{"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/Library/CloudStorage/GoogleDrive-dh.huang.2023@smu.edu.sg/My Drive/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/Library/CloudStorage/GoogleDrive-dh.huang.2023@smu.edu.sg/My Drive/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":11,"metadata":{},"outputs":[],"source":["import re\n","\n","\n","def clean_up(df, model_name):\n","    df[model_name] = df[model_name].apply(\n","        lambda x: re.sub(r\"回答.*是\", \"是\", x)\n","        .replace(\"是男孩\", \"是\")\n","        .replace(\"。\", \"\")\n","        .strip()\n","    )\n","    return df"]},{"cell_type":"code","execution_count":12,"metadata":{"id":"W2QyVreqhOGM","outputId":"68b9590e-1ac6-4c6f-e0c4-e273ec816419"},"outputs":[{"data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>text</th>\n","      <th>label</th>\n","      <th>title</th>\n","      <th>puzzle</th>\n","      <th>truth</th>\n","      <th>internlm/internlm2_5-7b-chat-1m</th>\n","      <th>internlm/internlm2_5-7b-chat-1m_checkpoint-562</th>\n","      <th>internlm/internlm2_5-7b-chat-1m_checkpoint-1124</th>\n","      <th>internlm/internlm2_5-7b-chat-1m_checkpoint-1686</th>\n","      <th>internlm/internlm2_5-7b-chat-1m_checkpoint-2248</th>\n","      <th>internlm/internlm2_5-7b-chat-1m_checkpoint-2810</th>\n","      <th>internlm/internlm2_5-7b-chat-1m_checkpoint-3372</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>甄加索是自杀吗</td>\n","      <td>不是</td>\n","      <td>海岸之谜</td>\n","      <td>在远离城市喧嚣的海边小屋，一天清晨，邻居发现甄加索僵卧在沙滩上，已无生命迹象。现场没有发现任...</td>\n","      <td>甄加索是一位热爱自然的画家，他每年都会来到这个海边小屋寻找灵感。在他生命的最后几天，他一直在...</td>\n","      <td>不是</td>\n","      <td>不是</td>\n","      <td>不是</td>\n","      <td>不是</td>\n","      <td>不是</td>\n","      <td>不是</td>\n","      <td>不是</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>甄加索有身体上的疾病吗</td>\n","      <td>是</td>\n","      <td>海岸之谜</td>\n","      <td>在远离城市喧嚣的海边小屋，一天清晨，邻居发现甄加索僵卧在沙滩上，已无生命迹象。现场没有发现任...</td>\n","      <td>甄加索是一位热爱自然的画家，他每年都会来到这个海边小屋寻找灵感。在他生命的最后几天，他一直在...</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>画作是甄的</td>\n","      <td>是</td>\n","      <td>海岸之谜</td>\n","      <td>在远离城市喧嚣的海边小屋，一天清晨，邻居发现甄加索僵卧在沙滩上，已无生命迹象。现场没有发现任...</td>\n","      <td>甄加索是一位热爱自然的画家，他每年都会来到这个海边小屋寻找灵感。在他生命的最后几天，他一直在...</td>\n","      <td>不是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>甄有心脏病吗</td>\n","      <td>是</td>\n","      <td>海岸之谜</td>\n","      <td>在远离城市喧嚣的海边小屋，一天清晨，邻居发现甄加索僵卧在沙滩上，已无生命迹象。现场没有发现任...</td>\n","      <td>甄加索是一位热爱自然的画家，他每年都会来到这个海边小屋寻找灵感。在他生命的最后几天，他一直在...</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>车轮是凶手留下的</td>\n","      <td>不是</td>\n","      <td>海岸之谜</td>\n","      <td>在远离城市喧嚣的海边小屋，一天清晨，邻居发现甄加索僵卧在沙滩上，已无生命迹象。现场没有发现任...</td>\n","      <td>甄加索是一位热爱自然的画家，他每年都会来到这个海边小屋寻找灵感。在他生命的最后几天，他一直在...</td>\n","      <td>不是</td>\n","      <td>不重要</td>\n","      <td>不是</td>\n","      <td>不是</td>\n","      <td>不是</td>\n","      <td>不是</td>\n","      <td>不是</td>\n","    </tr>\n","    <tr>\n","      <th>...</th>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>2995</th>\n","      <td>哭泣者必须在晚上祭奠吗</td>\n","      <td>是</td>\n","      <td>甄庄哭声</td>\n","      <td>在一个安静的夜晚，小村庄的湖边突然传来了阵阵哭泣声。第二天早晨，村长甄锐发现湖边的石头上放着...</td>\n","      <td>原来，这顶破旧的帽子属于一个小男孩，他小时候与爷爷在湖边生活。爷爷教他钓鱼、游泳，还告诉他湖...</td>\n","      <td>不是</td>\n","      <td>不重要</td>\n","      <td>不重要</td>\n","      <td>不重要</td>\n","      <td>不重要</td>\n","      <td>不重要</td>\n","      <td>不重要</td>\n","    </tr>\n","    <tr>\n","      <th>2996</th>\n","      <td>尸体在湖里吗</td>\n","      <td>不是</td>\n","      <td>甄庄哭声</td>\n","      <td>在一个安静的夜晚，小村庄的湖边突然传来了阵阵哭泣声。第二天早晨，村长甄锐发现湖边的石头上放着...</td>\n","      <td>原来，这顶破旧的帽子属于一个小男孩，他小时候与爷爷在湖边生活。爷爷教他钓鱼、游泳，还告诉他湖...</td>\n","      <td>不是</td>\n","      <td>不重要</td>\n","      <td>不重要</td>\n","      <td>不是</td>\n","      <td>不是</td>\n","      <td>不是</td>\n","      <td>不是</td>\n","    </tr>\n","    <tr>\n","      <th>2997</th>\n","      <td>哭泣者和死者有特殊关系吗</td>\n","      <td>是</td>\n","      <td>甄庄哭声</td>\n","      <td>在一个安静的夜晚，小村庄的湖边突然传来了阵阵哭泣声。第二天早晨，村长甄锐发现湖边的石头上放着...</td>\n","      <td>原来，这顶破旧的帽子属于一个小男孩，他小时候与爷爷在湖边生活。爷爷教他钓鱼、游泳，还告诉他湖...</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","    </tr>\n","    <tr>\n","      <th>2998</th>\n","      <td>是帽子的主人去世了吗</td>\n","      <td>不是</td>\n","      <td>甄庄哭声</td>\n","      <td>在一个安静的夜晚，小村庄的湖边突然传来了阵阵哭泣声。第二天早晨，村长甄锐发现湖边的石头上放着...</td>\n","      <td>原来，这顶破旧的帽子属于一个小男孩，他小时候与爷爷在湖边生活。爷爷教他钓鱼、游泳，还告诉他湖...</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","    </tr>\n","    <tr>\n","      <th>2999</th>\n","      <td>死者受伤了吗</td>\n","      <td>不是</td>\n","      <td>甄庄哭声</td>\n","      <td>在一个安静的夜晚，小村庄的湖边突然传来了阵阵哭泣声。第二天早晨，村长甄锐发现湖边的石头上放着...</td>\n","      <td>原来，这顶破旧的帽子属于一个小男孩，他小时候与爷爷在湖边生活。爷爷教他钓鱼、游泳，还告诉他湖...</td>\n","      <td>不是</td>\n","      <td>不重要</td>\n","      <td>不重要</td>\n","      <td>不是</td>\n","      <td>不重要</td>\n","      <td>不是</td>\n","      <td>不重要</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>3000 rows × 12 columns</p>\n","</div>"],"text/plain":["              text label title  \\\n","0          甄加索是自杀吗    不是  海岸之谜   \n","1      甄加索有身体上的疾病吗     是  海岸之谜   \n","2            画作是甄的     是  海岸之谜   \n","3           甄有心脏病吗     是  海岸之谜   \n","4         车轮是凶手留下的    不是  海岸之谜   \n","...            ...   ...   ...   \n","2995   哭泣者必须在晚上祭奠吗     是  甄庄哭声   \n","2996        尸体在湖里吗    不是  甄庄哭声   \n","2997  哭泣者和死者有特殊关系吗     是  甄庄哭声   \n","2998    是帽子的主人去世了吗    不是  甄庄哭声   \n","2999        死者受伤了吗    不是  甄庄哭声   \n","\n","                                                 puzzle  \\\n","0     在远离城市喧嚣的海边小屋，一天清晨，邻居发现甄加索僵卧在沙滩上，已无生命迹象。现场没有发现任...   \n","1     在远离城市喧嚣的海边小屋，一天清晨，邻居发现甄加索僵卧在沙滩上，已无生命迹象。现场没有发现任...   \n","2     在远离城市喧嚣的海边小屋，一天清晨，邻居发现甄加索僵卧在沙滩上，已无生命迹象。现场没有发现任...   \n","3     在远离城市喧嚣的海边小屋，一天清晨，邻居发现甄加索僵卧在沙滩上，已无生命迹象。现场没有发现任...   \n","4     在远离城市喧嚣的海边小屋，一天清晨，邻居发现甄加索僵卧在沙滩上，已无生命迹象。现场没有发现任...   \n","...                                                 ...   \n","2995  在一个安静的夜晚，小村庄的湖边突然传来了阵阵哭泣声。第二天早晨，村长甄锐发现湖边的石头上放着...   \n","2996  在一个安静的夜晚，小村庄的湖边突然传来了阵阵哭泣声。第二天早晨，村长甄锐发现湖边的石头上放着...   \n","2997  在一个安静的夜晚，小村庄的湖边突然传来了阵阵哭泣声。第二天早晨，村长甄锐发现湖边的石头上放着...   \n","2998  在一个安静的夜晚，小村庄的湖边突然传来了阵阵哭泣声。第二天早晨，村长甄锐发现湖边的石头上放着...   \n","2999  在一个安静的夜晚，小村庄的湖边突然传来了阵阵哭泣声。第二天早晨，村长甄锐发现湖边的石头上放着...   \n","\n","                                                  truth  \\\n","0     甄加索是一位热爱自然的画家，他每年都会来到这个海边小屋寻找灵感。在他生命的最后几天，他一直在...   \n","1     甄加索是一位热爱自然的画家，他每年都会来到这个海边小屋寻找灵感。在他生命的最后几天，他一直在...   \n","2     甄加索是一位热爱自然的画家，他每年都会来到这个海边小屋寻找灵感。在他生命的最后几天，他一直在...   \n","3     甄加索是一位热爱自然的画家，他每年都会来到这个海边小屋寻找灵感。在他生命的最后几天，他一直在...   \n","4     甄加索是一位热爱自然的画家，他每年都会来到这个海边小屋寻找灵感。在他生命的最后几天，他一直在...   \n","...                                                 ...   \n","2995  原来，这顶破旧的帽子属于一个小男孩，他小时候与爷爷在湖边生活。爷爷教他钓鱼、游泳，还告诉他湖...   \n","2996  原来，这顶破旧的帽子属于一个小男孩，他小时候与爷爷在湖边生活。爷爷教他钓鱼、游泳，还告诉他湖...   \n","2997  原来，这顶破旧的帽子属于一个小男孩，他小时候与爷爷在湖边生活。爷爷教他钓鱼、游泳，还告诉他湖...   \n","2998  原来，这顶破旧的帽子属于一个小男孩，他小时候与爷爷在湖边生活。爷爷教他钓鱼、游泳，还告诉他湖...   \n","2999  原来，这顶破旧的帽子属于一个小男孩，他小时候与爷爷在湖边生活。爷爷教他钓鱼、游泳，还告诉他湖...   \n","\n","     internlm/internlm2_5-7b-chat-1m  \\\n","0                                 不是   \n","1                                  是   \n","2                                 不是   \n","3                                  是   \n","4                                 不是   \n","...                              ...   \n","2995                              不是   \n","2996                              不是   \n","2997                               是   \n","2998                               是   \n","2999                              不是   \n","\n","     internlm/internlm2_5-7b-chat-1m_checkpoint-562  \\\n","0                                                不是   \n","1                                                 是   \n","2                                                 是   \n","3                                                 是   \n","4                                               不重要   \n","...                                             ...   \n","2995                                            不重要   \n","2996                                            不重要   \n","2997                                              是   \n","2998                                              是   \n","2999                                            不重要   \n","\n","     internlm/internlm2_5-7b-chat-1m_checkpoint-1124  \\\n","0                                                 不是   \n","1                                                  是   \n","2                                                  是   \n","3                                                  是   \n","4                                                 不是   \n","...                                              ...   \n","2995                                             不重要   \n","2996                                             不重要   \n","2997                                               是   \n","2998                                               是   \n","2999                                             不重要   \n","\n","     internlm/internlm2_5-7b-chat-1m_checkpoint-1686  \\\n","0                                                 不是   \n","1                                                  是   \n","2                                                  是   \n","3                                                  是   \n","4                                                 不是   \n","...                                              ...   \n","2995                                             不重要   \n","2996                                              不是   \n","2997                                               是   \n","2998                                               是   \n","2999                                              不是   \n","\n","     internlm/internlm2_5-7b-chat-1m_checkpoint-2248  \\\n","0                                                 不是   \n","1                                                  是   \n","2                                                  是   \n","3                                                  是   \n","4                                                 不是   \n","...                                              ...   \n","2995                                             不重要   \n","2996                                              不是   \n","2997                                               是   \n","2998                                               是   \n","2999                                             不重要   \n","\n","     internlm/internlm2_5-7b-chat-1m_checkpoint-2810  \\\n","0                                                 不是   \n","1                                                  是   \n","2                                                  是   \n","3                                                  是   \n","4                                                 不是   \n","...                                              ...   \n","2995                                             不重要   \n","2996                                              不是   \n","2997                                               是   \n","2998                                               是   \n","2999                                              不是   \n","\n","     internlm/internlm2_5-7b-chat-1m_checkpoint-3372  \n","0                                                 不是  \n","1                                                  是  \n","2                                                  是  \n","3                                                  是  \n","4                                                 不是  \n","...                                              ...  \n","2995                                             不重要  \n","2996                                              不是  \n","2997                                               是  \n","2998                                               是  \n","2999                                             不重要  \n","\n","[3000 rows x 12 columns]"]},"execution_count":12,"metadata":{},"output_type":"execute_result"}],"source":["import pandas as pd\n","\n","df = pd.read_csv(\"results/mgtv-results_nv4080_r2.csv\")\n","df = clean_up(df, \"internlm/internlm2_5-7b-chat-1m\")\n","df"]},{"cell_type":"code","execution_count":6,"metadata":{},"outputs":[],"source":["import matplotlib.pyplot as plt\n","from matplotlib import rcParams\n","\n","def plot_value_counts(df, column):\n","    font_family = rcParams[\"font.family\"]\n","    # Set the font to SimHei to support Chinese characters\n","    rcParams[\"font.family\"] = \"STHeiti\"\n","    rcParams[\"axes.unicode_minus\"] = False  # This is to support the minus sign in Chinese.\n","\n","    plt.figure(figsize=(12, 6))\n","    df[column].value_counts().plot(kind=\"bar\")\n","    # add values on top of bars\n","    for i, v in enumerate(df[column].value_counts()):\n","        plt.text(i, v + 0.1, str(v), ha=\"center\")\n","    plt.show()\n","    \n","    rcParams[\"font.family\"] = font_family\n"]},{"cell_type":"code","execution_count":7,"metadata":{},"outputs":[{"data":{"text/plain":["['text',\n"," 'label',\n"," 'title',\n"," 'puzzle',\n"," 'truth',\n"," 'internlm/internlm2_5-7b-chat-1m',\n"," 'internlm/internlm2_5-7b-chat-1m_checkpoint-562',\n"," 'internlm/internlm2_5-7b-chat-1m_checkpoint-1124',\n"," 'internlm/internlm2_5-7b-chat-1m_checkpoint-1686',\n"," 'internlm/internlm2_5-7b-chat-1m_checkpoint-2248',\n"," 'internlm/internlm2_5-7b-chat-1m_checkpoint-2810',\n"," 'internlm/internlm2_5-7b-chat-1m_checkpoint-3372']"]},"execution_count":7,"metadata":{},"output_type":"execute_result"}],"source":["df.columns.to_list()"]},{"cell_type":"code","execution_count":13,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["********** internlm/internlm2_5-7b-chat-1m **********\n","internlm/internlm2_5-7b-chat-1m\n","不是     1670\n","是      1284\n","不重要      46\n","Name: count, dtype: int64\n"]},{"data":{"image/png":"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","text/plain":["<Figure size 1200x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"},{"name":"stdout","output_type":"stream","text":["********** internlm/internlm2_5-7b-chat-1m_checkpoint-562 **********\n","internlm/internlm2_5-7b-chat-1m_checkpoint-562\n","不重要     1828\n","是        875\n","不是       257\n","回答正确      28\n","问法错误      12\n","Name: count, dtype: int64\n"]},{"data":{"image/png":"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","text/plain":["<Figure size 1200x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"},{"name":"stdout","output_type":"stream","text":["********** internlm/internlm2_5-7b-chat-1m_checkpoint-1124 **********\n","internlm/internlm2_5-7b-chat-1m_checkpoint-1124\n","是       1069\n","不是       966\n","不重要      946\n","回答正确      10\n","问法错误       9\n","Name: count, dtype: int64\n"]},{"data":{"image/png":"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","text/plain":["<Figure size 1200x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"},{"name":"stdout","output_type":"stream","text":["********** internlm/internlm2_5-7b-chat-1m_checkpoint-1686 **********\n","internlm/internlm2_5-7b-chat-1m_checkpoint-1686\n","不是      1581\n","是        999\n","不重要      383\n","回答正确      24\n","问法错误      13\n","Name: count, dtype: int64\n"]},{"data":{"image/png":"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","text/plain":["<Figure size 1200x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"},{"name":"stdout","output_type":"stream","text":["********** internlm/internlm2_5-7b-chat-1m_checkpoint-2248 **********\n","internlm/internlm2_5-7b-chat-1m_checkpoint-2248\n","不是      1490\n","是        878\n","不重要      563\n","问法错误      45\n","回答正确      24\n","Name: count, dtype: int64\n"]},{"data":{"image/png":"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","text/plain":["<Figure size 1200x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"},{"name":"stdout","output_type":"stream","text":["********** internlm/internlm2_5-7b-chat-1m_checkpoint-2810 **********\n","internlm/internlm2_5-7b-chat-1m_checkpoint-2810\n","不是      1342\n","是       1060\n","不重要      544\n","回答正确      31\n","问法错误      23\n","Name: count, dtype: int64\n"]},{"data":{"image/png":"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","text/plain":["<Figure size 1200x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"},{"name":"stdout","output_type":"stream","text":["********** internlm/internlm2_5-7b-chat-1m_checkpoint-3372 **********\n","internlm/internlm2_5-7b-chat-1m_checkpoint-3372\n","不是      1338\n","是       1006\n","不重要      598\n","回答正确      30\n","问法错误      28\n","Name: count, dtype: int64\n"]},{"data":{"image/png":"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","text/plain":["<Figure size 1200x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["for col in df.columns[5:]:\n","    print(\"*\" * 10, col, \"*\" * 10)\n","    print(df[col].value_counts())\n","    plot_value_counts(df, col)"]},{"cell_type":"code","execution_count":15,"metadata":{},"outputs":[],"source":["import pandas as pd\n","import numpy as np\n","from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score\n","\n","\n","def calc_metrics_for_col(df, col):\n","    y_true = df[\"label\"]\n","    y_pred = df[col]\n","\n","    accuracy = accuracy_score(y_true, y_pred)\n","    precision = precision_score(y_true, y_pred, average=\"weighted\", labels=np.unique(y_pred))\n","    recall = recall_score(y_true, y_pred, average=\"weighted\", labels=np.unique(y_pred))\n","    f1 = f1_score(y_true, y_pred, average=\"weighted\", labels=np.unique(y_pred))\n","\n","    return accuracy, float(precision), float(recall), float(f1)"]},{"cell_type":"code","execution_count":19,"metadata":{},"outputs":[{"name":"stderr","output_type":"stream","text":["/var/folders/7x/56svhln929zdh2xhr3mwqg4r0000gn/T/ipykernel_34085/961288552.py:9: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation.\n","  perf_df = pd.concat([perf_df, pd.DataFrame([new_model_metrics])], ignore_index=True)\n"]},{"data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>epoch</th>\n","      <th>model</th>\n","      <th>accuracy</th>\n","      <th>precision</th>\n","      <th>recall</th>\n","      <th>f1</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>0</td>\n","      <td>internlm/internlm2_5-7b-chat-1m</td>\n","      <td>0.759667</td>\n","      <td>0.741854</td>\n","      <td>0.781014</td>\n","      <td>0.758887</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>1</td>\n","      <td>internlm/internlm2_5-7b-chat-1m_checkpoint-562</td>\n","      <td>0.392000</td>\n","      <td>0.865731</td>\n","      <td>0.392000</td>\n","      <td>0.459125</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>2</td>\n","      <td>internlm/internlm2_5-7b-chat-1m_checkpoint-1124</td>\n","      <td>0.611000</td>\n","      <td>0.807798</td>\n","      <td>0.611000</td>\n","      <td>0.674668</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>3</td>\n","      <td>internlm/internlm2_5-7b-chat-1m_checkpoint-1686</td>\n","      <td>0.713667</td>\n","      <td>0.761735</td>\n","      <td>0.713667</td>\n","      <td>0.728502</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>4</td>\n","      <td>internlm/internlm2_5-7b-chat-1m_checkpoint-2248</td>\n","      <td>0.653000</td>\n","      <td>0.749475</td>\n","      <td>0.653000</td>\n","      <td>0.685228</td>\n","    </tr>\n","    <tr>\n","      <th>5</th>\n","      <td>5</td>\n","      <td>internlm/internlm2_5-7b-chat-1m_checkpoint-2810</td>\n","      <td>0.684667</td>\n","      <td>0.769066</td>\n","      <td>0.684667</td>\n","      <td>0.716450</td>\n","    </tr>\n","    <tr>\n","      <th>6</th>\n","      <td>6</td>\n","      <td>internlm/internlm2_5-7b-chat-1m_checkpoint-3372</td>\n","      <td>0.668333</td>\n","      <td>0.767219</td>\n","      <td>0.668333</td>\n","      <td>0.705321</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["  epoch                                            model  accuracy  precision  \\\n","0     0                  internlm/internlm2_5-7b-chat-1m  0.759667   0.741854   \n","1     1   internlm/internlm2_5-7b-chat-1m_checkpoint-562  0.392000   0.865731   \n","2     2  internlm/internlm2_5-7b-chat-1m_checkpoint-1124  0.611000   0.807798   \n","3     3  internlm/internlm2_5-7b-chat-1m_checkpoint-1686  0.713667   0.761735   \n","4     4  internlm/internlm2_5-7b-chat-1m_checkpoint-2248  0.653000   0.749475   \n","5     5  internlm/internlm2_5-7b-chat-1m_checkpoint-2810  0.684667   0.769066   \n","6     6  internlm/internlm2_5-7b-chat-1m_checkpoint-3372  0.668333   0.767219   \n","\n","     recall        f1  \n","0  0.781014  0.758887  \n","1  0.392000  0.459125  \n","2  0.611000  0.674668  \n","3  0.713667  0.728502  \n","4  0.653000  0.685228  \n","5  0.684667  0.716450  \n","6  0.668333  0.705321  "]},"execution_count":19,"metadata":{},"output_type":"execute_result"}],"source":["import pandas as pd\n","\n","perf_df = pd.DataFrame(columns=[\"epoch\", \"model\", \"accuracy\", \"precision\", \"recall\", \"f1\"])\n","for i, col in enumerate(df.columns[5:]):\n","    accuracy, precision, recall, f1 = calc_metrics_for_col(df, col)\n","    new_model_metrics = {\"epoch\": i, \"model\": col, \"accuracy\": accuracy, \"precision\": precision, \"recall\": recall, \"f1\": f1}\n","\n","    # Convert the dictionary to a DataFrame and concatenate it with the existing DataFrame\n","    perf_df = pd.concat([perf_df, pd.DataFrame([new_model_metrics])], ignore_index=True)\n","\n","perf_df"]},{"cell_type":"code","execution_count":24,"metadata":{},"outputs":[{"data":{"image/png":"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","text/plain":["<Figure size 1200x500 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["# plot metrics for each model\n","import matplotlib.pyplot as plt\n","\n","fig, ax = plt.subplots(1, 1, figsize=(12, 5))\n","\n","perf_df.plot(x=\"epoch\", y=[\"accuracy\", \"precision\", \"recall\", \"f1\"], kind=\"bar\", ax=ax)\n","\n","# add values on top of bars\n","for p in ax.patches:\n","    ax.annotate(\n","        f\"{p.get_height():.2f}\",\n","        (p.get_x() + p.get_width() / 2, p.get_height()),\n","        ha=\"center\",\n","        va=\"bottom\",\n","        fontsize=10,\n","    )\n","\n","# add title and labels\n","# ax.set_title(\"Metrics for different settings\")\n","# ax.set_ylabel(\"Value\")\n","ax.set_xlabel(\"Epoch (0: base model, 1-6: fine-tuned models)\")\n","# rotate x labels\n","plt.xticks(rotation=0)\n","\n","# set legend at the right to avoid overlapping with bars\n","plt.legend(loc=\"center left\", bbox_to_anchor=(1.0, 0.5))\n","# plt.tight_layout()\n","\n","plt.show()"]}],"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}