| | --- |
| | license: apache-2.0 |
| | base_model: google/vit-base-patch16-224-in21k |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - imagefolder |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: CrackDetectionLowRes |
| | results: |
| | - task: |
| | name: Image Classification |
| | type: image-classification |
| | dataset: |
| | name: imagefolder |
| | type: imagefolder |
| | config: default |
| | split: train |
| | args: default |
| | metrics: |
| | - name: Accuracy |
| | type: accuracy |
| | value: 0.9940476190476191 |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # CrackDetectionLowRes |
| |
|
| | 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 imagefolder dataset. |
| | It achieves the following results on the evaluation set: |
| | - Accuracy: 0.9940 |
| | - Loss: 0.0183 |
| |
|
| | ## 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: 2e-05 |
| | - train_batch_size: 8 |
| | - eval_batch_size: 8 |
| | - seed: 1337 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 5.0 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Accuracy | Validation Loss | |
| | |:-------------:|:-----:|:----:|:--------:|:---------------:| |
| | | 0.0126 | 1.0 | 992 | 0.9879 | 0.0344 | |
| | | 0.0788 | 2.0 | 1904 | 0.9933 | 0.0220 | |
| | | 0.1336 | 3.0 | 2856 | 0.9933 | 0.0222 | |
| | | 0.0066 | 4.0 | 3808 | 0.9933 | 0.0190 | |
| | | 0.0528 | 5.0 | 4760 | 0.9940 | 0.0183 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.31.0.dev0 |
| | - Pytorch 2.0.1+cpu |
| | - Datasets 2.13.1 |
| | - Tokenizers 0.13.3 |
| |
|
