Model hyperparameter tuning

[therealnb]

We need to explore the dimensions and learning parameters of the ANN and optimise it.

[poppysec]

I've started a notebook here - nn_hyperparameters

Using Optuna optimisation with 50 trials
Best parameters found via Optuna: {'hidden_dim': 170, 'learning_rate': 0.0014823754382745518, 'epochs': 83, 'test_size': 0.200317595018103, 'random_state': 42} Best validation accuracy: 0.9928516281300459
Using the MiniLM-L6 ANN with these parameters yields:

{'true_positive': 176,
 'false_positive': 38,
 'true_negative': 81,
 'false_negative': 16,
 'total_time': 12.742049217224121,
 'mean_time': 0.041103384571690715,
 'max_time': 0.37363195419311523,
 'min_time': 0.006579160690307617,
 'count': 310}

{'sensitivity': 0.9166666666666666,
  'specificity': 0.680672268907563,
  'precision': 0.822429906542056,
  'recall': 0.9166666666666666,
  'f1_score': 0.8669950738916257}