03-02_model_finbert.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Model - FinBERT"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "NAME = '03-02_model_finbert'\n",
    "PROJECT = 'conference-calls-sentiment'\n",
    "PYTHON_VERSION = '3.7.0'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Imports  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import re\n",
    "import torch\n",
    "from finbert_model import BertClassification"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Settings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "workdir = re.sub(\"(?<={})[\\w\\W]*\".format(PROJECT), \"\", os.getcwd())\n",
    "os.chdir(workdir)\n",
    "\n",
    "pipeline = os.path.join('2_pipeline', NAME)\n",
    "if not os.path.exists(pipeline):\n",
    "    os.makedirs(pipeline)\n",
    "    for folder in ['out', 'store', 'tmp']:\n",
    "        os.makedirs(os.path.join(pipeline, folder))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "# Main Code "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "PRETRAINED_WEIGHTS_PATH = os.path.join('0_data', 'finbert', 'finbert_pretrained_weights')\n",
    "FINE_TUNED_WEIGHTS_PATH = os.path.join('0_data', 'finbert', 'huang_fine_tuned.pth')\n",
    "DEVICE = 'cuda:0'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load FinBert Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "finbert = BertClassification(weight_path=PRETRAINED_WEIGHTS_PATH)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Fine-tune FinBERT Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "<All keys matched successfully>"
      ]
     },
     "metadata": {},
     "execution_count": 6
    }
   ],
   "source": [
    "finbert.load_state_dict(torch.load(FINE_TUNED_WEIGHTS_PATH, map_location=DEVICE))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Save"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "torch.save(finbert, os.path.join(pipeline, 'out', 'finbert'))"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "name": "python370jvsc74a57bd00fd244f8153bc805f524f29c23b1aa2814d4e93d2f2c2e96a05bc405a61fe891",
   "display_name": "Python 3.7.0 64-bit ('ccs': conda)"
  },
  "language_info": {
   "name": "python",
   "version": "3.7.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}