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# colab20240326ryan2

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: 0.8884
- Accuracy: 0.6668

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4599        | 0.05  | 100  | 0.9329          | 0.6642   |
| 0.3904        | 0.09  | 200  | 1.1326          | 0.6132   |
| 0.3971        | 0.14  | 300  | 1.0731          | 0.6333   |
| 0.3444        | 0.19  | 400  | 1.1920          | 0.6198   |
| 0.3266        | 0.23  | 500  | 1.1286          | 0.6459   |
| 0.704         | 0.28  | 600  | 1.1258          | 0.6260   |
| 0.5476        | 0.32  | 700  | 0.9590          | 0.6361   |
| 0.6925        | 0.37  | 800  | 0.9508          | 0.6318   |
| 0.4905        | 0.42  | 900  | 0.9142          | 0.6464   |
| 0.6835        | 0.46  | 1000 | 0.9453          | 0.6316   |
| 0.6919        | 0.51  | 1100 | 0.8452          | 0.6683   |
| 0.8017        | 0.56  | 1200 | 0.9353          | 0.6431   |
| 0.5504        | 0.6   | 1300 | 0.8929          | 0.6592   |
| 0.5523        | 0.65  | 1400 | 0.8705          | 0.6650   |
| 0.7787        | 0.7   | 1500 | 0.9147          | 0.6378   |
| 0.4896        | 0.74  | 1600 | 0.8985          | 0.6635   |
| 0.5114        | 0.79  | 1700 | 0.8605          | 0.6735   |
| 0.4811        | 0.84  | 1800 | 0.9524          | 0.6524   |
| 0.6161        | 0.88  | 1900 | 0.8507          | 0.6698   |
| 0.648         | 0.93  | 2000 | 0.8478          | 0.6748   |
| 0.5534        | 0.97  | 2100 | 0.8884          | 0.6668   |


### 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