Update README.md

README.md

@@ -140,7 +140,8 @@ The model can be used by fine-tuning it for a specific task:
 >>> dataset = load_dataset("PORTULAN/glueptpt", "rte")
 
 >>> def tokenize_function(examples):
-...     return tokenizer(examples["text"], padding="max_length", truncation=True)
+...     return tokenizer(examples["sentence1"], examples["sentence2"], padding="max_length", truncation=True)
+
 >>> tokenized_datasets = dataset.map(tokenize_function, batched=True)
 
 >>> training_args = TrainingArguments(output_dir="albertina-pt-pt-rte", evaluation_strategy="epoch")
@@ -150,6 +151,7 @@ The model can be used by fine-tuning it for a specific task:
 ...     train_dataset=tokenized_datasets["train"],
 ...     eval_dataset=tokenized_datasets["validation"],
 ... )
+
 >>> trainer.train()
 
 ```