---
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: vit-brats-artifact-classifier
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# vit-brats-artifact-classifier

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: 0.5891
- Accuracy: 0.8624
- Precision: 0.8765
- Recall: 0.8624
- F1: 0.8638

## 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- 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: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log        | 1.0   | 80   | 0.6962          | 0.6924   | 0.7009    | 0.6924 | 0.6672 |
| 0.8725        | 2.0   | 160  | 0.5648          | 0.7711   | 0.8219    | 0.7711 | 0.7728 |
| 0.8725        | 3.0   | 240  | 0.4637          | 0.8244   | 0.8342    | 0.8244 | 0.8249 |
| 0.3152        | 4.0   | 320  | 0.3919          | 0.8413   | 0.8415    | 0.8413 | 0.8405 |
| 0.3152        | 5.0   | 400  | 0.4121          | 0.8764   | 0.8848    | 0.8764 | 0.8778 |
| 0.1611        | 6.0   | 480  | 0.2989          | 0.8876   | 0.8923    | 0.8876 | 0.8881 |
| 0.1611        | 7.0   | 560  | 0.6423          | 0.8244   | 0.8607    | 0.8244 | 0.8278 |
| 0.1022        | 8.0   | 640  | 0.3978          | 0.8764   | 0.8787    | 0.8764 | 0.8769 |
| 0.1022        | 9.0   | 720  | 0.5891          | 0.8624   | 0.8765    | 0.8624 | 0.8638 |


### Framework versions

- Transformers 4.53.3
- Pytorch 2.6.0+cu124
- Datasets 4.4.1
- Tokenizers 0.21.2