---
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-256-2
  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: 0.9759358288770054
    - name: Recall
      type: recall
      value: 0.9756944444444444
    - name: Precision
      type: precision
      value: 0.9929328621908127
---

<!-- 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-256-2

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: 0.0916
- Accuracy: 0.9759
- F1 Score: 0.9842
- Recall: 0.9757
- Precision: 0.9929

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:------:|:---------:|
| 0.6896        | 0.99  | 26   | 0.6707          | 0.7701   | 0.8701   | 1.0    | 0.7701    |
| 0.5438        | 1.98  | 52   | 0.4302          | 0.7701   | 0.8701   | 1.0    | 0.7701    |
| 0.3756        | 2.97  | 78   | 0.2762          | 0.8850   | 0.9285   | 0.9688 | 0.8914    |
| 0.3017        | 4.0   | 105  | 0.2002          | 0.9225   | 0.9503   | 0.9618 | 0.9390    |
| 0.257         | 4.99  | 131  | 0.1794          | 0.9385   | 0.9605   | 0.9722 | 0.9492    |
| 0.2345        | 5.98  | 157  | 0.1485          | 0.9358   | 0.9582   | 0.9549 | 0.9615    |
| 0.2318        | 6.97  | 183  | 0.1302          | 0.9439   | 0.9631   | 0.9514 | 0.9751    |
| 0.2173        | 8.0   | 210  | 0.1277          | 0.9519   | 0.9689   | 0.9722 | 0.9655    |
| 0.2058        | 8.99  | 236  | 0.1269          | 0.9572   | 0.9722   | 0.9722 | 0.9722    |
| 0.1955        | 9.98  | 262  | 0.1146          | 0.9572   | 0.9724   | 0.9792 | 0.9658    |
| 0.2083        | 10.97 | 288  | 0.1083          | 0.9652   | 0.9772   | 0.9688 | 0.9859    |
| 0.1886        | 12.0  | 315  | 0.1048          | 0.9599   | 0.9741   | 0.9792 | 0.9691    |
| 0.1618        | 12.99 | 341  | 0.1033          | 0.9626   | 0.9757   | 0.9757 | 0.9757    |
| 0.1908        | 13.98 | 367  | 0.1044          | 0.9599   | 0.9739   | 0.9722 | 0.9756    |
| 0.1594        | 14.97 | 393  | 0.0915          | 0.9626   | 0.9758   | 0.9792 | 0.9724    |
| 0.1474        | 16.0  | 420  | 0.0916          | 0.9759   | 0.9842   | 0.9757 | 0.9929    |
| 0.1734        | 16.99 | 446  | 0.0951          | 0.9652   | 0.9773   | 0.9722 | 0.9825    |
| 0.1484        | 17.98 | 472  | 0.1049          | 0.9706   | 0.9809   | 0.9792 | 0.9826    |
| 0.1495        | 18.97 | 498  | 0.0930          | 0.9679   | 0.9791   | 0.9757 | 0.9825    |
| 0.1385        | 20.0  | 525  | 0.0955          | 0.9626   | 0.9759   | 0.9826 | 0.9692    |
| 0.1492        | 20.99 | 551  | 0.0911          | 0.9599   | 0.9741   | 0.9792 | 0.9691    |
| 0.1401        | 21.98 | 577  | 0.0927          | 0.9706   | 0.9809   | 0.9792 | 0.9826    |
| 0.1288        | 22.97 | 603  | 0.0940          | 0.9706   | 0.9809   | 0.9792 | 0.9826    |
| 0.1304        | 24.0  | 630  | 0.0913          | 0.9652   | 0.9775   | 0.9826 | 0.9725    |
| 0.14          | 24.99 | 656  | 0.0979          | 0.9652   | 0.9776   | 0.9861 | 0.9693    |
| 0.1461        | 25.98 | 682  | 0.0874          | 0.9706   | 0.9810   | 0.9861 | 0.9759    |
| 0.1429        | 26.97 | 708  | 0.0837          | 0.9706   | 0.9808   | 0.9757 | 0.9860    |
| 0.1444        | 28.0  | 735  | 0.0876          | 0.9679   | 0.9792   | 0.9792 | 0.9792    |
| 0.145         | 28.99 | 761  | 0.0903          | 0.9706   | 0.9809   | 0.9792 | 0.9826    |
| 0.1445        | 29.71 | 780  | 0.0882          | 0.9679   | 0.9791   | 0.9757 | 0.9825    |


### Framework versions

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