transformers tensorboard 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
  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: 0.9831460674157303
    - name: Recall
      type: recall
      value: 0.9789473684210527
    - name: Precision
      type: precision
      value: 0.9893617021276596
---

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# teacher-status-van-tiny-256

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: 0.0988
- Accuracy: 0.9831
- F1 Score: 0.9841
- Recall: 0.9789
- Precision: 0.9894

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:------:|:---------:|
| 0.6928        | 0.96  | 12   | 0.6904          | 0.6685   | 0.7631   | 1.0    | 0.6169    |
| 0.6893        | 2.0   | 25   | 0.6683          | 0.5393   | 0.6985   | 1.0    | 0.5367    |
| 0.6726        | 2.96  | 37   | 0.5704          | 0.5843   | 0.7197   | 1.0    | 0.5621    |
| 0.5295        | 4.0   | 50   | 0.4148          | 0.9213   | 0.9263   | 0.9263 | 0.9263    |
| 0.4745        | 4.96  | 62   | 0.3108          | 0.9382   | 0.9430   | 0.9579 | 0.9286    |
| 0.4206        | 6.0   | 75   | 0.2301          | 0.9438   | 0.9474   | 0.9474 | 0.9474    |
| 0.3898        | 6.96  | 87   | 0.1820          | 0.9494   | 0.9519   | 0.9368 | 0.9674    |
| 0.3153        | 8.0   | 100  | 0.1545          | 0.9494   | 0.9538   | 0.9789 | 0.93      |
| 0.3077        | 8.96  | 112  | 0.1521          | 0.9607   | 0.9622   | 0.9368 | 0.9889    |
| 0.3048        | 10.0  | 125  | 0.1331          | 0.9607   | 0.9626   | 0.9474 | 0.9783    |
| 0.3004        | 10.96 | 137  | 0.1314          | 0.9607   | 0.9634   | 0.9684 | 0.9583    |
| 0.2839        | 12.0  | 150  | 0.1272          | 0.9607   | 0.9622   | 0.9368 | 0.9889    |
| 0.286         | 12.96 | 162  | 0.1189          | 0.9607   | 0.9622   | 0.9368 | 0.9889    |
| 0.2473        | 14.0  | 175  | 0.0977          | 0.9719   | 0.9733   | 0.9579 | 0.9891    |
| 0.2774        | 14.96 | 187  | 0.0988          | 0.9831   | 0.9841   | 0.9789 | 0.9894    |
| 0.2541        | 16.0  | 200  | 0.0969          | 0.9719   | 0.9733   | 0.9579 | 0.9891    |
| 0.2383        | 16.96 | 212  | 0.1042          | 0.9719   | 0.9733   | 0.9579 | 0.9891    |
| 0.2552        | 18.0  | 225  | 0.1081          | 0.9719   | 0.9733   | 0.9579 | 0.9891    |
| 0.2223        | 18.96 | 237  | 0.1150          | 0.9663   | 0.9681   | 0.9579 | 0.9785    |
| 0.2561        | 20.0  | 250  | 0.1234          | 0.9551   | 0.9574   | 0.9474 | 0.9677    |
| 0.2462        | 20.96 | 262  | 0.1178          | 0.9607   | 0.9630   | 0.9579 | 0.9681    |
| 0.2294        | 22.0  | 275  | 0.1262          | 0.9382   | 0.9430   | 0.9579 | 0.9286    |
| 0.2296        | 22.96 | 287  | 0.1290          | 0.9438   | 0.9479   | 0.9579 | 0.9381    |
| 0.2224        | 24.0  | 300  | 0.1153          | 0.9494   | 0.9529   | 0.9579 | 0.9479    |
| 0.2205        | 24.96 | 312  | 0.1150          | 0.9494   | 0.9529   | 0.9579 | 0.9479    |
| 0.2169        | 26.0  | 325  | 0.1121          | 0.9551   | 0.9574   | 0.9474 | 0.9677    |
| 0.2212        | 26.96 | 337  | 0.1145          | 0.9494   | 0.9529   | 0.9579 | 0.9479    |
| 0.2188        | 28.0  | 350  | 0.1131          | 0.9494   | 0.9524   | 0.9474 | 0.9574    |
| 0.2015        | 28.8  | 360  | 0.1130          | 0.9494   | 0.9524   | 0.9474 | 0.9574    |


### Framework versions

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