KRED-Model_Train.ipynb

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 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
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   "source": [
    "import gzip\n",
    "import time\n",
    "import torch\n",
    "import os\n",
    "from utils import *\n",
    "from train_test import *\n",
    "import argparse\n",
    "from parse_config import ConfigParser"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "outputs": [],
   "source": [
    "# Config Loading\n",
    "parser = argparse.ArgumentParser(description='KRED')\n",
    "parser.add_argument('-f')\n",
    "parser.add_argument('-c', '--config', default=\"./config.json\", type=str,\n",
    "                    help='config file path (default: None)')\n",
    "parser.add_argument('-r', '--resume', default=None, type=str,\n",
    "                    help='path to latest checkpoint (default: None)')\n",
    "parser.add_argument('-d', '--device', default=None, type=str,\n",
    "                    help='indices of GPUs to enable (default: all)')\n",
    "\n",
    "config = ConfigParser.from_args(parser)"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "outputs": [],
   "source": [
    "data = load_pretrained_data_mind(config)"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "model training\n",
      "Training epoch 0/6 - 0.0\n",
      "######\n",
      " Step: 0, 0.0 \n",
      "######\n",
      "######\n",
      " Step: 100, 0.7352941176470589 \n",
      "######\n",
      "all loss: tensor(67.9950, device='cuda:0', grad_fn=<AddBackward0>)\n",
      "_train_epoch\n",
      "auc socre: 0.6016769477529045\n",
      "valid_socre\n",
      "valid_scores\n",
      "early_stopping\n",
      "Saving checkpoint: out/saved/models/KRED/1224_162557/checkpoint-model-epoch1.pth ...\n",
      "epoch % self.save_period\n",
      "Training epoch 1/6 - 0.16666666666666666\n",
      "######\n",
      " Step: 0, 0.0 \n",
      "######\n",
      "######\n",
      " Step: 100, 0.7352941176470589 \n",
      "######\n",
      "all loss: tensor(67.5678, device='cuda:0', grad_fn=<AddBackward0>)\n",
      "_train_epoch\n",
      "auc socre: 0.6122532964868165\n",
      "valid_socre\n",
      "valid_scores\n",
      "early_stopping\n",
      "Saving checkpoint: out/saved/models/KRED/1224_162557/checkpoint-model-epoch2.pth ...\n",
      "epoch % self.save_period\n",
      "Training epoch 2/6 - 0.3333333333333333\n",
      "######\n",
      " Step: 0, 0.0 \n",
      "######\n",
      "######\n",
      " Step: 100, 0.7352941176470589 \n",
      "######\n",
      "all loss: tensor(66.3738, device='cuda:0', grad_fn=<AddBackward0>)\n",
      "_train_epoch\n",
      "auc socre: 0.6163112281855666\n",
      "valid_socre\n",
      "valid_scores\n",
      "early_stopping\n",
      "Saving checkpoint: out/saved/models/KRED/1224_162557/checkpoint-model-epoch3.pth ...\n",
      "epoch % self.save_period\n",
      "Training epoch 3/6 - 0.5\n",
      "######\n",
      " Step: 0, 0.0 \n",
      "######\n",
      "######\n",
      " Step: 100, 0.7352941176470589 \n",
      "######\n",
      "all loss: tensor(65.2543, device='cuda:0', grad_fn=<AddBackward0>)\n",
      "_train_epoch\n",
      "auc socre: 0.6129660111026131\n",
      "valid_socre\n",
      "valid_scores\n",
      "early_stopping\n",
      "Saving checkpoint: out/saved/models/KRED/1224_162557/checkpoint-model-epoch4.pth ...\n",
      "epoch % self.save_period\n",
      "Training epoch 4/6 - 0.6666666666666666\n",
      "######\n",
      " Step: 0, 0.0 \n",
      "######\n",
      "######\n",
      " Step: 100, 0.7352941176470589 \n",
      "######\n",
      "all loss: tensor(64.6711, device='cuda:0', grad_fn=<AddBackward0>)\n",
      "_train_epoch\n",
      "auc socre: 0.6136670800353788\n",
      "valid_socre\n",
      "valid_scores\n",
      "early_stopping\n",
      "Saving checkpoint: out/saved/models/KRED/1224_162557/checkpoint-model-epoch5.pth ...\n",
      "epoch % self.save_period\n"
     ]
    }
   ],
   "source": [
    "hif config['trainer']['training_type'] == \"single_task\":\n",
    "    single_task_training(config, data)\n",
    "else:\n",
    "    multi_task_training(config, data)"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "auc score:0.6136670800353788\n",
      "ndcg score:0.32852655509261247\n"
     ]
    }
   ],
   "source": [
    "test_data = data[-1]\n",
    "testing(test_data, config)"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [],
   "metadata": {
    "collapsed": false
   }
  }
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