1_train_a_FastText_model.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xrp9OubIz-8i"
      },
      "source": [
        "# Train a FastText model on the SLED categorization dataset"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "dkNIJuHBz-8r",
        "outputId": "b8e884e8-6782-48d4-82e0-2eae0dad1ea9"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
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            "/content/fastText-0.9.2\n",
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Processing /content/fastText-0.9.2\n",
            "\u001b[33m  DEPRECATION: A future pip version will change local packages to be built in-place without first copying to a temporary directory. We recommend you use --use-feature=in-tree-build to test your packages with this new behavior before it becomes the default.\n",
            "   pip 21.3 will remove support for this functionality. You can find discussion regarding this at https://github.com/pypa/pip/issues/7555.\u001b[0m\n",
            "Collecting pybind11>=2.2\n",
            "  Using cached pybind11-2.10.0-py3-none-any.whl (213 kB)\n",
            "Requirement already satisfied: setuptools>=0.7.0 in /usr/local/lib/python3.7/dist-packages (from fasttext==0.9.2) (57.4.0)\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.7/dist-packages (from fasttext==0.9.2) (1.21.6)\n",
            "Building wheels for collected packages: fasttext\n",
            "  Building wheel for fasttext (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for fasttext: filename=fasttext-0.9.2-cp37-cp37m-linux_x86_64.whl size=3164897 sha256=51f40638056196eae1658cea59f0e1ec04cba76ce956044ad6e0994e6d312f74\n",
            "  Stored in directory: /root/.cache/pip/wheels/87/b3/c9/4ae793bec22dc8570ea6defb4ebb24d699f12b8c954db5f44f\n",
            "Successfully built fasttext\n",
            "Installing collected packages: pybind11, fasttext\n",
            "Successfully installed fasttext-0.9.2 pybind11-2.10.0\n"
          ]
        }
      ],
      "source": [
        "# Install and import fastText\n",
        "!wget https://github.com/facebookresearch/fastText/archive/v0.9.2.zip\n",
        "!unzip v0.9.2.zip\n",
        "\n",
        "%cd fastText-0.9.2\n",
        "\n",
        "!pip install .\n",
        "import fasttext as ft"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%cd /content\n",
        "%pwd"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 54
        },
        "id": "aXUqEjlB9NCR",
        "outputId": "b28da783-3fe9-4a68-fd2d-abd3ff46bd68"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'/content'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 2
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "kDgnyEzoz-8v",
        "outputId": "172d7ad4-26d4-402d-a7e9-8506a605f9bb"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Collecting parse\n",
            "  Downloading parse-1.19.0.tar.gz (30 kB)\n",
            "Building wheels for collected packages: parse\n",
            "  Building wheel for parse (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for parse: filename=parse-1.19.0-py3-none-any.whl size=24591 sha256=639405a6fed42cacf8ff5e3f53bd88576a1ac0ab80f163df330025f27a1e4937\n",
            "  Stored in directory: /root/.cache/pip/wheels/9c/aa/cc/f2228050ccb40f22144b073f15a2c84f11204f29fc0dce028e\n",
            "Successfully built parse\n",
            "Installing collected packages: parse\n",
            "Successfully installed parse-1.19.0\n"
          ]
        }
      ],
      "source": [
        "# Install the parse module\n",
        "!pip install parse"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "id": "1-fv3etLz-8x"
      },
      "outputs": [],
      "source": [
        "# Import necessary libraries\n",
        "import parse\n",
        "import fasttext as ft\n",
        "import numpy as np\n",
        "from sklearn.metrics import f1_score\n",
        "from sklearn.metrics import confusion_matrix\n",
        "import matplotlib.pyplot as plt\n",
        "import pandas as pd\n",
        "import time\n",
        "from sklearn.metrics import classification_report"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "id": "zkYh1SMuz-8y"
      },
      "outputs": [],
      "source": [
        "# Upload the data to google collab and define paths to them\n",
        "# (click on the Folder on the right of the window, and click on the file icon (\"Upload to session storage\")\n",
        "train = \"/content/sled_categorization_TRAINSMALL_PREPROCESSED.txt\"\n",
        "\n",
        "test = \"/content/sled_categorization_TEST_PREPROCESSED.txt\"\n",
        "\n",
        "dev = \"/content/sled_categorization_DEV_PREPROCESSED.txt\""
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "id": "i6RcGQyRz-80"
      },
      "outputs": [],
      "source": [
        "# Parse the file to separate labels from text\n",
        "def parse_file(path: str):\n",
        "    \"\"\"Reads fasttext formatted file and returns labels, texts.\"\"\"\n",
        "    with open(path, \"r\") as f:\n",
        "        content = f.readlines()\n",
        "    pattern = \"{label} {text}\\n\"\n",
        "    p = parse.compile(pattern)\n",
        "\n",
        "    labels, texts = list(), list()\n",
        "    for line in content:\n",
        "        rez = p.parse(line)\n",
        "        if rez is not None:\n",
        "            labels.append(rez[\"label\"])\n",
        "            texts.append(rez[\"text\"])\n",
        "        else:\n",
        "            print(\"error parsing line \", line)\n",
        "    return labels, texts"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "32cOUBaAz-81",
        "outputId": "25c23e37-2b51-4056-ed21-346f6c652c5e"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['na tolminskem se je dopoldne zgodila prometna nesreča v kateri je umrl 43-letni voznik osebnega avtomobila po tem ko je zapeljal v 100 metrov globoko grapo  nesreča se je zgodila ob 916 uri po prvih ugotovitvah policistov je domačin peljal iz tolmina proti vasi zadlaz - žabče kjer je v neposredni bližini ene od tamkajšnjih stanovanjskih hiš zapeljal levo z vozišča globoko približno 100 metrov v grapo  poleg policistov iz tolmina in nove gorice ter novogoriške gorske policijske enote so na kraju nesreče posredovali tudi gasilci pripadniki gorske reševalne službe in reševalci iz tolmina v nadaljevanju je bila ugotovljena in potrjena identiteta voznika in sicer je za posledicami telesnih poškodb v prometni nesreči podlegel 43-letni voznik so sporočili iz policijske uprave nova gorica zdravnica je odredila sanitarno obdukcijo ki jo bodo opravili na inštitutu za sodno medicino v ljubljani o nesreči so obvestili tudi preiskovalno sodnico in državno tožilstvo v novi gorici',\n",
              " 'na cesti zadlaz-žabče se je zgodila prometna nesreča v kateri je umrl 43-letni voznik osebnega avtomobila po prvih ugotovitvah je v neposredni bližini ene od tamkajšnjih stanovanjskih hiš zapeljal levo z vozišča približno 100 metrov globoko v grapo  ob 916 so novogoriške policiste obvestili o prometni nesreči s smrtnim izidom na cesti zadlaz-žabče v kateri je bil udeležen 43-letni voznik osebnega avtomobila z območja upravne enote tolmin  po prvih ugotovitvah je voznik peljal iz tolmina proti omenjeni vasi kjer je v neposredni bližini ene od tamkajšnjih stanovanjskih hiš zapeljal levo z vozišča približno 100 metrov globoko v grapo in pri tem utrpel tako hude poškodbe da je umrl  poleg policistov pp tolmin postaje prometne policije nova gorica in gorske policijske enote pu nova gorica so na kraju nesreče posredovali tudi gasilci pripadniki gorske reševalne službe in reševalci nmp zd tolmin zdravnica je odredila sanitarno obdukcijo ki jo bodo opravili na inštitutu za sodno medicino v ljubljani policija je o nesreči obvestila tudi pristojne pravosodne organe preiskovalno sodnico okrožnega sodišča in državno tožilstvo v novi gorici)',\n",
              " 'v sredo ob 1321 je bila novogoriška policija obveščena o sumu kaznivega dejanja hude telesne poškodbe na območju naselja dornberk kjer sta se v zasebnih prostorih fizično sprla dva moška stara 34 in 41 let takoj po obvestilu so bili na kraj napoteni policisti in kriminalisti ki so ugotovili da sta bila v sporu oba moška huje telesno poškodovana pri čemer je 34-letnik v sporu utrpel tudi vbodno rano z nožem drugi udeleženec spora pa je utrpel poškodbe obraza kasneje so oba moška reševalci odpeljali na nadaljnje zdravljenje v šempetrsko bolnišnico  policija je glede omenjenega primera obvestila tudi preiskovalnega sodnika okrožnega sodišča in državno tožilstvo v novi gorici zoper oba udeleženca bo po zaključku preiskave podana kazenska ovadba zaradi utemeljenega suma storitve kaznivega dejanja hude telesne poškodbe']"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ],
      "source": [
        "# Create a list of texts and labels from the train file\n",
        "train_labels, train_texts = parse_file(train)\n",
        "\n",
        "# Inspect the results\n",
        "train_texts[:3]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "z64Gj62Fz-82",
        "outputId": "d628cc10-024f-4d5c-c70c-3c181344c778"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['__label__gospodarstvo',\n",
              " '__label__okolje',\n",
              " '__label__crnakronika',\n",
              " '__label__znanost',\n",
              " '__label__zabava',\n",
              " '__label__zdravje',\n",
              " '__label__izobrazevanje',\n",
              " '__label__sport',\n",
              " '__label__vreme',\n",
              " '__label__kultura',\n",
              " '__label__prosticas',\n",
              " '__label__druzba',\n",
              " '__label__politika']"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ],
      "source": [
        "# Create a list of labels - by creating a set, we get only unique labels from the list of all labels,\n",
        "# then we transform the set back to a list\n",
        "\n",
        "LABELS = list(set(train_labels))\n",
        "\n",
        "LABELS"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ra1866SWz-83"
      },
      "source": [
        "## Hyperparameters search"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "id": "GrJMvfAKz-83"
      },
      "outputs": [],
      "source": [
        "def prediction_to_label(prediction):\n",
        "    \"\"\"Transforms predictions as returned by fasttext into pure labels.\"\"\"\n",
        "    return np.array(prediction[0])[:, 0]\n",
        "\n",
        "# Create a function to evaluate the results (it calculates the scores and creates a confusion matrix)\n",
        "def plot_cm():\n",
        "    \"\"\"\n",
        "    Plots confusion matrix for prediction on the test set.\n",
        "    Takes the predictions, named as y_pred, true values, named as y_true,\n",
        "    and labels, named as LABELS.\n",
        "    \"\"\"\n",
        "    # Plot the confusion matrix:\n",
        "    cm = confusion_matrix(y_true, y_pred, labels=LABELS)\n",
        "    plt.figure(figsize=(9, 9))\n",
        "    plt.imshow(cm, cmap=\"Oranges\")\n",
        "    for (i, j), z in np.ndenumerate(cm):\n",
        "        plt.text(j, i, '{:d}'.format(z), ha='center', va='center')\n",
        "    classNames = LABELS\n",
        "    plt.ylabel('True label')\n",
        "    plt.xlabel('Predicted label')\n",
        "    tick_marks = np.arange(len(classNames))\n",
        "    plt.xticks(tick_marks, classNames, rotation=90)\n",
        "    plt.yticks(tick_marks, classNames)\n",
        "\n",
        "    plt.tight_layout()\n",
        "    fig1 = plt.gcf()\n",
        "    plt.show()\n",
        "    plt.draw()\n",
        "\n",
        "    # Calculate micro and macro F1 scores\n",
        "    microF1 = f1_score(y_true, y_pred, labels=LABELS, average =\"micro\")\n",
        "    macroF1 = f1_score(y_true, y_pred, labels=LABELS, average =\"macro\")\n",
        "\n",
        "    print(f\"Micro F1: {microF1:0.4}, Macro F1: {macroF1:0.4}\")\n",
        "\n",
        "    return microF1, macroF1"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5UxisuJFz-85"
      },
      "source": [
        "I'll experiment with various epochs to see which epoch number provides the best results"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "cob43dKtz-84"
      },
      "outputs": [],
      "source": [
        "# Create a list with results\n",
        "results = []"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "fITly3ZWz-85",
        "outputId": "75cd8b1e-0545-42b2-ced3-d15d4c442074"
      },
      "outputs": [
        {
          "metadata": {
            "tags": null
          },
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Training started for epoch_num 700.\n",
            "Training finished. Testing started.\n",
            "Training took 12.81 minutes.\n"
          ]
        },
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 648x648 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "metadata": {
            "tags": null
          },
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Micro F1: 0.83, Macro F1: 0.8306\n",
            "Testing took 0.02 minutes.\n",
            "\n",
            "\n",
            "Training started for epoch_num 800.\n",
            "Training finished. Testing started.\n",
            "Training took 13.89 minutes.\n"
          ]
        },
        {
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 0 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 648x648 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "metadata": {
            "tags": null
          },
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Micro F1: 0.8346, Macro F1: 0.8348\n",
            "Testing took 0.02 minutes.\n",
            "\n",
            "\n",
            "Training started for epoch_num 900.\n",
            "Training finished. Testing started.\n",
            "Training took 14.86 minutes.\n"
          ]
        },
        {
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 0 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 648x648 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "metadata": {
            "tags": null
          },
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Micro F1: 0.8346, Macro F1: 0.8347\n",
            "Testing took 0.02 minutes.\n",
            "\n",
            "\n",
            "Training started for epoch_num 1000.\n",
            "Training finished. Testing started.\n",
            "Training took 15.43 minutes.\n"
          ]
        },
        {
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 0 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 648x648 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "metadata": {
            "tags": null
          },
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Micro F1: 0.8338, Macro F1: 0.8339\n",
            "Testing took 0.02 minutes.\n",
            "\n",
            "\n"
          ]
        },
        {
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 0 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# Define which epochs we want to try\n",
        "#exp_range = [10, 50, 100, 150]\n",
        "# Additional experiments - the highest scores were achieved on 150 epochs\n",
        "#exp_range = [200, 250, 300, 350, 400, 450, 500, 550, 600]\n",
        "exp_range = [700, 800, 900, 1000]\n",
        "\n",
        "for i in exp_range:\n",
        "    print(f\"Training started for epoch_num {i}.\")\n",
        "\n",
        "    training_start_time = time.time()\n",
        "\n",
        "    model = ft.train_supervised(input=train,\n",
        "                                epoch = i,\n",
        "                                #lr = 0.7,\n",
        "                                #wordNgrams=1,\n",
        "                                verbose = 2\n",
        "                                            )\n",
        "\n",
        "    print(f\"Training finished. Testing started.\")\n",
        "    print(f\"Training took {round((time.time() - training_start_time)/60,2)} minutes.\")\n",
        "\n",
        "    testing_start_time = time.time()\n",
        "    # Parse the dev files so that labels and texts are separated\n",
        "    y_true, y_texts = parse_file(dev)\n",
        "\n",
        "    # Evaluate the model on dev data\n",
        "    y_pred = model.predict(y_texts)\n",
        "    y_pred = prediction_to_label(y_pred)\n",
        "\n",
        "    # Plot the confusion matrix:\n",
        "    m, M = plot_cm()\n",
        "    \n",
        "    rezdict = dict(\n",
        "        microF1=m,\n",
        "        macroF1=M,\n",
        "        epoch_num = i,\n",
        "    )\n",
        "    results.append(rezdict)\n",
        "\n",
        "    print(f\"Testing took {round((time.time() - testing_start_time)/60,2)} minutes.\\n\\n\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BKb4gfgRz-86",
        "outputId": "58f5c932-c69a-495c-9755-5192ca28616f"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(('__label__zabava',), array([1.00000954]))"
            ]
          },
          "metadata": {},
          "execution_count": 34
        }
      ],
      "source": [
        "# Test the model\n",
        "model.predict(\"V Celju se je zgodila nesreča, umrla je 42-letna ženska.\")"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "results"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9pJ8gHLM6_d2",
        "outputId": "15521a78-58dd-49a2-e08d-a01cbd8a6b1c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[{'microF1': 0.15846153846153846,\n",
              "  'macroF1': 0.10194771788090756,\n",
              "  'epoch_num': 10},\n",
              " {'microF1': 0.41846153846153844,\n",
              "  'macroF1': 0.4054240167951187,\n",
              "  'epoch_num': 50},\n",
              " {'microF1': 0.6223076923076923,\n",
              "  'macroF1': 0.6211575882523663,\n",
              "  'epoch_num': 100},\n",
              " {'microF1': 0.7123076923076922,\n",
              "  'macroF1': 0.7066407993101933,\n",
              "  'epoch_num': 150},\n",
              " {'microF1': 0.7492307692307694,\n",
              "  'macroF1': 0.7471417299434271,\n",
              "  'epoch_num': 200},\n",
              " {'microF1': 0.7676923076923077,\n",
              "  'macroF1': 0.7686271631185997,\n",
              "  'epoch_num': 250},\n",
              " {'microF1': 0.7907692307692308,\n",
              "  'macroF1': 0.7932182933066403,\n",
              "  'epoch_num': 300},\n",
              " {'microF1': 0.8000000000000002,\n",
              "  'macroF1': 0.801711647118303,\n",
              "  'epoch_num': 350},\n",
              " {'microF1': 0.8053846153846154,\n",
              "  'macroF1': 0.8070391572223017,\n",
              "  'epoch_num': 400},\n",
              " {'microF1': 0.8084615384615385,\n",
              "  'macroF1': 0.810002604002464,\n",
              "  'epoch_num': 450},\n",
              " {'microF1': 0.8161538461538461,\n",
              "  'macroF1': 0.8174033688519522,\n",
              "  'epoch_num': 500},\n",
              " {'microF1': 0.82, 'macroF1': 0.8210551070388769, 'epoch_num': 550},\n",
              " {'microF1': 0.8238461538461539,\n",
              "  'macroF1': 0.8246504101376202,\n",
              "  'epoch_num': 600},\n",
              " {'microF1': 0.83, 'macroF1': 0.8306019218410566, 'epoch_num': 700},\n",
              " {'microF1': 0.8346153846153846,\n",
              "  'macroF1': 0.8348435211474332,\n",
              "  'epoch_num': 800},\n",
              " {'microF1': 0.8346153846153846,\n",
              "  'macroF1': 0.8346904166576776,\n",
              "  'epoch_num': 900},\n",
              " {'microF1': 0.8338461538461538,\n",
              "  'macroF1': 0.8339234990322436,\n",
              "  'epoch_num': 1000}]"
            ]
          },
          "metadata": {},
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 307
        },
        "id": "Q-XkVWwGz-87",
        "outputId": "2ee1ca6d-fe39-4cbe-b5b8-12a7e69a86c8"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x300 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "# Analyse the results of experiments\n",
        "import matplotlib.pyplot as plt\n",
        "from matplotlib.pyplot import figure\n",
        "\n",
        "plt.style.use(\"ggplot\")\n",
        "\n",
        "# make data\n",
        "\n",
        "x = []\n",
        "mi = []\n",
        "ma = []\n",
        "\n",
        "for i in results:\n",
        "    x.append(i['epoch_num'])\n",
        "    mi.append(i['microF1'])\n",
        "    ma.append(i[\"macroF1\"])\n",
        "\n",
        "# plot\n",
        "plt.figure(figsize=(6,3), dpi=100)\n",
        "\n",
        "plt.plot(x, mi, label=\"Micro F1\")\n",
        "plt.plot(x, ma, label=\"Macro F1\")\n",
        "\n",
        "plt.xticks(x, fontsize = 8)\n",
        "\n",
        "plt.xlabel('Epoch')\n",
        "plt.ylabel('F1 Score')\n",
        "plt.legend(loc=\"lower right\")\n",
        "\n",
        "plt.tight_layout()\n",
        "\n",
        "#plt.savefig(Epoch-number-hyperparameter-search.png\")\n",
        "plt.show()\n"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "As we can see from the figure, the micro and macro F1 scores keep rising until the epoch 800, afterwards, the scores remain around 0.83. For testing, I will use 800 epochs."
      ],
      "metadata": {
        "id": "vB5yeXobACNO"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Save results of the hyperparameter search as a JSON file\n",
        "import json\n",
        "\n",
        "with open(\"SLED-hyperparameter-search-results.json\",\"w\") as file:\n",
        "  json.dump(results, file)"
      ],
      "metadata": {
        "id": "mysl02UHDsig"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Training the model and testing on the test set"
      ],
      "metadata": {
        "id": "HDxu0Z6UelVb"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "lNeN_6edz-87",
        "outputId": "c27b699a-1635-4b8e-a250-1c9e809e9f72"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Training started.\n",
            "Training finished. Testing started.\n",
            "Training took 12.24 minutes.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 648x648 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Micro F1: 0.8285, Macro F1: 0.8282\n",
            "                        precision    recall  f1-score   support\n",
            "\n",
            " __label__gospodarstvo       0.73      0.79      0.76       100\n",
            "       __label__okolje       0.70      0.81      0.75       100\n",
            "  __label__crnakronika       0.94      0.84      0.89       100\n",
            "      __label__znanost       0.80      0.77      0.79       100\n",
            "       __label__zabava       0.84      0.85      0.85       100\n",
            "      __label__zdravje       0.86      0.84      0.85       100\n",
            "__label__izobrazevanje       0.87      0.80      0.83       100\n",
            "        __label__sport       0.94      0.94      0.94       100\n",
            "        __label__vreme       0.98      0.96      0.97       100\n",
            "      __label__kultura       0.80      0.91      0.85       100\n",
            "    __label__prosticas       0.65      0.58      0.61       100\n",
            "       __label__druzba       0.80      0.76      0.78       100\n",
            "     __label__politika       0.88      0.92      0.90       100\n",
            "\n",
            "              accuracy                           0.83      1300\n",
            "             macro avg       0.83      0.83      0.83      1300\n",
            "          weighted avg       0.83      0.83      0.83      1300\n",
            "\n",
            "Testing took 0.02 minutes.\n",
            "\n",
            "\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 0 Axes>"
            ]
          },
          "metadata": {}
        }
      ],
      "source": [
        "test_results = []\n",
        "\n",
        "for i in [800]:\n",
        "    print(f\"Training started.\")\n",
        "\n",
        "    training_start_time = time.time()\n",
        "\n",
        "    model = ft.train_supervised(input=train,\n",
        "                                epoch = 800,\n",
        "                                verbose = 2)\n",
        "\n",
        "    print(f\"Training finished. Testing started.\")\n",
        "    print(f\"Training took {round((time.time() - training_start_time)/60,2)} minutes.\")\n",
        "\n",
        "    testing_start_time = time.time()\n",
        "    \n",
        "    # Parse the test files so that labels and texts are separated\n",
        "    y_true, y_texts = parse_file(test)\n",
        "\n",
        "    # Test the model on test data\n",
        "    y_pred = model.predict(y_texts)\n",
        "    y_pred = prediction_to_label(y_pred)\n",
        "\n",
        "    # Plot the confusion matrix:\n",
        "    m, M = plot_cm()\n",
        "    \n",
        "    rezdict = dict(\n",
        "        microF1=m,\n",
        "        macroF1=M,\n",
        "        epoch_num = i,\n",
        "        y_true = {\"y_true\": y_true, \"y_texts\": y_texts},\n",
        "        y_pred = y_pred,\n",
        "    )\n",
        "    test_results.append(rezdict)\n",
        "\n",
        "    # Add classification report\n",
        "    print(classification_report(y_true, y_pred, labels=LABELS))\n",
        "\n",
        "    print(f\"Testing took {round((time.time() - testing_start_time)/60,2)} minutes.\\n\\n\")"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Inspect results in a dataframe format\n",
        "\n",
        "df = pd.DataFrame(test_results)\n",
        "\n",
        "df"
      ],
      "metadata": {
        "id": "wragTi20rI5V",
        "outputId": "6b570b74-8c69-45b9-ce07-98cbc0a66445",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 81
        }
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    microF1   macroF1  epoch_num  \\\n",
              "0  0.828462  0.828174        800   \n",
              "\n",
              "                                              y_true  \\\n",
              "0  {'y_true': ['__label__crnakronika', '__label__...   \n",
              "\n",
              "                                              y_pred  \n",
              "0  [__label__crnakronika, __label__crnakronika, _...  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-1ffae735-6eef-445e-bc55-f1c9d0df389c\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>microF1</th>\n",
              "      <th>macroF1</th>\n",
              "      <th>epoch_num</th>\n",
              "      <th>y_true</th>\n",
              "      <th>y_pred</th>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.828462</td>\n",
              "      <td>0.828174</td>\n",
              "      <td>800</td>\n",
              "      <td>{'y_true': ['__label__crnakronika', '__label__...</td>\n",
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              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
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              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "      fill: #FFFFFF;\n",
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              "\n",
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              "        const buttonEl =\n",
              "          document.querySelector('#df-1ffae735-6eef-445e-bc55-f1c9d0df389c button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-1ffae735-6eef-445e-bc55-f1c9d0df389c');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "As we can see, the results in different runs remain stable - the model achieves micro F1 0.8285 and macro F1 0.8282."
      ],
      "metadata": {
        "id": "SValGZynrco8"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "25Qr_IOmz-88"
      },
      "outputs": [],
      "source": [
        "# Save results as csv file\n",
        "df.to_csv(\"SLED-results-on-test.csv\", sep = \"\\t\")"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Save the model\n",
        "model.save_model(\"FastText-model-trainsmall-noembeddings.bin\")"
      ],
      "metadata": {
        "id": "afdBDNYcdxQL"
      },
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install wandb\n",
        "import wandb\n",
        "\n",
        "# Login to wandb\n",
        "wandb.login()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "p9xVs4Pkf3hU",
        "outputId": "8b1d0f8f-d620-4610-d92b-e764105706d9"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Collecting wandb\n",
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            "  Stored in directory: /root/.cache/pip/wheels/3e/31/09/fa59cef12cdcfecc627b3d24273699f390e71828921b2cbba2\n",
            "Successfully built pathtools\n",
            "Installing collected packages: smmap, gitdb, shortuuid, setproctitle, sentry-sdk, pathtools, GitPython, docker-pycreds, wandb\n",
            "Successfully installed GitPython-3.1.27 docker-pycreds-0.4.0 gitdb-4.0.9 pathtools-0.1.2 sentry-sdk-1.9.0 setproctitle-1.3.2 shortuuid-1.0.9 smmap-5.0.0 wandb-0.13.2\n"
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          "text": [
            "\u001b[34m\u001b[1mwandb\u001b[0m: Logging into wandb.ai. (Learn how to deploy a W&B server locally: https://wandb.me/wandb-server)\n",
            "\u001b[34m\u001b[1mwandb\u001b[0m: You can find your API key in your browser here: https://wandb.ai/authorize\n",
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            "\u001b[34m\u001b[1mwandb\u001b[0m: Appending key for api.wandb.ai to your netrc file: /root/.netrc\n"
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        {
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      "cell_type": "code",
      "source": [
        "# Save the trained model to Wandb\n",
        "run = wandb.init(project=\"SLED-categorization\", name=\"saving-trainsmall-noembeddings-model\")\n",
        "trained_model_artifact = wandb.Artifact(\"SLED-categorization-trainsmall-noembeddings-model\", type=\"model\", description=\"a fastText model trained on the 'trainsmall' SLED dataset, trained without pre-trained embeddings.\")\n",
        "trained_model_artifact.add_dir(\"/content/model\")\n",
        "run.log_artifact(trained_model_artifact)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 210,
          "referenced_widgets": [
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              "Find logs at: <code>./wandb/run-20220831_060914-ioblnjxg/logs</code>"
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