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# vit-base-patch16-224-in21k_covid_19_ct_scans-finetuned-RCC

This model is a fine-tuned version of [DunnBC22/vit-base-patch16-224-in21k_covid_19_ct_scans](https://huggingface.co/DunnBC22/vit-base-patch16-224-in21k_covid_19_ct_scans) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3235
- Accuracy: 0.9032
- Precision: 0.9032
- Recall: 1.0
- F1: 0.4746
- Auc: 0.5

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Auc |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:---:|
| No log        | 1.0   | 7    | 0.3327          | 0.9032   | 0.9032    | 1.0    | 0.4746 | 0.5 |
| 0.3866        | 2.0   | 14   | 0.3213          | 0.9032   | 0.9032    | 1.0    | 0.4746 | 0.5 |
| 0.2647        | 3.0   | 21   | 0.3226          | 0.9032   | 0.9032    | 1.0    | 0.4746 | 0.5 |
| 0.2647        | 4.0   | 28   | 0.3246          | 0.9032   | 0.9032    | 1.0    | 0.4746 | 0.5 |
| 0.2593        | 5.0   | 35   | 0.3235          | 0.9032   | 0.9032    | 1.0    | 0.4746 | 0.5 |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.0.0+cu117
- Datasets 2.19.1
- Tokenizers 0.19.1

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