fix: Add weights_only=False for PyTorch 2.6 checkpoint loading

PyTorch 2.6 changed the default value of weights_only parameter in
torch.load() from False to True. Since Lightning checkpoints contain
optimizer and scheduler state (not just tensors), loading now requires
weights_only=False.

This is safe as the checkpoint is self-generated during training.

Author: micedre

torchTextClassifiers/torchTextClassifiers.py

@@ -198,6 +198,12 @@ def train(
         - Model training with early stopping
         - Best model loading after training
 
+        Note on Checkpoints:
+            After training, the best model checkpoint is automatically loaded.
+            This checkpoint contains the full training state (model weights,
+            optimizer, and scheduler state). Loading uses weights_only=False
+            as the checkpoint is self-generated and trusted.
+
         Args:
             X_train: Training input data
             y_train: Training labels
@@ -361,6 +367,7 @@ def train(
             best_model_path,
             model=self.pytorch_model,
             loss=training_config.loss,
+            weights_only=False,  # Required: checkpoint contains optimizer/scheduler state
         )
 
         self.pytorch_model = self.lightning_module.model.to(self.device)