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# ee8225-group4-vit-trashnet-enhanced

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the edwinpalegre/trashnet-enhanced dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0793
- Accuracy: 0.9817

## 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: 64
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0603        | 0.4   | 100  | 0.1482          | 0.9623   |
| 0.0363        | 0.8   | 200  | 0.1123          | 0.9698   |
| 0.0306        | 1.2   | 300  | 0.1069          | 0.9721   |
| 0.023         | 1.61  | 400  | 0.1188          | 0.9706   |
| 0.0172        | 2.01  | 500  | 0.1019          | 0.9734   |
| 0.0161        | 2.41  | 600  | 0.1112          | 0.9746   |
| 0.0163        | 2.81  | 700  | 0.0874          | 0.9801   |
| 0.0024        | 3.21  | 800  | 0.0793          | 0.9817   |
| 0.0133        | 3.61  | 900  | 0.0831          | 0.9812   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

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