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# colab20240326ryan

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: 0.8730
- Accuracy: 0.6652

## 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: 16
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7644        | 0.05  | 100  | 0.8799          | 0.6399   |
| 0.6947        | 0.09  | 200  | 0.9719          | 0.6044   |
| 0.6656        | 0.14  | 300  | 0.8993          | 0.6590   |
| 0.6741        | 0.19  | 400  | 0.9202          | 0.6351   |
| 0.5095        | 0.23  | 500  | 0.8826          | 0.6557   |
| 0.602         | 0.28  | 600  | 0.8469          | 0.6617   |
| 0.5516        | 0.32  | 700  | 0.9219          | 0.6567   |
| 0.6998        | 0.37  | 800  | 0.9070          | 0.6409   |
| 0.5686        | 0.42  | 900  | 0.8590          | 0.6572   |
| 0.6308        | 0.46  | 1000 | 0.9953          | 0.6165   |
| 0.6242        | 0.51  | 1100 | 0.8730          | 0.6652   |


### Framework versions

- Transformers 4.39.1
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2

not applicable poor fair good great excellent