diff --git "a/notebooks/00_Data Analysis.ipynb" "b/notebooks/00_Data Analysis.ipynb"
--- "a/notebooks/00_Data Analysis.ipynb"
+++ "b/notebooks/00_Data Analysis.ipynb"
@@ -1 +1 @@
-{"cells":[{"cell_type":"code","execution_count":122,"metadata":{"executionInfo":{"elapsed":476,"status":"ok","timestamp":1720679526275,"user":{"displayName":"HUANG DONGHAO _","userId":"00977795705617022768"},"user_tz":-480},"id":"uWKRSV6eZsCn"},"outputs":[{"name":"stdout","output_type":"stream","text":["The autoreload extension is already loaded. To reload it, use:\n","  %reload_ext autoreload\n"]}],"source":["%load_ext autoreload\n","%autoreload 2"]},{"cell_type":"code","execution_count":123,"metadata":{"application/vnd.databricks.v1+cell":{"cellMetadata":{"byteLimit":2048000,"rowLimit":10000},"inputWidgets":{},"nuid":"eb33b19f-1206-41ee-84e2-e6258a12eef7","showTitle":false,"title":""},"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":2534,"status":"ok","timestamp":1720679529344,"user":{"displayName":"HUANG DONGHAO _","userId":"00977795705617022768"},"user_tz":-480},"id":"xwFh14uiZBrI","outputId":"d767799c-34c2-46a5-f052-378146a55321"},"outputs":[],"source":["from pathlib import Path\n","\n","if \"workding_dir\" not in locals():\n","    try:\n","        from google.colab import drive\n","\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":124,"metadata":{"application/vnd.databricks.v1+cell":{"cellMetadata":{"byteLimit":2048000,"rowLimit":10000},"inputWidgets":{},"nuid":"6d394937-6c99-4a7c-9d32-7600a280032f","showTitle":false,"title":""},"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":5,"status":"ok","timestamp":1720679529345,"user":{"displayName":"HUANG DONGHAO _","userId":"00977795705617022768"},"user_tz":-480},"id":"G5pNu3zgZBrL","outputId":"160a554f-fb08-4aa0-bc00-0422fb7c1fac"},"outputs":[{"name":"stdout","output_type":"stream","text":["workding dir: /Users/inflaton/code/engd/projects/logical-reasoning\n"]}],"source":["import os\n","import sys\n","from pathlib import Path\n","\n","os.chdir(workding_dir)\n","sys.path.append(workding_dir)\n","print(\"workding dir:\", workding_dir)"]},{"cell_type":"code","execution_count":125,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["working dir: /Users/inflaton/code/engd/projects/logical-reasoning\n"]}],"source":["# haotian comp\n","import os\n","import sys\n","from pathlib import Path\n","\n","if \"workding_dir\" not in locals():\n","    workding_dir = str(Path.cwd().parent)\n","os.chdir(workding_dir)\n","sys.path.append(workding_dir)\n","print(\"working dir:\", workding_dir)"]},{"cell_type":"code","execution_count":126,"metadata":{"application/vnd.databricks.v1+cell":{"cellMetadata":{"byteLimit":2048000,"rowLimit":10000},"inputWidgets":{},"nuid":"9f67ec60-2f24-411c-84eb-0dd664b44775","showTitle":false,"title":""},"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":3,"status":"ok","timestamp":1720679529345,"user":{"displayName":"HUANG DONGHAO _","userId":"00977795705617022768"},"user_tz":-480},"id":"hPCC-6m7ZBrM","outputId":"c7aa2c96-5e99-440a-c148-201d79465ff9"},"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":126,"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":127,"metadata":{"application/vnd.databricks.v1+cell":{"cellMetadata":{"byteLimit":2048000,"rowLimit":10000},"inputWidgets":{},"nuid":"f1597656-8042-4878-9d3b-9ebfb8dd86dc","showTitle":false,"title":""},"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":3,"status":"ok","timestamp":1720679529345,"user":{"displayName":"HUANG DONGHAO _","userId":"00977795705617022768"},"user_tz":-480},"id":"1M3IraVtZBrM","outputId":"29ab35f6-2970-4ade-d85d-3174acf8cda0"},"outputs":[],"source":["model_orders = {\n","    \"Mistral-7B-v0.3-Chinese-Chat\": 5,\n","    \"internlm2_5-7b-chat-1m\": 10,\n","    \"Qwen2-7B-Instruct\": 20,\n","    \"Llama3.1-8B-Chinese-Chat\": 30,\n","    \"Llama3.1-70B-Chinese-Chat\": 40,\n","    \"Qwen2-72B-Instruct\": 50,\n","}"]},{"cell_type":"code","execution_count":128,"metadata":{},"outputs":[],"source":["markers = [\n","    \"o\",\n","    \"x\",\n","    \"^\",\n","    \"s\",\n","    \"d\",\n","    \"P\",\n","    \"X\",\n","    \"*\",\n","    \"v\",\n","    \">\",\n","    \"<\",\n","    \"p\",\n","    \"h\",\n","    \"H\",\n","    \"+\",\n","    \"|\",\n","    \"_\",\n","]\n","model_markers = {k: markers[i] for i, k in enumerate(model_orders.keys())}"]},{"cell_type":"code","execution_count":129,"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","      <th>ratio_valid_classifications</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>0.0</td>\n","      <td>shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat_torc...</td>\n","      <td>0.711333</td>\n","      <td>0.702205</td>\n","      <td>0.711333</td>\n","      <td>0.689497</td>\n","      <td>0.004</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>0.2</td>\n","      <td>shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/chec...</td>\n","      <td>0.702000</td>\n","      <td>0.793273</td>\n","      <td>0.702000</td>\n","      <td>0.734271</td>\n","      <td>1.000</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>0.4</td>\n","      <td>shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/chec...</td>\n","      <td>0.742000</td>\n","      <td>0.789829</td>\n","      <td>0.742000</td>\n","      <td>0.753668</td>\n","      <td>1.000</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>0.6</td>\n","      <td>shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/chec...</td>\n","      <td>0.659667</td>\n","      <td>0.792340</td>\n","      <td>0.659667</td>\n","      <td>0.706754</td>\n","      <td>1.000</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>0.8</td>\n","      <td>shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/chec...</td>\n","      <td>0.714667</td>\n","      <td>0.786134</td>\n","      <td>0.714667</td>\n","      <td>0.740468</td>\n","      <td>1.000</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","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>0.4</td>\n","      <td>Qwen/Qwen2-72B-Instruct/checkpoint-70_torch.bf...</td>\n","      <td>0.736667</td>\n","      <td>0.822487</td>\n","      <td>0.736667</td>\n","      <td>0.770063</td>\n","      <td>1.000</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>0.6</td>\n","      <td>Qwen/Qwen2-72B-Instruct/checkpoint-105_torch.b...</td>\n","      <td>0.757000</td>\n","      <td>0.825382</td>\n","      <td>0.757000</td>\n","      <td>0.784000</td>\n","      <td>1.000</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>0.8</td>\n","      <td>Qwen/Qwen2-72B-Instruct/checkpoint-140_torch.b...</td>\n","      <td>0.789333</td>\n","      <td>0.822910</td>\n","      <td>0.789333</td>\n","      <td>0.803312</td>\n","      <td>1.000</td>\n","    </tr>\n","    <tr>\n","      <th>5</th>\n","      <td>1.0</td>\n","      <td>Qwen/Qwen2-72B-Instruct/checkpoint-175_torch.b...</td>\n","      <td>0.737667</td>\n","      <td>0.824365</td>\n","      <td>0.737667</td>\n","      <td>0.769962</td>\n","      <td>1.000</td>\n","    </tr>\n","    <tr>\n","      <th>6</th>\n","      <td>1.2</td>\n","      <td>Qwen/Qwen2-72B-Instruct/checkpoint-210_torch.b...</td>\n","      <td>0.763000</td>\n","      <td>0.831888</td>\n","      <td>0.763000</td>\n","      <td>0.790108</td>\n","      <td>1.000</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>62 rows × 7 columns</p>\n","</div>"],"text/plain":["    epoch                                              model  accuracy  \\\n","0     0.0  shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat_torc...  0.711333   \n","1     0.2  shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/chec...  0.702000   \n","2     0.4  shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/chec...  0.742000   \n","3     0.6  shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/chec...  0.659667   \n","4     0.8  shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/chec...  0.714667   \n","..    ...                                                ...       ...   \n","2     0.4  Qwen/Qwen2-72B-Instruct/checkpoint-70_torch.bf...  0.736667   \n","3     0.6  Qwen/Qwen2-72B-Instruct/checkpoint-105_torch.b...  0.757000   \n","4     0.8  Qwen/Qwen2-72B-Instruct/checkpoint-140_torch.b...  0.789333   \n","5     1.0  Qwen/Qwen2-72B-Instruct/checkpoint-175_torch.b...  0.737667   \n","6     1.2  Qwen/Qwen2-72B-Instruct/checkpoint-210_torch.b...  0.763000   \n","\n","    precision    recall        f1  ratio_valid_classifications  \n","0    0.702205  0.711333  0.689497                        0.004  \n","1    0.793273  0.702000  0.734271                        1.000  \n","2    0.789829  0.742000  0.753668                        1.000  \n","3    0.792340  0.659667  0.706754                        1.000  \n","4    0.786134  0.714667  0.740468                        1.000  \n","..        ...       ...       ...                          ...  \n","2    0.822487  0.736667  0.770063                        1.000  \n","3    0.825382  0.757000  0.784000                        1.000  \n","4    0.822910  0.789333  0.803312                        1.000  \n","5    0.824365  0.737667  0.769962                        1.000  \n","6    0.831888  0.763000  0.790108                        1.000  \n","\n","[62 rows x 7 columns]"]},"execution_count":129,"metadata":{},"output_type":"execute_result"}],"source":["import pandas as pd\n","\n","perf_df = None\n","model_perf_dfs = {}\n","for model_name in model_orders.keys():\n","    metrics_csv = f\"data/{model_name}_metrics.csv\"\n","    if not Path(metrics_csv).exists():\n","        continue\n","    df = pd.read_csv(metrics_csv)\n","    model_perf_dfs[model_name] = df\n","    perf_df = df if perf_df is None else pd.concat([perf_df, df])\n","\n","perf_df"]},{"cell_type":"code","execution_count":137,"metadata":{},"outputs":[],"source":["import matplotlib.pyplot as plt\n","from matplotlib.ticker import MultipleLocator\n","\n","def plot_perf(\n","    model_perf_dfs,\n","    model_markers,\n","    x_major_locator=0.2,\n","    y_offset=0.005,\n","):\n","    fig, ax = plt.subplots(1, 1, figsize=(12, 6))\n","\n","    for model_name, perf_df in model_perf_dfs.items():\n","        # Ensure the lengths of perf_df[\"epoch\"], perf_df[\"accuracy\"], and perf_df[\"f1\"] are the same\n","        min_length = min(len(perf_df[\"epoch\"]), len(perf_df[\"accuracy\"]), len(perf_df[\"f1\"]))\n","        perf_df = perf_df.iloc[:min_length]\n","\n","        (line,) = ax.plot(\n","            perf_df[\"epoch\"],\n","            perf_df[\"f1\"],\n","            marker=model_markers[model_name],\n","            label=model_name,\n","        )\n","\n","        line_color = line.get_color()\n","\n","        best_f1 = perf_df[\"f1\"].idxmax()\n","        print(\n","            f\"Best F1 for {model_name} @ {perf_df['epoch'].iloc[best_f1]:.2f} epoch: {perf_df['f1'].iloc[best_f1]}\"\n","        )\n","        ax.annotate(\n","            f\"{perf_df['f1'].iloc[best_f1]*100:.2f}%\",\n","            (perf_df[\"epoch\"].iloc[best_f1], perf_df[\"f1\"].iloc[best_f1]),\n","            ha=\"center\",\n","            va=\"bottom\",\n","            xytext=(0, 0),\n","            textcoords=\"offset points\",\n","            fontsize=10,\n","            color=line_color,\n","        )\n","\n","    # Set y-axis limit\n","    y_scales = ax.get_ylim()\n","    ax.set_ylim(y_scales[0], y_scales[1] + y_offset)\n","\n","    # Add title and labels\n","    ax.set_xlabel(\"Epoch (0: base model, 0.2 - 2: fine-tuned models)\")\n","    ax.set_ylabel(\"F1 Score\")\n","\n","    # Set x-axis grid spacing to 0.2\n","    ax.xaxis.set_major_locator(MultipleLocator(x_major_locator))\n","    ax.set_title(\n","        \"Performance Analysis Across Checkpoints for Models\"\n","    )\n","\n","    # Rotate x labels\n","    plt.xticks(rotation=0)\n","    plt.grid(True)\n","    # plt.tight_layout()\n","\n","    # Set legend at the right to avoid overlapping with lines\n","    plt.legend(loc=\"center left\", bbox_to_anchor=(1.0, 0.5))\n","\n","    plt.show()"]},{"cell_type":"code","execution_count":138,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["Best F1 for Mistral-7B-v0.3-Chinese-Chat @ 1.40 epoch: 0.7648234347578796\n","Best F1 for internlm2_5-7b-chat-1m @ 0.80 epoch: 0.8028064320197301\n","Best F1 for Qwen2-7B-Instruct @ 0.40 epoch: 0.7748745026535183\n","Best F1 for Llama3.1-8B-Chinese-Chat @ 1.00 epoch: 0.7924651054056209\n","Best F1 for Llama3.1-70B-Chinese-Chat @ 1.00 epoch: 0.8076868978089201\n","Best F1 for Qwen2-72B-Instruct @ 0.80 epoch: 0.8033124955993173\n"]},{"data":{"image/png":"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","text/plain":["<Figure size 1200x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["plot_perf(model_perf_dfs, model_markers)"]}],"metadata":{"accelerator":"GPU","application/vnd.databricks.v1+notebook":{"dashboards":[],"environmentMetadata":null,"language":"python","notebookMetadata":{"mostRecentlyExecutedCommandWithImplicitDF":{"commandId":-1,"dataframes":["_sqldf"]},"pythonIndentUnit":4},"notebookName":"10_eval-lf-medium-py3.11","widgets":{}},"colab":{"gpuType":"L4","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}
+{"cells":[{"cell_type":"code","execution_count":1,"metadata":{"executionInfo":{"elapsed":476,"status":"ok","timestamp":1720679526275,"user":{"displayName":"HUANG DONGHAO _","userId":"00977795705617022768"},"user_tz":-480},"id":"uWKRSV6eZsCn"},"outputs":[],"source":["%load_ext autoreload\n","%autoreload 2"]},{"cell_type":"code","execution_count":2,"metadata":{"application/vnd.databricks.v1+cell":{"cellMetadata":{"byteLimit":2048000,"rowLimit":10000},"inputWidgets":{},"nuid":"eb33b19f-1206-41ee-84e2-e6258a12eef7","showTitle":false,"title":""},"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":2534,"status":"ok","timestamp":1720679529344,"user":{"displayName":"HUANG DONGHAO _","userId":"00977795705617022768"},"user_tz":-480},"id":"xwFh14uiZBrI","outputId":"d767799c-34c2-46a5-f052-378146a55321"},"outputs":[],"source":["from pathlib import Path\n","\n","if \"workding_dir\" not in locals():\n","    try:\n","        from google.colab import drive\n","\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":{"application/vnd.databricks.v1+cell":{"cellMetadata":{"byteLimit":2048000,"rowLimit":10000},"inputWidgets":{},"nuid":"6d394937-6c99-4a7c-9d32-7600a280032f","showTitle":false,"title":""},"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":5,"status":"ok","timestamp":1720679529345,"user":{"displayName":"HUANG DONGHAO _","userId":"00977795705617022768"},"user_tz":-480},"id":"G5pNu3zgZBrL","outputId":"160a554f-fb08-4aa0-bc00-0422fb7c1fac"},"outputs":[{"name":"stdout","output_type":"stream","text":["workding dir: /Users/inflaton/code/engd/projects/logical-reasoning\n"]}],"source":["import os\n","import sys\n","from pathlib import Path\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":{},"outputs":[{"name":"stdout","output_type":"stream","text":["working dir: /Users/inflaton/code/engd/projects/logical-reasoning\n"]}],"source":["# haotian comp\n","import os\n","import sys\n","from pathlib import Path\n","\n","if \"workding_dir\" not in locals():\n","    workding_dir = str(Path.cwd().parent)\n","os.chdir(workding_dir)\n","sys.path.append(workding_dir)\n","print(\"working dir:\", workding_dir)"]},{"cell_type":"code","execution_count":5,"metadata":{"application/vnd.databricks.v1+cell":{"cellMetadata":{"byteLimit":2048000,"rowLimit":10000},"inputWidgets":{},"nuid":"9f67ec60-2f24-411c-84eb-0dd664b44775","showTitle":false,"title":""},"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":3,"status":"ok","timestamp":1720679529345,"user":{"displayName":"HUANG DONGHAO _","userId":"00977795705617022768"},"user_tz":-480},"id":"hPCC-6m7ZBrM","outputId":"c7aa2c96-5e99-440a-c148-201d79465ff9"},"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":5,"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":6,"metadata":{"application/vnd.databricks.v1+cell":{"cellMetadata":{"byteLimit":2048000,"rowLimit":10000},"inputWidgets":{},"nuid":"f1597656-8042-4878-9d3b-9ebfb8dd86dc","showTitle":false,"title":""},"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":3,"status":"ok","timestamp":1720679529345,"user":{"displayName":"HUANG DONGHAO _","userId":"00977795705617022768"},"user_tz":-480},"id":"1M3IraVtZBrM","outputId":"29ab35f6-2970-4ade-d85d-3174acf8cda0"},"outputs":[],"source":["model_orders = {\n","    \"Mistral-7B-v0.3-Chinese-Chat\": 5,\n","    \"internlm2_5-7b-chat-1m\": 10,\n","    \"Qwen2-7B-Instruct\": 20,\n","    \"Llama3.1-8B-Chinese-Chat\": 30,\n","    \"Llama3.1-70B-Chinese-Chat\": 40,\n","    \"Qwen2-72B-Instruct\": 50,\n","}"]},{"cell_type":"code","execution_count":7,"metadata":{},"outputs":[],"source":["markers = [\n","    \"o\",\n","    \"x\",\n","    \"^\",\n","    \"s\",\n","    \"d\",\n","    \"P\",\n","    \"X\",\n","    \"*\",\n","    \"v\",\n","    \">\",\n","    \"<\",\n","    \"p\",\n","    \"h\",\n","    \"H\",\n","    \"+\",\n","    \"|\",\n","    \"_\",\n","]\n","model_markers = {k: markers[i] for i, k in enumerate(model_orders.keys())}"]},{"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>run</th>\n","      <th>accuracy</th>\n","      <th>precision</th>\n","      <th>recall</th>\n","      <th>f1</th>\n","      <th>ratio_valid_classifications</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>0.0</td>\n","      <td>Mistral-7B-v0.3-Chinese-Chat</td>\n","      <td>shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat_torc...</td>\n","      <td>0.711333</td>\n","      <td>0.702205</td>\n","      <td>0.711333</td>\n","      <td>0.689497</td>\n","      <td>0.004</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>0.2</td>\n","      <td>Mistral-7B-v0.3-Chinese-Chat</td>\n","      <td>shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/chec...</td>\n","      <td>0.702000</td>\n","      <td>0.793273</td>\n","      <td>0.702000</td>\n","      <td>0.734271</td>\n","      <td>1.000</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>0.4</td>\n","      <td>Mistral-7B-v0.3-Chinese-Chat</td>\n","      <td>shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/chec...</td>\n","      <td>0.742000</td>\n","      <td>0.789829</td>\n","      <td>0.742000</td>\n","      <td>0.753668</td>\n","      <td>1.000</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>0.6</td>\n","      <td>Mistral-7B-v0.3-Chinese-Chat</td>\n","      <td>shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/chec...</td>\n","      <td>0.659667</td>\n","      <td>0.792340</td>\n","      <td>0.659667</td>\n","      <td>0.706754</td>\n","      <td>1.000</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>0.8</td>\n","      <td>Mistral-7B-v0.3-Chinese-Chat</td>\n","      <td>shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/chec...</td>\n","      <td>0.714667</td>\n","      <td>0.786134</td>\n","      <td>0.714667</td>\n","      <td>0.740468</td>\n","      <td>1.000</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>6</th>\n","      <td>1.2</td>\n","      <td>Qwen2-72B-Instruct</td>\n","      <td>Qwen/Qwen2-72B-Instruct/checkpoint-210_torch.b...</td>\n","      <td>0.763000</td>\n","      <td>0.831888</td>\n","      <td>0.763000</td>\n","      <td>0.790108</td>\n","      <td>1.000</td>\n","    </tr>\n","    <tr>\n","      <th>7</th>\n","      <td>1.4</td>\n","      <td>Qwen2-72B-Instruct</td>\n","      <td>Qwen/Qwen2-72B-Instruct/checkpoint-245_torch.b...</td>\n","      <td>0.765667</td>\n","      <td>0.828827</td>\n","      <td>0.765667</td>\n","      <td>0.790627</td>\n","      <td>1.000</td>\n","    </tr>\n","    <tr>\n","      <th>8</th>\n","      <td>1.6</td>\n","      <td>Qwen2-72B-Instruct</td>\n","      <td>Qwen/Qwen2-72B-Instruct/checkpoint-280_torch.b...</td>\n","      <td>0.769333</td>\n","      <td>0.829280</td>\n","      <td>0.769333</td>\n","      <td>0.793017</td>\n","      <td>1.000</td>\n","    </tr>\n","    <tr>\n","      <th>9</th>\n","      <td>1.8</td>\n","      <td>Qwen2-72B-Instruct</td>\n","      <td>Qwen/Qwen2-72B-Instruct/checkpoint-315_torch.b...</td>\n","      <td>0.784000</td>\n","      <td>0.835435</td>\n","      <td>0.784000</td>\n","      <td>0.804195</td>\n","      <td>1.000</td>\n","    </tr>\n","    <tr>\n","      <th>10</th>\n","      <td>2.0</td>\n","      <td>Qwen2-72B-Instruct</td>\n","      <td>Qwen/Qwen2-72B-Instruct/checkpoint-350_torch.b...</td>\n","      <td>0.773667</td>\n","      <td>0.833015</td>\n","      <td>0.773667</td>\n","      <td>0.797366</td>\n","      <td>1.000</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>66 rows × 8 columns</p>\n","</div>"],"text/plain":["    epoch                         model  \\\n","0     0.0  Mistral-7B-v0.3-Chinese-Chat   \n","1     0.2  Mistral-7B-v0.3-Chinese-Chat   \n","2     0.4  Mistral-7B-v0.3-Chinese-Chat   \n","3     0.6  Mistral-7B-v0.3-Chinese-Chat   \n","4     0.8  Mistral-7B-v0.3-Chinese-Chat   \n","..    ...                           ...   \n","6     1.2            Qwen2-72B-Instruct   \n","7     1.4            Qwen2-72B-Instruct   \n","8     1.6            Qwen2-72B-Instruct   \n","9     1.8            Qwen2-72B-Instruct   \n","10    2.0            Qwen2-72B-Instruct   \n","\n","                                                  run  accuracy  precision  \\\n","0   shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat_torc...  0.711333   0.702205   \n","1   shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/chec...  0.702000   0.793273   \n","2   shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/chec...  0.742000   0.789829   \n","3   shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/chec...  0.659667   0.792340   \n","4   shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/chec...  0.714667   0.786134   \n","..                                                ...       ...        ...   \n","6   Qwen/Qwen2-72B-Instruct/checkpoint-210_torch.b...  0.763000   0.831888   \n","7   Qwen/Qwen2-72B-Instruct/checkpoint-245_torch.b...  0.765667   0.828827   \n","8   Qwen/Qwen2-72B-Instruct/checkpoint-280_torch.b...  0.769333   0.829280   \n","9   Qwen/Qwen2-72B-Instruct/checkpoint-315_torch.b...  0.784000   0.835435   \n","10  Qwen/Qwen2-72B-Instruct/checkpoint-350_torch.b...  0.773667   0.833015   \n","\n","      recall        f1  ratio_valid_classifications  \n","0   0.711333  0.689497                        0.004  \n","1   0.702000  0.734271                        1.000  \n","2   0.742000  0.753668                        1.000  \n","3   0.659667  0.706754                        1.000  \n","4   0.714667  0.740468                        1.000  \n","..       ...       ...                          ...  \n","6   0.763000  0.790108                        1.000  \n","7   0.765667  0.790627                        1.000  \n","8   0.769333  0.793017                        1.000  \n","9   0.784000  0.804195                        1.000  \n","10  0.773667  0.797366                        1.000  \n","\n","[66 rows x 8 columns]"]},"execution_count":8,"metadata":{},"output_type":"execute_result"}],"source":["import pandas as pd\n","\n","perf_df = None\n","model_perf_dfs = {}\n","for model_name in model_orders.keys():\n","    metrics_csv = f\"data/{model_name}_metrics.csv\"\n","    if not Path(metrics_csv).exists():\n","        continue\n","    df = pd.read_csv(metrics_csv)\n","    model_perf_dfs[model_name] = df\n","    perf_df = df if perf_df is None else pd.concat([perf_df, df])\n","\n","perf_df"]},{"cell_type":"code","execution_count":9,"metadata":{},"outputs":[],"source":["import matplotlib.pyplot as plt\n","from matplotlib.ticker import MultipleLocator\n","\n","def plot_perf(\n","    model_perf_dfs,\n","    model_markers,\n","    x_major_locator=0.2,\n","    y_offset=0.005,\n","):\n","    fig, ax = plt.subplots(1, 1, figsize=(12, 6))\n","\n","    for model_name, perf_df in model_perf_dfs.items():\n","        # Ensure the lengths of perf_df[\"epoch\"], perf_df[\"accuracy\"], and perf_df[\"f1\"] are the same\n","        min_length = min(len(perf_df[\"epoch\"]), len(perf_df[\"accuracy\"]), len(perf_df[\"f1\"]))\n","        perf_df = perf_df.iloc[:min_length]\n","\n","        (line,) = ax.plot(\n","            perf_df[\"epoch\"],\n","            perf_df[\"f1\"],\n","            marker=model_markers[model_name],\n","            label=model_name,\n","        )\n","\n","        line_color = line.get_color()\n","\n","        best_f1 = perf_df[\"f1\"].idxmax()\n","        print(\n","            f\"Best F1 for {model_name} @ {perf_df['epoch'].iloc[best_f1]:.2f} epoch: {perf_df['f1'].iloc[best_f1]}\"\n","        )\n","        ax.annotate(\n","            f\"{perf_df['f1'].iloc[best_f1]*100:.2f}%\",\n","            (perf_df[\"epoch\"].iloc[best_f1], perf_df[\"f1\"].iloc[best_f1]),\n","            ha=\"center\",\n","            va=\"bottom\",\n","            xytext=(0, 0),\n","            textcoords=\"offset points\",\n","            fontsize=10,\n","            color=line_color,\n","        )\n","\n","    # Set y-axis limit\n","    y_scales = ax.get_ylim()\n","    ax.set_ylim(y_scales[0], y_scales[1] + y_offset)\n","\n","    # Add title and labels\n","    ax.set_xlabel(\"Epoch (0: base model, 0.2 - 2: fine-tuned models)\")\n","    ax.set_ylabel(\"F1 Score\")\n","\n","    # Set x-axis grid spacing to 0.2\n","    ax.xaxis.set_major_locator(MultipleLocator(x_major_locator))\n","    ax.set_title(\n","        \"Performance Analysis Across Checkpoints for Models\"\n","    )\n","\n","    # Rotate x labels\n","    plt.xticks(rotation=0)\n","    plt.grid(True)\n","    # plt.tight_layout()\n","\n","    # Set legend at the right to avoid overlapping with lines\n","    plt.legend(loc=\"center left\", bbox_to_anchor=(1.0, 0.5))\n","\n","    plt.show()"]},{"cell_type":"code","execution_count":10,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["Best F1 for Mistral-7B-v0.3-Chinese-Chat @ 1.40 epoch: 0.7648234347578796\n","Best F1 for internlm2_5-7b-chat-1m @ 0.80 epoch: 0.8028064320197301\n","Best F1 for Qwen2-7B-Instruct @ 0.40 epoch: 0.7748745026535183\n","Best F1 for Llama3.1-8B-Chinese-Chat @ 1.00 epoch: 0.7924651054056209\n","Best F1 for Llama3.1-70B-Chinese-Chat @ 1.00 epoch: 0.8076868978089201\n","Best F1 for Qwen2-72B-Instruct @ 1.80 epoch: 0.804194683154365\n"]},{"data":{"image/png":"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","text/plain":["<Figure size 1200x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["plot_perf(model_perf_dfs, model_markers)"]},{"cell_type":"code","execution_count":11,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["<class 'pandas.core.frame.DataFrame'>\n","RangeIndex: 11 entries, 0 to 10\n","Data columns (total 8 columns):\n"," #   Column                       Non-Null Count  Dtype  \n","---  ------                       --------------  -----  \n"," 0   epoch                        11 non-null     float64\n"," 1   model                        11 non-null     object \n"," 2   run                          11 non-null     object \n"," 3   accuracy                     11 non-null     float64\n"," 4   precision                    11 non-null     float64\n"," 5   recall                       11 non-null     float64\n"," 6   f1                           11 non-null     float64\n"," 7   ratio_valid_classifications  11 non-null     float64\n","dtypes: float64(6), object(2)\n","memory usage: 836.0+ bytes\n"]}],"source":["df_openai = pd.read_csv(\"data/openai_results.csv\")\n","df.info()"]},{"cell_type":"code","execution_count":12,"metadata":{},"outputs":[{"data":{"text/plain":["Index(['epoch', 'model', 'run', 'accuracy', 'precision', 'recall', 'f1',\n","       'ratio_valid_classifications'],\n","      dtype='object')"]},"execution_count":12,"metadata":{},"output_type":"execute_result"}],"source":["df.columns"]},{"cell_type":"code","execution_count":13,"metadata":{},"outputs":[],"source":["df_best = df_openai[\n","    [\n","        \"text\",\n","        \"label\",\n","        \"title\",\n","        \"puzzle\",\n","        \"truth\",\n","    ]\n","].copy()"]},{"cell_type":"code","execution_count":14,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["loading /Users/inflaton/code/engd/projects/logical-reasoning/llm_toolkit/logical_reasoning_utils.py\n"]}],"source":["from llm_toolkit.logical_reasoning_utils import *"]},{"cell_type":"code","execution_count":15,"metadata":{},"outputs":[],"source":["df = pd.read_csv(\"data/internlm2_5-7b-chat-1m_results.csv\")\n","df_best[\"internlm2_5-7b-chat-1m\"] = df[\n","    \"internlm/internlm2_5-7b-chat-1m/checkpoint-140_torch.bfloat16_lf\"\n","].apply(extract_answer)"]},{"cell_type":"code","execution_count":16,"metadata":{},"outputs":[],"source":["df = pd.read_csv(\"data/Mistral-7B-v0.3-Chinese-Chat_results.csv\")\n","df_best[\"Mistral-7B-v0.3-Chinese-Chat\"] = df[\n","    \"shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-245_torch.float16_lf\"\n","].apply(extract_answer)"]},{"cell_type":"code","execution_count":17,"metadata":{},"outputs":[],"source":["df = pd.read_csv(\"data/Qwen2-7B-Instruct_results.csv\")\n","df_best[\"Qwen2-7B-Instruct\"] = df[\n","    \"Qwen/Qwen2-7B-Instruct/checkpoint-70_torch.float16_lf\"\n","].apply(extract_answer)"]},{"cell_type":"code","execution_count":18,"metadata":{},"outputs":[],"source":["df = pd.read_csv(\"data/Llama3.1-8B-Chinese-Chat_results.csv\")\n","df_best[\"Llama3.1-8B-Chinese-Chat\"] = df[\n","    \"shenzhi-wang/Llama3.1-8B-Chinese-Chat/checkpoint-175_torch.float16_lf\"\n","].apply(extract_answer)"]},{"cell_type":"code","execution_count":19,"metadata":{},"outputs":[],"source":["df = pd.read_csv(\"data/Llama3.1-70B-Chinese-Chat_results.csv\")\n","df_best[\"Llama3.1-70B-Chinese-Chat\"] = df[\n","    \"shenzhi-wang/Llama3.1-70B-Chinese-Chat/checkpoint-175_torch.bfloat16_4bit_lf\"\n","].apply(extract_answer)"]},{"cell_type":"code","execution_count":20,"metadata":{},"outputs":[],"source":["df = pd.read_csv(\"data/Qwen2-72B-Instruct_results.csv\")\n","df_best[\"Qwen2-72B-Instruct\"] = df[\n","    \"Qwen/Qwen2-72B-Instruct/checkpoint-315_torch.bfloat16_4bit_lf\"\n","].apply(extract_answer)"]},{"cell_type":"code","execution_count":21,"metadata":{},"outputs":[],"source":["df_best[\"Ensemble Model\"] = df_best.apply(\n","    lambda x: majority_vote(\n","        x[\"internlm2_5-7b-chat-1m\"],\n","        x[\"Qwen2-72B-Instruct\"],\n","        x[\"Llama3.1-70B-Chinese-Chat\"],\n","    ),\n","    axis=1,\n",")"]},{"cell_type":"code","execution_count":22,"metadata":{},"outputs":[],"source":["df_best[\"gpt-4o-mini\"] = df_openai[\"gpt-4o-mini/shots-00\"].apply(extract_answer)\n","df_best[\"gpt-4o\"] = df_openai[\"gpt-4o/shots-10\"].apply(extract_answer)"]},{"cell_type":"code","execution_count":23,"metadata":{},"outputs":[{"name":"stderr","output_type":"stream","text":["/Users/inflaton/code/engd/projects/logical-reasoning/llm_toolkit/logical_reasoning_utils.py:439: 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(\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>index</th>\n","      <th>model</th>\n","      <th>run</th>\n","      <th>accuracy</th>\n","      <th>precision</th>\n","      <th>recall</th>\n","      <th>f1</th>\n","      <th>ratio_valid_classifications</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>1</td>\n","      <td>internlm2_5-7b-chat-1m</td>\n","      <td>internlm2_5-7b-chat-1m</td>\n","      <td>0.803000</td>\n","      <td>0.803141</td>\n","      <td>0.803000</td>\n","      <td>0.802806</td>\n","      <td>1.000000</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>2</td>\n","      <td>Mistral-7B-v0.3-Chinese-Chat</td>\n","      <td>Mistral-7B-v0.3-Chinese-Chat</td>\n","      <td>0.750000</td>\n","      <td>0.788587</td>\n","      <td>0.750000</td>\n","      <td>0.764823</td>\n","      <td>1.000000</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>3</td>\n","      <td>Qwen2-7B-Instruct</td>\n","      <td>Qwen2-7B-Instruct</td>\n","      <td>0.759000</td>\n","      <td>0.800530</td>\n","      <td>0.759000</td>\n","      <td>0.774875</td>\n","      <td>1.000000</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>4</td>\n","      <td>Llama3.1-8B-Chinese-Chat</td>\n","      <td>Llama3.1-8B-Chinese-Chat</td>\n","      <td>0.780000</td>\n","      <td>0.810583</td>\n","      <td>0.780000</td>\n","      <td>0.792465</td>\n","      <td>1.000000</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>5</td>\n","      <td>Llama3.1-70B-Chinese-Chat</td>\n","      <td>Llama3.1-70B-Chinese-Chat</td>\n","      <td>0.796333</td>\n","      <td>0.824897</td>\n","      <td>0.796333</td>\n","      <td>0.807687</td>\n","      <td>1.000000</td>\n","    </tr>\n","    <tr>\n","      <th>5</th>\n","      <td>6</td>\n","      <td>Qwen2-72B-Instruct</td>\n","      <td>Qwen2-72B-Instruct</td>\n","      <td>0.784000</td>\n","      <td>0.835435</td>\n","      <td>0.784000</td>\n","      <td>0.804195</td>\n","      <td>1.000000</td>\n","    </tr>\n","    <tr>\n","      <th>6</th>\n","      <td>7</td>\n","      <td>Ensemble Model</td>\n","      <td>Ensemble Model</td>\n","      <td>0.819333</td>\n","      <td>0.840746</td>\n","      <td>0.819333</td>\n","      <td>0.828054</td>\n","      <td>1.000000</td>\n","    </tr>\n","    <tr>\n","      <th>7</th>\n","      <td>8</td>\n","      <td>gpt-4o-mini</td>\n","      <td>gpt-4o-mini</td>\n","      <td>0.717667</td>\n","      <td>0.785707</td>\n","      <td>0.717667</td>\n","      <td>0.729606</td>\n","      <td>1.000000</td>\n","    </tr>\n","    <tr>\n","      <th>8</th>\n","      <td>9</td>\n","      <td>gpt-4o</td>\n","      <td>gpt-4o</td>\n","      <td>0.791667</td>\n","      <td>0.822771</td>\n","      <td>0.791667</td>\n","      <td>0.803615</td>\n","      <td>0.999667</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["  index                         model                           run  accuracy  \\\n","0     1        internlm2_5-7b-chat-1m        internlm2_5-7b-chat-1m  0.803000   \n","1     2  Mistral-7B-v0.3-Chinese-Chat  Mistral-7B-v0.3-Chinese-Chat  0.750000   \n","2     3             Qwen2-7B-Instruct             Qwen2-7B-Instruct  0.759000   \n","3     4      Llama3.1-8B-Chinese-Chat      Llama3.1-8B-Chinese-Chat  0.780000   \n","4     5     Llama3.1-70B-Chinese-Chat     Llama3.1-70B-Chinese-Chat  0.796333   \n","5     6            Qwen2-72B-Instruct            Qwen2-72B-Instruct  0.784000   \n","6     7                Ensemble Model                Ensemble Model  0.819333   \n","7     8                   gpt-4o-mini                   gpt-4o-mini  0.717667   \n","8     9                        gpt-4o                        gpt-4o  0.791667   \n","\n","   precision    recall        f1  ratio_valid_classifications  \n","0   0.803141  0.803000  0.802806                     1.000000  \n","1   0.788587  0.750000  0.764823                     1.000000  \n","2   0.800530  0.759000  0.774875                     1.000000  \n","3   0.810583  0.780000  0.792465                     1.000000  \n","4   0.824897  0.796333  0.807687                     1.000000  \n","5   0.835435  0.784000  0.804195                     1.000000  \n","6   0.840746  0.819333  0.828054                     1.000000  \n","7   0.785707  0.717667  0.729606                     1.000000  \n","8   0.822771  0.791667  0.803615                     0.999667  "]},"execution_count":23,"metadata":{},"output_type":"execute_result"}],"source":["perf_df = get_metrics_df(df_best, variant=\"index\")\n","perf_df"]},{"cell_type":"code","execution_count":25,"metadata":{},"outputs":[{"name":"stderr","output_type":"stream","text":["/var/folders/7x/56svhln929zdh2xhr3mwqg4r0000gn/T/ipykernel_52538/4003496019.py:8: FutureWarning: \n","\n","Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `y` variable to `hue` and set `legend=False` for the same effect.\n","\n","  sns.barplot(\n"]},{"data":{"image/png":"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","text/plain":["<Figure size 800x400 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["# plot horizontal bar chart\n","\n","import matplotlib.pyplot as plt\n","import seaborn as sns\n","\n","fig, ax = plt.subplots(1, 1, figsize=(8, 4))\n","\n","sns.barplot(\n","    x=\"f1\",\n","    y=\"model\",\n","    data=perf_df,\n","    ax=ax,\n","    palette=\"viridis\",\n","    orient=\"h\",  # Specify horizontal orientation\n",")\n","\n","# Add data labels\n","for p in ax.patches:\n","    ax.annotate(\n","        f\"{p.get_width()*100:.2f}%\",\n","        (p.get_width(), p.get_y() + p.get_height() / 2),\n","        ha=\"left\",\n","        va=\"center\",\n","        xytext=(5, 0),  # Offset by 5 points horizontally\n","        textcoords=\"offset points\",\n","    )\n","\n","ax.set_title(\"F1 Score Comparison Across Models\")\n","ax.set_ylabel(\"Model\")\n","ax.set_xlabel(\"F1 Score\")\n","ax.set_xlim(0, 0.95)\n","\n","plt.tight_layout()\n","plt.show()"]}],"metadata":{"accelerator":"GPU","application/vnd.databricks.v1+notebook":{"dashboards":[],"environmentMetadata":null,"language":"python","notebookMetadata":{"mostRecentlyExecutedCommandWithImplicitDF":{"commandId":-1,"dataframes":["_sqldf"]},"pythonIndentUnit":4},"notebookName":"10_eval-lf-medium-py3.11","widgets":{}},"colab":{"gpuType":"L4","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}