| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - beans |
| metrics: |
| - accuracy |
| widget: |
|
|
| - src: https://huggingface.co/EdwarV/computer_vision_example/blob/main/bean_rust.jpeg |
| - src: https://huggingface.co/EdwarV/computer_vision_example/blob/main/healthy.jpeg |
| example_title: Bean Rust |
|
|
| model-index: |
| - name: computer_vision_example |
| results: |
| - task: |
| name: Image Classification |
| type: image-classification |
| dataset: |
| name: beans |
| type: beans |
| config: default |
| split: validation |
| args: default |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 1.0 |
| --- |
| |
| <!-- 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. --> |
|
|
| # computer_vision_example |
|
|
| 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 beans dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.0117 |
| - Accuracy: 1.0 |
|
|
| ## 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: 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: 4 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | 0.137 | 3.85 | 500 | 0.0117 | 1.0 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.30.2 |
| - Pytorch 2.1.0+cu121 |
| - Datasets 2.15.0 |
| - Tokenizers 0.13.3 |
|
|
