| --- |
| license: apache-2.0 |
| base_model: google/vit-base-patch16-224-in21k |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: results |
| results: [] |
| library_name: transformers |
| pipeline_tag: image-classification |
| --- |
| |
| <!-- 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. --> |
|
|
| # results |
|
|
| 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: 0.0398 |
| - Accuracy: 1.0 |
|
|
| ## Model description |
|
|
| This model was trained for the Kaggle competition [Cleaned vs Dirty V2](https://www.kaggle.com/competitions/platesv2). |
| Despite good results in training, the model shows poor results on test data, and should not be used in this competition. |
|
|
|
|
| ### Training hyperparameters |
|
|
| The following hyperparameters were used during training: |
| - learning_rate: 5e-05 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 3 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | No log | 1.0 | 20 | 0.0907 | 1.0 | |
| | No log | 2.0 | 40 | 0.0468 | 1.0 | |
| | No log | 3.0 | 60 | 0.0398 | 1.0 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.42.4 |
| - Pytorch 2.3.1+cu121 |
| - Datasets 2.21.0 |
| - Tokenizers 0.19.1 |
