updated train_abuse_model to save the traind model after training process

train_abuse_model.py

@@ -225,5 +225,17 @@ trainer = Trainer(
 # Start training!
 trainer.train()
 
-label_map = {0.0: "no", 0.5: "plausibly", 1.0: "yes"}
-evaluate_model_with_thresholds(trainer, test_dataset)
+# Save the model and tokenizer
+if not os.path.exists("saved_model/"):
+    os.makedirs("saved_model/")
+model.save_pretrained("saved_model/")
+tokenizer.save_pretrained("saved_model/")
+
+# Evaluation
+try:
+    label_map = {0.0: "no", 0.5: "plausibly", 1.0: "yes"}
+    evaluate_model_with_thresholds(trainer, test_dataset)
+except Exception as e:
+    print(f"Evaluation failed: {e}")
+
+