无法复现论文中的结果 Unable to reproduce the results in the paper

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我尝试复现中论文中的结果，现在我是直接导入hugging face上的chatgpt-detector-roberta作为model和tokenizer，根据页面上的描述这是由mixed数据集训练的，在论文中对raw-full的F1 score应该为99.44，但我没办法得到这个数据，我使用的数据集是在hc3中readme中的谷歌网盘下载的，以下是我得到的结果
{'0': {'precision': 0.9994103425909546, 'recall': 0.9951852504256943, 'f1-score': 0.9972933215651661, 'support': 17031.0}, '1': {'precision': 0.9898640296662546, 'recall': 0.9987528061860813, 'f1-score': 0.994288552272163, 'support': 8018.0}, 'accuracy': 0.9963271986905665, 'macro avg': {'precision': 0.9946371861286046, 'recall': 0.9969690283058878, 'f1-score': 0.9957909369186646, 'support': 25049.0}, 'weighted avg': {'precision': 0.9963546382901745, 'recall': 0.9963271986905665, 'f1-score': 0.9963315170942771, 'support': 25049.0}}

I am trying to reproduce the results of a paper. Currently, I am using the 'chatgpt-detector-roberta' model and tokenizer directly imported from Hugging Face. According to the information on their website, this model was trained on a mixed dataset. In the paper, the F1 score for 'raw-full' should be 99.44. However, I am unable to achieve this result, The dataset used was downloaded from the Google Drive link provided in the README of hc3, and here are the results I obtained.
{'0': {'precision': 0.9994103425909546, 'recall': 0.9951852504256943, 'f1-score': 0.9972933215651661, 'support': 17031.0}, '1': {'precision': 0.9898640296662546, 'recall': 0.9987528061860813, 'f1-score': 0.994288552272163, 'support': 8018.0}, 'accuracy': 0.9963271986905665, 'macro avg': {'precision': 0.9946371861286046, 'recall': 0.9969690283058878, 'f1-score': 0.9957909369186646, 'support': 25049.0}, 'weighted avg': {'precision': 0.9963546382901745, 'recall': 0.9963271986905665, 'f1-score': 0.9963315170942771, 'support': 25049.0}}