diff --git "a/competition/14c_GLM-4-9b_p2_analysis.ipynb" "b/competition/14c_GLM-4-9b_p2_analysis.ipynb"
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+++ "b/competition/14c_GLM-4-9b_p2_analysis.ipynb"
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+{"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":5,"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>THUDM/glm-4-9b-chat-1m</th>\n","      <th>THUDM/glm-4-9b-chat-1m_checkpoint-175</th>\n","      <th>THUDM/glm-4-9b-chat-1m_checkpoint-350</th>\n","      <th>THUDM/glm-4-9b-chat-1m_checkpoint-525</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>回答：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","    </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>回答正确</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","    </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>不重要</td>\n","      <td>不是</td>\n","      <td>问法错误</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","    </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>不重要</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</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>不重要</td>\n","      <td>不是</td>\n","      <td>不重要</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","    </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","    </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>不重要</td>\n","      <td>不是</td>\n","      <td>不重要</td>\n","      <td>不重要</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>3000 rows × 9 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","     THUDM/glm-4-9b-chat-1m THUDM/glm-4-9b-chat-1m_checkpoint-175  \\\n","0                     回答：不是                                    不是   \n","1                         是                                     是   \n","2                      回答正确                                     是   \n","3                         是                                     是   \n","4                       不重要                                    不是   \n","...                     ...                                   ...   \n","2995                    不重要                                     是   \n","2996                    不重要                                    不是   \n","2997                      是                                     是   \n","2998                      是                                     是   \n","2999                    不重要                                    不是   \n","\n","     THUDM/glm-4-9b-chat-1m_checkpoint-350  \\\n","0                                       不是   \n","1                                        是   \n","2                                        是   \n","3                                        是   \n","4                                     问法错误   \n","...                                    ...   \n","2995                                     是   \n","2996                                   不重要   \n","2997                                     是   \n","2998                                     是   \n","2999                                   不重要   \n","\n","     THUDM/glm-4-9b-chat-1m_checkpoint-525  \n","0                                       不是  \n","1                                        是  \n","2                                        是  \n","3                                        是  \n","4                                       不是  \n","...                                    ...  \n","2995                                     是  \n","2996                                    不是  \n","2997                                     是  \n","2998                                     是  \n","2999                                   不重要  \n","\n","[3000 rows x 9 columns]"]},"execution_count":5,"metadata":{},"output_type":"execute_result"}],"source":["import pandas as pd\n","\n","df = pd.read_csv(\"results/glm-4-9b_lora_sft_bf16-p2.csv\")\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"," 'THUDM/glm-4-9b-chat-1m',\n"," 'THUDM/glm-4-9b-chat-1m_checkpoint-175',\n"," 'THUDM/glm-4-9b-chat-1m_checkpoint-350',\n"," 'THUDM/glm-4-9b-chat-1m_checkpoint-525']"]},"execution_count":7,"metadata":{},"output_type":"execute_result"}],"source":["df.columns.to_list()"]},{"cell_type":"code","execution_count":8,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["********** THUDM/glm-4-9b-chat-1m **********\n","THUDM/glm-4-9b-chat-1m\n","不重要       1204\n","是          859\n","不是         557\n","问法错误       197\n","回答正确       165\n","回答：不重要       9\n","回答：是         8\n","回答：不是        1\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":["********** THUDM/glm-4-9b-chat-1m_checkpoint-175 **********\n","THUDM/glm-4-9b-chat-1m_checkpoint-175\n","不是      1378\n","是        917\n","不重要      679\n","问法错误      17\n","回答正确       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":["********** THUDM/glm-4-9b-chat-1m_checkpoint-350 **********\n","THUDM/glm-4-9b-chat-1m_checkpoint-350\n","不是      1372\n","不重要      790\n","是        715\n","问法错误      87\n","回答正确      36\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":["********** THUDM/glm-4-9b-chat-1m_checkpoint-525 **********\n","THUDM/glm-4-9b-chat-1m_checkpoint-525\n","不是      1633\n","是        666\n","不重要      591\n","问法错误      78\n","回答正确      32\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":9,"metadata":{},"outputs":[],"source":["import re\n","\n","\n","def extract_exact_answer(match_obj):\n","    if match_obj.group(1) is not None:\n","        # print(match_obj.group(1))\n","        return match_obj.group(1)"]},{"cell_type":"code","execution_count":10,"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: (\n","            re.sub(r\"回答.*(不重要|是|不是|问法错误|回答正确)\", extract_exact_answer, x)\n","            .replace(\"是男孩\", \"是\")\n","            .replace(\"是\\n问法错误\", \"问法错误\")\n","            .replace(\"。\", \"\")\n","            .strip()\n","            if isinstance(x, str)\n","            else x\n","        )\n","    )\n","    return df"]},{"cell_type":"code","execution_count":11,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["********** THUDM/glm-4-9b-chat-1m **********\n","THUDM/glm-4-9b-chat-1m\n","不重要     1213\n","是        868\n","不是       557\n","问法错误     197\n","回答正确     165\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":["********** THUDM/glm-4-9b-chat-1m_checkpoint-175 **********\n","THUDM/glm-4-9b-chat-1m_checkpoint-175\n","不是      1378\n","是        917\n","不重要      679\n","问法错误      17\n","回答正确       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":["********** THUDM/glm-4-9b-chat-1m_checkpoint-350 **********\n","THUDM/glm-4-9b-chat-1m_checkpoint-350\n","不是      1372\n","不重要      790\n","是        715\n","问法错误      87\n","回答正确      36\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":["********** THUDM/glm-4-9b-chat-1m_checkpoint-525 **********\n","THUDM/glm-4-9b-chat-1m_checkpoint-525\n","不是      1633\n","是        666\n","不重要      591\n","问法错误      78\n","回答正确      32\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","    df = clean_up(df, col)\n","    print(\"*\" * 10, col, \"*\" * 10)\n","    print(df[col].value_counts())\n","    plot_value_counts(df, col)"]},{"cell_type":"code","execution_count":12,"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","    try:\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","    except Exception as e:\n","        print(e)\n","        accuracy = precision = recall = f1 = np.nan\n","\n","    return accuracy, float(precision), float(recall), float(f1)"]},{"cell_type":"code","execution_count":13,"metadata":{},"outputs":[{"name":"stderr","output_type":"stream","text":["/var/folders/7x/56svhln929zdh2xhr3mwqg4r0000gn/T/ipykernel_90673/961288552.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>THUDM/glm-4-9b-chat-1m</td>\n","      <td>0.395000</td>\n","      <td>0.667648</td>\n","      <td>0.395000</td>\n","      <td>0.458390</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>1</td>\n","      <td>THUDM/glm-4-9b-chat-1m_checkpoint-175</td>\n","      <td>0.594667</td>\n","      <td>0.705625</td>\n","      <td>0.594667</td>\n","      <td>0.631524</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>2</td>\n","      <td>THUDM/glm-4-9b-chat-1m_checkpoint-350</td>\n","      <td>0.549000</td>\n","      <td>0.700654</td>\n","      <td>0.549000</td>\n","      <td>0.595640</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>3</td>\n","      <td>THUDM/glm-4-9b-chat-1m_checkpoint-525</td>\n","      <td>0.598667</td>\n","      <td>0.715051</td>\n","      <td>0.598667</td>\n","      <td>0.625357</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["  epoch                                  model  accuracy  precision    recall  \\\n","0     0                 THUDM/glm-4-9b-chat-1m  0.395000   0.667648  0.395000   \n","1     1  THUDM/glm-4-9b-chat-1m_checkpoint-175  0.594667   0.705625  0.594667   \n","2     2  THUDM/glm-4-9b-chat-1m_checkpoint-350  0.549000   0.700654  0.549000   \n","3     3  THUDM/glm-4-9b-chat-1m_checkpoint-525  0.598667   0.715051  0.598667   \n","\n","         f1  \n","0  0.458390  \n","1  0.631524  \n","2  0.595640  \n","3  0.625357  "]},"execution_count":13,"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":14,"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():.3f}\",\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, 1-4: 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()"]},{"cell_type":"code","execution_count":15,"metadata":{},"outputs":[],"source":["perf_df.to_csv(\"results/mgtv-glm-4-9b_p2_full_metrics.csv\", index=False)"]}],"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}