| | --- |
| | 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 |
| |
|
