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# vit-base-patch16-224-finetuned-noh

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5148
- Accuracy: 0.8210

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.4728        | 1.0    | 23   | 0.4540          | 0.7750   |
| 0.3998        | 2.0    | 46   | 0.4063          | 0.8128   |
| 0.3388        | 3.0    | 69   | 0.3919          | 0.8358   |
| 0.2665        | 4.0    | 92   | 0.4299          | 0.8539   |
| 0.2112        | 5.0    | 115  | 0.4299          | 0.8227   |
| 0.187         | 6.0    | 138  | 0.4721          | 0.8259   |
| 0.1363        | 7.0    | 161  | 0.4639          | 0.8440   |
| 0.119         | 8.0    | 184  | 0.5293          | 0.7898   |
| 0.1042        | 9.0    | 207  | 0.5141          | 0.8161   |
| 0.1153        | 9.5778 | 220  | 0.5148          | 0.8210   |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1
- Datasets 2.19.1
- Tokenizers 0.21.0

normal cancer