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"execution_count": 3, "outputs": [] }, { "cell_type": "markdown", "source": [ "# Import Libraries" ], "metadata": { "id": "uIKNDYDiJ5t0" } }, { "cell_type": "code", "execution_count": 4, "metadata": { "id": "87GzWAYYHHJ6" }, "outputs": [], "source": [ "import os\n", "import re\n", "import nltk\n", "import shap\n", "import torch\n", "import zipfile\n", "import warnings\n", "import numpy as np\n", "import pandas as pd\n", "import seaborn as sns\n", "from datasets import Dataset\n", "from collections import Counter\n", "import matplotlib.pyplot as plt\n", "warnings.filterwarnings(\"ignore\")\n", "from nltk.corpus import stopwords\n", "from nltk.stem import WordNetLemmatizer\n", "from sklearn.model_selection import GridSearchCV\n", "from sklearn.linear_model import LogisticRegression\n", "from transformers import Trainer, TrainingArguments\n", "from sklearn.model_selection import train_test_split\n", "from sklearn.feature_extraction.text import TfidfVectorizer\n", "from transformers import BertTokenizer, BertForSequenceClassification\n", "from sklearn.metrics import accuracy_score, classification_report, confusion_matrix" ] }, { "cell_type": "code", "source": [ "nltk.download('stopwords')\n", "nltk.download('wordnet')" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "R08AJ7E2KqDL", "outputId": "a9c9273f-28db-45bc-9915-99d5ce29d371" }, "execution_count": 5, "outputs": [ { "output_type": "stream", "name": "stderr", "text": [ "[nltk_data] Downloading package stopwords to /root/nltk_data...\n", "[nltk_data] Package stopwords is already up-to-date!\n", "[nltk_data] Downloading package wordnet to /root/nltk_data...\n", "[nltk_data] Package wordnet is already up-to-date!\n" ] }, { "output_type": "execute_result", "data": { "text/plain": [ "True" ] }, "metadata": {}, "execution_count": 5 } ] }, { "cell_type": "markdown", "source": [ "# Data Extract from ZIP" ], "metadata": { "id": "iEnPsJuVKf2b" } }, { "cell_type": "code", "source": [ "# zip_path = \"/content/drive/MyDrive/Sentiment_Analysis/aclImdb.zip\"\n", "# extract_path = \"/content/drive/MyDrive/Sentiment_Analysis/\"\n", "\n", "# with zipfile.ZipFile(zip_path, 'r') as zip_ref:\n", "# zip_ref.extractall(extract_path)\n", "\n", "# print(\"Dataset extracted successfully!\")" ], "metadata": { "id": "MtXMNWo8HlyQ" }, "execution_count": 6, "outputs": [] }, { "cell_type": "markdown", "source": [ "# Load IMDB Dataset" ], "metadata": { "id": "vpmKlWq4Kv5j" } }, { "cell_type": "code", "source": [ "def load_imdb_data(data_dir, limit=100):\n", "\n", " texts = []\n", " labels = []\n", "\n", " for label in ['pos', 'neg']:\n", "\n", " folder = os.path.join(data_dir, label)\n", "\n", " files = os.listdir(folder)[:limit]\n", "\n", " for file in files:\n", "\n", " path = os.path.join(folder, file)\n", "\n", " with open(path, encoding=\"utf8\") as f:\n", " texts.append(f.read())\n", "\n", " labels.append(1 if label == \"pos\" else 0)\n", "\n", " return texts, labels" ], "metadata": { "id": "aO6eGZqEHlv-" }, "execution_count": 7, "outputs": [] }, { "cell_type": "code", "source": [ "train_dir = \"/content/drive/MyDrive/Sentiment_Analysis/aclImdb/train\"\n", "test_dir = \"/content/drive/MyDrive/Sentiment_Analysis/aclImdb/test\"" ], "metadata": { "id": "ahPYUMIpHltm" }, "execution_count": 8, "outputs": [] }, { "cell_type": "code", "source": [ "train_texts, train_labels = load_imdb_data(train_dir, limit=100)\n", "test_texts, test_labels = load_imdb_data(test_dir, limit=100)\n", "\n", "print(\"Train samples:\", len(train_texts))\n", "print(\"Test samples:\", len(test_texts))" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "h5sFmxFDN9tp", "outputId": "4508c58a-6895-4263-83fd-b014d89f4f93" }, "execution_count": 9, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Train samples: 200\n", "Test samples: 200\n" ] } ] }, { "cell_type": "markdown", "source": [ "# Create DataFrame" ], "metadata": { "id": "OywHVRQALCuK" } }, { "cell_type": 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\n" ], "application/vnd.google.colaboratory.intrinsic+json": { "type": "dataframe", "variable_name": "train_df", "summary": "{\n \"name\": \"train_df\",\n \"rows\": 200,\n \"fields\": [\n {\n \"column\": \"review\",\n \"properties\": {\n \"dtype\": \"string\",\n \"num_unique_values\": 200,\n \"samples\": [\n \"This is a lot of silliness about a woman from London who marries a tea planter from Ceylon whom she barely knows. It's full of cliches, and the Liz Taylor character is not believable. It has a marvelous set, some exotic location footage. It shows Taylor at the height of her beauty. She looks stunning.\",\n \"Like one of the previous commenters said, this had the foundations of a great movie but something happened on the way to delivery. Such a waste because Collette's performance was eerie and Williams was believable. I just kept waiting for it to get better. I don't think it was bad editing or needed another director, it could have just been the film. It came across as a Canadian movie, something like the first few seasons of X-Files. Not cheap, just hokey. Also, it needed a little more suspense. Something that makes you jump off your seat. The movie reached that moment then faded away; kind of like a false climax. I can see how being too suspenseful would have taken away from the \\\"reality\\\" of the story but I thought that part was reached when Gabriel was in the hospital looking for the boy. This movie needs to have a Director's cut that tries to fix these problems.\",\n \"Sure, Titanic was a good movie, the first time you see it, but you really should see it a second time and your opinion of the film will definetly change. The first time you see the movie you see the underlying love-story and think: ooh, how romantic. The second time (and I am not the only one to think this) it is just annoying and you just sit there watching the movie thinking, When is this d**n ship going to sink??? And even this is not as impressive when you see it several times. The acting in this film is not bad, but definetly not great either. Was I glad DiCaprio did not win an oscar for that film, I mean who does he think he is, Anthony Hopkins or Denzel Washington? He does 1 half-good movie and won't do a film for less than $20 million. And then everyone is suprised that there are hardly any films with him in it. But enough about, in my eyes, the worst character of the film. Kate Winslet's performance on the other hand was wonderful. I also tink that the director is very talented to put a film of such a magnitude together. There is one lesson to be learned about this movie: there are too many love-stories as it is, filmmakers shouldn't try to add a crummy romance in to every single movie!!! Out of a possible 100% I give this film a mere 71%.\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"sentiment\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0,\n \"min\": 0,\n \"max\": 1,\n \"num_unique_values\": 2,\n \"samples\": [\n 0,\n 1\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}" } }, "metadata": {}, "execution_count": 10 } ] }, { "cell_type": "code", "source": [ "test_df = pd.DataFrame({\n", " \"review\":test_texts,\n", " \"sentiment\":test_labels\n", "})\n", "\n", "test_df.head()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 206 }, "id": "SFzDTgt0O-1n", "outputId": "f0046b40-873b-4f84-f768-2668a1a5de27" }, "execution_count": 11, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ " review sentiment\n", "0 I went and saw this movie last night after bei... 1\n", "1 Actor turned director Bill Paxton follows up h... 1\n", "2 As a recreational golfer with some knowledge o... 1\n", "3 I saw this film in a sneak preview, and it is ... 1\n", "4 Bill Paxton has taken the true story of the 19... 1" ], "text/html": [ "\n", "
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reviewsentiment
0I went and saw this movie last night after bei...1
1Actor turned director Bill Paxton follows up h...1
2As a recreational golfer with some knowledge o...1
3I saw this film in a sneak preview, and it is ...1
4Bill Paxton has taken the true story of the 19...1
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\n" ], "application/vnd.google.colaboratory.intrinsic+json": { "type": "dataframe", "variable_name": "test_df", "summary": "{\n \"name\": \"test_df\",\n \"rows\": 200,\n \"fields\": [\n {\n \"column\": \"review\",\n \"properties\": {\n \"dtype\": \"string\",\n \"num_unique_values\": 199,\n \"samples\": [\n \"Watching this little movie is a sheer delight from start to finish. The story is always entertaining, the tension never loosing up. The whole cast is wonderful. The teaming of Walken and Bracco works to perfection, it is almost like an echo of a classic screwball romance. Bracco is very sexy and really funny as the scam artist who fights for her independence. For some reason they gave Walken a very strange make up and the weirdest haircut I can imagine \\u0096 it's sort of a parody of the one Burt Lancaster had in Elmer Gantry. For me it added to the pleasure. It's the first movie I saw Miguel Ferrer in, probably one of the most under-appreciated movie actors of his generation. He's very good in a small role as Bracco's pimp. Even the Jamaican thugs are a sight to behold. I can highly recommend this movie.\",\n \"I saw this film at the Rotterdam International Film Festival 2002. This seemed to be one of the less popular films on the festival, however, as it turned out, all the more interesting.

The story, of an actor trying to come to grips with himself and his environment after withdrawing from a drug addiction, is based on actual facts. Moreover, the characters playing in the film are the real people living this experience over again, this time for the film, which is partly set up as a stage play. Not only do they all happen to be good actors, Jia Hongsheng's parents are actors in real life as well, the methods used in highlighting their relationship towards Jia are very effective.

Jia Hongsheng is the actor of some Chinese action films late eighties start nineties. Later you can see him in great films such as Frozen and Suzhou River. In between these two career paths Jia becomes a drug addict and looses all drive to act or even do anything productive, except for making somewhat futile attempts at becoming a guitar virtuoso.

I like the way the writer of the scenario choose to emphasize on his behavior after withdrawal more than on the horror of drugs. We really feel the pain and struggle Jia is in. At the same time we hate him for the way he treats those around him.

The film draws the viewer into a tiring pattern Jia seems to be caught in, dragging with him his parents and sister who try to take care of him. Because there are personal 'interviews' with the characters we feel like we are getting to know Jia not only through himself but through others as well.

The film has a heavy feel, but scenes of Jia cycling through Bejing and partying with his friends lighten the tone. So does the bitter humor in a lot of events throughout the film. The music is beautiful and stayed with me for a while after. This is a film that might not easily appeal to many people but for those interested in the more serious and modern Chinese film this is a strong recommendation.\",\n \"So tell me - what serious boozer drinks Budweiser? How many suicidally-obsessed drinkers house a fully stocked and barely touched range of drinks in their lonely motel room that a millionaire playboy's bachelor-pad bar would be proud to boast? And what kind of an alcoholic tends to drink with the bottle held about 8 inches from his hungry mouth so that the contents generally spill all over his face? Not to mention wasting good whisky by dousing your girlfriend's tits with it, just so the cinema audience can get a good eyeful of Elisabeth Shue's assets.

Cage seems to be portraying the most attention-seeking look-at-me alcoholic ever to have graced the screen while Shue looks more like a Berkely preppy slumming it for a summer than some seasoned street-walker. She is humiliated and subjugated as often as possible in this revolting movie with beatings, skin lacerations, anal rape and graphic verbal abuse - all of it completely implausible and included apparently only to convey a sense of her horribly demeaned state and offer the male viewers an astonishingly clich\\u00e9d sentimental sexual fantasy of the 'tart-with-a-heart'.

Still - I did watch it to the end, by which time I was actually laughing out loud as Shue's tough street hooker chopped carrots in the kitchen wanly, pathetically smiling while Cage - all eyes popping and shaking like like a man operating a road drill in an earthquake - grimaced and mugged his way through the final half-hour...\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"sentiment\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0,\n \"min\": 0,\n \"max\": 1,\n \"num_unique_values\": 2,\n \"samples\": [\n 0,\n 1\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}" } }, "metadata": {}, "execution_count": 11 } ] }, { "cell_type": "markdown", "source": [ "# Text Preprocessing" ], "metadata": { "id": "G1ngndxRLFuK" } }, { "cell_type": "markdown", "source": [ "### Initialize tools" ], "metadata": { "id": "g_eolcORLKiC" } }, { "cell_type": "code", "source": [ "stop_words = set(stopwords.words('english'))\n", "lemmatizer = WordNetLemmatizer()" ], "metadata": { "id": "fzszRhnOHlpM" }, "execution_count": 12, "outputs": [] }, { "cell_type": "markdown", "source": [ "### Cleaning function" ], "metadata": { "id": "5T0Dvj9XLMiT" } }, { "cell_type": "code", "source": [ "def preprocess_text(text):\n", "\n", " text = text.lower()\n", "\n", " text = re.sub(r'<.*?>','',text)\n", "\n", " text = re.sub(r'[^a-zA-Z]',' ',text)\n", "\n", " words = text.split()\n", "\n", " words = [w for w in words if w not in stop_words]\n", "\n", " words = [lemmatizer.lemmatize(w) for w in words]\n", "\n", " return \" \".join(words)" ], "metadata": { "id": "YhQlOeclHlnY" }, "execution_count": 13, "outputs": [] }, { "cell_type": "markdown", "source": [ "### Apply preprocessing" ], "metadata": { "id": "7QGfFIvQLQMC" } }, { "cell_type": "code", "source": [ "train_df['clean_review'] = train_df['review'].apply(preprocess_text)\n", "test_df['clean_review'] = test_df['review'].apply(preprocess_text)" ], "metadata": { "id": "oxsL_YlYHlj7" }, "execution_count": 14, "outputs": [] }, { "cell_type": "markdown", "source": [ "# Exploratory Data Analysis" ], "metadata": { "id": "1CcdxLJlLTQd" } }, { "cell_type": "markdown", "source": [ "### Class Distribution" ], "metadata": { "id": "OBupoPNVLVbq" } }, { "cell_type": "code", "source": [ "sns.countplot(x=train_df['sentiment'])\n", "plt.title(\"Sentiment Distribution\")\n", "plt.show()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 472 }, "id": "c3_pHtLoHlhO", "outputId": "e00f4ad6-652a-4fe9-bb20-9abb2246ce77" }, "execution_count": 15, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "
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\n" }, "metadata": {} } ] }, { "cell_type": "markdown", "source": [ "### Word Frequency" ], "metadata": { "id": "gG9lJcoaLYgL" } }, { "cell_type": "code", "source": [ "all_words = \" \".join(train_df['clean_review']).split()\n", "\n", "word_freq = Counter(all_words).most_common(20)\n", "freq_df = pd.DataFrame(word_freq,columns=['word','count'])\n", "sns.barplot(x='count',y='word',data=freq_df)\n", "plt.title(\"Top 20 Words\")\n", "plt.show()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 472 }, "id": "ug_SSB3yHle3", "outputId": "37bddb6e-38cf-4fd4-9527-23095613df7b" }, "execution_count": 16, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "
" ], "image/png": 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\n" }, "metadata": {} } ] }, { "cell_type": "markdown", "source": [ "# TF-IDF Feature Extraction" ], "metadata": { "id": "OhscQQfPLdMS" } }, { "cell_type": "code", "source": [ "tfidf = TfidfVectorizer(max_features=10000)\n", "\n", "X_train = tfidf.fit_transform(train_df['clean_review'])\n", "\n", "X_test = tfidf.transform(test_df['clean_review'])\n", "\n", "y_train = train_df['sentiment']\n", "y_test = test_df['sentiment']" ], "metadata": { "id": "l9l33Tv5HlcW" }, "execution_count": 17, "outputs": [] }, { "cell_type": "markdown", "source": [ "# Model 1: Logistic Regression" ], "metadata": { "id": "8ZhqN61sLg3r" } }, { "cell_type": "code", "source": [ "lr_model = LogisticRegression(max_iter=1000)\n", "lr_model.fit(X_train,y_train)" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 81 }, "id": "-3HkBxmCHlX3", "outputId": "19077c02-7089-44c8-9c9c-37b37cfea960" }, "execution_count": 18, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "LogisticRegression(max_iter=1000)" ], "text/html": [ "
LogisticRegression(max_iter=1000)
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
" ] }, "metadata": {}, "execution_count": 18 } ] }, { "cell_type": "code", "source": [ "y_pred_lr = lr_model.predict(X_test)" ], "metadata": { "id": "GaU7tKuTHlVm" }, "execution_count": 19, "outputs": [] }, { "cell_type": "markdown", "source": [ "### Evaluate Logistic Regression" ], "metadata": { "id": "yce8PvL4Lpa6" } }, { "cell_type": "code", "source": [ "print(\"Accuracy:\",accuracy_score(y_test,y_pred_lr))" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "WRzuOCspLpTS", "outputId": "c474f8f4-b330-4e13-c2f9-def741c2616b" }, "execution_count": 20, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Accuracy: 0.73\n" ] } ] }, { "cell_type": "code", "source": [ "print(classification_report(y_test,y_pred_lr))" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "qWxGDk-gLpOk", "outputId": "5ab28c80-fd28-4b0e-d463-368b2e2fa5aa" }, "execution_count": 21, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ " precision recall f1-score support\n", "\n", " 0 0.69 0.82 0.75 100\n", " 1 0.78 0.64 0.70 100\n", "\n", " accuracy 0.73 200\n", " macro avg 0.74 0.73 0.73 200\n", "weighted avg 0.74 0.73 0.73 200\n", "\n" ] } ] }, { "cell_type": "code", "source": [ "cm = confusion_matrix(y_test,y_pred_lr)\n", "\n", "sns.heatmap(cm,annot=True,fmt='d',cmap='Blues')\n", "\n", "plt.title(\"Confusion Matrix - Logistic Regression\")\n", "plt.xlabel(\"Predicted\")\n", "plt.ylabel(\"Actual\")\n", "plt.show()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 472 }, "id": "RuHo3ni4LpL1", "outputId": "bd343967-0103-452a-e026-9c130a73d057" }, "execution_count": 22, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "
" ], "image/png": 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\n" }, "metadata": {} } ] }, { "cell_type": "markdown", "source": [ "### Hyperparameter Tuning" ], "metadata": { "id": "8evjiXDeLvOR" } }, { "cell_type": "code", "source": [ "param_grid = {\n", " 'C':[0.1,1,10]\n", "}\n", "\n", "grid = GridSearchCV(LogisticRegression(max_iter=1000),param_grid,cv=3)\n", "\n", "grid.fit(X_train,y_train)\n", "\n", "print(\"Best parameter:\",grid.best_params_)" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "1uAcnl_TLpJU", "outputId": "d6b36677-6818-4299-e593-69ff4fcea003" }, "execution_count": 23, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Best parameter: {'C': 10}\n" ] } ] }, { "cell_type": "markdown", "source": [ "# Model 2: BERT (Transformer)" ], "metadata": { "id": "9gkyEtbdLz5w" } }, { "cell_type": "markdown", "source": [ "### Prepare Dataset" ], "metadata": { "id": "OffsdX-wPbTk" } }, { "cell_type": "code", "source": [ "train_dataset = Dataset.from_pandas(train_df[['review','sentiment']])\n", "test_dataset = Dataset.from_pandas(test_df[['review','sentiment']])" ], "metadata": { "id": "HdkOWSVSLpER" }, "execution_count": 24, "outputs": [] }, { "cell_type": "code", "source": [ "train_dataset = train_dataset.rename_column(\"sentiment\", \"labels\")\n", "test_dataset = test_dataset.rename_column(\"sentiment\", \"labels\")" ], "metadata": { "id": "SS6zhMBRYGO8" }, "execution_count": 25, "outputs": [] }, { "cell_type": "markdown", "source": [ "### Load Tokenizer" ], "metadata": { "id": "sOiDTAI2Pijl" } }, { "cell_type": "code", "source": [ "tokenizer = BertTokenizer.from_pretrained('bert-base-uncased')" ], "metadata": { "id": "8NxOz8jTLpB5" }, "execution_count": 26, "outputs": [] }, { "cell_type": "markdown", "source": [ "### Tokenization" ], "metadata": { "id": "sIyC8nciPoBW" } }, { "cell_type": "code", "source": [ "def tokenize(example):\n", " return tokenizer(example['review'],padding='max_length',truncation=True)\n", "\n", "train_dataset = train_dataset.map(tokenize,batched=True)\n", "test_dataset = test_dataset.map(tokenize,batched=True)" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 81, "referenced_widgets": [ "067d3393e6024386a7094247cb6ae8f0", "d8e640fbccb54994a4c7cf2fb25b10e0", "517f0d15b4b7426aba76c3c08f7ea299", "938898780ee74bdd805d68d49a1a7256", "8cc9cfa95348459fb54b66639d9ade20", "4ace88300ab54e10a71273afc674f584", "0498ab2693134edea5d22d749d1b750e", "08632a2ccdc34a4696274ba2288db119", "3584a422118c458692b3107f7078e53f", "0a4cf79e6a314c1fbbe2405a6142b0c0", "8d55a57eefde4291b6f04bfd0632ef59", "32e79d67f48b446585d2effd26b7b98a", "5dc1ca3fbdb54bb691cf94576bd10d86", "c830b700349c4588ae3e2145b30dff99", "c2a2a6864d3548fdac36978a2b5e80be", "e9df10a2efa545a2a4b39761d5e2565e", "7ba7ceefa790467d8dfccc47dd38ddae", "9ecfacc406f746a3a932698dae5754fa", "f4b524b2501a45ebb3b27753748ca9fd", "c058450a43af41feb2093c6b8421a8f1", "0523d6b430bd4e5cab86a44afa47f0fb", "2bbc57efbabd4de9915cd8c2882c5dbd" ] }, "id": "yO8jVsy5HlTe", "outputId": "ad857ebd-e937-49b4-c82b-5c90a0c09b41" }, "execution_count": 27, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "Map: 0%| | 0/200 [00:00" ], "text/html": [ "\n", "
\n", " \n", " \n", " [50/50 01:10, Epoch 2/2]\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
StepTraining Loss

" ] }, "metadata": {} }, { "output_type": "display_data", "data": { "text/plain": [ "Writing model shards: 0%| | 0/1 [00:00" ], "text/html": [] }, "metadata": {} }, { "output_type": "stream", "name": "stdout", "text": [ " precision recall f1-score support\n", "\n", " 0 0.89 0.68 0.77 100\n", " 1 0.74 0.92 0.82 100\n", "\n", " accuracy 0.80 200\n", " macro avg 0.82 0.80 0.80 200\n", "weighted avg 0.82 0.80 0.80 200\n", "\n" ] } ] }, { "cell_type": "code", "source": [ "cm = confusion_matrix(y_test,preds)\n", "\n", "sns.heatmap(cm,annot=True,fmt='d',cmap='Greens')\n", "\n", "plt.title(\"Confusion Matrix - BERT\")\n", "\n", "plt.show()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 452 }, "id": "bMbFtWc3L-O9", "outputId": "8804eecc-ca5d-46fc-f363-78d973ccb8b7" }, "execution_count": 34, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "

" ], "image/png": 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\n" }, "metadata": {} } ] }, { "cell_type": "markdown", "source": [ "# Model Comparison" ], "metadata": { "id": "ydAvuBgxMGxB" } }, { "cell_type": "code", "source": [ "lr_accuracy = accuracy_score(y_test,y_pred_lr)\n", "bert_accuracy = accuracy_score(y_test,preds)\n", "\n", "print(\"Logistic Regression Accuracy:\",lr_accuracy)\n", "print(\"BERT Accuracy:\",bert_accuracy)" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "kG0mD8ihMGlq", "outputId": "07110058-d3b4-4165-f82d-f03642037f50" }, "execution_count": 35, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Logistic Regression Accuracy: 0.73\n", "BERT Accuracy: 0.8\n" ] } ] }, { "cell_type": "markdown", "source": [ "# SHAP Interpretability" ], "metadata": { "id": "jcZtTDI6MKOj" } }, { "cell_type": "code", "source": [ "explainer = shap.Explainer(lr_model,X_train)\n", "\n", "shap_values = explainer(X_test[:100])\n", "\n", "shap.summary_plot(shap_values,X_test[:100])" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 957 }, "id": "7-0rGNcmMGjJ", "outputId": "c5b92e75-9660-47d3-f6af-0cb77ea6d490" }, "execution_count": 36, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "
" ], "image/png": 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\n" 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