| --- |
| license: apache-2.0 |
| base_model: google/vit-base-patch16-224-in21k |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: car_orientation_classification_zoomed |
| 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. --> |
|
|
| # car_orientation_classification_zoomed |
| |
| 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 None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.6108 |
| - Accuracy: 0.7597 |
| |
| ## 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: 40 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | 1.9887 | 1.0 | 68 | 1.9011 | 0.3463 | |
| | 1.4388 | 2.0 | 136 | 1.3001 | 0.4594 | |
| | 1.1799 | 3.0 | 204 | 1.1267 | 0.4841 | |
| | 1.0245 | 4.0 | 272 | 0.9695 | 0.5936 | |
| | 0.8203 | 5.0 | 340 | 0.8157 | 0.6890 | |
| | 0.7146 | 6.0 | 408 | 0.7898 | 0.6678 | |
| | 0.6137 | 7.0 | 476 | 0.6343 | 0.7420 | |
| | 0.5746 | 8.0 | 544 | 0.6351 | 0.7527 | |
| | 0.5316 | 9.0 | 612 | 0.5899 | 0.7986 | |
| | 0.5073 | 10.0 | 680 | 0.6193 | 0.7491 | |
| | 0.4854 | 11.0 | 748 | 0.5721 | 0.7845 | |
| | 0.4347 | 12.0 | 816 | 0.6495 | 0.7562 | |
| | 0.3937 | 13.0 | 884 | 0.6108 | 0.7597 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.42.4 |
| - Pytorch 2.3.1+cu121 |
| - Datasets 2.20.0 |
| - Tokenizers 0.19.1 |
| |
