| --- |
| library_name: keras |
| tags: |
| - computer-vision |
| - classification |
| - 'multiple-instance-learning ' |
| --- |
| |
| ## 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: |
| - optimizer: {'name': 'Adam', 'learning_rate': 0.001, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False} |
| - training_precision: float32 |
|
|
| ## Training Metrics |
|
|
| | Epochs | Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | |
| |--- |--- |--- |--- |--- | |
| | 1| 0.315| 0.915| 0.066| 0.983| |
| | 2| 0.089| 0.982| 0.049| 0.99| |
| | 3| 0.078| 0.987| 0.084| 0.983| |
| | 4| 0.059| 0.983| 0.033| 0.993| |
| | 5| 0.042| 0.99| 0.053| 0.99| |
| | 6| 0.042| 0.996| 0.019| 0.993| |
| | 7| 0.013| 0.999| 0.067| 0.987| |
| | 8| 0.055| 0.988| 0.049| 0.99| |
| | 9| 0.005| 1.0| 0.039| 0.993| |
| | 10| 0.005| 1.0| 0.038| 0.99| |
| | 11| 0.039| 0.995| 0.214| 0.97| |
| | 12| 0.008| 1.0| 0.039| 0.99| |
| | 13| 0.002| 1.0| 0.047| 0.993| |
| | 14| 0.016| 0.999| 0.057| 0.99| |
| | 15| 0.046| 0.993| 0.026| 0.997| |
| | 16| 0.002| 1.0| 0.06| 0.99| |
| ## Model Plot |
|
|
| <details> |
| <summary>View Model Plot</summary> |
|
|
|  |
|
|
| </details> |
