---
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-fold3
  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-fold3

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: 0.4529
- 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    | 0.8367          | 0.4051   |
| No log        | 2.0     | 7    | 0.7223          | 0.4557   |
| 0.7025        | 2.8571  | 10   | 0.7199          | 0.4684   |
| 0.7025        | 4.0     | 14   | 0.6096          | 0.7089   |
| 0.7025        | 4.8571  | 17   | 0.6278          | 0.5823   |
| 0.6356        | 6.0     | 21   | 0.5629          | 0.7089   |
| 0.6356        | 6.8571  | 24   | 0.5924          | 0.6835   |
| 0.6356        | 8.0     | 28   | 0.5365          | 0.7722   |
| 0.5493        | 8.8571  | 31   | 0.6082          | 0.6329   |
| 0.5493        | 10.0    | 35   | 0.7239          | 0.5949   |
| 0.5493        | 10.8571 | 38   | 0.5435          | 0.7722   |
| 0.5205        | 12.0    | 42   | 0.8530          | 0.5570   |
| 0.5205        | 12.8571 | 45   | 0.5530          | 0.6709   |
| 0.5205        | 14.0    | 49   | 0.4728          | 0.7722   |
| 0.4979        | 14.8571 | 52   | 0.9571          | 0.5570   |
| 0.4979        | 16.0    | 56   | 0.5193          | 0.7722   |
| 0.4979        | 16.8571 | 59   | 0.4529          | 0.8228   |
| 0.4957        | 18.0    | 63   | 0.4686          | 0.7975   |
| 0.4957        | 18.8571 | 66   | 0.5060          | 0.7722   |
| 0.3659        | 20.0    | 70   | 0.4821          | 0.7848   |
| 0.3659        | 20.8571 | 73   | 0.6116          | 0.7089   |
| 0.3659        | 22.0    | 77   | 0.5860          | 0.7215   |
| 0.2973        | 22.8571 | 80   | 0.7100          | 0.7089   |
| 0.2973        | 24.0    | 84   | 0.6446          | 0.7342   |
| 0.2973        | 24.8571 | 87   | 0.6294          | 0.7342   |
| 0.2647        | 26.0    | 91   | 0.5988          | 0.7342   |
| 0.2647        | 26.8571 | 94   | 0.5256          | 0.7342   |
| 0.2647        | 28.0    | 98   | 0.6628          | 0.7595   |
| 0.2527        | 28.8571 | 101  | 0.5054          | 0.7595   |
| 0.2527        | 30.0    | 105  | 0.7632          | 0.7595   |
| 0.2527        | 30.8571 | 108  | 0.5917          | 0.7848   |
| 0.2176        | 32.0    | 112  | 0.5293          | 0.7848   |
| 0.2176        | 32.8571 | 115  | 0.6048          | 0.7468   |
| 0.2176        | 34.0    | 119  | 0.5710          | 0.7468   |
| 0.1633        | 34.8571 | 122  | 0.5901          | 0.7595   |
| 0.1633        | 36.0    | 126  | 0.8161          | 0.7468   |
| 0.1633        | 36.8571 | 129  | 0.7202          | 0.7468   |
| 0.1753        | 38.0    | 133  | 0.8239          | 0.7215   |
| 0.1753        | 38.8571 | 136  | 0.8908          | 0.7215   |
| 0.1743        | 40.0    | 140  | 0.8519          | 0.7342   |
| 0.1743        | 40.8571 | 143  | 1.0071          | 0.7215   |
| 0.1743        | 42.0    | 147  | 0.7842          | 0.7342   |
| 0.1532        | 42.8571 | 150  | 0.7827          | 0.7089   |
| 0.1532        | 44.0    | 154  | 0.7150          | 0.7468   |
| 0.1532        | 44.8571 | 157  | 0.6905          | 0.7595   |
| 0.1526        | 46.0    | 161  | 0.9260          | 0.7089   |
| 0.1526        | 46.8571 | 164  | 0.7933          | 0.7595   |
| 0.1526        | 48.0    | 168  | 0.8580          | 0.7468   |
| 0.1519        | 48.8571 | 171  | 0.6899          | 0.7975   |
| 0.1519        | 50.0    | 175  | 0.7069          | 0.7848   |
| 0.1519        | 50.8571 | 178  | 0.6741          | 0.7595   |
| 0.1292        | 52.0    | 182  | 0.7183          | 0.7848   |
| 0.1292        | 52.8571 | 185  | 0.8051          | 0.7468   |
| 0.1292        | 54.0    | 189  | 0.6883          | 0.7722   |
| 0.1305        | 54.8571 | 192  | 0.8266          | 0.7468   |
| 0.1305        | 56.0    | 196  | 1.0871          | 0.7595   |
| 0.1305        | 56.8571 | 199  | 0.7595          | 0.7595   |
| 0.1129        | 58.0    | 203  | 0.6880          | 0.7595   |
| 0.1129        | 58.8571 | 206  | 1.0676          | 0.7595   |
| 0.1369        | 60.0    | 210  | 0.8078          | 0.7595   |
| 0.1369        | 60.8571 | 213  | 0.7850          | 0.7595   |
| 0.1369        | 62.0    | 217  | 0.6975          | 0.7722   |
| 0.127         | 62.8571 | 220  | 0.7212          | 0.7595   |
| 0.127         | 64.0    | 224  | 0.8967          | 0.7468   |
| 0.127         | 64.8571 | 227  | 1.0046          | 0.7595   |
| 0.1238        | 66.0    | 231  | 0.8611          | 0.7342   |
| 0.1238        | 66.8571 | 234  | 0.9676          | 0.7975   |
| 0.1238        | 68.0    | 238  | 1.3115          | 0.7215   |
| 0.1068        | 68.8571 | 241  | 1.0992          | 0.7468   |
| 0.1068        | 70.0    | 245  | 0.8765          | 0.7848   |
| 0.1068        | 70.8571 | 248  | 0.8510          | 0.7848   |
| 0.1019        | 72.0    | 252  | 0.7403          | 0.7975   |
| 0.1019        | 72.8571 | 255  | 0.7459          | 0.7975   |
| 0.1019        | 74.0    | 259  | 0.7705          | 0.7975   |
| 0.1002        | 74.8571 | 262  | 0.7535          | 0.7975   |
| 0.1002        | 76.0    | 266  | 0.7124          | 0.7722   |
| 0.1002        | 76.8571 | 269  | 0.7014          | 0.7342   |
| 0.1222        | 78.0    | 273  | 0.8068          | 0.7722   |
| 0.1222        | 78.8571 | 276  | 0.9451          | 0.7722   |
| 0.1091        | 80.0    | 280  | 1.0048          | 0.7848   |
| 0.1091        | 80.8571 | 283  | 0.9518          | 0.7722   |
| 0.1091        | 82.0    | 287  | 0.8575          | 0.7848   |
| 0.0957        | 82.8571 | 290  | 0.8441          | 0.7848   |
| 0.0957        | 84.0    | 294  | 0.8602          | 0.7848   |
| 0.0957        | 84.8571 | 297  | 0.8701          | 0.7848   |
| 0.1111        | 85.7143 | 300  | 0.8731          | 0.7848   |


### Framework versions

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