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# swinv2-tiny-patch4-window8-256-finetuned-THFOOD-50

This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window8-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256) on the [THFOOD-50](https://huggingface.co/datasets/thean/THFOOD-50) dataset.
It achieves the following results on the:  
Train set
- Loss: 0.1669
- Accuracy: 0.9557
  
Validation set
- Loss: 0.2535
- Accuracy: 0.9344

Test set
- Loss: 0.2669
- Accuracy: 0.9292

## 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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.6558        | 0.99  | 47   | 3.1956          | 0.28     |
| 1.705         | 1.99  | 94   | 1.1701          | 0.6787   |
| 0.9805        | 2.98  | 141  | 0.6492          | 0.8125   |
| 0.7925        | 4.0   | 189  | 0.4724          | 0.8644   |
| 0.6169        | 4.99  | 236  | 0.4129          | 0.8738   |
| 0.5343        | 5.99  | 283  | 0.3717          | 0.8825   |
| 0.5196        | 6.98  | 330  | 0.3654          | 0.8906   |
| 0.5059        | 8.0   | 378  | 0.3267          | 0.8969   |
| 0.4432        | 8.99  | 425  | 0.2996          | 0.9081   |
| 0.3819        | 9.99  | 472  | 0.3056          | 0.9087   |
| 0.3627        | 10.98 | 519  | 0.2796          | 0.9213   |
| 0.3505        | 12.0  | 567  | 0.2753          | 0.915    |
| 0.3224        | 12.99 | 614  | 0.2830          | 0.9206   |
| 0.3206        | 13.99 | 661  | 0.2797          | 0.9231   |
| 0.3141        | 14.98 | 708  | 0.2569          | 0.9287   |
| 0.2946        | 16.0  | 756  | 0.2582          | 0.9319   |
| 0.3008        | 16.99 | 803  | 0.2583          | 0.9337   |
| 0.2356        | 17.99 | 850  | 0.2567          | 0.9281   |
| 0.2954        | 18.98 | 897  | 0.2581          | 0.9319   |
| 0.2628        | 19.89 | 940  | 0.2535          | 0.9344   |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3

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