| --- |
| license: apache-2.0 |
| tags: |
| - image-classification |
| - generated_from_trainer |
| datasets: |
| - uta_rldd |
| metrics: |
| - accuracy |
| model-index: |
| - name: vit-base-driver-drowsiness-detection |
| results: |
| - task: |
| name: Image Classification |
| type: image-classification |
| dataset: |
| name: chbh7051/vit-base-driver-drowsiness-detection |
| type: uta_rldd |
| config: default |
| split: train |
| args: default |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.9751972942502819 |
| library_name: transformers |
| --- |
| |
| <!-- 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-base-driver-drowsiness-detection |
|
|
| This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the chbh7051/driver-drowsiness-detection dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.0800 |
| - Accuracy: 0.9752 |
|
|
| ## 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: 0.0002 |
| - train_batch_size: 16 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 6 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:-----:|:---------------:|:--------:| |
| | 0.4811 | 0.6 | 2000 | 0.5214 | 0.7636 | |
| | 0.3339 | 1.2 | 4000 | 0.3437 | 0.8621 | |
| | 0.284 | 1.8 | 6000 | 0.2679 | 0.8932 | |
| | 0.2143 | 2.41 | 8000 | 0.2269 | 0.9125 | |
| | 0.0997 | 3.01 | 10000 | 0.1576 | 0.9444 | |
| | 0.1168 | 3.61 | 12000 | 0.1214 | 0.9596 | |
| | 0.0873 | 4.21 | 14000 | 0.1256 | 0.9550 | |
| | 0.06 | 4.81 | 16000 | 0.0800 | 0.9752 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.27.4 |
| - Pytorch 1.13.0 |
| - Datasets 2.1.0 |
| - Tokenizers 0.13.2 |
