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# Resnet152-30VN

This model is a fine-tuned version of [microsoft/resnet-152](https://huggingface.co/microsoft/resnet-152) on the vuongnhathien/30VNFoods dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5769
- Accuracy: 0.8353

## 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: 0.0003
- train_batch_size: 64
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| 1.4198        | 1.0   | 275  | 0.7348   | 0.8741          |
| 0.565         | 2.0   | 550  | 0.8119   | 0.6347          |
| 0.2846        | 3.0   | 825  | 0.8310   | 0.6003          |
| 0.1727        | 4.0   | 1100 | 0.8410   | 0.6041          |
| 0.0835        | 5.0   | 1375 | 0.8461   | 0.6464          |
| 0.0534        | 6.0   | 1650 | 0.8565   | 0.6776          |
| 0.0283        | 7.0   | 1925 | 0.7107   | 0.8501          |
| 0.0186        | 8.0   | 2200 | 0.7066   | 0.8620          |
| 0.0111        | 9.0   | 2475 | 0.6772   | 0.8648          |
| 0.0096        | 10.0  | 2750 | 0.6898   | 0.8628          |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2

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