
<!-- 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. -->

# finetuned-bangladeshi-traditional-food

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3157
- Accuracy: 0.9529
- Precision: 0.9560
- Recall: 0.9529
- F1: 0.9538

## 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: 0.0002
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.2056        | 1.0   | 48   | 0.9746          | 0.8560   | 0.8761    | 0.8560 | 0.8530 |
| 0.5285        | 2.0   | 96   | 0.5351          | 0.9188   | 0.9236    | 0.9188 | 0.9196 |
| 0.3189        | 3.0   | 144  | 0.3756          | 0.9372   | 0.9386    | 0.9372 | 0.9370 |
| 0.221         | 4.0   | 192  | 0.3157          | 0.9529   | 0.9560    | 0.9529 | 0.9538 |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.4.0
- Datasets 3.1.0
- Tokenizers 0.20.3

amshotto bakhorkhani narikel naru nimki nokul dana shonpapri tiler khaja muri mowa batasha chira jilapi khoi kotkoti misri morobba muri