---
license: apache-2.0
base_model: Visual-Attention-Network/van-tiny
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
- recall
- precision
model-index:
- name: teacher-status-van-tiny-256-0
  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: 0.9777777777777777
    - name: Recall
      type: recall
      value: 0.9893162393162394
    - name: Precision
      type: precision
      value: 0.9788583509513742
---

<!-- 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. -->

# teacher-status-van-tiny-256-0

This model is a fine-tuned version of [Visual-Attention-Network/van-tiny](https://huggingface.co/Visual-Attention-Network/van-tiny) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0672
- Accuracy: 0.9778
- F1 Score: 0.9841
- Recall: 0.9893
- Precision: 0.9789

## 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: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Score | Recall | Precision |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:------:|:---------:|
| 0.6788        | 0.99  | 47   | 0.6437          | 0.6933   | 0.8189   | 1.0    | 0.6933    |
| 0.463         | 2.0   | 95   | 0.3406          | 0.8756   | 0.9162   | 0.9808 | 0.8596    |
| 0.3596        | 2.99  | 142  | 0.2072          | 0.9304   | 0.9504   | 0.9615 | 0.9395    |
| 0.3505        | 4.0   | 190  | 0.1564          | 0.9526   | 0.9661   | 0.9744 | 0.9580    |
| 0.2962        | 4.99  | 237  | 0.1262          | 0.9556   | 0.9681   | 0.9722 | 0.9640    |
| 0.2762        | 6.0   | 285  | 0.1038          | 0.9644   | 0.9745   | 0.9808 | 0.9684    |
| 0.2604        | 6.99  | 332  | 0.0932          | 0.9719   | 0.9798   | 0.9829 | 0.9766    |
| 0.2427        | 8.0   | 380  | 0.0928          | 0.9719   | 0.9797   | 0.9786 | 0.9807    |
| 0.2465        | 8.99  | 427  | 0.0898          | 0.9719   | 0.9797   | 0.9786 | 0.9807    |
| 0.2519        | 10.0  | 475  | 0.0913          | 0.9689   | 0.9775   | 0.9765 | 0.9786    |
| 0.2258        | 10.99 | 522  | 0.0847          | 0.9733   | 0.9809   | 0.9872 | 0.9747    |
| 0.2184        | 12.0  | 570  | 0.0812          | 0.9793   | 0.9851   | 0.9893 | 0.9809    |
| 0.2208        | 12.99 | 617  | 0.0693          | 0.9807   | 0.9861   | 0.9872 | 0.9851    |
| 0.2201        | 14.0  | 665  | 0.0628          | 0.9763   | 0.9829   | 0.9850 | 0.9809    |
| 0.2251        | 14.99 | 712  | 0.0811          | 0.9733   | 0.9810   | 0.9915 | 0.9707    |
| 0.2135        | 16.0  | 760  | 0.0718          | 0.9763   | 0.9829   | 0.9850 | 0.9809    |
| 0.1851        | 16.99 | 807  | 0.0791          | 0.9763   | 0.9830   | 0.9872 | 0.9788    |
| 0.2152        | 18.0  | 855  | 0.0737          | 0.9748   | 0.9818   | 0.9808 | 0.9829    |
| 0.1871        | 18.99 | 902  | 0.0814          | 0.9763   | 0.9830   | 0.9872 | 0.9788    |
| 0.1714        | 20.0  | 950  | 0.0692          | 0.9763   | 0.9830   | 0.9893 | 0.9768    |
| 0.188         | 20.99 | 997  | 0.0641          | 0.9778   | 0.9840   | 0.9850 | 0.9829    |
| 0.191         | 22.0  | 1045 | 0.0644          | 0.9793   | 0.9851   | 0.9872 | 0.9830    |
| 0.2025        | 22.99 | 1092 | 0.0675          | 0.9793   | 0.9850   | 0.9829 | 0.9871    |
| 0.1753        | 24.0  | 1140 | 0.0655          | 0.9822   | 0.9872   | 0.9893 | 0.9851    |
| 0.1857        | 24.99 | 1187 | 0.0731          | 0.9793   | 0.9851   | 0.9915 | 0.9789    |
| 0.2007        | 26.0  | 1235 | 0.0677          | 0.9793   | 0.9851   | 0.9915 | 0.9789    |
| 0.2086        | 26.99 | 1282 | 0.0640          | 0.9793   | 0.9851   | 0.9893 | 0.9809    |
| 0.1666        | 28.0  | 1330 | 0.0712          | 0.9778   | 0.9841   | 0.9893 | 0.9789    |
| 0.157         | 28.99 | 1377 | 0.0661          | 0.9807   | 0.9862   | 0.9893 | 0.9830    |
| 0.1758        | 29.68 | 1410 | 0.0672          | 0.9778   | 0.9841   | 0.9893 | 0.9789    |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0