
<!-- 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. -->

# vit-base-trashnet-demo

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: 0.0701
- Accuracy: 0.9822

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.2636        | 0.4   | 100  | 0.2388          | 0.9394   |
| 0.1748        | 0.8   | 200  | 0.1414          | 0.9623   |
| 0.1231        | 1.2   | 300  | 0.1565          | 0.9545   |
| 0.0769        | 1.61  | 400  | 0.1074          | 0.9713   |
| 0.0556        | 2.01  | 500  | 0.0994          | 0.9726   |
| 0.0295        | 2.41  | 600  | 0.0720          | 0.9812   |
| 0.0311        | 2.81  | 700  | 0.0774          | 0.9806   |
| 0.0061        | 3.21  | 800  | 0.0703          | 0.9822   |
| 0.0289        | 3.61  | 900  | 0.0701          | 0.9822   |


### Framework versions

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

biodegradable cardboard glass metal paper plastic trash