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Import Libraries"],"metadata":{"id":"b96hXQC2FvEN"}},{"cell_type":"code","execution_count":34,"metadata":{"id":"P9AbCyJrFjde","executionInfo":{"status":"ok","timestamp":1774868394310,"user_tz":-60,"elapsed":4,"user":{"displayName":"Patel Shivam","userId":"17668739110627672419"}}},"outputs":[],"source":["import pandas as pd\n","import numpy as np\n","import matplotlib.pyplot as plt\n","import seaborn as sns\n","import re\n","import nltk\n","from nltk.corpus import stopwords\n","from nltk.stem import WordNetLemmatizer\n","from collections import Counter"]},{"cell_type":"code","source":["# Download necessary NLTK resources\n","nltk.download('stopwords')\n","nltk.download('wordnet')\n","nltk.download('omw-1.4')\n"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"NGws37xyFz9o","executionInfo":{"status":"ok","timestamp":1774868394322,"user_tz":-60,"elapsed":9,"user":{"displayName":"Patel Shivam","userId":"17668739110627672419"}},"outputId":"921df307-0c43-4971-d61c-5c8edd6d6ce9"},"execution_count":35,"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","[nltk_data] Downloading package omw-1.4 to /root/nltk_data...\n","[nltk_data]   Package omw-1.4 is already up-to-date!\n"]},{"output_type":"execute_result","data":{"text/plain":["True"]},"metadata":{},"execution_count":35}]},{"cell_type":"markdown","source":["DATA LOADING"],"metadata":{"id":"zmeqMvfwGhHe"}},{"cell_type":"code","source":["# --- 1. DATA LOADING ---\n","# Load the IMDB dataset (ensure the file path is correct for your environment)\n","df = pd.read_csv('/content/drive/MyDrive/UWTSD/IMDB-Dataset.csv')\n","\n","# Display basic info and the first few rows to understand structure [cite: 1]\n","print(\"Dataset Overview:\")\n","print(df.info())\n","print(df.head())\n"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"hwVPSHm-F_8u","executionInfo":{"status":"ok","timestamp":1774868395008,"user_tz":-60,"elapsed":685,"user":{"displayName":"Patel Shivam","userId":"17668739110627672419"}},"outputId":"bc9a91f5-a3f9-4900-895f-6ca1ccff61d0"},"execution_count":36,"outputs":[{"output_type":"stream","name":"stdout","text":["Dataset Overview:\n","<class 'pandas.core.frame.DataFrame'>\n","RangeIndex: 50000 entries, 0 to 49999\n","Data columns (total 2 columns):\n"," #   Column     Non-Null Count  Dtype \n","---  ------     --------------  ----- \n"," 0   review     50000 non-null  object\n"," 1   sentiment  50000 non-null  object\n","dtypes: object(2)\n","memory usage: 781.4+ KB\n","None\n","                                              review sentiment\n","0  One of the other reviewers has mentioned that ...  positive\n","1  A wonderful little production. <br /><br />The...  positive\n","2  I thought this was a wonderful way to spend ti...  positive\n","3  Basically there's a family where a little boy ...  negative\n","4  Petter Mattei's \"Love in the Time of Money\" is...  positive\n"]}]},{"cell_type":"markdown","source":["DATA CLEANING & PREPROCESSING"],"metadata":{"id":"no2MkeJCGJWo"}},{"cell_type":"code","source":["# --- 2. DATA CLEANING & PREPROCESSING ---\n","def preprocess_text(text):\n","    # a. Remove HTML tags (like <br /> seen in the raw data) [cite: 1]\n","    text = re.sub(r'<.*?>', '', text)\n","\n","    # b. Remove non-alphabetic characters and convert to lowercase\n","    text = re.sub(r'[^a-zA-Z]', ' ', text).lower()\n","\n","    # c. Tokenization (splitting into words)\n","    words = text.split()\n","\n","    # d. Stopword Removal\n","    stop_words = set(stopwords.words('english'))\n","    words = [w for w in words if w not in stop_words]\n","\n","    # e. Lemmatization (reducing words to their root form)\n","    lemmatizer = WordNetLemmatizer()\n","    words = [lemmatizer.lemmatize(w) for w in words]\n","\n","    return \" \".join(words)\n","\n","print(\"\\nCleaning text data... this may take a moment.\")\n","df['cleaned_review'] = df['review'].apply(preprocess_text)\n"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"_9fDmw_6GXqm","executionInfo":{"status":"ok","timestamp":1774868434109,"user_tz":-60,"elapsed":39099,"user":{"displayName":"Patel Shivam","userId":"17668739110627672419"}},"outputId":"b6b2a38f-4400-4314-bbc7-f9720574cb0c"},"execution_count":37,"outputs":[{"output_type":"stream","name":"stdout","text":["\n","Cleaning text data... this may take a moment.\n"]}]},{"cell_type":"markdown","source":["EXPLORATORY DATA ANALYSIS (EDA)"],"metadata":{"id":"lijpSN7LGoE8"}},{"cell_type":"code","source":["# --- 3. EXPLORATORY DATA ANALYSIS (EDA) ---\n","\n","# a. Class Balance: Check if the dataset is balanced between positive/negative\n","plt.figure(figsize=(6, 4))\n","sns.countplot(x='sentiment', data=df, palette='viridis')\n","plt.title('Distribution of Sentiments')\n","plt.show()\n","\n","print(\"\\nSentiment Counts:\")\n","print(df['sentiment'].value_counts())\n","\n","# b. Word Frequency: Find the most common words in the cleaned reviews\n","all_words = \" \".join(df['cleaned_review']).split()\n","word_freq = Counter(all_words)\n","common_words = word_freq.most_common(20)\n","\n","# Convert to DataFrame for plotting\n","words_df = pd.DataFrame(common_words, columns=['Word', 'Frequency'])\n","\n","plt.figure(figsize=(10, 6))\n","sns.barplot(x='Frequency', y='Word', data=words_df, palette='magma')\n","plt.title('Top 20 Most Frequent Words in IMDB Reviews')\n","plt.show()\n","\n","# c. Review Length Analysis\n","df['review_length'] = df['cleaned_review'].apply(lambda x: len(x.split()))\n","plt.figure(figsize=(8, 5))\n","sns.histplot(df['review_length'], bins=50, kde=True, color='blue')\n","plt.title('Distribution of Review Word Counts')\n","plt.xlabel('Number of Words')\n","plt.show()\n","\n","print(\"\\nTask 1 Completion: Data is cleaned and ready for Model Building.\")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"id":"f8xcEJCGZSWY","executionInfo":{"status":"ok","timestamp":1774868436992,"user_tz":-60,"elapsed":2877,"user":{"displayName":"Patel Shivam","userId":"17668739110627672419"}},"outputId":"24b0cab8-a415-4bf4-b65f-e035c34207a4"},"execution_count":38,"outputs":[{"output_type":"stream","name":"stderr","text":["/tmp/ipykernel_4852/2937949399.py:5: FutureWarning: \n","\n","Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n","\n","  sns.countplot(x='sentiment', data=df, palette='viridis')\n"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 600x400 with 1 Axes>"],"image/png":"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\n"},"metadata":{}},{"output_type":"stream","name":"stdout","text":["\n","Sentiment Counts:\n","sentiment\n","positive    25000\n","negative    25000\n","Name: count, dtype: int64\n"]},{"output_type":"stream","name":"stderr","text":["/tmp/ipykernel_4852/2937949399.py:21: FutureWarning: \n","\n","Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `y` variable to `hue` and set `legend=False` for the same effect.\n","\n","  sns.barplot(x='Frequency', y='Word', data=words_df, palette='magma')\n"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 1000x600 with 1 Axes>"],"image/png":"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\n"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["<Figure 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\n"},"metadata":{}},{"output_type":"stream","name":"stdout","text":["\n","Task 1 Completion: Data is cleaned and ready for Model Building.\n"]}]},{"cell_type":"markdown","source":["TF-IDF Feature Extraction"],"metadata":{"id":"98fR279dIEVP"}},{"cell_type":"code","source":["from sklearn.model_selection import train_test_split\n","from sklearn.feature_extraction.text import TfidfVectorizer\n","from sklearn.linear_model import LogisticRegression\n","from sklearn.metrics import classification_report, accuracy_score\n","\n","# 1. Split Data\n","X = df['cleaned_review']\n","y = df['sentiment'].apply(lambda x: 1 if x == 'positive' else 0) # Encode labels\n","\n","X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n","\n","# 2. Design Decision: TF-IDF Vectorization\n","tfidf = TfidfVectorizer(max_features=5000, ngram_range=(1, 2))\n","\n","X_train_tfidf = tfidf.fit_transform(X_train)\n","X_test_tfidf = tfidf.transform(X_test)"],"metadata":{"id":"gObAxTpgU0G5","executionInfo":{"status":"ok","timestamp":1774868459890,"user_tz":-60,"elapsed":22896,"user":{"displayName":"Patel Shivam","userId":"17668739110627672419"}}},"execution_count":39,"outputs":[]},{"cell_type":"markdown","source":["# Model 1: Logistic Regression and Hyperparameter Tuning"],"metadata":{"id":"hPGxTE87IPSA"}},{"cell_type":"code","source":["# 3. Model & Hyperparameter Tuning\n","# 'C' is the inverse of regularization strength; smaller values specify stronger regularization.\n","lr_model = LogisticRegression(C=1.0, solver='liblinear', max_iter=1000)\n","lr_model.fit(X_train_tfidf, y_train)\n","\n","# 4. Initial Evaluation\n","lr_preds = lr_model.predict(X_test_tfidf)\n","print(\"Logistic Regression Accuracy:\", accuracy_score(y_test, lr_preds))\n","print(classification_report(y_test, lr_preds))"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"GwxrjL0KIMxq","executionInfo":{"status":"ok","timestamp":1774868460657,"user_tz":-60,"elapsed":756,"user":{"displayName":"Patel Shivam","userId":"17668739110627672419"}},"outputId":"04ebca57-e85f-4154-9599-b58dbb2cb21f"},"execution_count":40,"outputs":[{"output_type":"stream","name":"stdout","text":["Logistic Regression Accuracy: 0.8914\n","              precision    recall  f1-score   support\n","\n","           0       0.90      0.88      0.89      4961\n","           1       0.88      0.90      0.89      5039\n","\n","    accuracy                           0.89     10000\n","   macro avg       0.89      0.89      0.89     10000\n","weighted avg       0.89      0.89      0.89     10000\n","\n"]}]},{"cell_type":"markdown","source":["# Model 2: BERT (Transformer Model)"],"metadata":{"id":"2Ka3uFDuI6Xm"}},{"cell_type":"code","source":["import torch\n","from transformers import AutoTokenizer, AutoModelForSequenceClassification, Trainer, TrainingArguments\n","from datasets import Dataset\n","from sklearn.metrics import accuracy_score, precision_recall_fscore_support\n","\n","# 1. DESIGN DECISION & TOKENIZER\n","\n","model_name = \"distilbert-base-uncased\"\n","tokenizer = AutoTokenizer.from_pretrained(model_name)\n"],"metadata":{"id":"agSTDHEAIr11","executionInfo":{"status":"ok","timestamp":1774868582208,"user_tz":-60,"elapsed":121548,"user":{"displayName":"Patel Shivam","userId":"17668739110627672419"}}},"execution_count":41,"outputs":[]},{"cell_type":"markdown","source":["PREPARE DATASET FOR HUGGING FACE"],"metadata":{"id":"P1mnML5HJqNA"}},{"cell_type":"code","source":["# 2. PREPARE DATASET FOR HUGGING FACE\n","# We must ensure truncation and padding are handled to avoid \"too many dimensions\"\n","def tokenize_function(examples):\n","    return tokenizer(examples[\"text\"], padding=\"max_length\", truncation=True, max_length=128)\n","\n","# Convert Pandas to Hugging Face Dataset format\n","# Using a subset (2000 for train, 500 for test) to ensure the assignment runs quickly\n","train_df_subset = pd.DataFrame({'text': X_train[:2000], 'label': y_train[:2000]})\n","test_df_subset = pd.DataFrame({'text': X_test[:500], 'label': y_test[:500]})\n","\n","train_ds = Dataset.from_pandas(train_df_subset).map(tokenize_function, batched=True)\n","test_ds = Dataset.from_pandas(test_df_subset).map(tokenize_function, batched=True)\n","\n","# Set format to PyTorch tensors\n","train_ds.set_format(type='torch', columns=['input_ids', 'attention_mask', 'label'])\n","test_ds.set_format(type='torch', columns=['input_ids', 'attention_mask', 'label'])"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":81,"referenced_widgets":["060cdf55353b412db4007bfacb773e07","480e200c0c2d4b3bb6e5f6ad7697f79f","faa63914b0bb4ccaa4ecf72d2fb2687d","5873a90433dd46dc8c5e8aae766611a8","adc792c325e74e2bb1dd939d98484429","7ad17f75b0fb47efa4542c3ace77c503","b02e16b644204408b1cc10c688738a7e","54a80097b1574b558322f267e09903cc","81d80c8300a044c0b1fd35c602da2b58","9914170629124f88a8b64c11b3efe635","060702f6f13746438460dd0a784506a0","d43eb80e21da443fba9341c8924c9f9e","e2f682c8031949acbe427bca8778c2cc","6140b4dc6f4b4369bcf7770a635b5a39","b5f9ca5a2db145d382ebc71a8f5e225c","60cb948c48d44ee1ad034a5701419805","e56b01164885405689b0718508d704b6","a23e581214c642569871bde4654e8719","ccfdbb19c5984e88b882db6ebb26d3ad","9c48dd26c69f46b0a40141f96396857c","232b0fb782b14ec690fea8449a3401f2","d75ec186a42f4f6e8bf9ff04929704e1"]},"id":"DCOEx5sQJYgc","executionInfo":{"status":"ok","timestamp":1774868583687,"user_tz":-60,"elapsed":1481,"user":{"displayName":"Patel Shivam","userId":"17668739110627672419"}},"outputId":"99cf60f6-dca2-4cf6-e979-10b5dca74287"},"execution_count":42,"outputs":[{"output_type":"display_data","data":{"text/plain":["Map:   0%|          | 0/2000 [00:00<?, ? examples/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"060cdf55353b412db4007bfacb773e07"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Map:   0%|          | 0/500 [00:00<?, ? examples/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"d43eb80e21da443fba9341c8924c9f9e"}},"metadata":{}}]},{"cell_type":"code","source":["# 3. METRICS FUNCTION\n","def compute_metrics(eval_pred):\n","    logits, labels = eval_pred\n","    predictions = np.argmax(logits, axis=-1)\n","    precision, recall, f1, _ = precision_recall_fscore_support(labels, predictions, average='binary')\n","    acc = accuracy_score(labels, predictions)\n","    return {\"accuracy\": acc, \"f1\": f1, \"precision\": precision, \"recall\": recall}"],"metadata":{"id":"I8CDoJdOJrIW","executionInfo":{"status":"ok","timestamp":1774868583698,"user_tz":-60,"elapsed":10,"user":{"displayName":"Patel Shivam","userId":"17668739110627672419"}}},"execution_count":43,"outputs":[]},{"cell_type":"markdown","source":["LOAD MODEL"],"metadata":{"id":"pB25B8LWJ70I"}},{"cell_type":"code","source":["# 4. LOAD MODEL\n","model = AutoModelForSequenceClassification.from_pretrained(model_name, num_labels=2)\n"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":347,"referenced_widgets":["e02e4ea563344d738052475dd8880053","a3e5fd09a03e48e8a3e91b081ef4be4c","dc9944b4660c4767a883aff41a6d0504","65719ba2759c4771adc267aeb672932c","be763f3f59864c88a5a1a0e69289d494","b4eaf80440cd40a6a8dc9cc28c35174c","7f4e9566328143689182a8e4dc987ad8","00d949e96fac4e26ba7703efcb25c6d6","e0e7a20680f8480dbe9c3e6b617d1ed7","56747e23f9164284a93a5a561a4d9e5e","87e73de7d11c46d58e126133cfc653eb"]},"id":"9FZBdfkMJ3sK","executionInfo":{"status":"ok","timestamp":1774868584833,"user_tz":-60,"elapsed":1134,"user":{"displayName":"Patel Shivam","userId":"17668739110627672419"}},"outputId":"f3b3afb7-51de-4d85-d139-87bd0fb3f448"},"execution_count":44,"outputs":[{"output_type":"display_data","data":{"text/plain":["Loading weights:   0%|          | 0/100 [00:00<?, ?it/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"e02e4ea563344d738052475dd8880053"}},"metadata":{}},{"output_type":"stream","name":"stderr","text":["DistilBertForSequenceClassification LOAD REPORT from: distilbert-base-uncased\n","Key                     | Status     | \n","------------------------+------------+-\n","vocab_transform.weight  | UNEXPECTED | \n","vocab_layer_norm.weight | UNEXPECTED | \n","vocab_projector.bias    | UNEXPECTED | \n","vocab_layer_norm.bias   | UNEXPECTED | \n","vocab_transform.bias    | UNEXPECTED | \n","classifier.weight       | MISSING    | \n","pre_classifier.bias     | MISSING    | \n","classifier.bias         | MISSING    | \n","pre_classifier.weight   | MISSING    | \n","\n","Notes:\n","- UNEXPECTED\t:can be ignored when loading from different task/architecture; not ok if you expect identical arch.\n","- MISSING\t:those params were newly initialized because missing from the checkpoint. Consider training on your downstream task.\n"]}]},{"cell_type":"markdown","source":["### Training Settings"],"metadata":{"id":"OS9IpxrXKE-P"}},{"cell_type":"code","source":["# 5. TRAINING ARGUMENTS\n","training_args = TrainingArguments(\n","    output_dir=\"./results\",\n","    learning_rate=2e-5,      # Design decision: Low learning rate to prevent catastrophic forgetting\n","    per_device_train_batch_size=16,\n","    num_train_epochs=3,      # Standard for fine-tuning\n","    weight_decay=0.01,\n","    eval_strategy=\"epoch\",   # Evaluate after every epoch\n","    save_strategy=\"epoch\",\n","    load_best_model_at_end=True,\n","    report_to=\"none\"         # Keeps the output clean\n",")\n"],"metadata":{"id":"Zohzi67wKAEc","executionInfo":{"status":"ok","timestamp":1774868584838,"user_tz":-60,"elapsed":2,"user":{"displayName":"Patel Shivam","userId":"17668739110627672419"}}},"execution_count":45,"outputs":[]},{"cell_type":"markdown","source":["TRAINER"],"metadata":{"id":"esYPxcTWKN0w"}},{"cell_type":"code","source":["# 6. INITIALIZE TRAINER\n","trainer = Trainer(\n","    model=model,\n","    args=training_args,\n","    train_dataset=train_ds,\n","    eval_dataset=test_ds,\n","    compute_metrics=compute_metrics\n",")\n"],"metadata":{"id":"uAAIGYrJKGxo","executionInfo":{"status":"ok","timestamp":1774868585766,"user_tz":-60,"elapsed":925,"user":{"displayName":"Patel Shivam","userId":"17668739110627672419"}}},"execution_count":46,"outputs":[]},{"cell_type":"code","source":["# 7. EXECUTE TRAINING & EVALUATION\n","print(\"Starting BERT Fine-tuning...\")\n","trainer.train()\n","\n","# Final evaluation to get the scores for  comparison table\n","bert_performance = trainer.evaluate()\n","print(\"\\n--- BERT Evaluation Metrics ---\")\n","print(bert_performance)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":409,"referenced_widgets":["ad9a6a8d2fa248be80aaeca32601a469","76d0afdb228646e092536a0d168f9274","54a0efe2906041a48d624b3ec591769a","d97312dfa64445388b678f3d1fbbccc6","0817b1ed54c54a3c87e62824cb289292","0af4891dc5de47a5be86253205c93f31","f77172fcf2dd4ad1b9d3c7f8bf9da8cb","2ed2c7acb403475f97aca1bbae0cdb47","4b5e210b262d4a7cbb295ca8194c15f1","8e0dc5fced3a40e899119ea938946d4d","3dea392e9b4740778af482c775a061a9","5bdda9258c8a4f60bf8d93588bbd7bfb","feb1162be9594dea9d0e01b9d2cc3a12","d903862986e04465b60927df83c1196f","cda5e82e17da4a5fa9d7b27aa8f4e307","c497b793780b414492ad94b12599d2cb","a080222072b54646a64663a98d30321a","0349e17bd4f7443aae192e7c37f47ce9","5a31aab18fd5459bb43e605ee210a55e","910f274fef6649209f900832cca78e83","f73d68ea62054d5e8e03d56dd3621757","5c7e4c819c7a4febae0fd07278a92c7f","8500d14a472944d08810e229c4b4e353","dcd6febe798f4048b55d3e046ecf6ef7","e86524750c254da8b15b2c7dbed8030d","0ac68f735cac4ee38f47d08eaf646871","c3eafe85039f4d2a91e959e66e154c19","ad62af2b1e5443d58305269ca9e1a69a","677261d3f47f421984d7e1811638c2d3","bc4555b9558040ee93f4bed40e0bc343","ab8d973d340b4d48af8c344e8075a8bf","b04b0725485743199cb34d6d54a1ba01","20ea743f3d644eb48508ba23a0ffb0ff"]},"id":"CBn2zzB7KPqx","executionInfo":{"status":"ok","timestamp":1774868695309,"user_tz":-60,"elapsed":109540,"user":{"displayName":"Patel Shivam","userId":"17668739110627672419"}},"outputId":"d678713e-810e-4dd1-e4ac-8c477170fd04"},"execution_count":47,"outputs":[{"output_type":"stream","name":"stdout","text":["Starting BERT Fine-tuning...\n"]},{"output_type":"display_data","data":{"text/plain":["<IPython.core.display.HTML object>"],"text/html":["\n","    <div>\n","      \n","      <progress value='375' max='375' style='width:300px; height:20px; vertical-align: middle;'></progress>\n","      [375/375 01:46, Epoch 3/3]\n","    </div>\n","    <table border=\"1\" class=\"dataframe\">\n","  <thead>\n"," <tr style=\"text-align: left;\">\n","      <th>Epoch</th>\n","      <th>Training Loss</th>\n","      <th>Validation Loss</th>\n","      <th>Accuracy</th>\n","      <th>F1</th>\n","      <th>Precision</th>\n","      <th>Recall</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <td>1</td>\n","      <td>No log</td>\n","      <td>0.367622</td>\n","      <td>0.848000</td>\n","      <td>0.843621</td>\n","      <td>0.857741</td>\n","      <td>0.829960</td>\n","    </tr>\n","    <tr>\n","      <td>2</td>\n","      <td>No log</td>\n","      <td>0.342604</td>\n","      <td>0.856000</td>\n","      <td>0.853659</td>\n","      <td>0.857143</td>\n","      <td>0.850202</td>\n","    </tr>\n","    <tr>\n","      <td>3</td>\n","      <td>No log</td>\n","      <td>0.373502</td>\n","      <td>0.864000</td>\n","      <td>0.860082</td>\n","      <td>0.874477</td>\n","      <td>0.846154</td>\n","    </tr>\n","  </tbody>\n","</table><p>"]},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"ad9a6a8d2fa248be80aaeca32601a469"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"5bdda9258c8a4f60bf8d93588bbd7bfb"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"8500d14a472944d08810e229c4b4e353"}},"metadata":{}},{"output_type":"stream","name":"stderr","text":["There were missing keys in the checkpoint model loaded: ['distilbert.embeddings.LayerNorm.weight', 'distilbert.embeddings.LayerNorm.bias'].\n","There were unexpected keys in the checkpoint model loaded: ['distilbert.embeddings.LayerNorm.beta', 'distilbert.embeddings.LayerNorm.gamma'].\n"]},{"output_type":"display_data","data":{"text/plain":["<IPython.core.display.HTML object>"],"text/html":["\n","    <div>\n","      \n","      <progress value='63' max='63' style='width:300px; height:20px; vertical-align: middle;'></progress>\n","      [63/63 00:02]\n","    </div>\n","    "]},"metadata":{}},{"output_type":"stream","name":"stdout","text":["\n","--- BERT Evaluation Metrics ---\n","{'eval_loss': 0.34260043501853943, 'eval_accuracy': 0.856, 'eval_f1': 0.8536585365853658, 'eval_precision': 0.8571428571428571, 'eval_recall': 0.8502024291497976, 'eval_runtime': 2.2015, 'eval_samples_per_second': 227.113, 'eval_steps_per_second': 28.616, 'epoch': 3.0}\n"]}]},{"cell_type":"markdown","source":["# Model Comparison"],"metadata":{"id":"6Z1SV5ZDKj_I"}},{"cell_type":"code","source":["from sklearn.metrics import classification_report, confusion_matrix, ConfusionMatrixDisplay\n","import matplotlib.pyplot as plt\n","\n","# Function to plot confusion matrix\n","def plot_cm(y_true, y_pred, title):\n","    cm = confusion_matrix(y_true, y_pred)\n","    disp = ConfusionMatrixDisplay(confusion_matrix=cm, display_labels=['Negative', 'Positive'])\n","    disp.plot(cmap=plt.cm.Blues)\n","    plt.title(title)\n","    plt.show()\n","\n","# --- Evaluate Traditional ML (Logistic Regression) ---\n","print(\"--- Logistic Regression Evaluation ---\")\n","print(classification_report(y_test, lr_preds))\n","plot_cm(y_test, lr_preds, \"Confusion Matrix: Logistic Regression\")\n","\n","# --- Evaluate Transformer Model (BERT/DistilBERT) ---\n","# Assuming 'trainer' and 'test_ds' are from the previous task\n","bert_predictions = trainer.predict(test_ds)\n","bert_preds = np.argmax(bert_predictions.predictions, axis=-1)\n","bert_true_labels = bert_predictions.label_ids\n","\n","print(\"--- DistilBERT Evaluation ---\")\n","print(classification_report(bert_true_labels, bert_preds))\n","plot_cm(bert_true_labels, bert_preds, \"Confusion Matrix: DistilBERT\")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"id":"LB9MheKzKXpL","executionInfo":{"status":"ok","timestamp":1774868697938,"user_tz":-60,"elapsed":2628,"user":{"displayName":"Patel Shivam","userId":"17668739110627672419"}},"outputId":"26d263a3-2f41-416a-b682-41a6c56feea1"},"execution_count":48,"outputs":[{"output_type":"stream","name":"stdout","text":["--- Logistic Regression Evaluation ---\n","              precision    recall  f1-score   support\n","\n","           0       0.90      0.88      0.89      4961\n","           1       0.88      0.90      0.89      5039\n","\n","    accuracy                           0.89     10000\n","   macro avg       0.89      0.89      0.89     10000\n","weighted avg       0.89      0.89      0.89     10000\n","\n"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 640x480 with 2 Axes>"],"image/png":"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\n"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["<IPython.core.display.HTML 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\n"},"metadata":{}}]},{"cell_type":"markdown","source":["# SHAP Interpretability"],"metadata":{"id":"dA7Phpn4Kp4k"}},{"cell_type":"code","source":["import shap\n","\n","# --- INTERPRETABILITY (SHAP) ---\n","\n","# Prepare a subset of the transformed test data for SHAP, as it can be computationally intensive.\n","X_test_tfidf_subset = tfidf.transform(X_test[:100])\n","\n","# Explain the Logistic Regression model using SHAP\n","# Use the already defined lr_model and tfidf objects\n","explainer = shap.Explainer(lr_model,\n","                           X_test_tfidf_subset,\n","                           feature_names=tfidf.get_feature_names_out())\n","\n","# Calculate SHAP values for the subset\n","shap_values = explainer(X_test_tfidf_subset)\n","\n","# Plot the SHAP summary\n","shap.summary_plot(shap_values, feature_names=tfidf.get_feature_names_out())"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"id":"ONImfkMVKsRG","executionInfo":{"status":"ok","timestamp":1774868698381,"user_tz":-60,"elapsed":437,"user":{"displayName":"Patel Shivam","userId":"17668739110627672419"}},"outputId":"04a8ff44-baf9-44d0-c2b8-ca72988af5c9"},"execution_count":49,"outputs":[{"output_type":"stream","name":"stderr","text":["/tmp/ipykernel_4852/3152530212.py:18: FutureWarning: The NumPy global RNG was seeded by calling `np.random.seed`. In a future version this function will no longer use the global RNG. Pass `rng` explicitly to opt-in to the new behaviour and silence this warning.\n","  shap.summary_plot(shap_values, feature_names=tfidf.get_feature_names_out())\n"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 800x950 with 2 Axes>"],"image/png":"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\n"},"metadata":{}}]}]}