Hello, thank you, Actually I was printing the initial prediction and not the prediction from the label that’s why It was changing I return the right variable and now the logits functions. I have a question can directly transform the logits to probabilities after the classification is done on the test so that I can set a threshold
                test_dataset = process_and_tokenize_file(input, input_label)
		raw_pred, _, _ = trainer.predict(test_dataset)
		print("raw :", raw_pred)
		# Preprocess raw predictions
		y_pred = np.argmax(raw_pred, axis=1)
		print("true label :", y_pred)
		
		proba = nn.functional.softmax(raw_pred, dim=-1) #raw_pred = logits from what it is return from the self.classifier