init

app.py

@@ -34,7 +34,7 @@ def fine_tune_model(model_name, dataset_name, hub_id, api_key, num_epochs, batch
     
         # Load the model and tokenizer
         model = AutoModelForSeq2SeqLM.from_pretrained(model_name.strip(), num_labels=2)
-        model = get_peft_model(model, lora_config)
+        #model = get_peft_model(model, lora_config)
         tokenizer = AutoTokenizer.from_pretrained(model_name)
     
         # Tokenize the dataset
@@ -62,7 +62,7 @@ def fine_tune_model(model_name, dataset_name, hub_id, api_key, num_epochs, batch
             logging_steps=10,
             #push_to_hub=True,
             hub_model_id=hub_id.strip(),
-            fp16=True,
+            #fp16=True,
             lr_scheduler_type='cosine',
         )
         
@@ -72,7 +72,6 @@ def fine_tune_model(model_name, dataset_name, hub_id, api_key, num_epochs, batch
             args=training_args,
             train_dataset=tokenized_datasets['train'],
             eval_dataset=tokenized_datasets['test'],
-            test_dataset=tokenized_datasets['validation'],
             callbacks=[LoggingCallback()], 
         )