transformers safetensors van image-classification generated_from_trainer dataset:imagefolder base_model:Visual-Attention-Network/van-tiny license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
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-256-1-2
  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: 0.9716684155299056
    - name: Recall
      type: recall
      value: 0.9754098360655737
    - name: Precision
      type: precision
      value: 0.9802306425041186
---

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# teacher-status-van-tiny-256-1-2

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: 0.0859
- Accuracy: 0.9717
- F1 Score: 0.9778
- Recall: 0.9754
- Precision: 0.9802

## 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: 128
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 256
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:------:|:---------:|
| 0.6722        | 0.99  | 33   | 0.6499          | 0.6401   | 0.7806   | 1.0    | 0.6401    |
| 0.5431        | 2.0   | 67   | 0.4164          | 0.7817   | 0.8531   | 0.9902 | 0.7494    |
| 0.393         | 2.99  | 100  | 0.2833          | 0.8877   | 0.9078   | 0.8639 | 0.9564    |
| 0.354         | 4.0   | 134  | 0.1930          | 0.9276   | 0.9436   | 0.9459 | 0.9413    |
| 0.3007        | 4.99  | 167  | 0.1585          | 0.9370   | 0.9511   | 0.9557 | 0.9464    |
| 0.2898        | 6.0   | 201  | 0.1445          | 0.9465   | 0.9581   | 0.9557 | 0.9605    |
| 0.2824        | 6.99  | 234  | 0.1353          | 0.9465   | 0.9580   | 0.9525 | 0.9635    |
| 0.2763        | 8.0   | 268  | 0.1359          | 0.9486   | 0.9603   | 0.9721 | 0.9488    |
| 0.2473        | 8.99  | 301  | 0.1213          | 0.9570   | 0.9664   | 0.9672 | 0.9656    |
| 0.2598        | 10.0  | 335  | 0.1091          | 0.9570   | 0.9665   | 0.9705 | 0.9626    |
| 0.2476        | 10.99 | 368  | 0.1041          | 0.9633   | 0.9714   | 0.9754 | 0.9675    |
| 0.2376        | 12.0  | 402  | 0.0997          | 0.9601   | 0.9686   | 0.9623 | 0.9751    |
| 0.2402        | 12.99 | 435  | 0.0972          | 0.9622   | 0.9704   | 0.9672 | 0.9736    |
| 0.2324        | 14.0  | 469  | 0.0950          | 0.9664   | 0.9739   | 0.9803 | 0.9676    |
| 0.2256        | 14.99 | 502  | 0.0909          | 0.9706   | 0.9770   | 0.9754 | 0.9786    |
| 0.21          | 16.0  | 536  | 0.0922          | 0.9622   | 0.9703   | 0.9656 | 0.9752    |
| 0.217         | 16.99 | 569  | 0.0933          | 0.9612   | 0.9695   | 0.9656 | 0.9736    |
| 0.2092        | 18.0  | 603  | 0.0891          | 0.9664   | 0.9738   | 0.9754 | 0.9722    |
| 0.2063        | 18.99 | 636  | 0.0913          | 0.9654   | 0.9730   | 0.9738 | 0.9722    |
| 0.2217        | 20.0  | 670  | 0.0917          | 0.9643   | 0.9720   | 0.9672 | 0.9768    |
| 0.1952        | 20.99 | 703  | 0.0859          | 0.9717   | 0.9778   | 0.9754 | 0.9802    |
| 0.2068        | 22.0  | 737  | 0.0907          | 0.9685   | 0.9755   | 0.9770 | 0.9739    |
| 0.1914        | 22.99 | 770  | 0.0847          | 0.9696   | 0.9763   | 0.9787 | 0.9739    |
| 0.1961        | 24.0  | 804  | 0.0870          | 0.9685   | 0.9755   | 0.9770 | 0.9739    |
| 0.1911        | 24.99 | 837  | 0.0884          | 0.9664   | 0.9739   | 0.9770 | 0.9707    |
| 0.1961        | 26.0  | 871  | 0.0870          | 0.9685   | 0.9754   | 0.9738 | 0.9770    |
| 0.1978        | 26.99 | 904  | 0.0871          | 0.9685   | 0.9754   | 0.9754 | 0.9754    |
| 0.1854        | 28.0  | 938  | 0.0858          | 0.9685   | 0.9755   | 0.9770 | 0.9739    |
| 0.1733        | 28.99 | 971  | 0.0860          | 0.9685   | 0.9754   | 0.9738 | 0.9770    |
| 0.1762        | 29.55 | 990  | 0.0858          | 0.9664   | 0.9738   | 0.9738 | 0.9738    |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
