---
license: apache-2.0
base_model: facebook/deit-base-distilled-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: deit-base-distilled-patch16-224-55-fold5
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8227848101265823
---

<!-- 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. -->

# deit-base-distilled-patch16-224-55-fold5

This model is a fine-tuned version of [facebook/deit-base-distilled-patch16-224](https://huggingface.co/facebook/deit-base-distilled-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6452
- Accuracy: 0.8228

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 100

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| No log        | 0.8571  | 3    | 0.7319          | 0.5190   |
| No log        | 2.0     | 7    | 0.6756          | 0.5696   |
| 0.6544        | 2.8571  | 10   | 0.6199          | 0.6456   |
| 0.6544        | 4.0     | 14   | 0.5987          | 0.6203   |
| 0.6544        | 4.8571  | 17   | 0.5676          | 0.6709   |
| 0.6173        | 6.0     | 21   | 0.6543          | 0.5823   |
| 0.6173        | 6.8571  | 24   | 0.5310          | 0.7342   |
| 0.6173        | 8.0     | 28   | 0.6724          | 0.6076   |
| 0.5245        | 8.8571  | 31   | 0.6444          | 0.6582   |
| 0.5245        | 10.0    | 35   | 0.5027          | 0.7342   |
| 0.5245        | 10.8571 | 38   | 0.6328          | 0.6582   |
| 0.4554        | 12.0    | 42   | 0.4883          | 0.7595   |
| 0.4554        | 12.8571 | 45   | 0.6736          | 0.6582   |
| 0.4554        | 14.0    | 49   | 0.4584          | 0.7342   |
| 0.4575        | 14.8571 | 52   | 0.8099          | 0.6456   |
| 0.4575        | 16.0    | 56   | 0.4767          | 0.7468   |
| 0.4575        | 16.8571 | 59   | 0.6059          | 0.6835   |
| 0.3798        | 18.0    | 63   | 0.4863          | 0.7595   |
| 0.3798        | 18.8571 | 66   | 0.5636          | 0.7468   |
| 0.3419        | 20.0    | 70   | 0.4677          | 0.7342   |
| 0.3419        | 20.8571 | 73   | 0.4883          | 0.7089   |
| 0.3419        | 22.0    | 77   | 0.5549          | 0.7215   |
| 0.3079        | 22.8571 | 80   | 0.4324          | 0.7848   |
| 0.3079        | 24.0    | 84   | 0.6184          | 0.6709   |
| 0.3079        | 24.8571 | 87   | 0.6149          | 0.7089   |
| 0.2616        | 26.0    | 91   | 0.4488          | 0.7848   |
| 0.2616        | 26.8571 | 94   | 0.4368          | 0.7722   |
| 0.2616        | 28.0    | 98   | 0.4566          | 0.7722   |
| 0.2157        | 28.8571 | 101  | 0.4657          | 0.7848   |
| 0.2157        | 30.0    | 105  | 0.4514          | 0.7722   |
| 0.2157        | 30.8571 | 108  | 0.5083          | 0.7848   |
| 0.2258        | 32.0    | 112  | 0.5261          | 0.7848   |
| 0.2258        | 32.8571 | 115  | 0.5567          | 0.7595   |
| 0.2258        | 34.0    | 119  | 0.5566          | 0.8101   |
| 0.1972        | 34.8571 | 122  | 0.5495          | 0.8101   |
| 0.1972        | 36.0    | 126  | 0.4992          | 0.7975   |
| 0.1972        | 36.8571 | 129  | 0.5661          | 0.7595   |
| 0.1709        | 38.0    | 133  | 0.7326          | 0.7342   |
| 0.1709        | 38.8571 | 136  | 0.5635          | 0.8101   |
| 0.1537        | 40.0    | 140  | 0.8130          | 0.7468   |
| 0.1537        | 40.8571 | 143  | 0.6984          | 0.7848   |
| 0.1537        | 42.0    | 147  | 0.7777          | 0.7595   |
| 0.1687        | 42.8571 | 150  | 0.6452          | 0.8228   |
| 0.1687        | 44.0    | 154  | 0.8527          | 0.7215   |
| 0.1687        | 44.8571 | 157  | 0.6483          | 0.7975   |
| 0.1588        | 46.0    | 161  | 0.8185          | 0.7342   |
| 0.1588        | 46.8571 | 164  | 0.6821          | 0.7722   |
| 0.1588        | 48.0    | 168  | 0.7594          | 0.7342   |
| 0.144         | 48.8571 | 171  | 1.0232          | 0.7595   |
| 0.144         | 50.0    | 175  | 0.6178          | 0.7848   |
| 0.144         | 50.8571 | 178  | 0.6243          | 0.7595   |
| 0.1449        | 52.0    | 182  | 0.8159          | 0.7342   |
| 0.1449        | 52.8571 | 185  | 0.6664          | 0.7722   |
| 0.1449        | 54.0    | 189  | 0.7070          | 0.7342   |
| 0.144         | 54.8571 | 192  | 0.7361          | 0.7468   |
| 0.144         | 56.0    | 196  | 0.6656          | 0.7595   |
| 0.144         | 56.8571 | 199  | 0.7487          | 0.7468   |
| 0.1199        | 58.0    | 203  | 0.7993          | 0.7342   |
| 0.1199        | 58.8571 | 206  | 0.7426          | 0.7722   |
| 0.1258        | 60.0    | 210  | 0.7531          | 0.7975   |
| 0.1258        | 60.8571 | 213  | 0.7388          | 0.7848   |
| 0.1258        | 62.0    | 217  | 0.7395          | 0.7975   |
| 0.1392        | 62.8571 | 220  | 0.8238          | 0.7468   |
| 0.1392        | 64.0    | 224  | 0.9302          | 0.7215   |
| 0.1392        | 64.8571 | 227  | 0.7539          | 0.7722   |
| 0.1303        | 66.0    | 231  | 0.6739          | 0.8101   |
| 0.1303        | 66.8571 | 234  | 0.6627          | 0.7848   |
| 0.1303        | 68.0    | 238  | 0.6403          | 0.7848   |
| 0.1423        | 68.8571 | 241  | 0.6379          | 0.7975   |
| 0.1423        | 70.0    | 245  | 0.7658          | 0.7595   |
| 0.1423        | 70.8571 | 248  | 0.9195          | 0.7342   |
| 0.1019        | 72.0    | 252  | 0.7287          | 0.7722   |
| 0.1019        | 72.8571 | 255  | 0.6548          | 0.7975   |
| 0.1019        | 74.0    | 259  | 0.6534          | 0.7848   |
| 0.1286        | 74.8571 | 262  | 0.7331          | 0.7848   |
| 0.1286        | 76.0    | 266  | 0.7845          | 0.7595   |
| 0.1286        | 76.8571 | 269  | 0.7188          | 0.7975   |
| 0.1054        | 78.0    | 273  | 0.6595          | 0.7722   |
| 0.1054        | 78.8571 | 276  | 0.6623          | 0.7722   |
| 0.1053        | 80.0    | 280  | 0.7337          | 0.7722   |
| 0.1053        | 80.8571 | 283  | 0.8085          | 0.7468   |
| 0.1053        | 82.0    | 287  | 0.8201          | 0.7468   |
| 0.1086        | 82.8571 | 290  | 0.7947          | 0.7468   |
| 0.1086        | 84.0    | 294  | 0.7669          | 0.7722   |
| 0.1086        | 84.8571 | 297  | 0.7582          | 0.7595   |
| 0.1186        | 85.7143 | 300  | 0.7541          | 0.7595   |


### Framework versions

- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1