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evaluation accuracy remains 0 #14

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@2proveit

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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