Update app.py

app.py

@@ -64,7 +64,7 @@ def load_counseling_dataset():
     return dataset
 
 # Process the dataset in batches to avoid memory overuse
-def process_dataset_in_batches(dataset, batch_size=1000):
+def process_dataset_in_batches(dataset, batch_size=500):
     for example in dataset.shuffle().select(range(batch_size)):
         yield example
 
@@ -93,14 +93,14 @@ def fine_tune_model():
         output_dir="./fine_tuned_model",
         evaluation_strategy="steps",
         learning_rate=2e-5,
-        per_device_train_batch_size=8,
-        per_device_eval_batch_size=8,
+        per_device_train_batch_size=5,
+        per_device_eval_batch_size=5,
         num_train_epochs=3,
         weight_decay=0.01,
         fp16=True,  # Enable FP16 for lower memory usage
         save_total_limit=2,
-        save_steps=500,
-        logging_steps=100,
+        save_steps=250,
+        logging_steps=50,
     )
 
     # Trainer