{"cells":[{"cell_type":"code","execution_count":1,"metadata":{"application/vnd.databricks.v1+cell":{"cellMetadata":{},"inputWidgets":{},"nuid":"0ea8b46b-839b-445b-8043-ccdf4e920ace","showTitle":false,"title":""},"id":"YLH80COBzi_F"},"outputs":[],"source":["%load_ext autoreload\n","%autoreload 2"]},{"cell_type":"code","execution_count":2,"metadata":{"id":"63B5exAuzq4M"},"outputs":[],"source":["from pathlib import Path\n","\n","try:\n","    from google.colab import drive\n","    drive.mount('/content/drive')\n","    workding_dir = \"/content/drive/MyDrive/logical-reasoning/\"\n","except ModuleNotFoundError:\n","    workding_dir = str(Path.cwd().parent)"]},{"cell_type":"code","execution_count":3,"metadata":{"executionInfo":{"elapsed":368,"status":"ok","timestamp":1719461634865,"user":{"displayName":"Donghao Huang","userId":"00463591218503521679"},"user_tz":-480},"id":"zFulf0bg0H-9","outputId":"debdd535-c828-40b9-efc0-8a180e5830dd"},"outputs":[{"name":"stdout","output_type":"stream","text":["workding dir: /Users/inflaton/code/engd/projects/logical-reasoning\n"]}],"source":["import os\n","import sys\n","\n","os.chdir(workding_dir)\n","sys.path.append(workding_dir)\n","print(\"workding dir:\", workding_dir)"]},{"cell_type":"code","execution_count":4,"metadata":{"application/vnd.databricks.v1+cell":{"cellMetadata":{},"inputWidgets":{},"nuid":"9f67ec60-2f24-411c-84eb-0dd664b44775","showTitle":false,"title":""},"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":589,"status":"ok","timestamp":1719462011879,"user":{"displayName":"Donghao Huang","userId":"00463591218503521679"},"user_tz":-480},"id":"DIUiweYYzi_I","outputId":"e16e9247-9077-4b0c-f8ea-17059f05a1c4"},"outputs":[{"name":"stdout","output_type":"stream","text":["loading env vars from: /Users/inflaton/code/engd/projects/logical-reasoning/.env\n"]},{"data":{"text/plain":["True"]},"execution_count":4,"metadata":{},"output_type":"execute_result"}],"source":["from dotenv import find_dotenv, load_dotenv\n","\n","found_dotenv = find_dotenv(\".env\")\n","\n","if len(found_dotenv) == 0:\n","    found_dotenv = find_dotenv(\".env.example\")\n","print(f\"loading env vars from: {found_dotenv}\")\n","load_dotenv(found_dotenv, override=True)"]},{"cell_type":"code","execution_count":17,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["internlm/internlm2_5-7b-chat-1m llama-factory/saves/internlm2_5_7b/lora/sft_bf16_p2_full_r2/checkpoint-175 False datasets/mgtv results/mgtv-results_m3.csv\n"]}],"source":["import os\n","\n","model_name = os.getenv(\"MODEL_NAME\")\n","adapter_name_or_path = os.getenv(\"ADAPTER_NAME_OR_PATH\")\n","load_in_4bit = os.getenv(\"LOAD_IN_4BIT\") == \"true\"\n","data_path = os.getenv(\"LOGICAL_REASONING_DATA_PATH\")\n","results_path = os.getenv(\"LOGICAL_REASONING_RESULTS_PATH\")\n","use_english_datasets = os.getenv(\"USE_ENGLISH_DATASETS\") == \"true\"\n","\n","print(model_name, adapter_name_or_path, load_in_4bit, data_path, results_path)"]},{"cell_type":"code","execution_count":5,"metadata":{"id":"4hQO8gkFzi_K"},"outputs":[],"source":["import pandas as pd\n","\n","df = pd.read_csv(\"datasets/mgtv/train_en.csv\")"]},{"cell_type":"code","execution_count":6,"metadata":{"id":"W2QyVreqhOGM","outputId":"68b9590e-1ac6-4c6f-e0c4-e273ec816419"},"outputs":[{"name":"stdout","output_type":"stream","text":["<class 'pandas.core.frame.DataFrame'>\n","RangeIndex: 25000 entries, 0 to 24999\n","Data columns (total 6 columns):\n"," #   Column  Non-Null Count  Dtype  \n","---  ------  --------------  -----  \n"," 0   text    25000 non-null  object \n"," 1   label   25000 non-null  object \n"," 2   answer  0 non-null      float64\n"," 3   title   25000 non-null  object \n"," 4   puzzle  25000 non-null  object \n"," 5   truth   25000 non-null  object \n","dtypes: float64(1), object(5)\n","memory usage: 1.1+ MB\n"]}],"source":["df.info()"]},{"cell_type":"code","execution_count":7,"metadata":{"id":"8mOMrIurhOGN","outputId":"1870d855-7c18-4850-eb88-302acad05719"},"outputs":[{"data":{"text/plain":["label\n","No                       11783\n","Yes                       6591\n","Unimportant               5076\n","Incorrect questioning      921\n","Correct answer             629\n","Name: count, dtype: int64"]},"execution_count":7,"metadata":{},"output_type":"execute_result"}],"source":["df[\"label\"].value_counts()"]},{"cell_type":"code","execution_count":8,"metadata":{},"outputs":[{"data":{"image/png":"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","text/plain":["<Figure size 1200x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["import matplotlib.pyplot as plt\n","from matplotlib import rcParams\n","\n","\n","plt.figure(figsize=(12, 6))\n","df[\"label\"].value_counts().plot(kind=\"bar\")\n","plt.show()"]},{"cell_type":"code","execution_count":9,"metadata":{},"outputs":[{"data":{"text/plain":["puzzle\n","One night, in the dead of night, Jia Jia and his friends ran out of the longtang on their way home from work, their faces full of terror. In the distance, a trash bin, empty and overturned, lay on the ground. Jia Jia was not a resident of the longtang, nor had he caused any trouble with anyone. What was the reason for his panic?                                                                                                                                                                 10058\n","In the basement of an old residential building. One day, the police received a report that someone had found Zhen Haoqi's body in the basement. There were no signs of a struggle and no obvious suicide tools. The deceased was found sitting in a chair, with a calm expression, as if he had not experienced any pain before death. There was nothing in the basement except for a TV and a table. There was a glass of water on the table, and the TV was still on. What caused Zhen Haoqi's death?     9345\n","One sunny weekend, a strange thing happened in the park. Every afternoon, an elderly man would sit on the same bench and read. But today, when he arrived at the park as usual, he found that his chair was gone. Even more strange was that all the other chairs in the park were in perfect condition, except for his own.                                                                                                                                                                                1719\n","On a quiet stretch of beach, Jing ran back and forth in panic, as if searching for something. His actions caught the attention of other beachgoers, but no one could figure out what he was doing.                                                                                                                                                                                                                                                                                                          1401\n","One night, the archaeologist, Zhenshi, was found dead in his newly-discovered Egyptian tomb. His body was sprawled out on a stone table, and around him were scattered various mysterious Egyptian artifacts. What was even more puzzling was that there were no signs of struggle. Zhenshi's expression was serene, as if he had ended his life in a state of incomprehensible peace.                                                                                                                       866\n","In the mysterious forest, there was a little thatched hut. One day, a fox suddenly burst into the hut, then ran out, then ran back in, and so on, all the way until it was ten times. What was going on?                                                                                                                                                                                                                                                                                                     539\n","One night, a sudden stoppage of the bells on the town clock caused people to wonder what had happened. The next morning, they found the bell tower's manager, Zhuan Dali, missing. The door was locked from the outside, and everything looked normal. The townspeople speculated about what had happened.                                                                                                                                                                                                   510\n","In a sealed room, we found the body of the Jing carpenter. There were no signs of struggle at the scene. The face of the corpse was filled with terror. There was only a bed and a chair in the room. What happened to Jing?                                                                                                                                                                                                                                                                                 131\n","In the mysterious forest, there was a little thatched hut. One day, a bear walked into the hut. But it didn't come to look for food; instead, it started crying. Why was it crying?                                                                                                                                                                                                                                                                                                                          106\n","One night, in a still night, a scream was heard coming from the old mansion. The next morning, people found the body of the famous collector Zhenshu in his study, with some valuable antiques scattered around him. What was even more puzzling was that the study door and windows were all locked from the inside, with no signs of forced entry. What could have caused Zhenshu's death?                                                                                                                  86\n","In the village of Zhen, there is a legend that every year, when the harvest season for pumpkins arrives, one of the largest pumpkins in the field disappears without a trace. The villagers are puzzled by this phenomenon.                                                                                                                                                                                                                                                                                   61\n","During lunch break at the company, everyone noticed that Zhen's desk was now filled with a steaming bowl of soup. But Zhen insisted that no one try it, even not wanting to reveal the contents of the soup. Colleagues discussed it, wondering what the soup was hiding.                                                                                                                                                                                                                                     54\n","One hot summer day, all the watermelons in the Jins' courtyard in the countryside were stolen in the night. The villagers speculated about where they might have gone. Did you know where they went?                                                                                                                                                                                                                                                                                                          49\n","In the deep forest, they found a man's body. The man's name was Zhennan. There were no obvious signs of injury on his body, and there were no signs of struggle. The only strange thing was that he had a green leaf in his hand. After the police investigated, they found that he had been desperately searching for something. Do you know what he was looking for?                                                                                                                                        32\n","Deep in the mountains, they found the body of the young man, with no signs of struggle. Next to him was a extinguished hiking lamp. They learned that he was a solo mountaineer. The night before, he had called his friend and told him that he would conquer a nearby peak the next day. After the investigation, the police ruled out murder. So, how did he die on the mountain?                                                                                                                          23\n","One night, in a quiet library reading room, only the two of them: the librarian and the reader. Suddenly, the reader stood up, looked very nervous, and walked over to the librarian. He asked if he could use the phone. The librarian nodded, but realized that the reader had not dialed the phone, but stood quietly in front of it for a moment before leaving.                                                                                                                                          20\n","Name: count, dtype: int64"]},"execution_count":9,"metadata":{},"output_type":"execute_result"}],"source":["df[\"puzzle\"].value_counts()"]},{"cell_type":"code","execution_count":10,"metadata":{},"outputs":[{"data":{"text/plain":["truth\n","It turned out that Jia Qijia was a petty thief on the run. That night, he was trying to find a target to steal from in the alley. But he was so scared that he didn't even notice a wild cat suddenly jumping out of the trash bin and scaring him. Thinking that the police had caught him, he ran away in a panic. The trash bin was where he had accidentally knocked over while searching for something.                                                                                                                                                                                                                                                                                                                                                10058\n","Although he was a science fiction author, Jindao suffered from severe claustrophobia. He often went to the underground room alone to watch science fiction movies in the hope of finding inspiration. Unfortunately, one day he was watching a movie when the power went out and the room was plunged into darkness. His claustrophobia flared up, and he panicked, thinking he was trapped in an unknown universe. In this extreme state of fear, he suffered a heart attack and died peacefully. His expression was calm, as if he had no pain. The water on the table and the TV were just things he did every day in the underground room.                                                                                                               9345\n","The truth was that a gardener had broken a streetlight while trimming some branches the night before. To fix the streetlight, they had moved the long bench over as a ladder. After they were done, they forgot to put the bench back in place, causing the old woman to lose her place. The bench was now lying in the corner of the park, with the inscription, 'I am not a chair, I am a temporary ladder.'                                                                                                                                                                                                                                                                                                                                               1719\n","It turned out that Jind was a volunteer for the environment. On the beach, he found a turtle caught in a fishing net. The turtle was on the brink of death. Jind was in a hurry to find tools to save it. However, his nervousness and anxiety prevented him from clearly expressing his intentions, which led other tourists to think he was looking for lost property.                                                                                                                                                                                                                                                                                                                                                                                     1401\n","During his research into Egyptian artifacts, Zhenduo discovered a rare magic stone. As he delved deeper into the stone, he inadvertently activated a curse. The curse would make anyone who touched it see their most desired thing in a dream, and then enter a state of false death. In reality, Zhenduo experienced the scene of returning to the golden age of ancient Egypt, and was satisfied with his death. No one could understand this except those who saw his death.                                                                                                                                                                                                                                                                              866\n","It turned out that the fox had eaten a fruit that had the power to predict the future. But the fruit also had a side effect: every time it predicted the future, it forgot the previous prediction. As it repeatedly entered and left the hut, the fox was trying to recall the fragments of its most recent prediction: 'It will be able to find my dinner in the corner of the hut.' This explanation made the other animals laugh. The fox's strange behavior was actually just to find dinner.                                                                                                                                                                                                                                                            539\n","The truth was that the bell tower's maintenance attendant, Zhong Lu Tower Manager Jin Dali, had fallen from the top of the bell tower in the middle of the night, but he was not dead. He had only gone into a coma. He had hit the clock mechanism that controls the clock's bells when he fell, causing the bells to stop ringing. He was lying on the bottom of the bell tower, but the door was locked from the inside, so no one could get to him. When he woke up in the middle of the afternoon the next day, he found himself in the middle of a panic in the town.                                                                                                                                                                                   510\n","It turned out that the craftsman had a serious heart disease, but he had been keeping it a secret. On the day of the accident, he was alone in his workshop, sawing wood, when a tiny splinter from a piece of wood pierced his foot. Since he had a heart condition, the infection from the splinter caused his heart to stop beating, and he died. Since the workshop door and window were locked and there was no one else around, the secret was kept hidden. It wasn't until the truth was finally revealed that the villagers realized what had happened.                                                                                                                                                                                               131\n","It turned out that this bear was a big fan of the show. It had been watching the bear-themed series all along. That day, it happened to see the bear protagonist weeping because he had lost his favorite toy. The bear was so moved that it couldn't help shedding tears. The tiny thatched hut was its secret hideout, and the other animals in the forest thought the bear was weeping because he couldn't find food, but in fact, he was just weeping because the bear-themed series was over.                                                                                                                                                                                                                                                            106\n","The truth was that Mr. Zhen had accidentally discovered a legendary poison ring in the collectibles market. Legend had it that this ring once belonged to a medieval wizard, and the gem set in the ring contained a deadly poison. Mr. Zhen was very interested in this poison ring and bought it. However, while playing with the poison ring, he accidentally dropped it on the ground, causing the gem on the ring to crack and release lethal gas. Because the study's doors and windows were tightly closed, the poisonous gas circulated indoors, and Mr. Zhen couldn't escape, ultimately dying of suffocation. As for the antiques scattered on the floor, it was because Mr. Zhen struggled in agony under the influence of the poisonous gas.       86\n","The truth turned out to be related to an old farmer. When he was young, he had fallen in love with a beautiful girl. They had agreed to marry when the season for harvesting pumpkins arrived. But fate had a way of playing tricks on people. The girl died in a car accident on the wedding day. Heartbroken, the farmer decided to remember his beloved by stealing the largest pumpkins every year and putting them in front of her grave. This act of kindness continued for many years, becoming a mysterious legend in the village.                                                                                                                                                                                                                     61\n","It turned out that Zhen Renzhen had recently been participating in a healthy eating challenge, and this bowl of soup was a low-calorie health soup he made himself. He was unwilling to share because it was his first attempt at cooking, and he was worried that his colleagues wouldn't like it and would make fun of his cooking skills. In addition, he added an herb to the soup that was said to improve alertness, hoping to maintain peak performance in the afternoon's work, which also became a secret he was unwilling to share.                                                                                                                                                                                                                  54\n","It turned out that a huge crow had stolen the bunches of watermelons. The crow had been feeding its young ones and had taken the opportunity to steal the watermelons from the Jins' courtyard. The villagers discovered the crow's nest and found it filled with watermelons. The unexpected truth made everyone laugh. 'The world is really big, and all kinds of things happen!' said the Jins' family head.                                                                                                                                                                                                                                                                                                                                                49\n","Zhen was a botanist. He knew the medicinal value of a rare plant in the forest. His wife was seriously ill and needed this plant to be cured. To save his wife, he ventured into the forest to find this plant. However, he ate a poisonous plant and died from heart attack. Just before he died, he realized his mistake and held the poisonous green leaf tightly, hoping it would serve as a warning to others not to make the same mistake. The plant he was looking for was actually right next to his body.                                                                                                                                                                                                                                             32\n","The truth was that Zhen Qingnian suffered from sleepwalking. That night, while sleepwalking in a tent deep in the mountains, he accidentally fell off a cliff. Due to his unclear consciousness while sleepwalking, he couldn't react to the danger in time, and because the hiking lamp wasn't turned on during his sleepwalking, he couldn't see the path clearly, ultimately leading to the tragedy. The next morning, his friends couldn't contact him and called the police for a search and rescue, finally discovering this unfortunate fact.                                                                                                                                                                                                           23\n","Zhen Duzhe was actually a detective evading pursuit. While researching in the library, he discovered that his pursuers might be close. To confirm his deduction, he borrowed a phone from the librarian to test if it was being tapped. The reason he didn't dial but stood quietly next to the phone was that he was checking for unusual tiny sounds in the receiver, a professional skill of his as a detective. After confirming the phone was safe, he left the library and secretly contacted his colleague using his mobile phone to arrange the next steps and a safe house.                                                                                                                                                                           20\n","Name: count, dtype: int64"]},"execution_count":10,"metadata":{},"output_type":"execute_result"}],"source":["df[\"truth\"].value_counts()"]},{"cell_type":"code","execution_count":11,"metadata":{},"outputs":[{"data":{"text/plain":["(16, 16, 16)"]},"execution_count":11,"metadata":{},"output_type":"execute_result"}],"source":["len(df[\"title\"].value_counts()), len(df[\"puzzle\"].value_counts()), len(df[\"truth\"].value_counts())"]},{"cell_type":"code","execution_count":12,"metadata":{},"outputs":[{"data":{"image/png":"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","text/plain":["<Figure size 1200x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["import matplotlib.pyplot as plt\n","from matplotlib import rcParams\n","\n","\n","plt.figure(figsize=(12, 6))\n","df[\"title\"].value_counts().plot(kind=\"bar\")\n","plt.show()"]},{"cell_type":"code","execution_count":13,"metadata":{},"outputs":[{"data":{"text/plain":["(5, 5, 5)"]},"execution_count":13,"metadata":{},"output_type":"execute_result"}],"source":["df_dev = pd.read_csv(\"datasets/mgtv/dev_en.csv\")\n","len(df_dev[\"title\"].value_counts()), len(df_dev[\"puzzle\"].value_counts()), len(\n","    df_dev[\"truth\"].value_counts()\n",")"]},{"cell_type":"code","execution_count":14,"metadata":{},"outputs":[{"data":{"image/png":"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","text/plain":["<Figure size 1200x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["import matplotlib.pyplot as plt\n","from matplotlib import rcParams\n","\n","\n","plt.figure(figsize=(12, 6))\n","df_dev[\"title\"].value_counts().plot(kind=\"bar\")\n","plt.show()"]},{"cell_type":"code","execution_count":15,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["--------------------------------------------------\n","text: Was Zhen Zhesuo suicide?\n","--------------------------------------------------\n","label: No\n","--------------------------------------------------\n","answer: nan\n","--------------------------------------------------\n","title: The Mystery of the Coast\n","--------------------------------------------------\n","puzzle: In the quiet seaside cottage of a neighbor, a morning in which a body was found on the beach, the cause of death was never determined.\n","--------------------------------------------------\n","truth: Zhen Zhesao was a nature-loving painter who came to this coastal cottage every year to find inspiration. In his final days, he was working on a painting of marine life. The day before the painting was finished, he went out on his bike to watch the night scene at the beach. However, he found a stranded dolphin on the beach and spent a lot of energy trying to rescue it. Exhausted, he fell asleep on the beach, having a heart condition that was so severe that he didn't tell anyone about it. The only evidence of his death was the tire tracks and the unfinished painting.\n"]}],"source":["# print details of the first row\n","for col in df_dev.columns:\n","    print(\"-\" * 50)\n","    print(f\"{col}: {df_dev[col].iloc[0]}\")"]},{"cell_type":"code","execution_count":27,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["loading /Users/inflaton/code/engd/projects/logical-reasoning/llm_toolkit/logical_reasoning_utils.py\n"]}],"source":["from llm_toolkit.logical_reasoning_utils import load_alpaca_data\n","from llm_toolkit.llm_utils import print_row_details"]},{"cell_type":"code","execution_count":26,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["loading existing data from: llama-factory/data/alpaca_mgtv_p1.json\n","--------------------------------------------------\n","instruction: 你是一个逻辑游戏的主持人。游戏规则如下：\n","\n","1. 参与者会得到一个谜题。\n","2. 参与者可以通过提问来获取线索，尝试解开谜题。\n","3. 对于每个问题，主持人将根据实际情况回答以下五个选项之一：是、不是、不重要、回答正确、问法错误。\n","4. 回答中不能添加任何其它信息，也不能省略选项中的任何一个字。例如，不可以把“不是”省略成“不”。\n","5. 参与者需要根据回答来推理，并最终找出谜题的正确答案。\n","\n","请严格按照这些规则回答参与者提出的问题。\n","\n","谜题: 在甄家村里，有一个古老的传说：每年南瓜丰收的季节，南瓜田里总有一个最大的南瓜会不翼而飞，村民们对此现象困惑不解。请找出南瓜失踪背后的原因。\n","\n","实际情况: 真相原来与一位年迈的农夫有关。这位农夫年轻时，曾与一位美丽的姑娘相恋。他们约定在南瓜丰收的季节结婚。然而，命运弄人，姑娘在婚礼前的一场意外中离世。悲伤的农夫为了纪念心爱的姑娘，每年都会将最大的南瓜偷走，放到姑娘的墓前，以此寄托自己的哀思。这一行为延续了多年，成为了乡村里一个神秘的传说。\n","\n","参与者提出的问题: 偷的人信神吗\n","\n","--------------------------------------------------\n","input: \n","--------------------------------------------------\n","output: 不是\n"]}],"source":["alpaca_p1 = load_alpaca_data(data_path, using_p1=True, use_english_datasets=False)\n","print_row_details(alpaca_p1, [0])"]},{"cell_type":"code","execution_count":25,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["loading existing data from: llama-factory/data/alpaca_mgtv_p2.json\n","--------------------------------------------------\n","instruction: 你是一个情景猜谜游戏的主持人。游戏规则如下：\n","\n","1. 参与者会得到一个谜面，谜面会描述一个简单又难以理解的事件。\n","2. 主持人知道谜底，谜底是谜面的答案。\n","3. 参与者可以询问任何封闭式问题来找寻事件的真相。\n","4. 对于每个问题，主持人将根据实际情况回答以下五个选项之一：是、不是、不重要、回答正确、问法错误。各回答的判断标准如下：\n","   - 若谜面和谜底能找到问题的答案，回答：是或者不是\n","   - 若谜面和谜底不能直接或者间接推断出问题的答案，回答：不重要\n","   - 若参与者提问不是一个封闭式问题或者问题难以理解，回答：问法错误\n","   - 若参与者提问基本还原了谜底真相，回答：回答正确\n","5. 回答中不能添加任何其它信息，也不能省略选项中的任何一个字。例如，不可以把“不是”省略成“不”。\n","\n","请严格按照这些规则回答参与者提出的问题。\n","\n","**谜面:** 在甄家村里，有一个古老的传说：每年南瓜丰收的季节，南瓜田里总有一个最大的南瓜会不翼而飞，村民们对此现象困惑不解。请找出南瓜失踪背后的原因。\n","\n","**谜底:** 真相原来与一位年迈的农夫有关。这位农夫年轻时，曾与一位美丽的姑娘相恋。他们约定在南瓜丰收的季节结婚。然而，命运弄人，姑娘在婚礼前的一场意外中离世。悲伤的农夫为了纪念心爱的姑娘，每年都会将最大的南瓜偷走，放到姑娘的墓前，以此寄托自己的哀思。这一行为延续了多年，成为了乡村里一个神秘的传说。\n","\n","**参与者提出的问题:** 偷的人信神吗\n","\n","--------------------------------------------------\n","input: \n","--------------------------------------------------\n","output: 不是\n"]}],"source":["alpaca_p2 = load_alpaca_data(data_path, using_p1=False, use_english_datasets=False)\n","print_row_details(alpaca_p2, [0])"]},{"cell_type":"code","execution_count":30,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["loading new data from: llama-factory/data/alpaca_mgtv_p1_en.json\n","loading train/test data files\n","DatasetDict({\n","    train: Dataset({\n","        features: ['text', 'label', 'answer', 'title', 'puzzle', 'truth'],\n","        num_rows: 25000\n","    })\n","    test: Dataset({\n","        features: ['text', 'label', 'answer', 'title', 'puzzle', 'truth'],\n","        num_rows: 3000\n","    })\n","})\n","--------------------------------------------------\n","instruction: You are the host of a logic game. The rules of the game are as follows:\n","\n","\t1.\tParticipants will receive a puzzle.\n","\t2.\tParticipants can ask questions to obtain clues and try to solve the puzzle.\n","\t3.\tFor each question, the host will answer with one of the following five options based on the actual situation: Yes, No, Unimportant, Correct answer, or Incorrect questioning.\n","\t4.\tThe answer cannot include any additional information, nor can any word in the options be omitted. For example, “No” cannot be shortened to “N”.\n","\t5.\tParticipants need to infer and ultimately find the correct answer to the puzzle based on the responses.\n","\n","Please strictly adhere to these rules when answering participants’ questions.\n","\n","Puzzle: In the village of Zhen, there is a legend that every year, when the harvest season for pumpkins arrives, one of the largest pumpkins in the field disappears without a trace. The villagers are puzzled by this phenomenon.\n","\n","Actual situation: The truth turned out to be related to an old farmer. When he was young, he had fallen in love with a beautiful girl. They had agreed to marry when the season for harvesting pumpkins arrived. But fate had a way of playing tricks on people. The girl died in a car accident on the wedding day. Heartbroken, the farmer decided to remember his beloved by stealing the largest pumpkins every year and putting them in front of her grave. This act of kindness continued for many years, becoming a mysterious legend in the village.\n","\n","Question from participants: Did the thief believe in the gods?\n","--------------------------------------------------\n","input: \n","--------------------------------------------------\n","output: No\n"]}],"source":["alpaca_p1_en = load_alpaca_data(data_path, using_p1=True, use_english_datasets=True)\n","print_row_details(alpaca_p1_en, [0])"]},{"cell_type":"code","execution_count":29,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["loading /Users/inflaton/code/engd/projects/logical-reasoning/llm_toolkit/logical_reasoning_utils.py\n","loading new data from: llama-factory/data/alpaca_mgtv_p2_en.json\n","loading train/test data files\n","DatasetDict({\n","    train: Dataset({\n","        features: ['text', 'label', 'answer', 'title', 'puzzle', 'truth'],\n","        num_rows: 25000\n","    })\n","    test: Dataset({\n","        features: ['text', 'label', 'answer', 'title', 'puzzle', 'truth'],\n","        num_rows: 3000\n","    })\n","})\n","--------------------------------------------------\n","instruction: You are the host of a situational guessing game. The rules of the game are as follows:\n","\n","1. Participants will receive a riddle that describes a simple yet difficult to understand event.\n","2. The host knows the answer, which is the solution to the riddle.\n","3. Participants can ask any closed-ended questions to uncover the truth of the event.\n","4. For each question, the host will respond with one of the following five options based on the actual situation: Yes, No, Unimportant, Correct answer, or Incorrect questioning. The criteria for each response are as follows:\n","   - If the riddle and answer can provide an answer to the question, respond with: Yes or No\n","   - If the riddle and answer cannot directly or indirectly infer an answer to the question, respond with: Unimportant\n","   - If the participant's question is not a closed-ended question or is difficult to understand, respond with: Incorrect questioning\n","   - If the participant's question essentially reveals the truth of the answer, respond with: Correct answer\n","5. The response must not include any additional information, nor should any word be omitted from the options. For example, \"No\" cannot be abbreviated to \"N\".\n","\n","Please strictly follow these rules when answering the participant's questions.\n","\n","**Riddle:** In the village of Zhen, there is a legend that every year, when the harvest season for pumpkins arrives, one of the largest pumpkins in the field disappears without a trace. The villagers are puzzled by this phenomenon.\n","\n","**Answer:** The truth turned out to be related to an old farmer. When he was young, he had fallen in love with a beautiful girl. They had agreed to marry when the season for harvesting pumpkins arrived. But fate had a way of playing tricks on people. The girl died in a car accident on the wedding day. Heartbroken, the farmer decided to remember his beloved by stealing the largest pumpkins every year and putting them in front of her grave. This act of kindness continued for many years, becoming a mysterious legend in the village.\n","\n","**Participant's question:** Did the thief believe in the gods?\n","\n","--------------------------------------------------\n","input: \n","--------------------------------------------------\n","output: No\n"]}],"source":["alpaca_p2_en = load_alpaca_data(data_path, using_p1=False, use_english_datasets=True)\n","print_row_details(alpaca_p2_en, [0])"]}],"metadata":{"accelerator":"GPU","application/vnd.databricks.v1+notebook":{"dashboards":[],"environmentMetadata":null,"language":"python","notebookMetadata":{"pythonIndentUnit":4},"notebookName":"07_MAC_+_Qwen2-7B-Instructi_Unsloth_train","widgets":{}},"colab":{"gpuType":"T4","provenance":[]},"kernelspec":{"display_name":"Python 3","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.11.9"}},"nbformat":4,"nbformat_minor":0}