---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bone-fracture-detection-using-x-rays
  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. -->

# bone-fracture-detection-using-x-rays

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: 0.0458
- Accuracy: 0.9769

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 16
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5407        | 1.0   | 111  | 0.2512          | 0.9143   |
| 0.1819        | 2.0   | 222  | 0.1203          | 0.9526   |
| 0.1351        | 3.0   | 333  | 0.1183          | 0.9521   |
| 0.101         | 4.0   | 444  | 0.0905          | 0.9616   |
| 0.0705        | 5.0   | 555  | 0.0958          | 0.9628   |
| 0.0658        | 6.0   | 666  | 0.0671          | 0.9729   |
| 0.0584        | 7.0   | 777  | 0.0498          | 0.9803   |
| 0.0507        | 8.0   | 888  | 0.0633          | 0.9735   |
| 0.0508        | 9.0   | 999  | 0.0640          | 0.9797   |
| 0.0432        | 10.0  | 1110 | 0.0458          | 0.9769   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2