Update fine_tuner.py

fine_tuner.py

@@ -3,20 +3,29 @@ from transformers import AutoModelForSequenceClassification, Trainer, TrainingAr
 from datasets import load_dataset
 
 def fine_tune_model(dataset, model_name, epochs, batch_size, learning_rate):
+    # Load the pre-trained model for sequence classification
     model = AutoModelForSequenceClassification.from_pretrained(model_name, num_labels=2)
+
+    # Define the training arguments
     training_args = TrainingArguments(
-        output_dir='./results',
-        num_train_epochs=epochs,
-        per_device_train_batch_size=batch_size,
-        learning_rate=learning_rate,
-        logging_dir='./logs',
-        logging_steps=10,
+        output_dir='./results',                # Directory for storing results
+        num_train_epochs=epochs,               # Number of training epochs
+        per_device_train_batch_size=batch_size,  # Batch size for training
+        learning_rate=learning_rate,          # Learning rate for the optimizer
+        logging_dir='./logs',                  # Directory for storing logs
+        logging_steps=10,                      # Log every 10 steps
     )
+
+    # Initialize the Trainer with the model, arguments, and dataset
     trainer = Trainer(
         model=model,
         args=training_args,
-        train_dataset=dataset['train'],
-        eval_dataset=dataset['validation'],
+        train_dataset=dataset['train'],        # Training dataset
+        eval_dataset=dataset['validation'],    # Validation dataset
     )
+
+    # Train the model
     trainer.train()
-    return {"status": "Training complete"}
+
+    # Return a status message after training completes
+    return {"status": "Training complete"}