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# test-cont-lr

This model is a fine-tuned version of [vuongnhathien/SwinV2-30VNFood](https://huggingface.co/vuongnhathien/SwinV2-30VNFood) on the jbarat/plant_species dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9419
- Accuracy: 0.7

## 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 | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 10   | 1.0693          | 0.6125   |
| No log        | 2.0   | 20   | 0.8939          | 0.675    |
| No log        | 3.0   | 30   | 1.1355          | 0.7      |
| No log        | 4.0   | 40   | 1.6583          | 0.6625   |
| No log        | 5.0   | 50   | 1.5728          | 0.7      |
| No log        | 6.0   | 60   | 1.4494          | 0.6625   |
| No log        | 7.0   | 70   | 1.3951          | 0.6625   |
| No log        | 8.0   | 80   | 1.7134          | 0.6875   |
| No log        | 9.0   | 90   | 1.5019          | 0.6875   |
| 0.2446        | 10.0  | 100  | 1.4587          | 0.675    |


### Framework versions

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

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