diff --git "a/competition/00a_InternLM_2.5_and_Llama_3_Results.ipynb" "b/competition/00a_InternLM_2.5_and_Llama_3_Results.ipynb"
deleted file mode 100644--- "a/competition/00a_InternLM_2.5_and_Llama_3_Results.ipynb"
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@@ -1 +0,0 @@
-{"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":{},"outputs":[],"source":["P1 = \"\"\"你是一个逻辑游戏的主持人。游戏规则如下：\n","\n","1. 参与者会得到一个谜题。\n","2. 参与者可以通过提问来获取线索，尝试解开谜题。\n","3. 对于每个问题，主持人将根据实际情况回答以下五个选项之一：是、不是、不重要、回答正确、问法错误。\n","4. 回答中不能添加任何其它信息，也不能省略选项中的任何一个字。例如，不可以把“不是”省略成“不”。\n","5. 参与者需要根据回答来推理，并最终找出谜题的正确答案。\n","\n","请严格按照这些规则回答参与者提出的问题。\n","\n","谜题: {}\n","\n","实际情况: {}\n","\n","参与者提出的问题: {}\n","\"\"\""]},{"cell_type":"code","execution_count":6,"metadata":{},"outputs":[],"source":["P2 = \"\"\"你是一个情景猜谜游戏的主持人。游戏规则如下：\n","\n","1. 参与者会得到一个谜面，谜面会描述一个简单又难以理解的事件。\n","2. 主持人知道谜底，谜底是谜面的答案。\n","3. 参与者可以询问任何封闭式问题来找寻事件的真相。\n","4. 对于每个问题，主持人将根据实际情况回答以下五个选项之一：是、不是、不重要、回答正确、问法错误。各回答的判断标准如下：\n","   - 若谜面和谜底能找到问题的答案，回答：是或者不是\n","   - 若谜面和谜底不能直接或者间接推断出问题的答案，回答：不重要\n","   - 若参与者提问不是一个封闭式问题或者问题难以理解，回答：问法错误\n","   - 若参与者提问基本还原了谜底真相，回答：回答正确\n","5. 回答中不能添加任何其它信息，也不能省略选项中的任何一个字。例如，不可以把“不是”省略成“不”。\n","\n","请严格按照这些规则回答参与者提出的问题。\n","\n","**谜面:** {}\n","\n","**谜底:** {}\n","\n","**参与者提出的问题:** {}\n","\"\"\""]},{"cell_type":"code","execution_count":7,"metadata":{},"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>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-44</td>\n","      <td>0.761667</td>\n","      <td>0.810873</td>\n","      <td>0.761667</td>\n","      <td>0.780018</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>2</td>\n","      <td>internlm/internlm2_5-7b-chat-1m_checkpoint-88</td>\n","      <td>0.741333</td>\n","      <td>0.816182</td>\n","      <td>0.741333</td>\n","      <td>0.769524</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>3</td>\n","      <td>internlm/internlm2_5-7b-chat-1m_checkpoint-132</td>\n","      <td>0.755000</td>\n","      <td>0.809829</td>\n","      <td>0.755000</td>\n","      <td>0.775657</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>4</td>\n","      <td>internlm/internlm2_5-7b-chat-1m_checkpoint-176</td>\n","      <td>0.719000</td>\n","      <td>0.803307</td>\n","      <td>0.719000</td>\n","      <td>0.750319</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-44  0.761667   0.810873   \n","2      2   internlm/internlm2_5-7b-chat-1m_checkpoint-88  0.741333   0.816182   \n","3      3  internlm/internlm2_5-7b-chat-1m_checkpoint-132  0.755000   0.809829   \n","4      4  internlm/internlm2_5-7b-chat-1m_checkpoint-176  0.719000   0.803307   \n","\n","     recall        f1  \n","0  0.781014  0.758887  \n","1  0.761667  0.780018  \n","2  0.741333  0.769524  \n","3  0.755000  0.775657  \n","4  0.719000  0.750319  "]},"execution_count":7,"metadata":{},"output_type":"execute_result"}],"source":["import pandas as pd\n","\n","df_p1 = pd.read_csv(\"results/mgtv-results_p1_full_metrics.csv\")\n","df_p1"]},{"cell_type":"code","execution_count":8,"metadata":{},"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>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>0.766000</td>\n","      <td>0.747969</td>\n","      <td>0.787526</td>\n","      <td>0.764922</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>1</td>\n","      <td>internlm/internlm2_5-7b-chat-1m_checkpoint-88</td>\n","      <td>0.796333</td>\n","      <td>0.808232</td>\n","      <td>0.796333</td>\n","      <td>0.798160</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>2</td>\n","      <td>internlm/internlm2_5-7b-chat-1m_checkpoint-176</td>\n","      <td>0.781333</td>\n","      <td>0.804716</td>\n","      <td>0.781333</td>\n","      <td>0.788581</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>3</td>\n","      <td>internlm/internlm2_5-7b-chat-1m_checkpoint-264</td>\n","      <td>0.759000</td>\n","      <td>0.805502</td>\n","      <td>0.759000</td>\n","      <td>0.777237</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>4</td>\n","      <td>internlm/internlm2_5-7b-chat-1m_checkpoint-352</td>\n","      <td>0.730333</td>\n","      <td>0.790676</td>\n","      <td>0.730333</td>\n","      <td>0.753716</td>\n","    </tr>\n","    <tr>\n","      <th>5</th>\n","      <td>5</td>\n","      <td>internlm/internlm2_5-7b-chat-1m_checkpoint-440</td>\n","      <td>0.730333</td>\n","      <td>0.790420</td>\n","      <td>0.730333</td>\n","      <td>0.753750</td>\n","    </tr>\n","    <tr>\n","      <th>6</th>\n","      <td>6</td>\n","      <td>internlm/internlm2_5-7b-chat-1m_checkpoint-528</td>\n","      <td>0.716000</td>\n","      <td>0.789892</td>\n","      <td>0.716000</td>\n","      <td>0.744833</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["   epoch                                           model  accuracy  precision  \\\n","0      0                 internlm/internlm2_5-7b-chat-1m  0.766000   0.747969   \n","1      1   internlm/internlm2_5-7b-chat-1m_checkpoint-88  0.796333   0.808232   \n","2      2  internlm/internlm2_5-7b-chat-1m_checkpoint-176  0.781333   0.804716   \n","3      3  internlm/internlm2_5-7b-chat-1m_checkpoint-264  0.759000   0.805502   \n","4      4  internlm/internlm2_5-7b-chat-1m_checkpoint-352  0.730333   0.790676   \n","5      5  internlm/internlm2_5-7b-chat-1m_checkpoint-440  0.730333   0.790420   \n","6      6  internlm/internlm2_5-7b-chat-1m_checkpoint-528  0.716000   0.789892   \n","\n","     recall        f1  \n","0  0.787526  0.764922  \n","1  0.796333  0.798160  \n","2  0.781333  0.788581  \n","3  0.759000  0.777237  \n","4  0.730333  0.753716  \n","5  0.730333  0.753750  \n","6  0.716000  0.744833  "]},"execution_count":8,"metadata":{},"output_type":"execute_result"}],"source":["df_p2 = pd.read_csv(\"results/mgtv-results_p2_full_metrics.csv\")\n","df_p2"]},{"cell_type":"code","execution_count":9,"metadata":{},"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>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>0.783667</td>\n","      <td>0.766712</td>\n","      <td>0.792917</td>\n","      <td>0.767940</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>1</td>\n","      <td>shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint...</td>\n","      <td>0.013000</td>\n","      <td>0.922640</td>\n","      <td>0.026621</td>\n","      <td>0.015316</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>2</td>\n","      <td>shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint...</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>3</td>\n","      <td>shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint...</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>4</td>\n","      <td>shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint...</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>5</th>\n","      <td>5</td>\n","      <td>shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint...</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>6</th>\n","      <td>6</td>\n","      <td>shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint...</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>7</th>\n","      <td>7</td>\n","      <td>shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint...</td>\n","      <td>0.134333</td>\n","      <td>0.678404</td>\n","      <td>0.134333</td>\n","      <td>0.197460</td>\n","    </tr>\n","    <tr>\n","      <th>8</th>\n","      <td>8</td>\n","      <td>shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint...</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>9</th>\n","      <td>9</td>\n","      <td>shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint...</td>\n","      <td>0.445333</td>\n","      <td>0.737958</td>\n","      <td>0.445333</td>\n","      <td>0.548035</td>\n","    </tr>\n","    <tr>\n","      <th>10</th>\n","      <td>10</td>\n","      <td>shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint...</td>\n","      <td>0.485000</td>\n","      <td>0.743099</td>\n","      <td>0.485000</td>\n","      <td>0.573525</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["    epoch                                              model  accuracy  \\\n","0       0                shenzhi-wang/Llama3-8B-Chinese-Chat  0.783667   \n","1       1  shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint...  0.013000   \n","2       2  shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint...       NaN   \n","3       3  shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint...       NaN   \n","4       4  shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint...       NaN   \n","5       5  shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint...       NaN   \n","6       6  shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint...       NaN   \n","7       7  shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint...  0.134333   \n","8       8  shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint...       NaN   \n","9       9  shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint...  0.445333   \n","10     10  shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint...  0.485000   \n","\n","    precision    recall        f1  \n","0    0.766712  0.792917  0.767940  \n","1    0.922640  0.026621  0.015316  \n","2         NaN       NaN       NaN  \n","3         NaN       NaN       NaN  \n","4         NaN       NaN       NaN  \n","5         NaN       NaN       NaN  \n","6         NaN       NaN       NaN  \n","7    0.678404  0.134333  0.197460  \n","8         NaN       NaN       NaN  \n","9    0.737958  0.445333  0.548035  \n","10   0.743099  0.485000  0.573525  "]},"execution_count":9,"metadata":{},"output_type":"execute_result"}],"source":["df_p1_llama3 = pd.read_csv(\"results/mgtv-llama3_p1_full_metrics.csv\")\n","df_p1_llama3"]},{"cell_type":"code","execution_count":10,"metadata":{},"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>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>0.730333</td>\n","      <td>0.771041</td>\n","      <td>0.730333</td>\n","      <td>0.746484</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>1</td>\n","      <td>shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint...</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>2</td>\n","      <td>shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint...</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>3</td>\n","      <td>shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint...</td>\n","      <td>0.707000</td>\n","      <td>0.800984</td>\n","      <td>0.707000</td>\n","      <td>0.741300</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>4</td>\n","      <td>shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint...</td>\n","      <td>0.702000</td>\n","      <td>0.776710</td>\n","      <td>0.702000</td>\n","      <td>0.728534</td>\n","    </tr>\n","    <tr>\n","      <th>5</th>\n","      <td>5</td>\n","      <td>shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint...</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>6</th>\n","      <td>6</td>\n","      <td>shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint...</td>\n","      <td>0.623333</td>\n","      <td>0.768108</td>\n","      <td>0.623333</td>\n","      <td>0.676031</td>\n","    </tr>\n","    <tr>\n","      <th>7</th>\n","      <td>7</td>\n","      <td>shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint...</td>\n","      <td>0.642333</td>\n","      <td>0.764460</td>\n","      <td>0.642333</td>\n","      <td>0.678280</td>\n","    </tr>\n","    <tr>\n","      <th>8</th>\n","      <td>8</td>\n","      <td>shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint...</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>9</th>\n","      <td>9</td>\n","      <td>shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint...</td>\n","      <td>0.556667</td>\n","      <td>0.755559</td>\n","      <td>0.556667</td>\n","      <td>0.628456</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["   epoch                                              model  accuracy  \\\n","0      0                shenzhi-wang/Llama3-8B-Chinese-Chat  0.730333   \n","1      1  shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint...       NaN   \n","2      2  shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint...       NaN   \n","3      3  shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint...  0.707000   \n","4      4  shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint...  0.702000   \n","5      5  shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint...       NaN   \n","6      6  shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint...  0.623333   \n","7      7  shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint...  0.642333   \n","8      8  shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint...       NaN   \n","9      9  shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint...  0.556667   \n","\n","   precision    recall        f1  \n","0   0.771041  0.730333  0.746484  \n","1        NaN       NaN       NaN  \n","2        NaN       NaN       NaN  \n","3   0.800984  0.707000  0.741300  \n","4   0.776710  0.702000  0.728534  \n","5        NaN       NaN       NaN  \n","6   0.768108  0.623333  0.676031  \n","7   0.764460  0.642333  0.678280  \n","8        NaN       NaN       NaN  \n","9   0.755559  0.556667  0.628456  "]},"execution_count":10,"metadata":{},"output_type":"execute_result"}],"source":["df_p2_llama3 = pd.read_csv(\"results/mgtv-llama3_p2_full_metrics.csv\")\n","df_p2_llama3"]},{"cell_type":"code","execution_count":11,"metadata":{},"outputs":[{"data":{"text/plain":["5"]},"execution_count":11,"metadata":{},"output_type":"execute_result"}],"source":["new_len = min(len(df_p1), len(df_p2), len(df_p1_llama3), len(df_p2_llama3))\n","new_len"]},{"cell_type":"code","execution_count":12,"metadata":{},"outputs":[],"source":["# df_p1 = df_p1[:new_len]\n","# df_p2 = df_p2[:new_len]\n","# df_p1_llama3 = df_p1_llama3[:new_len]\n","# df_p2_llama3 = df_p2_llama3[:new_len]"]},{"cell_type":"code","execution_count":13,"metadata":{},"outputs":[],"source":["def plot_results(df_p1, df_p2, best_p1, best_p2, color_p1=\"red\", color_p2=\"blue\", model_name=\"InternLM2.5_7b\"):\n","    sns.lineplot(\n","        x=\"epoch\",\n","        y=\"accuracy\",\n","        data=df_p1,\n","        ax=ax[0],\n","        color=color_p1,\n","        label=f\"{model_name}: P1\",\n","    )\n","    sns.lineplot(\n","        x=\"epoch\",\n","        y=\"accuracy\",\n","        data=df_p2,\n","        ax=ax[0],\n","        color=color_p2,\n","        label=f\"{model_name}: P2\",\n","    )\n","    sns.scatterplot(\n","        x=\"epoch\", y=\"accuracy\", data=best_p1, ax=ax[0], color=color_p1, s=50\n","    )\n","    sns.scatterplot(\n","        x=\"epoch\", y=\"accuracy\", data=best_p2, ax=ax[0], color=color_p2, s=50\n","    )\n","\n","    sns.lineplot(\n","        x=\"epoch\",\n","        y=\"f1\",\n","        data=df_p1,\n","        ax=ax[1],\n","        color=color_p1,\n","        label=f\"{model_name}: P1\",\n","    )\n","    sns.lineplot(\n","        x=\"epoch\",\n","        y=\"f1\",\n","        data=df_p2,\n","        ax=ax[1],\n","        color=color_p2,\n","        label=f\"{model_name}: P2\",\n","    )\n","    sns.scatterplot(x=\"epoch\", y=\"f1\", data=best_p1, ax=ax[1], color=color_p1, s=50)\n","    sns.scatterplot(x=\"epoch\", y=\"f1\", data=best_p2, ax=ax[1], color=color_p2, s=50)"]},{"cell_type":"code","execution_count":14,"metadata":{},"outputs":[],"source":["# plot the results\n","import matplotlib.pyplot as plt\n","import seaborn as sns\n","import matplotlib.ticker as ticker\n","\n","def plot_model_results(model_name, df_p1, df_p2, ax):\n","    print(f\"Model: {model_name}\")\n","    sns.set_theme(style=\"whitegrid\")\n","\n","    # print the best results\n","    best_p1 = df_p1[df_p1[\"accuracy\"] == df_p1[\"accuracy\"].max()]\n","    best_p2 = df_p2[df_p2[\"accuracy\"] == df_p2[\"accuracy\"].max()]\n","\n","    print(\"Best P1 accuracy:\")\n","    print(best_p1[\"accuracy\"].values[0])\n","    print(\"Best P2 accuracy:\")\n","    print(best_p2[\"accuracy\"].values[0])\n","\n","    plot_results(df_p1, df_p2, best_p1, best_p2, model_name=model_name)\n","\n","    for a in ax:\n","        for line_index, line in enumerate(a.lines):\n","            # Get the data\n","            line_color = line.get_color()\n","            xdata, ydata = line.get_data()\n","            for index in range(xdata.size):\n","                a.annotate(  # Use 'a' instead of 'ax' to refer to the current subplot\n","                    f\"{ydata[index]:.3f}\",\n","                    xy=(xdata[index], ydata[index]),\n","                    textcoords=\"offset points\",\n","                    xytext=(\n","                        0,\n","                        1,\n","                        # -10 if line_index % 2 == 0 else 10,\n","                    ),  # Adjusted for better visibility\n","                    ha=\"center\",\n","                    color=line_color,\n","                )\n","\n","    ax[0].set_title(\"Accuracy\")\n","    ax[1].set_title(\"F1\")\n","\n","    # After plotting your data and before plt.show(), add these lines\n","    ax[0].xaxis.set_major_locator(ticker.MaxNLocator(integer=True))\n","    ax[1].xaxis.set_major_locator(ticker.MaxNLocator(integer=True))\n","\n","    plt.show()"]},{"cell_type":"code","execution_count":15,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["Model: InternLM_2_5-7b\n","Best P1 accuracy:\n","0.7616666666666667\n","Best P2 accuracy:\n","0.7963333333333333\n"]},{"data":{"image/png":"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","text/plain":["<Figure size 1500x500 with 2 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["_, ax = plt.subplots(1, 2, figsize=(15, 5))\n","plot_model_results(\"InternLM_2_5-7b\", df_p1, df_p2, ax)"]},{"cell_type":"code","execution_count":16,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["Model: Llama3-8b\n","Best P1 accuracy:\n","0.7836666666666666\n","Best P2 accuracy:\n","0.7303333333333333\n"]},{"data":{"image/png":"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","text/plain":["<Figure size 1500x500 with 2 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["_, ax = plt.subplots(1, 2, figsize=(15, 5))\n","plot_model_results(\"Llama3-8b\", df_p1_llama3, df_p2_llama3, ax)"]}],"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}