{"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>hfl/llama-3-chinese-8b-instruct-v3_torch.bfloat16_lf</th>\n","      <th>hfl/llama-3-chinese-8b-instruct-v3/checkpoint-35_torch.bfloat16_lf</th>\n","      <th>hfl/llama-3-chinese-8b-instruct-v3/checkpoint-70_torch.bfloat16_lf</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","    </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>回答正确。</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","    </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>回答正确。</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>回答：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","    </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>回答正确。</td>\n","      <td>是</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>不重要。</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>回答正确。</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>回答正确。</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>回答正确。</td>\n","      <td>不是</td>\n","      <td>不是</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>3000 rows × 8 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","     hfl/llama-3-chinese-8b-instruct-v3_torch.bfloat16_lf  \\\n","0                                                 回答：不是     \n","1                                                 回答正确。     \n","2                                                 回答正确。     \n","3                                                 回答正确。     \n","4                                                 回答：不是     \n","...                                                 ...     \n","2995                                              回答正确。     \n","2996                                               不重要。     \n","2997                                              回答正确。     \n","2998                                              回答正确。     \n","2999                                              回答正确。     \n","\n","     hfl/llama-3-chinese-8b-instruct-v3/checkpoint-35_torch.bfloat16_lf  \\\n","0                                                    不是                   \n","1                                                     是                   \n","2                                                     是                   \n","3                                                     是                   \n","4                                                    不是                   \n","...                                                 ...                   \n","2995                                                  是                   \n","2996                                                不重要                   \n","2997                                                  是                   \n","2998                                                  是                   \n","2999                                                 不是                   \n","\n","     hfl/llama-3-chinese-8b-instruct-v3/checkpoint-70_torch.bfloat16_lf  \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","[3000 rows x 8 columns]"]},"execution_count":5,"metadata":{},"output_type":"execute_result"}],"source":["import pandas as pd\n","\n","df = pd.read_csv(\"results/llama3-8b_lora_sft_bf16-p2_r3.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"," 'hfl/llama-3-chinese-8b-instruct-v3_torch.bfloat16_lf',\n"," 'hfl/llama-3-chinese-8b-instruct-v3/checkpoint-35_torch.bfloat16_lf',\n"," 'hfl/llama-3-chinese-8b-instruct-v3/checkpoint-70_torch.bfloat16_lf']"]},"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":["********** hfl/llama-3-chinese-8b-instruct-v3_torch.bfloat16_lf **********\n","hfl/llama-3-chinese-8b-instruct-v3_torch.bfloat16_lf\n","回答正确。                     1315\n","是。                         344\n","不是。                        281\n","问法错误。                      225\n","回答：不是。                     187\n","回答：不重要。                    173\n","不重要。                       159\n","回答：是。                       91\n","回答：不是                       68\n","是                           39\n","回答：回答正确。                    31\n","不是                          23\n","回答：不重要                      22\n","回答错误。                       19\n","回答：是                        12\n","回答：回答正确                      5\n","不重要                          2\n","请问哭泣声是否是由一个人发出？              1\n","请问是不是有两个男人在湖边哭泣？             1\n","回答：问法错误。                     1\n","请问有没有其他人在湖边？\\n\\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":["********** hfl/llama-3-chinese-8b-instruct-v3/checkpoint-35_torch.bfloat16_lf **********\n","hfl/llama-3-chinese-8b-instruct-v3/checkpoint-35_torch.bfloat16_lf\n","不是      1420\n","是       1206\n","不重要      338\n","回答正确      27\n","问法错误       5\n","小男孩        4\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":["********** hfl/llama-3-chinese-8b-instruct-v3/checkpoint-70_torch.bfloat16_lf **********\n","hfl/llama-3-chinese-8b-instruct-v3/checkpoint-70_torch.bfloat16_lf\n","不是      1584\n","是       1052\n","不重要      336\n","回答正确      24\n","小男孩        2\n","问法错误       2\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":21,"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.*是\", \"是\", x.split(\"\\n\")[-1])\n","            .replace(\"是男孩\", \"是\")\n","            .replace(\"是\\n问法错误\", \"问法错误\")\n","            .replace(\"回答：\", \"\")\n","            .replace(\"答案是：\", \"\")\n","            .replace(\"答案：\", \"\")\n","            .replace(\"。\", \"\")\n","            .strip()\n","            if isinstance(x, str)\n","            else x\n","        )\n","    )\n","    return df"]},{"cell_type":"code","execution_count":22,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["********** hfl/llama-3-chinese-8b-instruct-v3_torch.bfloat16_lf **********\n","hfl/llama-3-chinese-8b-instruct-v3_torch.bfloat16_lf\n","回答正确                1351\n","是                    742\n","不重要                  356\n","不是                   304\n","问法错误                 226\n","回答错误                  19\n","请问哭泣声是否是由一个人发出？        1\n","请问是不是有两个男人在湖边哭泣？       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":["********** hfl/llama-3-chinese-8b-instruct-v3/checkpoint-35_torch.bfloat16_lf **********\n","hfl/llama-3-chinese-8b-instruct-v3/checkpoint-35_torch.bfloat16_lf\n","不是      1420\n","是       1206\n","不重要      338\n","回答正确      27\n","问法错误       5\n","小男孩        4\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":["********** hfl/llama-3-chinese-8b-instruct-v3/checkpoint-70_torch.bfloat16_lf **********\n","hfl/llama-3-chinese-8b-instruct-v3/checkpoint-70_torch.bfloat16_lf\n","不是      1584\n","是       1052\n","不重要      336\n","回答正确      24\n","小男孩        2\n","问法错误       2\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":23,"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":24,"metadata":{},"outputs":[{"name":"stderr","output_type":"stream","text":["/Users/inflaton/anaconda3/envs/logical-reasoning/lib/python3.11/site-packages/sklearn/metrics/_classification.py:1517: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n","  _warn_prf(average, modifier, f\"{metric.capitalize()} is\", len(result))\n","/var/folders/7x/56svhln929zdh2xhr3mwqg4r0000gn/T/ipykernel_91506/1032819893.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","/Users/inflaton/anaconda3/envs/logical-reasoning/lib/python3.11/site-packages/sklearn/metrics/_classification.py:1517: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n","  _warn_prf(average, modifier, f\"{metric.capitalize()} is\", len(result))\n","/Users/inflaton/anaconda3/envs/logical-reasoning/lib/python3.11/site-packages/sklearn/metrics/_classification.py:1517: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n","  _warn_prf(average, modifier, f\"{metric.capitalize()} is\", len(result))\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>0.0</td>\n","      <td>hfl/llama-3-chinese-8b-instruct-v3_torch.bfloa...</td>\n","      <td>0.250667</td>\n","      <td>0.685242</td>\n","      <td>0.250667</td>\n","      <td>0.326364</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>0.2</td>\n","      <td>hfl/llama-3-chinese-8b-instruct-v3/checkpoint-...</td>\n","      <td>0.728333</td>\n","      <td>0.772239</td>\n","      <td>0.728333</td>\n","      <td>0.742645</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>0.4</td>\n","      <td>hfl/llama-3-chinese-8b-instruct-v3/checkpoint-...</td>\n","      <td>0.741000</td>\n","      <td>0.786830</td>\n","      <td>0.741000</td>\n","      <td>0.751406</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["   epoch                                              model  accuracy  \\\n","0    0.0  hfl/llama-3-chinese-8b-instruct-v3_torch.bfloa...  0.250667   \n","1    0.2  hfl/llama-3-chinese-8b-instruct-v3/checkpoint-...  0.728333   \n","2    0.4  hfl/llama-3-chinese-8b-instruct-v3/checkpoint-...  0.741000   \n","\n","   precision    recall        f1  \n","0   0.685242  0.250667  0.326364  \n","1   0.772239  0.728333  0.742645  \n","2   0.786830  0.741000  0.751406  "]},"execution_count":24,"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 / 5, \"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":25,"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, others: 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":26,"metadata":{},"outputs":[],"source":["perf_df.to_csv(\"results/mgtv-llama3_p2_r3_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}