diff --git "a/competition/11_Llama-3_8b_analysis.ipynb" "b/competition/11_Llama-3_8b_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.example\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>shenzhi-wang/Llama3-8B-Chinese-Chat</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","    </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","    </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>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","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>车轮是凶手留下的</td>\n","      <td>不���</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","    </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","    </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","    </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","    </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","    </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","    </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","    </tr>\n","  </tbody>\n","</table>\n","<p>3000 rows × 6 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���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","     shenzhi-wang/Llama3-8B-Chinese-Chat  \n","0                                    不是。  \n","1                                     是。  \n","2                                      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","[3000 rows x 6 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-p1.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"," 'shenzhi-wang/Llama3-8B-Chinese-Chat']"]},"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":["********** shenzhi-wang/Llama3-8B-Chinese-Chat **********\n","shenzhi-wang/Llama3-8B-Chinese-Chat\n","不是。                            1624\n","是。                              876\n","是                               473\n","不重要。                             11\n","小男孩。                              2\n","小男孩放的。                            2\n","问法错误。                             2\n","不是                                1\n","他要带走的是物品。                         1\n","小男孩的哭声。                           1\n","小男孩和他的爷爷。                         1\n","小男孩是湖边的孩子。                        1\n","是男。                               1\n","小男孩把帽子放在湖边是希望能让爷爷的在天之灵得到安慰。       1\n","破旧。                               1\n","是小男孩。                             1\n","破旧帽子是小男孩的。                        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"}],"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 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":10,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["********** shenzhi-wang/Llama3-8B-Chinese-Chat **********\n","shenzhi-wang/Llama3-8B-Chinese-Chat\n","不是                            1625\n","是                             1349\n","不重要                             11\n","问法错误                             2\n","小男孩                              2\n","小男孩放的                            2\n","他要带走的是物品                         1\n","小男孩的哭声                           1\n","小男孩和他的爷爷                         1\n","小男孩是湖边的孩子                        1\n","是男                               1\n","小男孩把帽子放在湖边是希望能让爷爷的在天之灵得到安慰       1\n","破旧                               1\n","是小男孩                             1\n","破旧帽子是小男孩的                        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"}],"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":11,"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":12,"metadata":{},"outputs":[{"name":"stderr","output_type":"stream","text":["/Users/inflaton/anaconda3/envs/llm-finetuning/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_26910/961288552.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>shenzhi-wang/Llama3-8B-Chinese-Chat</td>\n","      <td>0.785333</td>\n","      <td>0.770106</td>\n","      <td>0.794604</td>\n","      <td>0.769681</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["  epoch                                model  accuracy  precision    recall  \\\n","0     0  shenzhi-wang/Llama3-8B-Chinese-Chat  0.785333   0.770106  0.794604   \n","\n","         f1  \n","0  0.769681  "]},"execution_count":12,"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, 1-3: 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":14,"metadata":{},"outputs":[],"source":["perf_df.to_csv(\"results/mgtv-results_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}