  | 0.4589          | 0.9286   |
| 0.0           | 41.0  | 8979  | 0.4480          | 0.9286   |
| 0.0           | 42.0  | 9198  | 0.4530          | 0.9286   |
| 0.0           | 43.0  | 9417  | 0.4708          | 0.9286   |
| 0.0           | 44.0  | 9636  | 0.4852          | 0.9286   |
| 0.0           | 45.0  | 9855  | 0.4662          | 0.9286   |
| 0.0           | 46.0  | 10074 | 0.4885          | 0.9286   |
| 0.0           | 47.0  | 10293 | 0.4916          | 0.9286   |
| 0.0           | 48.0  | 10512 | 0.4924          | 0.9286   |
| 0.0           | 49.0  | 10731 | 0.4929          | 0.9286   |
| 0.0           | 50.0  | 10950 | 0.4871          | 0.9286   |


### Framework versions

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