data/make-histogram-thing.ipynb


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{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "execution_state": "idle",
   "id": "7a21c467-a114-447d-bdb8-91778b59a3ad",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "csv_filename = 'wandb_export_2024-12-04T19_56_43.325-05_00.csv'\n",
    "df = pd.read_csv(csv_filename)\n",
    "# https://huggingface.co/datasets/ntotsuka123/ja-pretrain/viewer/default/train?p=1&row=120"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "execution_state": "idle",
   "id": "0732274a-bc56-44a3-912f-e023c344bc56",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.drop([0, 1, 10, 11, 12, 15,16,17,18,19])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "execution_state": "idle",
   "id": "23adfc0e-12af-4280-a31e-1601b1bfc3cf",
   "metadata": {},
   "outputs": [],
   "source": [
    "def extract_size(name):\n",
    "    if 'distilbert_base' in name:\n",
    "        return '67M'\n",
    "    elif 'bert_6M' in name or 'bert_6_' in name:\n",
    "        return '6M'\n",
    "    elif 'bert_11' in name:\n",
    "        return '11M'\n",
    "    elif 'bert_19' in name:\n",
    "        return '19M'\n",
    "    elif 'bert_35' in name:\n",
    "        return '35M'\n",
    "    elif 'bert_base' in name:\n",
    "        return '110M'  # Regular BERT base models have ~110M parameters\n",
    "    else:\n",
    "        return 'other'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "execution_state": "idle",
   "id": "895cde04-f6f8-4f47-8f48-16008dd68a55",
   "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>Name</th>\n",
       "      <th>val_loss</th>\n",
       "      <th>size</th>\n",
       "      <th>Type</th>\n",
       "      <th>val_loss_exp</th>\n",
       "      <th>params</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>bert_6M_rtl_scratch</td>\n",
       "      <td>4.744476</td>\n",
       "      <td>6M</td>\n",
       "      <td>RTL</td>\n",
       "      <td>114.947528</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>bert_6_ltr_scratch</td>\n",
       "      <td>4.761365</td>\n",
       "      <td>6M</td>\n",
       "      <td>LTR</td>\n",
       "      <td>116.905354</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>bert_11_rtl_scratch</td>\n",
       "      <td>4.446950</td>\n",
       "      <td>11M</td>\n",
       "      <td>RTL</td>\n",
       "      <td>85.366156</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>bert_11_ltr_scratch</td>\n",
       "      <td>4.462379</td>\n",
       "      <td>11M</td>\n",
       "      <td>LTR</td>\n",
       "      <td>86.693476</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>bert_19_rtl_scratch</td>\n",
       "      <td>4.177320</td>\n",
       "      <td>19M</td>\n",
       "      <td>RTL</td>\n",
       "      <td>65.190932</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>bert_19_ltr_scratch</td>\n",
       "      <td>4.186271</td>\n",
       "      <td>19M</td>\n",
       "      <td>LTR</td>\n",
       "      <td>65.777026</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>bert_35_rtl_scratch</td>\n",
       "      <td>3.927857</td>\n",
       "      <td>35M</td>\n",
       "      <td>RTL</td>\n",
       "      <td>50.797983</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>bert_35_ltr_scratch</td>\n",
       "      <td>3.941595</td>\n",
       "      <td>35M</td>\n",
       "      <td>LTR</td>\n",
       "      <td>51.500691</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>distilbert_base_ltr_scratch</td>\n",
       "      <td>3.686307</td>\n",
       "      <td>67M</td>\n",
       "      <td>LTR</td>\n",
       "      <td>39.897253</td>\n",
       "      <td>67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>distilbert_base_rtl_scratch</td>\n",
       "      <td>3.688566</td>\n",
       "      <td>67M</td>\n",
       "      <td>RTL</td>\n",
       "      <td>39.987461</td>\n",
       "      <td>67</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           Name  val_loss size Type  val_loss_exp  params\n",
       "2           bert_6M_rtl_scratch  4.744476   6M  RTL    114.947528       6\n",
       "3            bert_6_ltr_scratch  4.761365   6M  LTR    116.905354       6\n",
       "4           bert_11_rtl_scratch  4.446950  11M  RTL     85.366156      11\n",
       "5           bert_11_ltr_scratch  4.462379  11M  LTR     86.693476      11\n",
       "6           bert_19_rtl_scratch  4.177320  19M  RTL     65.190932      19\n",
       "7           bert_19_ltr_scratch  4.186271  19M  LTR     65.777026      19\n",
       "8           bert_35_rtl_scratch  3.927857  35M  RTL     50.797983      35\n",
       "9           bert_35_ltr_scratch  3.941595  35M  LTR     51.500691      35\n",
       "13  distilbert_base_ltr_scratch  3.686307  67M  LTR     39.897253      67\n",
       "14  distilbert_base_rtl_scratch  3.688566  67M  RTL     39.987461      67"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['size'] = df['Name'].apply(extract_size)\n",
    "df['Type'] = df['Name'].apply(lambda x: 'LTR' if 'ltr' in x else 'RTL')\n",
    "df['val_loss_exp'] = np.exp(df['val_loss'])\n",
    "df['params'] = df['size'].str.slice(stop=-1).apply(lambda s: int(s))\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "execution_state": "idle",
   "id": "5d5922ca-79bf-4761-954a-8755d70ad626",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_480557/1275629619.py:9: FutureWarning: \n",
      "\n",
      "The `ci` parameter is deprecated. Use `errorbar=None` for the same effect.\n",
      "\n",
      "  sns.barplot(x='size', y='val_loss_exp', hue='Type', data=df_sorted_pairs, dodge=True, palette=\"Set2\", ci=None)\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Sort by size and then by LTR/RTL to group them together\n",
    "df_sorted_pairs = df.sort_values(by=['params', 'Type'])\n",
    "\n",
    "# Plot configuration\n",
    "fig, axes = plt.subplots(figsize=(12, 8))\n",
    "sns.set_style(\"whitegrid\")\n",
    "\n",
    "# Create bar plot with LTR and RTL next to each other, no error bars (ci=None)\n",
    "sns.barplot(x='size', y='val_loss_exp', hue='Type', data=df_sorted_pairs, dodge=True, palette=\"Set2\", ci=None)\n",
    "\n",
    "# Adjustments to the plot\n",
    "# plt.xticks(rotation=45)\n",
    "plt.title(\"Perplexity vs Model Size, From Scratch\", fontsize=20)\n",
    "plt.xlabel(\"Model Size\", fontsize=20)\n",
    "plt.ylabel(\"Test Perplexity\", fontsize=20)\n",
    "# plt.legend(title=\"Model Type\",fontsize=20)\n",
    "plt.legend(title=\"\",fontsize=20)\n",
    "plt.tick_params(axis='both', labelsize=20)\n",
    "\n",
    "# Display the updated plot\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "execution_state": "idle",
   "id": "bb25f31d-91b1-4bd5-be03-36a63f1e857e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.0, 122.75062123923252)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "axes.get_ylim()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "execution_state": "idle",
   "id": "371bccdf-d3c1-4699-9c22-1e2c0b8cfd42",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Data\n",
    "names = ['LTR', 'RTL']\n",
    "val_loss = [np.exp(2.8237654270093375), np.exp(2.8326140656842465)]\n",
    "\n",
    "# Create bar plot\n",
    "plt.bar(names, val_loss, color=['#72B6A1', '#E99675'])\n",
    "\n",
    "# Add labels and title\n",
    "plt.xlabel('Model', fontsize=20)\n",
    "plt.ylabel('Validation Perplexity', fontsize=20)\n",
    "plt.title('DistilBERT Base Japan Perplexity', fontsize=20)\n",
    "\n",
    "# Show the plot\n",
    "# plt.xticks(rotation=45, ha=\"right\")  # Rotate x labels for better readability\n",
    "plt.tick_params(axis='both', labelsize=20)\n",
    "plt.tight_layout()  # Adjust layout to fit everything\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "execution_state": "idle",
   "id": "88c66310-bf62-44fc-b09d-5fb08ec084ad",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "execution_state": "idle",
   "id": "5c86ffd5-d280-4b9f-b250-97d3e398f9a7",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_2794676/549159718.py:15: FutureWarning: \n",
      "\n",
      "The `ci` parameter is deprecated. Use `errorbar=None` for the same effect.\n",
      "\n",
      "  sns.barplot(x='model', y='ppl', hue='direction', data=riddles_rtl_df_sorted_pairs, dodge=True, palette=\"Set2\", ci=None)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "riddles_rtl_df = pd.DataFrame({\n",
    "    'model': ['DistilBERT Base', 'DistilBERT Base', 'BERT Base', 'BERT Base'],\n",
    "    'order': [0, 0, 1, 1],\n",
    "    'direction': [\"LTR\", \"RTL\", \"LTR\", \"RTL\"],\n",
    "    'ppl': [290, 160, 1010, 520],\n",
    "})\n",
    "\n",
    "riddles_rtl_df_sorted_pairs = riddles_rtl_df.sort_values(by=['order', 'direction'])\n",
    "\n",
    "# Plot configuration\n",
    "plt.figure(figsize=(6, 8))\n",
    "sns.set_style(\"whitegrid\")\n",
    "\n",
    "# Create bar plot with LTR and RTL next to each other, no error bars (ci=None)\n",
    "sns.barplot(x='model', y='ppl', hue='direction', data=riddles_rtl_df_sorted_pairs, dodge=True, palette=\"Set2\", ci=None)\n",
    "\n",
    "# Adjustments to the plot\n",
    "# plt.xticks(rotation=45)\n",
    "plt.title(\"QA Riddle Perplexities\", fontsize=20)\n",
    "plt.xlabel(\"Model\", fontsize=20)\n",
    "plt.ylabel(\"Validation Perplexity\", fontsize=20)\n",
    "plt.legend(title=\"\", fontsize=20)\n",
    "plt.tick_params(axis='both', labelsize=20)\n",
    "\n",
    "# Display the updated plot\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "execution_state": "idle",
   "id": "26eba67f-ee2e-44ad-b18f-392aad75aedb",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_480557/2407310871.py:15: FutureWarning: \n",
      "\n",
      "The `ci` parameter is deprecated. Use `errorbar=None` for the same effect.\n",
      "\n",
      "  sns.barplot(x='model', y='ppl', hue='direction', data=riddles_ltr_df_sorted_pairs, dodge=True, palette=\"Set2\", ci=None)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "riddles_ltr_df = pd.DataFrame({\n",
    "    'model': ['DistilBERT Base', 'DistilBERT Base', 'BERT Base', 'BERT Base'],\n",
    "    'order': [0, 0, 1, 1],\n",
    "    'direction': [\"LTR\", \"RTL\", \"LTR\", \"RTL\"],\n",
    "    'ppl': [290, 530, 620, 690],\n",
    "})\n",
    "\n",
    "riddles_ltr_df_sorted_pairs = riddles_ltr_df.sort_values(by=['order', 'direction'])\n",
    "\n",
    "# Plot configuration\n",
    "plt.figure(figsize=(6, 8))\n",
    "sns.set_style(\"whitegrid\")\n",
    "\n",
    "# Create bar plot with LTR and RTL next to each other, no error bars (ci=None)\n",
    "sns.barplot(x='model', y='ppl', hue='direction', data=riddles_ltr_df_sorted_pairs, dodge=True, palette=\"Set2\", ci=None)\n",
    "\n",
    "# Adjustments to the plot\n",
    "# plt.xticks(rotation=45)\n",
    "plt.title(\"Perplexity vs Model Size, From MLM\", fontsize=20)\n",
    "plt.xlabel(\"Model\", fontsize=20)\n",
    "plt.ylabel(\"Test Perplexity\", fontsize=20)\n",
    "plt.legend(title=\"\", fontsize=20)\n",
    "plt.tick_params(axis='both', labelsize=20)\n",
    "\n",
    "# Display the updated plot\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "execution_state": "idle",
   "id": "8e5325e7-85ed-4cda-b24a-9f3248dec10b",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_480557/2459623878.py:14: FutureWarning: \n",
      "\n",
      "The `ci` parameter is deprecated. Use `errorbar=None` for the same effect.\n",
      "\n",
      "  sns.barplot(x='model', y='ppl', hue='direction', data=transfer_wikitext_df.sort_values(by=['order', 'direction']), dodge=True, palette=\"Set2\", ci=None)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "transfer_wikitext_df = pd.DataFrame({\n",
    "    'model': ['67M', '67M', '110M', '110M', '335M', '335M'],\n",
    "    'order': [0, 0, 1, 1, 2, 2],\n",
    "    'direction': [\"LTR\", \"RTL\", \"LTR\", \"RTL\", \"LTR\", \"RTL\"],\n",
    "    'ppl': [24.4, 24.4, 21.8, 21.9, 17.7, 18.1],\n",
    "})\n",
    "\n",
    "\n",
    "# Plot configuration\n",
    "plt.figure(figsize=(6, 8))\n",
    "sns.set_style(\"whitegrid\")\n",
    "\n",
    "# Create bar plot with LTR and RTL next to each other, no error bars (ci=None)\n",
    "sns.barplot(x='model', y='ppl', hue='direction', data=transfer_wikitext_df.sort_values(by=['order', 'direction']), dodge=True, palette=\"Set2\", ci=None)\n",
    "\n",
    "# Adjustments to the plot\n",
    "# plt.xticks(rotation=45)\n",
    "plt.title(\"Perplexity vs Model Size, From Scratch\", fontsize=20)\n",
    "plt.xlabel(\"Model Size\", fontsize=20)\n",
    "plt.ylabel(\"Test Perplexity\", fontsize=20)\n",
    "plt.ylim(0.0, 122.75062123923252)\n",
    "plt.legend(title=\"\", fontsize=20)\n",
    "plt.tick_params(axis='both', labelsize=20)\n",
    "\n",
    "# Display the updated plot\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9bc44c20-d2a8-431a-97cc-a43655e1f856",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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