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# vit-base-DogSick

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: 1.3041
- Acc: {'accuracy': 0.6102564102564103}
- F1: {'f1': 0.5980148081337936}

## 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: 4e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Acc                               | F1                         |
|:-------------:|:-----:|:----:|:---------------:|:---------------------------------:|:--------------------------:|
| 2.4055        | 0.61  | 50   | 2.2086          | {'accuracy': 0.41794871794871796} | {'f1': 0.3246788612052483} |
| 2.0379        | 1.22  | 100  | 1.9233          | {'accuracy': 0.4846153846153846}  | {'f1': 0.4386383497855148} |
| 1.7287        | 1.83  | 150  | 1.7200          | {'accuracy': 0.5256410256410257}  | {'f1': 0.4806042289317683} |
| 1.4667        | 2.44  | 200  | 1.6021          | {'accuracy': 0.5692307692307692}  | {'f1': 0.533374137436958}  |
| 1.3444        | 3.05  | 250  | 1.5410          | {'accuracy': 0.5333333333333333}  | {'f1': 0.4846134797922835} |
| 1.1334        | 3.66  | 300  | 1.4674          | {'accuracy': 0.5743589743589743}  | {'f1': 0.5533432367508125} |
| 1.007         | 4.27  | 350  | 1.4096          | {'accuracy': 0.5923076923076923}  | {'f1': 0.5801847507206119} |
| 0.897         | 4.88  | 400  | 1.3674          | {'accuracy': 0.6}                 | {'f1': 0.5903283954748092} |
| 0.7326        | 5.49  | 450  | 1.3359          | {'accuracy': 0.5923076923076923}  | {'f1': 0.5793036546532927} |
| 0.7105        | 6.1   | 500  | 1.3259          | {'accuracy': 0.6153846153846154}  | {'f1': 0.6064330281486513} |
| 0.6164        | 6.71  | 550  | 1.3183          | {'accuracy': 0.6102564102564103}  | {'f1': 0.6014695572651212} |
| 0.5804        | 7.32  | 600  | 1.3103          | {'accuracy': 0.6025641025641025}  | {'f1': 0.5965366941171513} |
| 0.5313        | 7.93  | 650  | 1.3041          | {'accuracy': 0.6102564102564103}  | {'f1': 0.5980148081337936} |


### Framework versions

- Transformers 4.23.1
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.1

결막염 궤양성각막질환 유루증 정상 핵경화 백내장 초기 비궤양성각막질환 비성숙 색소침착성각막염 성숙 안검내반증 안검염 안검종양