Cloned from QML-toolkit by: Kinshuk Sengupta
Dataset - Due to large file size, we could only upload some samples to the gitrepo.
Codebase: Some code files will be updated soon. The working code is commited to the branch using QNN.
Epoch | Loss | Val Loss | Hinge Accuracy | Val Hinge Accuracy | |||
1/10 | 0.6566 | 0.387 | 0.7534 | 0.816 | |||
2/10 | 0.3568 | 0.3348 | 0.8263 | 0.8311 | |||
3/10 | 0.3281 | 0.3269 | 0.8497 | 0.8579 | |||
4/10 | 0.2994 | 0.289467 | 0.9061 | 0.8769 | |||
5/10 | 0.2707 | 0.259417 | 0.95425 | 0.89785 | |||
6/10 | 0.2707 | 0.229367 | 0.95825 | 0.9188 | |||
7/10 | 0.2133 | 0.199317 | 0.95865 | 0.93975 | |||
8/10 | 0.1872 | 0.169267 | 0.95825 | 0.9607 | |||
9/10 | 0.1872 | 0.169267 | 0.95825 | 0.9607 | |||
10/10 | 0.1821 | 0.169167 | 0.96925 | 0.9657 |
Training Samples: 9580 Testing Samples: 1500
Predicted Values Positive Negative Positive 874 26 Negative 20 580 Total Evaluation Sample 1500
Training Time: 52 min avg on multiple instances.