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: smids_5x_deit_base_adamax_0001_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: 0.9181969949916527
---

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# smids_5x_deit_base_adamax_0001_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: 0.6997
- Accuracy: 0.9182

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.2162        | 1.0   | 376   | 0.2261          | 0.9082   |
| 0.1041        | 2.0   | 752   | 0.2663          | 0.8965   |
| 0.0837        | 3.0   | 1128  | 0.3441          | 0.9015   |
| 0.0172        | 4.0   | 1504  | 0.4099          | 0.9048   |
| 0.0131        | 5.0   | 1880  | 0.4724          | 0.9048   |
| 0.0004        | 6.0   | 2256  | 0.4925          | 0.9065   |
| 0.0017        | 7.0   | 2632  | 0.6831          | 0.8965   |
| 0.0006        | 8.0   | 3008  | 0.5273          | 0.9015   |
| 0.0324        | 9.0   | 3384  | 0.5755          | 0.8998   |
| 0.0           | 10.0  | 3760  | 0.6569          | 0.9048   |
| 0.0009        | 11.0  | 4136  | 0.5873          | 0.9082   |
| 0.0003        | 12.0  | 4512  | 0.6069          | 0.9065   |
| 0.0           | 13.0  | 4888  | 0.5862          | 0.9082   |
| 0.0063        | 14.0  | 5264  | 0.6445          | 0.9048   |
| 0.0           | 15.0  | 5640  | 0.6277          | 0.9132   |
| 0.0           | 16.0  | 6016  | 0.7053          | 0.9032   |
| 0.0           | 17.0  | 6392  | 0.6033          | 0.9098   |
| 0.0           | 18.0  | 6768  | 0.6638          | 0.9065   |
| 0.0           | 19.0  | 7144  | 0.6432          | 0.9082   |
| 0.004         | 20.0  | 7520  | 0.6467          | 0.9115   |
| 0.0           | 21.0  | 7896  | 0.7009          | 0.9115   |
| 0.0           | 22.0  | 8272  | 0.7221          | 0.9048   |
| 0.0           | 23.0  | 8648  | 0.6516          | 0.9149   |
| 0.0           | 24.0  | 9024  | 0.6399          | 0.9149   |
| 0.0           | 25.0  | 9400  | 0.6382          | 0.9182   |
| 0.0034        | 26.0  | 9776  | 0.6520          | 0.9098   |
| 0.0           | 27.0  | 10152 | 0.6761          | 0.9115   |
| 0.0           | 28.0  | 10528 | 0.6436          | 0.9182   |
| 0.003         | 29.0  | 10904 | 0.6339          | 0.9115   |
| 0.0041        | 30.0  | 11280 | 0.6392          | 0.9132   |
| 0.0           | 31.0  | 11656 | 0.6548          | 0.9182   |
| 0.0           | 32.0  | 12032 | 0.6680          | 0.9149   |
| 0.0           | 33.0  | 12408 | 0.6562          | 0.9115   |
| 0.0           | 34.0  | 12784 | 0.6705          | 0.9165   |
| 0.0           | 35.0  | 13160 | 0.6801          | 0.9098   |
| 0.0           | 36.0  | 13536 | 0.6653          | 0.9182   |
| 0.0           | 37.0  | 13912 | 0.6565          | 0.9165   |
| 0.0           | 38.0  | 14288 | 0.6618          | 0.9215   |
| 0.0           | 39.0  | 14664 | 0.6597          | 0.9149   |
| 0.0           | 40.0  | 15040 | 0.6689          | 0.9165   |
| 0.0           | 41.0  | 15416 | 0.6826          | 0.9149   |
| 0.0           | 42.0  | 15792 | 0.6835          | 0.9132   |
| 0.0           | 43.0  | 16168 | 0.6862          | 0.9149   |
| 0.0           | 44.0  | 16544 | 0.6860          | 0.9182   |
| 0.0           | 45.0  | 16920 | 0.6904          | 0.9182   |
| 0.0027        | 46.0  | 17296 | 0.6967          | 0.9132   |
| 0.0           | 47.0  | 17672 | 0.6971          | 0.9182   |
| 0.0           | 48.0  | 18048 | 0.6989          | 0.9182   |
| 0.0           | 49.0  | 18424 | 0.7000          | 0.9182   |
| 0.0022        | 50.0  | 18800 | 0.6997          | 0.9182   |


### Framework versions

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