import re
import pandas as pd

def parse_log_file(log_file_path):
    # 初始化存储数据的列表
    base_training_data = []
    fine_tuning_data = []
    
    with open(log_file_path, 'r', encoding='utf-8') as f:
        content = f.read()
        
    # 提取基础训练数据
    base_pattern = r'Epoch (\d+)/50 - Train Loss: ([\d.]+), Train Acc: ([\d.]+), Val Loss: ([\d.]+), Val Acc: ([\d.]+)'
    base_matches = re.finditer(base_pattern, content)
    
    for match in base_matches:
        epoch = int(match.group(1))
        train_loss = float(match.group(2))
        train_acc = float(match.group(3))
        val_loss = float(match.group(4))
        val_acc = float(match.group(5))
        
        # 如果epoch小于等于50，认为是基础训练数据
        if epoch <= 50:
            base_training_data.append({
                'epoch': epoch,
                'train_loss': train_loss,
                'train_acc': train_acc,
                'val_loss': val_loss,
                'val_acc': val_acc
            })
    
    # 提取微调训练数据
    fine_tune_pattern = r'Fine-tuning Epoch (\d+)/50 - Train Acc: ([\d.]+), Val Acc: ([\d.]+)'
    fine_tune_matches = re.finditer(fine_tune_pattern, content)
    
    for match in fine_tune_matches:
        epoch = int(match.group(1))
        train_acc = float(match.group(2))
        val_acc = float(match.group(3))
        
        fine_tuning_data.append({
            'epoch': epoch,
            'train_acc': train_acc,
            'val_acc': val_acc
        })
    
    # 转换为DataFrame并保存为CSV
    if base_training_data:
        base_df = pd.DataFrame(base_training_data)
        base_df.to_csv('base_training_metrics.csv', index=False)
        print(f"基础训练数据已保存到 base_training_metrics.csv，共 {len(base_training_data)} 条记录")
    
    if fine_tuning_data:
        fine_tune_df = pd.DataFrame(fine_tuning_data)
        fine_tune_df.to_csv('fine_tuning_metrics.csv', index=False)
        print(f"微调训练数据已保存到 fine_tuning_metrics.csv，共 {len(fine_tuning_data)} 条记录")

if __name__ == '__main__':
    # 指定日志文件路径
    log_file_path = '2025-04-11_14-13-49_train.log'
    parse_log_file(log_file_path)