change lr tuning range

env.py

@@ -106,7 +106,7 @@ class Env:
 
     def optuna_hp_space(self, trial: any) -> dict[str, any]:
         return {
-            "learning_rate": trial.suggest_float("learning_rate", 1e-5, 1e-4),
+            "learning_rate": trial.suggest_float("learning_rate", 5e-6, 5e-5),
             "per_device_train_batch_size": trial.suggest_categorical("per_device_train_batch_size", [16, 32]),
             "weight_decay": trial.suggest_float("weight_decay", 0.005, 0.05)
         }

hypertune.py

@@ -8,6 +8,7 @@ from os import path
 from time import time
 from transformers import Trainer
 
+
 # Hyperparameter training
 def get_optimal_hyperparameters(env: Env, upsample_factors=None) -> dict[str: any]:
     if upsample_factors is None: