FinalChatGPT_SentimentAnalysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "GY0wVnzwd8pq"
   },
   "source": [
    "# **Import ad install the Dependencies**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "wv52JjAIA0ca",
    "outputId": "af5e01dc-a449-453c-845c-9af42c00ab07"
   },
   "outputs": [],
   "source": [
    "import nltk\n",
    "nltk.download('stopwords')\n",
    "nltk.download('punkt')\n",
    "nltk.download('wordnet')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "1-JKrYULV5KT",
    "outputId": "50c072fa-3cae-488e-a568-0fc914ff8186"
   },
   "outputs": [],
   "source": [
    "from google.colab import drive\n",
    "drive.mount('/content/drive')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "WzS1hnlQA7a4",
    "outputId": "a7e5eb77-a10e-487b-cfae-03cee4dc0b3e"
   },
   "outputs": [],
   "source": [
    "!mkdir data/glove\n",
    "\n",
    "!wget http://nlp.stanford.edu/data/glove.6B.zip\n",
    "\n",
    "!unzip glove.6B.zip"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 285,
   "metadata": {
    "id": "6LXVn0aXfO9r"
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import re\n",
    "import tensorflow as tf\n",
    "import matplotlib.pyplot as plt\n",
    "import string\n",
    "import keras.backend as K\n",
    "\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "from keras.preprocessing.text import Tokenizer\n",
    "from keras.utils import pad_sequences\n",
    "from keras.utils.np_utils import to_categorical\n",
    "from keras.layers import Dense,Conv1D,MaxPooling1D\n",
    "from keras import models\n",
    "from keras import layers\n",
    "from nltk.tokenize import word_tokenize\n",
    "from nltk.stem import WordNetLemmatizer\n",
    "from nltk.corpus import stopwords\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "w_ZGH6yN90Lp"
   },
   "source": [
    "# **Functions For cleaning Text**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 286,
   "metadata": {
    "id": "8h9-gECPDObm"
   },
   "outputs": [],
   "source": [
    "def remove_links(tweet):\n",
    "    '''Ex:- https://www.google.com.eg/'''\n",
    "    return re.sub(\"(http[s]?:\\S+)\",\"\", tweet)\n",
    "\n",
    "def remove_shortwords(tweet):\n",
    "    tweet=re.sub(\"'\", \"\", tweet)\n",
    "    tweet = tweet.split()\n",
    "    clean_tweet = [word for word in tweet if  len(word) > 1]\n",
    "    return \" \".join(clean_tweet)\n",
    "\n",
    "\n",
    "def remove_mentions(tweet):\n",
    "    '''@User Mention'''\n",
    "    return re.sub(\"@[A-Za-z0-9_]+\",\"\", tweet)\n",
    "\n",
    "\n",
    "def remove_stopwords(tweet):\n",
    "    stopwords_list = stopwords.words('english')\n",
    "    tweet = tweet.split()\n",
    "    clean_tweet = [word for word in tweet if (word not in stopwords_list)]\n",
    "    return \" \".join(clean_tweet)\n",
    "\n",
    "def remove_nonwords(tweet):\n",
    "    tweet = re.sub('[^\\w]',' ',tweet)\n",
    "    return tweet\n",
    "\n",
    "def clean_text(tweet):\n",
    "    tweet = remove_links(tweet)\n",
    "    tweet = remove_mentions(tweet)\n",
    "    tweet = tweet.lower()\n",
    "    tweet = remove_stopwords(tweet)\n",
    "    tweet = remove_nonwords(tweet)\n",
    "    tweet = remove_shortwords(tweet)\n",
    "    tweet = tweet.strip()\n",
    "    return tweet"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "PWJLjX8sI7vT"
   },
   "source": [
    "# **Measurements (recall, precision, fscore)**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 287,
   "metadata": {
    "id": "hkg8roxKI_yr"
   },
   "outputs": [],
   "source": [
    "def recall_m(y_true, y_pred):\n",
    "    true_positives = K.sum(K.round(K.clip(y_true * y_pred, 0, 1)))\n",
    "    possible_positives = K.sum(K.round(K.clip(y_true, 0, 1)))\n",
    "    recall = true_positives / (possible_positives + K.epsilon())\n",
    "    return recall\n",
    "\n",
    "def precision_m(y_true, y_pred):\n",
    "    true_positives = K.sum(K.round(K.clip(y_true * y_pred, 0, 1)))\n",
    "    predicted_positives = K.sum(K.round(K.clip(y_pred, 0, 1)))\n",
    "    precision = true_positives / (predicted_positives + K.epsilon())\n",
    "    return precision\n",
    "\n",
    "def f1_m(y_true, y_pred):\n",
    "    precision = precision_m(y_true, y_pred)\n",
    "    recall = recall_m(y_true, y_pred)\n",
    "    return 2*((precision*recall)/(precision+recall+K.epsilon()))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "bgA_K_8O-S_B"
   },
   "source": [
    "# **Data Reading and Preprocessing**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 288,
   "metadata": {
    "id": "p4ldrDyMd1mK"
   },
   "outputs": [],
   "source": [
    "num_of_words = 32000 \n",
    "max_num_of_words = 50 # in sequence\n",
    "num_of_dimensions = 300  # For GloVe word embeddings"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "92gOrUJl_Aep"
   },
   "source": [
    "### Data Reading and Cleaning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 289,
   "metadata": {
    "id": "fVsvGn5YDO4q"
   },
   "outputs": [],
   "source": [
    "df = pd.read_csv('/content/drive/MyDrive/Colab Notebooks/file.csv')\n",
    "df.tweets = df.tweets.apply(clean_text)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "08JA_wW0XGL6"
   },
   "source": [
    "### Show Majority of tweets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 290,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 449
    },
    "id": "IvaFkQJHdiOp",
    "outputId": "92d5d1bb-a9e4-4eff-9426-90ddf1f509f1"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tweets_majority=sns.countplot(data=df, x='labels')\n",
    "plt.show()\n",
    "tweets_majority_fig = tweets_majority.get_figure()\n",
    "tweets_majority_fig.savefig('/content/drive/MyDrive/Colab Notebooks/ChatGPT_SentimentAnalysis/Images/Majority of tweets.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "tdV5hQv9_ntP"
   },
   "source": [
    "### Tokenization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 291,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "csF1RZinDPXL",
    "outputId": "cb5e66db-4922-4ff2-a137-35fcd97454c3"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    [chatgpt, optimizing, language, models, dialogue]\n",
       "1    [try, talking, chatgpt, new, ai, system, optim...\n",
       "2    [chatgpt, optimizing, language, models, dialog...\n",
       "3    [thrilled, share, chatgpt, new, model, optimiz...\n",
       "4    [minutes, ago, released, new, chatgpt, nand, u...\n",
       "Name: tweets, dtype: object"
      ]
     },
     "execution_count": 291,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tokenized_tweet = df['tweets'].apply(lambda x: word_tokenize(x))\n",
    "tokenized_tweet.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "7U1jZ3oUB5dq"
   },
   "source": [
    "### Lemmatization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 292,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 206
    },
    "id": "UTfCIAmBDP1L",
    "outputId": "c2938bce-0e9e-48c2-bd94-48ce731fbbad"
   },
   "outputs": [
    {
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       "   Unnamed: 0                                             tweets   labels\n",
       "0           0         chatgpt optimizing language model dialogue  neutral\n",
       "1           1  try talking chatgpt new ai system optimized di...     good\n",
       "2           2  chatgpt optimizing language model dialogue ai ...  neutral\n",
       "3           3  thrilled share chatgpt new model optimized dia...     good\n",
       "4           4     minute ago released new chatgpt nand use right      bad"
      ]
     },
     "execution_count": 292,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lemmatizer = WordNetLemmatizer()\n",
    "tokenized_tweet = tokenized_tweet.apply(lambda sentence: [lemmatizer.lemmatize(word) for word in sentence])\n",
    "tokenized_tweet.head()\n",
    "\n",
    "for i in range(len(tokenized_tweet)):\n",
    "    tokenized_tweet[i] = \" \".join(tokenized_tweet[i])\n",
    "    \n",
    "df['tweets'] = tokenized_tweet\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "4J2GbCEAKwUZ"
   },
   "source": [
    "### Splittig the dataset to training and testing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 293,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "qbQCtw66DTd5",
    "outputId": "13d708a2-5210-4c4e-ffba-918c3c4a6ce3"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "# number of training data: 175435\n",
      "# number of testing data: 43859\n"
     ]
    }
   ],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(df.tweets, df.labels, test_size=0.2, random_state=42)\n",
    "print(f'# number of training data: {X_train.shape[0]}')\n",
    "print(f'# number of testing data: {X_test.shape[0]}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Z-QP_v_0GfJX"
   },
   "source": [
    "### Generating Training and testing Data Files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "w2ePBRPFLT_z"
   },
   "outputs": [],
   "source": [
    "training_data=pd.DataFrame({'tweets':X_train[:], 'labels':y_train[:]})\n",
    "testing_data=pd.DataFrame({'tweets':X_test[:], 'labels':y_test[:]})\n",
    "training_data.to_csv('/content/drive/MyDrive/Colab Notebooks/ChatGPT_SentimentAnalysis/training data/training_data.csv')\n",
    "testing_data.to_csv('/content/drive/MyDrive/Colab Notebooks/ChatGPT_SentimentAnalysis/testing data/testing_data.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "c58N9cDZDsKf"
   },
   "source": [
    "# **Text Processing**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 294,
   "metadata": {
    "id": "jrgunPZnQWOP"
   },
   "outputs": [],
   "source": [
    "tokenizer = Tokenizer(num_words=num_of_words,filters=string.punctuation)\n",
    "tokenizer.fit_on_texts(X_train)\n",
    "\n",
    "X_train_sequences = tokenizer.texts_to_sequences(X_train)\n",
    "X_test_sequences = tokenizer.texts_to_sequences(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 295,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 300
    },
    "id": "_nxiuv7jDUZ9",
    "outputId": "b5cffe7a-3cc3-4ff9-f880-548bfaf95af9"
   },
   "outputs": [
    {
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       "              tweets\n",
       "count  175435.000000\n",
       "mean       12.629202\n",
       "std         7.920655\n",
       "min         1.000000\n",
       "25%         6.000000\n",
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       "max        49.000000"
      ]
     },
     "execution_count": 295,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_description = X_train.apply(lambda x: len(x.split(' ')))\n",
    "data_description_df=pd.DataFrame(data_description.describe())\n",
    "data_description_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 296,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "IRpkA6vlDT8I",
    "outputId": "51078b89-51b5-47a2-99d2-5af2254ab727"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Shape of samples: (175435, 49)\n"
     ]
    }
   ],
   "source": [
    "max_num_of_words=49\n",
    "\n",
    "\n",
    "X_train = pad_sequences(X_train_sequences, maxlen=max_num_of_words)\n",
    "X_test = pad_sequences(X_test_sequences, maxlen=max_num_of_words)\n",
    "\n",
    "print(f'Shape of samples: {X_train.shape}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "DJo2owZyHQ1f"
   },
   "source": [
    "### Format Output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "5kwaNSEfDVYc",
    "outputId": "fcd65807-68ed-4c65-d39c-49dd25899824"
   },
   "outputs": [],
   "source": [
    "label_encoder = LabelEncoder()\n",
    "y_train = to_categorical(label_encoder.fit_transform(y_train))\n",
    "y_test = to_categorical(label_encoder.transform(y_test))\n",
    "y_test[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Q4wcWkcNHqQu"
   },
   "source": [
    "# **Reading Glove Word Embeddings**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "id": "u3FcK9ptDWU1"
   },
   "outputs": [],
   "source": [
    "embedding_dict = {}\n",
    "glove = open(f'/content/glove.6B.300d.txt', encoding=\"utf8\")\n",
    "for line in glove:\n",
    "    values = line.split()\n",
    "    word = values[0]\n",
    "    vector = np.asarray(values[1:], dtype='float32')\n",
    "    embedding_dict[word] = vector\n",
    "glove.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "fiBHTGc2DW0Q",
    "outputId": "2822a1ba-3ab3-46b5-8c40-71985d9267cd"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Embedding Matrix Shape:  (32000, 300)\n"
     ]
    }
   ],
   "source": [
    "embedding_matrix = np.zeros((num_of_words, 300))\n",
    "\n",
    "for w, i in tokenizer.word_index.items():\n",
    "    if i < num_of_words:\n",
    "        vect = embedding_dict.get(w)\n",
    "        if vect is not None:\n",
    "            embedding_matrix[i] = vect\n",
    "    else:\n",
    "        break\n",
    "\n",
    "print ('Embedding Matrix Shape: ',embedding_matrix.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "X9PmSojrI8rl"
   },
   "source": [
    "# **Models Training**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "u_rrnxvf1Fgj"
   },
   "source": [
    "## **Fucntion for Plotting The Accuracy and Loss**\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "ydn-Z5iS1sgD"
   },
   "outputs": [],
   "source": [
    "def plotting_model_measurements(history,model_name,trial_num):\n",
    "    title_name=f'{model_name} Model (Trial-{trial_num})'\n",
    "    fig, ax = plt.subplots(1, 2, figsize=(10,4))\n",
    "    fig.subplots_adjust(hspace=0.8, wspace=0.8)\n",
    "    fig.suptitle(title_name, fontsize=16)\n",
    "    fig.trial_num=trial_num\n",
    "    \n",
    "    ax[0].plot(history.history['accuracy'])\n",
    "    ax[0].plot(history.history['val_accuracy'])\n",
    "    ax[0].set_title('Model Accuracy')\n",
    "    ax[0].set_xlabel('epoch')\n",
    "    ax[0].set_ylabel('accuracy')\n",
    "    ax[0].legend(['train', 'validation'], loc='best')\n",
    "    ax[1].plot(history.history['loss'])\n",
    "    ax[1].plot(history.history['val_loss'])\n",
    "    ax[1].set_title('Model Loss')\n",
    "    ax[1].set_xlabel('epoch')\n",
    "    ax[1].set_ylabel('loss')\n",
    "    ax[1].legend(['train', 'validation'], loc='best')\n",
    "    plt.savefig(f'/content/drive/MyDrive/Colab Notebooks/ChatGPT_SentimentAnalysis/Images/{model_name} Model Accuracy and Loss (Trial No.:{trial_num}).png')\n",
    "    plt.draw()\n",
    "    plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "upKfHHUuJ02m"
   },
   "source": [
    "# **Using Convolutional Neural Network(CNN) Architecture**\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "qMgCVKaxKBiu"
   },
   "source": [
    "## **Building The Model**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "id": "asFYsO7TKFgt"
   },
   "outputs": [],
   "source": [
    "\n",
    "\n",
    "def build_CNN(Conv1D_1,Conv1D_2,Conv1D_3,_learning_rate,embedding_trainable,model_name):\n",
    "    model = models.Sequential(name=model_name)\n",
    "    model.add(layers.Embedding(num_of_words, num_of_dimensions, input_length=max_num_of_words,name='embedding_Layer'))\n",
    "    if Conv1D_1:\n",
    "      model.add(Conv1D(128 , 16 , padding = 'same',activation = 'relu'))\n",
    "      model.add(MaxPooling1D(3))\n",
    "    \n",
    "    if Conv1D_2:\n",
    "       model.add(Conv1D(128 , 16 , padding = 'same',activation = 'relu'))\n",
    "       model.add(MaxPooling1D(3))\n",
    "\n",
    "    if Conv1D_3:\n",
    "       model.add(Conv1D(128 , 16 , padding = 'same',activation = 'relu'))\n",
    "       model.add(MaxPooling1D(3))  \n",
    "   \n",
    "    model.add(layers.Dropout(0.5))\n",
    "    model.add(layers.Flatten())\n",
    "    model.add(Dense(64, activation='relu'))\n",
    "    model.add(layers.Dropout(0.2))\n",
    "    model.add(Dense(32, activation='relu'))\n",
    "    model.add(layers.Dropout(0.2))\n",
    "    model.add(Dense(3, activation='softmax',name='Output_Layer'))\n",
    "    model.layers[0].set_weights([embedding_matrix])\n",
    "    if embedding_trainable:\n",
    "       model.layers[0].trainable = True\n",
    "    else:\n",
    "       model.layers[0].trainable = False\n",
    "    \n",
    "    model.compile(loss='categorical_crossentropy', optimizer=tf.keras.optimizers.Adam(learning_rate=_learning_rate), metrics=['accuracy',f1_m,precision_m, recall_m])\n",
    "    model.summary()\n",
    "    return model\n",
    "\n",
    "\n",
    "cnn_model_trials_dict = {\n",
    "             'Measurement' : ['Trial-1', 'Trial-2' , 'Trial-3', 'Trial-4', 'Trial-5'], # Trial-1 => 0 , Trial-2 => 1 , ...\n",
    "             'Training Accuaracy' : [0,0,0,0,0],\n",
    "             'Testing Accuaracy' : [0,0,0,0,0],\n",
    "             'Loss' : [0,0,0,0,0],\n",
    "             'Embedding layer Trainable':['No','No','No','No','No']\n",
    "}\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "YrRo-hcuP4MQ"
   },
   "source": [
    "## **CNN Model Training Trials**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "id": "wDJCMIZ3P1OT",
    "outputId": "e7523829-fc44-4249-dd24-c0cc906f6490"
   },
   "outputs": [],
   "source": [
    "# Trial-1 (embedding_trainable=True)\n",
    "\n",
    "cnn_model_trial1 = build_CNN(embedding_trainable=True, Conv1D_1=True, Conv1D_2=False, Conv1D_3=False, _learning_rate=0.0001, model_name='CNN_Trial-1')\n",
    "cnn_model_trial1_history = cnn_model_trial1.fit(X_train, y_train,epochs=10, verbose=1,batch_size=256,validation_split=0.2)\n",
    "\n",
    "'''Plotting Model Architecture For Trial-1'''\n",
    "tf.keras.utils.plot_model(cnn_model_trial1, show_shapes=True)\n",
    "plt.savefig('/content/drive/MyDrive/Colab Notebooks/ChatGPT_SentimentAnalysis/Images/CNN Model (Trial 1).png')\n",
    "\n",
    "cnn_model_trials_dict['Embedding layer Trainable'][0]='Yes'\n",
    "\n",
    "\n",
    "\n",
    "# Trial-2 (embedding_trainable=False)\n",
    "\n",
    "cnn_model_trial2 = build_CNN(embedding_trainable=False, Conv1D_1=True, Conv1D_2=False, Conv1D_3=False, _learning_rate=0.01, model_name='CNN_Trial-2')\n",
    "cnn_model_trial2_history = cnn_model_trial2.fit(X_train, y_train,epochs=10, verbose=1,batch_size=256,validation_split=0.2)\n",
    "\n",
    "'''Plotting Model Architecture For Trial-2'''\n",
    "tf.keras.utils.plot_model(cnn_model_trial2, show_shapes=True)\n",
    "plt.savefig('/content/drive/MyDrive/Colab Notebooks/ChatGPT_SentimentAnalysis/Images/CNN Model (Trial 2).png')\n",
    "\n",
    "cnn_model_trials_dict['Embedding layer Trainable'][1]='No'\n",
    "\n",
    "\n",
    "\n",
    "# Trial-3 (embedding_trainable=False)\n",
    "\n",
    "cnn_model_trial3 = build_CNN(embedding_trainable=False, Conv1D_1=True, Conv1D_2=True, Conv1D_3=True, _learning_rate=0.001, model_name='CNN_Trial-3')\n",
    "cnn_model_trial3_history = cnn_model_trial3.fit(X_train, y_train,epochs=10, verbose=1,batch_size=256,validation_split=0.2)\n",
    "\n",
    "'''Plotting Model Architecture For Trial-3'''\n",
    "tf.keras.utils.plot_model(cnn_model_trial3, show_shapes=True)\n",
    "plt.savefig('/content/drive/MyDrive/Colab Notebooks/ChatGPT_SentimentAnalysis/Images/CNN Model (Trial 3).png')\n",
    "\n",
    "cnn_model_trials_dict['Embedding layer Trainable'][2]='No'\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "# Trial-4 (embedding_trainable=True)\n",
    "\n",
    "cnn_model_trial4 = build_CNN(embedding_trainable=True, Conv1D_1=True, Conv1D_2=True, Conv1D_3=True, _learning_rate=0.001, model_name='CNN_Trial-4')\n",
    "cnn_model_trial4_history = cnn_model_trial4.fit(X_train, y_train,epochs=10, verbose=1,batch_size=256,validation_split=0.2)\n",
    "\n",
    "'''Plotting Model Architecture For Trial-4'''\n",
    "tf.keras.utils.plot_model(cnn_model_trial4, show_shapes=True)\n",
    "plt.savefig('/content/drive/MyDrive/Colab Notebooks/ChatGPT_SentimentAnalysis/Images/CNN Model (Trial 4).png')\n",
    "\n",
    "cnn_model_trials_dict['Embedding layer Trainable'][3]='Yes'\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "# Trial-5 (embedding_trainable=False)\n",
    "\n",
    "cnn_model_trial5 = build_CNN(embedding_trainable=False, Conv1D_1=True, Conv1D_2=True, Conv1D_3=True, _learning_rate=0.0001, model_name='CNN_Trial-5')\n",
    "cnn_model_trial5_history = cnn_model_trial5.fit(X_train, y_train,epochs=10, verbose=1,batch_size=256,validation_split=0.2)\n",
    "\n",
    "'''Plotting Model Architecture For Trial-5'''\n",
    "tf.keras.utils.plot_model(cnn_model_trial5, show_shapes=True)\n",
    "plt.savefig('/content/drive/MyDrive/Colab Notebooks/ChatGPT_SentimentAnalysis/Images/CNN Model (Trial 5).png')\n",
    "\n",
    "cnn_model_trials_dict['Embedding layer Trainable'][4]='No'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Wj9MCWBwLJIx"
   },
   "source": [
    "## **Testing The Model Trials**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "6dSQqTPvKGb2",
    "outputId": "d4e9b01f-5351-4595-f1be-d9359a6c83c9"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5483/5483 [==============================] - 25s 5ms/step - loss: 0.1422 - accuracy: 0.9599 - f1_m: 0.9599 - precision_m: 0.9608 - recall_m: 0.9591\n",
      "1371/1371 [==============================] - 6s 4ms/step - loss: 0.3316 - accuracy: 0.8959 - f1_m: 0.8958 - precision_m: 0.8971 - recall_m: 0.8945\n",
      "\n",
      "Trial 1\n",
      "Training Accuaracy (Trial 1): 96.0%\n",
      "Testing Accuaracy (Trial 1): 89.6%\n",
      "5483/5483 [==============================] - 23s 4ms/step - loss: 0.4240 - accuracy: 0.8332 - f1_m: 0.8214 - precision_m: 0.8801 - recall_m: 0.7717\n",
      "1371/1371 [==============================] - 6s 4ms/step - loss: 0.5418 - accuracy: 0.7769 - f1_m: 0.7655 - precision_m: 0.8266 - recall_m: 0.7144\n",
      "\n",
      "Trial 2\n",
      "Training Accuaracy (Trial 2): 83.3%\n",
      "Testing Accuaracy (Trial 2): 77.7%\n",
      "5483/5483 [==============================] - 24s 4ms/step - loss: 0.2303 - accuracy: 0.9440 - f1_m: 0.9440 - precision_m: 0.9445 - recall_m: 0.9435\n",
      "1371/1371 [==============================] - 7s 5ms/step - loss: 0.9219 - accuracy: 0.8007 - f1_m: 0.8007 - precision_m: 0.8016 - recall_m: 0.7997\n",
      "\n",
      "Trial 3\n",
      "Training Accuaracy (Trial 3): 94.4%\n",
      "Testing Accuaracy (Trial 3): 80.1%\n",
      "5483/5483 [==============================] - 24s 4ms/step - loss: 0.1124 - accuracy: 0.9771 - f1_m: 0.9771 - precision_m: 0.9774 - recall_m: 0.9767\n",
      "1371/1371 [==============================] - 6s 4ms/step - loss: 0.5076 - accuracy: 0.9049 - f1_m: 0.9046 - precision_m: 0.9057 - recall_m: 0.9036\n",
      "\n",
      "Trial 4\n",
      "Training Accuaracy (Trial 4): 97.7%\n",
      "Testing Accuaracy (Trial 4): 90.5%\n",
      "5483/5483 [==============================] - 24s 4ms/step - loss: 0.2227 - accuracy: 0.9456 - f1_m: 0.9456 - precision_m: 0.9458 - recall_m: 0.9453\n",
      "1371/1371 [==============================] - 6s 4ms/step - loss: 0.8698 - accuracy: 0.7901 - f1_m: 0.7899 - precision_m: 0.7905 - recall_m: 0.7893\n",
      "\n",
      "Trial 5\n",
      "Training Accuaracy (Trial 5): 94.6%\n",
      "Testing Accuaracy (Trial 5): 79.0%\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "\n",
    "# Trial-1\n",
    "training_score = cnn_model_trial1.evaluate(X_train, y_train)\n",
    "testing_score = cnn_model_trial1.evaluate(X_test, y_test)\n",
    "\n",
    "print(f'\\nTrial 1')\n",
    "print(f'Training Accuaracy (Trial 1): {round(training_score[1]*100,1)}%')\n",
    "print(f'Testing Accuaracy (Trial 1): {round(testing_score[1]*100,1)}%')\n",
    "\n",
    "'''   Save the data of trial 1 in cnn model trials dictionary   '''\n",
    "cnn_model_trials_dict['Training Accuaracy'][0]=round(training_score[1]*100,1)\n",
    "cnn_model_trials_dict['Testing Accuaracy'][0]=round(testing_score[1]*100,1)\n",
    "\n",
    "\n",
    "\n",
    "# Trial-2\n",
    "training_score = cnn_model_trial2.evaluate(X_train, y_train)\n",
    "testing_score = cnn_model_trial2.evaluate(X_test, y_test)\n",
    "\n",
    "print(f'\\nTrial 2')\n",
    "print(f'Training Accuaracy (Trial 2): {round(training_score[1]*100,1)}%')\n",
    "print(f'Testing Accuaracy (Trial 2): {round(testing_score[1]*100,1)}%')\n",
    "\n",
    "'''   Save the data of trial 2 in cnn model trials dictionary   '''\n",
    "cnn_model_trials_dict['Training Accuaracy'][1]=round(training_score[1]*100,1)\n",
    "cnn_model_trials_dict['Testing Accuaracy'][1]=round(testing_score[1]*100,1)\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "# Trial-3\n",
    "training_score = cnn_model_trial3.evaluate(X_train, y_train)\n",
    "testing_score = cnn_model_trial3.evaluate(X_test, y_test)\n",
    "\n",
    "print(f'\\nTrial 3')\n",
    "print(f'Training Accuaracy (Trial 3): {round(training_score[1]*100,1)}%')\n",
    "print(f'Testing Accuaracy (Trial 3): {round(testing_score[1]*100,1)}%')\n",
    "\n",
    "'''   Save the data of trial 3 in cnn model trials dictionary   '''\n",
    "cnn_model_trials_dict['Training Accuaracy'][2]=round(training_score[1]*100,1)\n",
    "cnn_model_trials_dict['Testing Accuaracy'][2]=round(testing_score[1]*100,1)\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "# Trial-4\n",
    "training_score = cnn_model_trial4.evaluate(X_train, y_train)\n",
    "testing_score = cnn_model_trial4.evaluate(X_test, y_test)\n",
    "\n",
    "print(f'\\nTrial 4')\n",
    "print(f'Training Accuaracy (Trial 4): {round(training_score[1]*100,1)}%')\n",
    "print(f'Testing Accuaracy (Trial 4): {round(testing_score[1]*100,1)}%')\n",
    "\n",
    "'''   Save the data of trial 4 in cnn model trials dictionary   '''\n",
    "cnn_model_trials_dict['Training Accuaracy'][3]=round(training_score[1]*100,1)\n",
    "cnn_model_trials_dict['Testing Accuaracy'][3]=round(testing_score[1]*100,1)\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "# Trial-5\n",
    "training_score = cnn_model_trial5.evaluate(X_train, y_train)\n",
    "testing_score = cnn_model_trial5.evaluate(X_test, y_test)\n",
    "\n",
    "print(f'\\nTrial 5')\n",
    "print(f'Training Accuaracy (Trial 5): {round(training_score[1]*100,1)}%')\n",
    "print(f'Testing Accuaracy (Trial 5): {round(testing_score[1]*100,1)}%\\n\\n')\n",
    "\n",
    "'''   Save the data of trial 5 in cnn model trials dictionary   '''\n",
    "cnn_model_trials_dict['Training Accuaracy'][4]=round(training_score[1]*100,1)\n",
    "cnn_model_trials_dict['Testing Accuaracy'][4]=round(testing_score[1]*100,1)\n",
    "\n",
    "\n",
    "cnn_model_trials_df = pd.DataFrame(cnn_model_trials_dict)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "rI2g0IAE4brD"
   },
   "source": [
    "## **Plotting The Accuracy and Loss For each Trial**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 413
    },
    "id": "c2C18phel4EO",
    "outputId": "d03f4fcb-194e-4d77-dac2-a6f932c0d150"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotting_model_measurements(cnn_model_trial1_history,'CNN',1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 413
    },
    "id": "RPg9Ow4PtnVi",
    "outputId": "05f6facc-8e70-40f4-e368-fd04cde30205"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotting_model_measurements(cnn_model_trial2_history,'CNN',2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 413
    },
    "id": "T3PfvmPLtoDT",
    "outputId": "d64c1482-e6d7-41b1-82fd-092809952fcd"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotting_model_measurements(cnn_model_trial3_history,'CNN',3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 413
    },
    "id": "GN81ZKTptonv",
    "outputId": "78479651-f262-4f0a-fdff-d01e487bcfd4"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotting_model_measurements(cnn_model_trial4_history,'CNN',4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 413
    },
    "id": "0pu7m7J7tpNh",
    "outputId": "879b8408-af3c-4fbf-c9d3-ed5a96c896fd"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotting_model_measurements(cnn_model_trial5_history,'CNN',5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "oWPVkyHMvK0H"
   },
   "source": [
    "## **Plotting The Accuracies For all Trials**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 472
    },
    "id": "oJIKmkQUvx2F",
    "outputId": "149a06f2-3a8d-4441-89f3-c79a72e62aa8"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cnn_model_trials_df[['Measurement','Training Accuaracy','Testing Accuaracy']].plot(x='Measurement', title = 'Accuaracy of All CNN Trials');\n",
    "plt.savefig('/content/drive/MyDrive/Colab Notebooks/ChatGPT_SentimentAnalysis/Images/CNN Model (All Trials Accuracies).png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "OFNxukaK6ECD"
   },
   "source": [
    "## **Saving The Models**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "vXNNvJyJ6FJQ",
    "outputId": "05a8aaf9-4d07-4cef-a196-1802cbee587f"
   },
   "outputs": [],
   "source": [
    "cnn_model_trial1.save('/content/drive/MyDrive/Colab Notebooks/ChatGPT_SentimentAnalysis/Saved Models/CNN/CNN_model_trial1_Saved')\n",
    "cnn_model_trial2.save('/content/drive/MyDrive/Colab Notebooks/ChatGPT_SentimentAnalysis/Saved Models/CNN/CNN_model_trial2_Saved')\n",
    "cnn_model_trial3.save('/content/drive/MyDrive/Colab Notebooks/ChatGPT_SentimentAnalysis/Saved Models/CNN/CNN_model_trial3_Saved')\n",
    "cnn_model_trial4.save('/content/drive/MyDrive/Colab Notebooks/ChatGPT_SentimentAnalysis/Saved Models/CNN/CNN_model_trial4_Saved')\n",
    "cnn_model_trial5.save('/content/drive/MyDrive/Colab Notebooks/ChatGPT_SentimentAnalysis/Saved Models/CNN/CNN_model_trial5_Saved')\n",
    "# model = tf.keras.models.load_model('/content/drive/MyDrive/Colab Notebooks/ChatGPT_SentimentAnalysis/Saved Models/LSTM/LSTM_model_trial5_Saved')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "-YXfb_wkEs6_"
   },
   "source": [
    "# **Long Short Term Memory (LSTM) Architecture**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "uxHXdbNVExTW"
   },
   "source": [
    "## **Building The Model**\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "lmL6QUxGDYw1"
   },
   "outputs": [],
   "source": [
    "\n",
    "def build_LSTM(Conv1D,Dense1,Dense2,lstm_units,_learning_rate,embedding_trainable,optimizer_type,model_name):\n",
    "    model = models.Sequential(name=model_name)\n",
    "    model.add(layers.Embedding(num_of_words, num_of_dimensions, input_length=max_num_of_words,name='embedding_Layer'))\n",
    "    if Conv1D:\n",
    "      model.add(layers.Conv1D(64, 8, activation = 'relu'))\n",
    "    \n",
    "    model.add(layers.Bidirectional(layers.LSTM(lstm_units, dropout = 0.2, recurrent_dropout = 0.2)))\n",
    "    \n",
    "    if Dense1:\n",
    "      model.add(layers.Dense(256, activation='relu'))\n",
    "      model.add(layers.Dropout(0.5))\n",
    "    \n",
    "    if Dense2:\n",
    "      model.add(layers.Dense(64, activation='relu'))\n",
    "      model.add(layers.Dropout(0.5))\n",
    "    \n",
    "    model.add(layers.Dense(3, activation='softmax',name='Output_Layer'))\n",
    "    model.layers[0].set_weights([embedding_matrix])\n",
    "    if embedding_trainable:\n",
    "       model.layers[0].trainable = True\n",
    "    else:\n",
    "       model.layers[0].trainable = False\n",
    "    \n",
    "    if optimizer_type=='adam':\n",
    "      model.compile(loss='categorical_crossentropy',optimizer=tf.keras.optimizers.Adam(learning_rate=_learning_rate),metrics=['accuracy',f1_m,precision_m, recall_m])\n",
    "    else:\n",
    "      model.compile(loss='categorical_crossentropy',optimizer = tf.keras.optimizers.RMSprop(learning_rate=_learning_rate),metrics=['accuracy',f1_m,precision_m, recall_m])\n",
    "    \n",
    "    model.summary()\n",
    "    return model\n",
    "\n",
    "\n",
    "lstm_model_trials_dict = {\n",
    "             'Measurement' : ['Trial-1', 'Trial-2' , 'Trial-3', 'Trial-4', 'Trial-5'], # Trial-1 => 0 , Trial-2 => 1 , ...\n",
    "             'Training Accuaracy' : [0,0,0,0,0],\n",
    "             'Testing Accuaracy' : [0,0,0,0,0],\n",
    "             'Loss' : [0,0,0,0,0],\n",
    "             'Embedding layer Trainable':['No','No','No','No','No']\n",
    "}\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "51jitfAS4UT6"
   },
   "source": [
    "## **LSTM Model Training Trials**\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "Vj_UcZX74bUi",
    "outputId": "6be28f9d-87ca-4942-ab6f-9f63d153f9f0"
   },
   "outputs": [],
   "source": [
    "# Trial-1 (embedding_trainable=True)\n",
    "\n",
    "lstm_model_trial1 = build_LSTM(Conv1D=False , Dense1=False , Dense2=True , lstm_units=64 , _learning_rate=0.01 , embedding_trainable=True , optimizer_type='adam' , model_name='LSTM_Trial-1')\n",
    "lstm_model_trial1_history = lstm_model_trial1.fit(X_train, y_train,epochs=6,batch_size=256,validation_split=0.2)\n",
    "\n",
    "'''Plotting Model Architecture For Trial-1'''\n",
    "tf.keras.utils.plot_model(lstm_model_trial1, show_shapes=True,to_file=\"/content/drive/MyDrive/Colab Notebooks/ChatGPT_SentimentAnalysis/Images/LSTM Model (Trial 1).png\")\n",
    "\n",
    "lstm_model_trials_dict['Embedding layer Trainable'][0]='Yes'\n",
    "\n",
    "\n",
    "\n",
    "# Trial-2 (embedding_trainable=False)\n",
    "\n",
    "lstm_model_trial2 = build_LSTM(Conv1D=True , Dense1=False , Dense2=False , lstm_units=512 , _learning_rate=0.001 , embedding_trainable=False , optimizer_type='adam' , model_name='LSTM_Trial-2')\n",
    "lstm_model_trial2_history = lstm_model_trial2.fit(X_train, y_train,epochs=6,batch_size=256,validation_split=0.2)\n",
    "\n",
    "'''Plotting Model Architecture For Trial-2'''\n",
    "tf.keras.utils.plot_model(lstm_model_trial2, show_shapes=True,to_file=\"/content/drive/MyDrive/Colab Notebooks/ChatGPT_SentimentAnalysis/Images/LSTM Model (Trial 2).png\")\n",
    "\n",
    "lstm_model_trials_dict['Embedding layer Trainable'][1]='No'\n",
    "\n",
    "\n",
    "\n",
    "# Trial-3 (embedding_trainable=False)\n",
    "\n",
    "lstm_model_trial3 = build_LSTM(Conv1D=False , Dense1=True , Dense2=False , lstm_units=128 , _learning_rate=0.001 , embedding_trainable=False , optimizer_type='rmsp' , model_name='LSTM_Trial-3')\n",
    "lstm_model_trial3_history = lstm_model_trial3.fit(X_train, y_train,epochs=6,batch_size=256,validation_split=0.2)\n",
    "\n",
    "'''Plotting Model Architecture For Trial-3'''\n",
    "tf.keras.utils.plot_model(lstm_model_trial3, show_shapes=True,to_file=\"/content/drive/MyDrive/Colab Notebooks/ChatGPT_SentimentAnalysis/Images/LSTM Model (Trial 3).png\")\n",
    "\n",
    "lstm_model_trials_dict['Embedding layer Trainable'][2]='No'\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "# Trial-4 (embedding_trainable=True)\n",
    "\n",
    "lstm_model_trial4 = build_LSTM(Conv1D=True , Dense1=True , Dense2=True , lstm_units=128 , _learning_rate=0.001 , embedding_trainable=True , optimizer_type='rmsp' , model_name='LSTM_Trial-4')\n",
    "lstm_model_trial4_history = lstm_model_trial4.fit(X_train, y_train,epochs=6,batch_size=256,validation_split=0.2)\n",
    "\n",
    "'''Plotting Model Architecture For Trial-4'''\n",
    "tf.keras.utils.plot_model(lstm_model_trial4, show_shapes=True,to_file=\"/content/drive/MyDrive/Colab Notebooks/ChatGPT_SentimentAnalysis/Images/LSTM Model (Trial 4).png\")\n",
    "\n",
    "lstm_model_trials_dict['Embedding layer Trainable'][3]='Yes'\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "# Trial-5 (embedding_trainable=True)\n",
    "\n",
    "lstm_model_trial5 = build_LSTM(Conv1D=True , Dense1=True , Dense2=False , lstm_units=256 , _learning_rate=0.001 , embedding_trainable=True , optimizer_type='adam' , model_name='LSTM_Trial-5')\n",
    "lstm_model_trial5_history = lstm_model_trial5.fit(X_train, y_train,epochs=6, verbose=1,batch_size=256,validation_split=0.2)\n",
    "\n",
    "'''Plotting Model Architecture For Trial-5'''\n",
    "tf.keras.utils.plot_model(lstm_model_trial5, show_shapes=True,to_file=\"/content/drive/MyDrive/Colab Notebooks/ChatGPT_SentimentAnalysis/Images/LSTM Model (Trial 5).png\")\n",
    "\n",
    "lstm_model_trials_dict['Embedding layer Trainable'][4]='Yes'\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "CUpcGPtgE4VH"
   },
   "source": [
    "## **Testing The Model Trials**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "jny9KsdBDZQA",
    "outputId": "1bb5c2e4-0d5e-427a-b9d9-a17ae246b260"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5483/5483 [==============================] - 181s 33ms/step - loss: 0.1438 - accuracy: 0.9559 - f1_m: 0.9559 - precision_m: 0.9578 - recall_m: 0.9540\n",
      "1371/1371 [==============================] - 45s 33ms/step - loss: 0.3327 - accuracy: 0.9067 - f1_m: 0.9062 - precision_m: 0.9088 - recall_m: 0.9038\n",
      "\n",
      "Trial 1\n",
      "Training Accuaracy (Trial 1): 95.6%\n",
      "Testing Accuaracy (Trial 1): 90.7%\n",
      "5483/5483 [==============================] - 168s 31ms/step - loss: 0.2465 - accuracy: 0.9120 - f1_m: 0.9116 - precision_m: 0.9195 - recall_m: 0.9040\n",
      "1371/1371 [==============================] - 43s 32ms/step - loss: 0.4360 - accuracy: 0.8413 - f1_m: 0.8405 - precision_m: 0.8491 - recall_m: 0.8323\n",
      "\n",
      "Trial 2\n",
      "Training Accuaracy (Trial 2): 91.2%\n",
      "Testing Accuaracy (Trial 2): 84.1%\n",
      "5483/5483 [==============================] - 178s 32ms/step - loss: 0.3220 - accuracy: 0.8751 - f1_m: 0.8742 - precision_m: 0.8894 - recall_m: 0.8599\n",
      "1371/1371 [==============================] - 45s 33ms/step - loss: 0.3795 - accuracy: 0.8583 - f1_m: 0.8568 - precision_m: 0.8726 - recall_m: 0.8420\n",
      "\n",
      "Trial 3\n",
      "Training Accuaracy (Trial 3): 87.5%\n",
      "Testing Accuaracy (Trial 3): 85.8%\n",
      "5483/5483 [==============================] - 158s 29ms/step - loss: 0.1834 - accuracy: 0.9373 - f1_m: 0.9374 - precision_m: 0.9400 - recall_m: 0.9349\n",
      "1371/1371 [==============================] - 39s 29ms/step - loss: 0.3651 - accuracy: 0.8965 - f1_m: 0.8965 - precision_m: 0.8992 - recall_m: 0.8940\n",
      "\n",
      "Trial 4\n",
      "Training Accuaracy (Trial 4): 93.7%\n",
      "Testing Accuaracy (Trial 4): 89.6%\n",
      "5483/5483 [==============================] - 158s 29ms/step - loss: 0.1077 - accuracy: 0.9681 - f1_m: 0.9681 - precision_m: 0.9691 - recall_m: 0.9671\n",
      "1371/1371 [==============================] - 39s 29ms/step - loss: 0.3362 - accuracy: 0.9106 - f1_m: 0.9106 - precision_m: 0.9117 - recall_m: 0.9096\n",
      "\n",
      "Trial 5\n",
      "Training Accuaracy (Trial 5): 96.8%\n",
      "Testing Accuaracy (Trial 5): 91.1%\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "\n",
    "# Trial-1\n",
    "training_score = lstm_model_trial1.evaluate(X_train, y_train)\n",
    "testing_score = lstm_model_trial1.evaluate(X_test, y_test)\n",
    "\n",
    "print(f'\\nTrial 1')\n",
    "print(f'Training Accuaracy (Trial 1): {round(training_score[1]*100,1)}%')\n",
    "print(f'Testing Accuaracy (Trial 1): {round(testing_score[1]*100,1)}%')\n",
    "\n",
    "'''   Save the data of trial 1 in lstm model trials dictionary   '''\n",
    "lstm_model_trials_dict['Training Accuaracy'][0]=round(training_score[1]*100,1)\n",
    "lstm_model_trials_dict['Testing Accuaracy'][0]=round(testing_score[1]*100,1)\n",
    "\n",
    "\n",
    "\n",
    "# Trial-2\n",
    "training_score = lstm_model_trial2.evaluate(X_train, y_train)\n",
    "testing_score = lstm_model_trial2.evaluate(X_test, y_test)\n",
    "\n",
    "print(f'\\nTrial 2')\n",
    "print(f'Training Accuaracy (Trial 2): {round(training_score[1]*100,1)}%')\n",
    "print(f'Testing Accuaracy (Trial 2): {round(testing_score[1]*100,1)}%')\n",
    "\n",
    "'''   Save the data of trial 2 in lstm model trials dictionary   '''\n",
    "lstm_model_trials_dict['Training Accuaracy'][1]=round(training_score[1]*100,1)\n",
    "lstm_model_trials_dict['Testing Accuaracy'][1]=round(testing_score[1]*100,1)\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "# Trial-3\n",
    "training_score = lstm_model_trial3.evaluate(X_train, y_train)\n",
    "testing_score = lstm_model_trial3.evaluate(X_test, y_test)\n",
    "\n",
    "print(f'\\nTrial 3')\n",
    "print(f'Training Accuaracy (Trial 3): {round(training_score[1]*100,1)}%')\n",
    "print(f'Testing Accuaracy (Trial 3): {round(testing_score[1]*100,1)}%')\n",
    "\n",
    "'''   Save the data of trial 3 in lstm model trials dictionary   '''\n",
    "lstm_model_trials_dict['Training Accuaracy'][2]=round(training_score[1]*100,1)\n",
    "lstm_model_trials_dict['Testing Accuaracy'][2]=round(testing_score[1]*100,1)\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "# Trial-4\n",
    "training_score = lstm_model_trial4.evaluate(X_train, y_train)\n",
    "testing_score = lstm_model_trial4.evaluate(X_test, y_test)\n",
    "\n",
    "print(f'\\nTrial 4')\n",
    "print(f'Training Accuaracy (Trial 4): {round(training_score[1]*100,1)}%')\n",
    "print(f'Testing Accuaracy (Trial 4): {round(testing_score[1]*100,1)}%')\n",
    "\n",
    "'''   Save the data of trial 4 in lstm model trials dictionary   '''\n",
    "lstm_model_trials_dict['Training Accuaracy'][3]=round(training_score[1]*100,1)\n",
    "lstm_model_trials_dict['Testing Accuaracy'][3]=round(testing_score[1]*100,1)\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "# Trial-5\n",
    "training_score = lstm_model_trial5.evaluate(X_train, y_train)\n",
    "testing_score = lstm_model_trial5.evaluate(X_test, y_test)\n",
    "\n",
    "print(f'\\nTrial 5')\n",
    "print(f'Training Accuaracy (Trial 5): {round(training_score[1]*100,1)}%')\n",
    "print(f'Testing Accuaracy (Trial 5): {round(testing_score[1]*100,1)}%\\n\\n')\n",
    "\n",
    "'''   Save the data of trial 5 in lstm model trials dictionary   '''\n",
    "lstm_model_trials_dict['Training Accuaracy'][4]=round(training_score[1]*100,1)\n",
    "lstm_model_trials_dict['Testing Accuaracy'][4]=round(testing_score[1]*100,1)\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "colab": {
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     "height": 206
    },
    "id": "RCeDu3e-03DR",
    "outputId": "2c0e5173-066f-40bb-fb9d-ff85e5e3fa37"
   },
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       "      <th></th>\n",
       "      <th>Measurement</th>\n",
       "      <th>Training Accuaracy</th>\n",
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      "text/plain": [
       "  Measurement  Training Accuaracy  Testing Accuaracy  Loss  \\\n",
       "0     Trial-1                95.6               90.7     0   \n",
       "1     Trial-2                91.2               84.1     0   \n",
       "2     Trial-3                87.5               85.8     0   \n",
       "3     Trial-4                93.7               89.6     0   \n",
       "4     Trial-5                96.8               91.1     0   \n",
       "\n",
       "  Embedding layer Trainable  \n",
       "0                       Yes  \n",
       "1                        No  \n",
       "2                        No  \n",
       "3                       Yes  \n",
       "4                       Yes  "
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lstm_model_trials_df = pd.DataFrame(lstm_model_trials_dict)\n",
    "lstm_model_trials_df.to_csv('/content/drive/MyDrive/Colab Notebooks/ChatGPT_SentimentAnalysis/Files/LSTM_Trials_Table.csv')\n",
    "lstm_model_trials_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "ay29kaw91g0T"
   },
   "source": [
    "## **Plotting The Accuracy and Loss For each Trial**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 413
    },
    "id": "j5U_k1qfz1Oz",
    "outputId": "2ef5b504-d211-4892-9ae6-4565c020e9de"
   },
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1000x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotting_model_measurements(lstm_model_trial1_history,'LSTM',1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 413
    },
    "id": "9qUWCD7b5RMC",
    "outputId": "40317f0a-4ea9-48ba-ef86-4416054afbb8"
   },
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1000x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotting_model_measurements(lstm_model_trial2_history,'LSTM',2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 413
    },
    "id": "1xlrQC0a5RS_",
    "outputId": "d7c2ca4b-00f1-4ccc-d6d3-1846070e1e90"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotting_model_measurements(lstm_model_trial3_history,'LSTM',3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 413
    },
    "id": "4ZVzdIP75RYY",
    "outputId": "156878f0-bc70-4407-b963-3e34428f4ce8"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotting_model_measurements(lstm_model_trial4_history,'LSTM',4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 413
    },
    "id": "E4jMuxJt5RfM",
    "outputId": "183d80bf-1bac-4142-b169-fa2516e958f7"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotting_model_measurements(lstm_model_trial5_history,'LSTM',5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "AZTbuTzL3m4h"
   },
   "source": [
    "## **Plotting The Accuracies For all Trials**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 472
    },
    "id": "HqZO9ue33ndi",
    "outputId": "0a525b06-8d50-4579-829d-5556bb56c6dc"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "lstm_model_trials_df[['Measurement','Training Accuaracy','Testing Accuaracy']].plot(x='Measurement', title = 'Accuaracy of All LSTM Trials');\n",
    "plt.savefig('/content/drive/MyDrive/Colab Notebooks/ChatGPT_SentimentAnalysis/Images/LSTM Model (All Trials Accuracies).png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "U14rkPDkzLcT"
   },
   "source": [
    "## **Saving The Models**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "-2FLV7JCzSF6"
   },
   "outputs": [],
   "source": [
    "lstm_model_trial1.save('/content/drive/MyDrive/Colab Notebooks/ChatGPT_SentimentAnalysis/Saved Models/LSTM/LSTM_model_trial1_Saved')\n",
    "lstm_model_trial2.save('/content/drive/MyDrive/Colab Notebooks/ChatGPT_SentimentAnalysis/Saved Models/LSTM/LSTM_model_trial2_Saved')\n",
    "lstm_model_trial3.save('/content/drive/MyDrive/Colab Notebooks/ChatGPT_SentimentAnalysis/Saved Models/LSTM/LSTM_model_trial3_Saved')\n",
    "lstm_model_trial4.save('/content/drive/MyDrive/Colab Notebooks/ChatGPT_SentimentAnalysis/Saved Models/LSTM/LSTM_model_trial4_Saved')\n",
    "lstm_model_trial5.save('/content/drive/MyDrive/Colab Notebooks/ChatGPT_SentimentAnalysis/Saved Models/LSTM/LSTM_model_trial5_Saved')\n",
    "# model = tf.keras.models.load_model('/content/drive/MyDrive/Colab Notebooks/ChatGPT_SentimentAnalysis/Saved Models/LSTM/LSTM_model_trial5_Saved')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "5wnNAzpp87UL"
   },
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "hT2rhAh5MEdh"
   },
   "source": [
    "\n",
    "\n",
    "  \n",
    "\n",
    "---\n",
    "\n",
    "\n",
    "#  > **We Notice that the high accuracy for the 2 models after training them is:-**\n",
    "\n",
    "\n",
    "  *   ### CNN Model => **Trial 4**\n",
    "  *   ### LSTM Model => **Trial 5**\n",
    "\n",
    "\n",
    "---\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "fjvPsLbZ8_0V"
   },
   "source": [
    "# **New tweets Predictions**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "nfjPUOX9dflf"
   },
   "source": [
    "## **Labels**\n",
    "\n",
    "*   Negative => 0\n",
    "*   Positive => 1\n",
    "*   Neutral  => 2\n",
    "\n",
    "\n",
    "---\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 191,
   "metadata": {
    "id": "oPiMy9aSev2c"
   },
   "outputs": [],
   "source": [
    "def sentiment_category(label_id):\n",
    "    label = ''\n",
    "    if label_id==1:\n",
    "        label = 'positive'\n",
    "    elif label_id==2:\n",
    "        label = 'neutral'\n",
    "    else:\n",
    "        label = 'negative'\n",
    "    return label"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "otxbqMOk9RnW"
   },
   "source": [
    "## **Using CNN Model**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "nZe0dTk1Hs-w",
    "outputId": "d3666a7a-c658-413b-8489-e96c1e415690"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"CNN_Trial-4\"\n",
      "_________________________________________________________________\n",
      " Layer (type)                Output Shape              Param #   \n",
      "=================================================================\n",
      " embedding_Layer (Embedding)  (None, 49, 300)          9600000   \n",
      "                                                                 \n",
      " conv1d_10 (Conv1D)          (None, 49, 128)           614528    \n",
      "                                                                 \n",
      " max_pooling1d_6 (MaxPooling  (None, 16, 128)          0         \n",
      " 1D)                                                             \n",
      "                                                                 \n",
      " conv1d_11 (Conv1D)          (None, 16, 128)           262272    \n",
      "                                                                 \n",
      " max_pooling1d_7 (MaxPooling  (None, 5, 128)           0         \n",
      " 1D)                                                             \n",
      "                                                                 \n",
      " conv1d_12 (Conv1D)          (None, 5, 128)            262272    \n",
      "                                                                 \n",
      " max_pooling1d_8 (MaxPooling  (None, 1, 128)           0         \n",
      " 1D)                                                             \n",
      "                                                                 \n",
      " dropout_19 (Dropout)        (None, 1, 128)            0         \n",
      "                                                                 \n",
      " flatten_4 (Flatten)         (None, 128)               0         \n",
      "                                                                 \n",
      " dense_15 (Dense)            (None, 64)                8256      \n",
      "                                                                 \n",
      " dropout_20 (Dropout)        (None, 64)                0         \n",
      "                                                                 \n",
      " dense_16 (Dense)            (None, 32)                2080      \n",
      "                                                                 \n",
      " dropout_21 (Dropout)        (None, 32)                0         \n",
      "                                                                 \n",
      " Output_Layer (Dense)        (None, 3)                 99        \n",
      "                                                                 \n",
      "=================================================================\n",
      "Total params: 10,749,507\n",
      "Trainable params: 10,749,507\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "cnn_model = tf.keras.models.load_model('/content/drive/MyDrive/Colab Notebooks/ChatGPT_SentimentAnalysis/Saved Models/CNN/CNN_model_trial4_Saved',\n",
    "                                              custom_objects={\"f1_m\": f1_m, \"precision_m\": precision_m, \"recall_m\": recall_m })\n",
    "cnn_model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 281,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "jDyIZvBsFOX5",
    "outputId": "2b40f130-6759-461b-da71-b915a600ad5f"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1/1 [==============================] - 0s 43ms/step\n",
      "Text: High quality pants. Very comfortable and great for sport activities. Good price for nice quality! I recommend to all fans of sports\n",
      "Label ID: 1\n",
      "Label Name: positive\n",
      "Polarity: 0.9909900426864624\n",
      "\n",
      "\n",
      "1/1 [==============================] - 0s 41ms/step\n",
      "Text: Sooo SAD I will miss you here in San Diego\n",
      "Label ID: 0\n",
      "Label Name: negative\n",
      "Polarity: 0.9999892711639404\n",
      "\n",
      "\n",
      "1/1 [==============================] - 0s 53ms/step\n",
      "Text:  My daughter went to a Bday party today caled, 'Grace' of Cakes...the little girl is named Grace & they made cupcakes!\n",
      "Label ID: 2\n",
      "Label Name: neutral\n",
      "Polarity: 0.8654656410217285\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Postive Example\n",
    "tweet = \"High quality pants. Very comfortable and great for sport activities. Good price for nice quality! I recommend to all fans of sports\"  # positive\n",
    "\n",
    "new_tweet=clean_text(tweet)\n",
    "new_tweet=word_tokenize(new_tweet)\n",
    "new_tweet=lemmatizer.lemmatize(new_tweet)\n",
    "sequences = tokenizer.texts_to_sequences([new_tweet])\n",
    "data = pad_sequences(sequences, maxlen=max_num_of_words)\n",
    "\n",
    "output = cnn_model.predict(data)\n",
    "label_id = np.argmax(output)\n",
    "print(f'Text: {text}\\nLabel ID: {label_id}\\nLabel Name: {sentiment_category(label_id)}\\nPolarity: {np.take(output, label_id)}\\n\\n')\n",
    "\n",
    "\n",
    "\n",
    "# Negative Example\n",
    "tweet = \"Sooo SAD I will miss you here in San Diego\"  # negative\n",
    "\n",
    "new_tweet=clean_text(tweet)\n",
    "new_tweet=word_tokenize(new_tweet)\n",
    "new_tweet=lemmatizer.lemmatize(new_tweet)\n",
    "sequences = tokenizer.texts_to_sequences([new_tweet])\n",
    "data = pad_sequences(sequences, maxlen=max_num_of_words)\n",
    "\n",
    "output = cnn_model.predict(data)\n",
    "label_id = np.argmax(output)\n",
    "print(f'Text: {text}\\nLabel ID: {label_id}\\nLabel Name: {sentiment_category(label_id)}\\nPolarity: {np.take(output, label_id)}\\n\\n')\n",
    "\n",
    "\n",
    "\n",
    "# Negative Example\n",
    "tweet = \" My daughter went to a Bday party today caled, 'Grace' of Cakes...the little girl is named Grace & they made cupcakes!\"  # negative\n",
    "\n",
    "new_tweet=clean_text(tweet)\n",
    "new_tweet=word_tokenize(new_tweet)\n",
    "new_tweet=lemmatizer.lemmatize(new_tweet)\n",
    "sequences = tokenizer.texts_to_sequences([new_tweet])\n",
    "data = pad_sequences(sequences, maxlen=max_num_of_words)\n",
    "\n",
    "output = cnn_model.predict(data)\n",
    "label_id = np.argmax(output)\n",
    "print(f'Text: {text}\\nLabel ID: {label_id}\\nLabel Name: {sentiment_category(label_id)}\\nPolarity: {np.take(output, label_id)}\\n\\n')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Y1XbItfpp2HR"
   },
   "source": [
    "## **Using LSTM Model**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 283,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "ZmpXgsqkp3_M",
    "outputId": "dac54fe3-9d05-4507-ade5-90a19a82523d"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"LSTM_Trial-5\"\n",
      "_________________________________________________________________\n",
      " Layer (type)                Output Shape              Param #   \n",
      "=================================================================\n",
      " embedding_Layer (Embedding)  (None, 49, 300)          9600000   \n",
      "                                                                 \n",
      " conv1d_3 (Conv1D)           (None, 42, 64)            153664    \n",
      "                                                                 \n",
      " bidirectional_9 (Bidirectio  (None, 512)              657408    \n",
      " nal)                                                            \n",
      "                                                                 \n",
      " dense_6 (Dense)             (None, 256)               131328    \n",
      "                                                                 \n",
      " dropout_6 (Dropout)         (None, 256)               0         \n",
      "                                                                 \n",
      " Output_Layer (Dense)        (None, 3)                 771       \n",
      "                                                                 \n",
      "=================================================================\n",
      "Total params: 10,543,171\n",
      "Trainable params: 10,543,171\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "lstm_model = tf.keras.models.load_model('/content/drive/MyDrive/Colab Notebooks/ChatGPT_SentimentAnalysis/Saved Models/LSTM/LSTM_model_trial5_Saved',\n",
    "                                              custom_objects={\"f1_m\": f1_m, \"precision_m\": precision_m, \"recall_m\": recall_m })\n",
    "lstm_model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 284,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "I-sLbINsqPpu",
    "outputId": "a5c39172-03a1-4d4e-ac49-0bf50b0d0ffb"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1/1 [==============================] - 1s 985ms/step\n",
      "Text: High quality pants. Very comfortable and great for sport activities. Good price for nice quality! I recommend to all fans of sports\n",
      "Label ID: 1\n",
      "Label Name: positive\n",
      "Polarity: 0.997701108455658\n",
      "\n",
      "\n",
      "1/1 [==============================] - 0s 53ms/step\n",
      "Text: Sooo SAD I will miss you here in San Diego\n",
      "Label ID: 0\n",
      "Label Name: negative\n",
      "Polarity: 0.9965170621871948\n",
      "\n",
      "\n",
      "1/1 [==============================] - 0s 47ms/step\n",
      "Text:  My daughter went to a Bday party today caled, 'Grace' of Cakes...the little girl is named Grace & they made cupcakes!\n",
      "Label ID: 2\n",
      "Label Name: neutral\n",
      "Polarity: 0.9750921130180359\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Postive Example\n",
    "tweet = \"High quality pants. Very comfortable and great for sport activities. Good price for nice quality! I recommend to all fans of sports\"  # positive\n",
    "\n",
    "new_tweet=clean_text(tweet)\n",
    "new_tweet=word_tokenize(new_tweet)\n",
    "new_tweet=lemmatizer.lemmatize(new_tweet)\n",
    "sequences = tokenizer.texts_to_sequences([new_tweet])\n",
    "data = pad_sequences(sequences, maxlen=max_num_of_words)\n",
    "\n",
    "output = lstm_model.predict(data)\n",
    "label_id = np.argmax(output)\n",
    "print(f'Text: {text}\\nLabel ID: {label_id}\\nLabel Name: {sentiment_category(label_id)}\\nPolarity: {np.take(output, label_id)}\\n\\n')\n",
    "\n",
    "\n",
    "\n",
    "# Negative Example\n",
    "tweet = \"Sooo SAD I will miss you here in San Diego\"  # negative\n",
    "\n",
    "new_tweet=clean_text(tweet)\n",
    "new_tweet=word_tokenize(new_tweet)\n",
    "new_tweet=lemmatizer.lemmatize(new_tweet)\n",
    "sequences = tokenizer.texts_to_sequences([new_tweet])\n",
    "data = pad_sequences(sequences, maxlen=max_num_of_words)\n",
    "\n",
    "output = lstm_model.predict(data)\n",
    "label_id = np.argmax(output)\n",
    "print(f'Text: {text}\\nLabel ID: {label_id}\\nLabel Name: {sentiment_category(label_id)}\\nPolarity: {np.take(output, label_id)}\\n\\n')\n",
    "\n",
    "\n",
    "\n",
    "# neutral Example\n",
    "tweet = \" My daughter went to a Bday party today caled, 'Grace' of Cakes...the little girl is named Grace & they made cupcakes!\"  # neutral\n",
    "\n",
    "new_tweet=clean_text(tweet)\n",
    "new_tweet=word_tokenize(new_tweet)\n",
    "new_tweet=lemmatizer.lemmatize(new_tweet)\n",
    "sequences = tokenizer.texts_to_sequences([new_tweet])\n",
    "data = pad_sequences(sequences, maxlen=max_num_of_words)\n",
    "\n",
    "output = lstm_model.predict(data)\n",
    "label_id = np.argmax(output)\n",
    "print(f'Text: {text}\\nLabel ID: {label_id}\\nLabel Name: {sentiment_category(label_id)}\\nPolarity: {np.take(output, label_id)}\\n\\n')\n"
   ]
  }
 ],
 "metadata": {
  "accelerator": "GPU",
  "colab": {
   "gpuType": "T4",
   "provenance": []
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  "gpuClass": "standard",
  "kernelspec": {
   "display_name": "Python 3",
   "name": "python3"
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  "language_info": {
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 },
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