Update app.py

app.py

@@ -54,10 +54,20 @@ def summarize():
         return {k: round(v, 4) for k, v in result.items()}
 
     model = AutoModelForSeq2SeqLM.from_pretrained(checkpoint)
+
+
+
+    
+    
+    
+    
+
+    
     
     training_args = Seq2SeqTrainingArguments(
-        output_dir="my_awesome_billsum_model",
-        eval_strategy="no",
+        output_dir="./results",
+        logging_dir="./logs",  # Save logs here
+        eval_strategy="steps",
         learning_rate=2e-5,
         per_device_train_batch_size=16,  # Increase batch size
         per_device_eval_batch_size=16,
@@ -68,9 +78,11 @@ def summarize():
         fp16=True,  # Keep mixed precision
         push_to_hub=False,
     #    optim="adamw_bnb_8bit",  # Use 8-bit optimizer
-        logging_steps=100,  # Reduce logging overhead
+        logging_steps=10,  # Log every 10 steps
+        logging_strategy="steps",
         dataloader_num_workers=4,  # Speed up data loading
         save_strategy="epoch",  # Reduce checkpointing overhead
+        save_steps=500,
         gradient_accumulation_steps=4  # Effective larger batch size
     )
     trainer = Seq2SeqTrainer(