Thanks for your great work in creating this dataset, I have questions while evaluating ```llama2-7b-chat``` on this dataset. - The accuracy of the ```llama2-7b-chat``` output remains 0 when the training goes, here is my code: ``` def acc(eval_preds:EvalPrediction): logits, labels = eval_preds preds = tokenizer.batch_decode(logits, skip_special_tokens=True) labels = tokenizer.batch_decode(labels, skip_special_tokens=True) save_results(preds, labels) # save results to json file preds = [last_boxed_only_string(s) for s in preds] correct = 0 total = 0 for pred, label in zip(preds, labels): if is_equiv(pred, label): correct += 1 total += 1 return {"accuracy": correct / total} return acc ``` - whether the preprocess is required or recommended to use?
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