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import json
import re
import argparse
# 字母到数字的映射
letter_to_number = {
"A": "0",
"B": "1",
"C": "2",
"D": "3"
}
# 函数：从text中提取模型预测的答案
def extract_predicted_answer(text):
# 匹配类似 "A", "B", "C", "D" 的答案
match = re.search(r'\b[A-D]\b', text)
if match:
return match.group(0)
return None
# 函数：计算正确率
def calculate_accuracy(file_path):
total = 0
correct = 0
# 逐行读取JSONL文件
with open(file_path, 'r', encoding='utf-8') as file:
for line in file:
item = json.loads(line)
total += 1
pred_letter = extract_predicted_answer(item['text']) # 从text中提取答案
true_answer = item['answer'] # 正确答案
if pred_letter:
pred = letter_to_number[pred_letter] # 映射到数字 (1-4)
true_answer = str(item['answer']) # 转为字符串，避免类型问题
if pred == true_answer:
correct += 1
# 计算正确率
accuracy = (correct / total) * 100
# 打印结果
print(f"总样本数: {total}")
print(f"正确样本数: {correct}")
print(f"错误样本数: {total - correct}")
print(f"正确率: {accuracy:.2f}%")
# 主程序
if __name__ == "__main__":
# 使用 argparse 获取命令行参数
parser = argparse.ArgumentParser(description="Evaluate model accuracy from JSONL file.")
parser.add_argument("file_path", type=str, help="Path to the JSONL file containing inference results.")
args = parser.parse_args()
# 调用计算函数
calculate_accuracy(args.file_path)
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