sarcasm-detection-using-bert.ipynb

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   },
   "source": [
    "# Sarcasm Detection using the Pre-Trained BERT model from Transformers "
   ]
  },
  {
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/kaggle/input/news-headlines-dataset-for-sarcasm-detection/Sarcasm_Headlines_Dataset_v2.json\n",
      "/kaggle/input/news-headlines-dataset-for-sarcasm-detection/Sarcasm_Headlines_Dataset.json\n"
     ]
    }
   ],
   "source": [
    "import numpy as np \n",
    "import pandas as pd \n",
    "import os\n",
    "for dirname, _, filenames in os.walk('/kaggle/input'):\n",
    "    for filename in filenames:\n",
    "        print(os.path.join(dirname, filename))\n"
   ]
  },
  {
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   "outputs": [
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     "output_type": "stream",
     "text": [
      "\u001b[34m\u001b[1mwandb\u001b[0m: \u001b[33mWARNING\u001b[0m W&B installed but not logged in.  Run `wandb login` or set the WANDB_API_KEY env variable.\n"
     ]
    }
   ],
   "source": [
    "import tensorflow as tf\n",
    "import matplotlib.pyplot as plt\n",
    "from transformers import TFBertModel, BertTokenizer\n",
    "from sklearn.model_selection import train_test_split\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
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    {
     "data": {
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       "        text-align: right;\n",
       "    }\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>is_sarcastic</th>\n",
       "      <th>headline</th>\n",
       "      <th>article_link</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>thirtysomething scientists unveil doomsday clo...</td>\n",
       "      <td>https://www.theonion.com/thirtysomething-scien...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>dem rep. totally nails why congress is falling...</td>\n",
       "      <td>https://www.huffingtonpost.com/entry/donna-edw...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>eat your veggies: 9 deliciously different recipes</td>\n",
       "      <td>https://www.huffingtonpost.com/entry/eat-your-...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>inclement weather prevents liar from getting t...</td>\n",
       "      <td>https://local.theonion.com/inclement-weather-p...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>mother comes pretty close to using word 'strea...</td>\n",
       "      <td>https://www.theonion.com/mother-comes-pretty-c...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   is_sarcastic                                           headline  \\\n",
       "0             1  thirtysomething scientists unveil doomsday clo...   \n",
       "1             0  dem rep. totally nails why congress is falling...   \n",
       "2             0  eat your veggies: 9 deliciously different recipes   \n",
       "3             1  inclement weather prevents liar from getting t...   \n",
       "4             1  mother comes pretty close to using word 'strea...   \n",
       "\n",
       "                                        article_link  \n",
       "0  https://www.theonion.com/thirtysomething-scien...  \n",
       "1  https://www.huffingtonpost.com/entry/donna-edw...  \n",
       "2  https://www.huffingtonpost.com/entry/eat-your-...  \n",
       "3  https://local.theonion.com/inclement-weather-p...  \n",
       "4  https://www.theonion.com/mother-comes-pretty-c...  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_json(\"../input/news-headlines-dataset-for-sarcasm-detection/Sarcasm_Headlines_Dataset_v2.json\", lines=True)\n",
    "labels = data.is_sarcastic.values\n",
    "sentences = data.headline.values\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
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     "duration": 0.018198,
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     "start_time": "2021-05-21T12:15:06.289399",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "**Tokenizing all the sentences using pre-trained BERT model from Tranformers**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
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   },
   "outputs": [
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      "\n"
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   "source": [
    "PRE_TRAINED_MODEL_NAME = 'bert-base-uncased'\n",
    "tokenizer = BertTokenizer.from_pretrained(PRE_TRAINED_MODEL_NAME,do_lower_case = True)\n",
    "\n",
    "def encoder(sentences):\n",
    "  ids = []\n",
    "  for sentence in sentences:\n",
    "    encoding = tokenizer.encode_plus(\n",
    "    sentence,\n",
    "    max_length=16,\n",
    "    truncation = True,\n",
    "    add_special_tokens=True,\n",
    "    return_token_type_ids=False,\n",
    "    pad_to_max_length=True,\n",
    "    return_attention_mask=False)\n",
    "    ids.append(encoding['input_ids'])\n",
    "  return ids\n",
    "\n",
    "#Train test split\n",
    "train_sents,test_sents, train_labels, test_labels  = train_test_split(sentences,labels,test_size=0.20, random_state=3)\n",
    "dev_sents,test_sents, dev_labels, test_labels  = train_test_split(test_sents,test_labels,test_size=0.50, random_state=3)\n",
    "\n",
    "train_ids = encoder(train_sents)\n",
    "dev_ids = encoder(dev_sents)\n",
    "test_ids = encoder(test_sents) "
   ]
  },
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   "source": [
    "Converting arrays to tensors"
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   },
   "outputs": [],
   "source": [
    "train_ids = tf.convert_to_tensor(train_ids)\n",
    "train_labels = tf.convert_to_tensor(train_labels)\n",
    "\n",
    "dev_ids = tf.convert_to_tensor(dev_ids)\n",
    "dev_labels = tf.convert_to_tensor(dev_labels)\n",
    "\n",
    "test_ids = tf.convert_to_tensor(test_ids)\n",
    "test_labels = tf.convert_to_tensor(test_labels)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
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     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Building Model from transformers using pre-trained bert-base-uncased (12-layer, 768-hidden, 12-heads, 110M parameters.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
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     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "bert_encoder = TFBertModel.from_pretrained('bert-base-uncased')\n",
    "input_word_ids = tf.keras.Input(shape=(16,), dtype=tf.int32, name=\"input_word_ids\")  \n",
    "embedding = bert_encoder([input_word_ids])\n",
    "dense = tf.keras.layers.Lambda(lambda seq: seq[:, 0, :])(embedding[0])\n",
    "#dense = tf.keras.layers.Dense(128, activation='relu')(dense)\n",
    "dense = tf.keras.layers.Dense(256, activation='relu')(dense)\n",
    "dense = tf.keras.layers.Dense(128, activation='tanh')(dense)\n",
    "dense = tf.keras.layers.Dropout(0.2)(dense)\n",
    "\n",
    "output = tf.keras.layers.Dense(1, activation='sigmoid')(dense)    \n",
    "\n",
    "\n",
    "model = tf.keras.Model(inputs=[input_word_ids], outputs=output)  \n"
   ]
  },
  {
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   "execution_count": 7,
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"functional_1\"\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "input_word_ids (InputLayer)  [(None, 16)]              0         \n",
      "_________________________________________________________________\n",
      "tf_bert_model (TFBertModel)  ((None, 16, 768), (None,  109482240 \n",
      "_________________________________________________________________\n",
      "lambda (Lambda)              (None, 768)               0         \n",
      "_________________________________________________________________\n",
      "dense (Dense)                (None, 256)               196864    \n",
      "_________________________________________________________________\n",
      "dense_1 (Dense)              (None, 128)               32896     \n",
      "_________________________________________________________________\n",
      "dropout_37 (Dropout)         (None, 128)               0         \n",
      "_________________________________________________________________\n",
      "dense_2 (Dense)              (None, 1)                 129       \n",
      "=================================================================\n",
      "Total params: 109,712,129\n",
      "Trainable params: 109,712,129\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model.compile(tf.keras.optimizers.Adam(1e-5), loss='binary_crossentropy', metrics=['accuracy'])\n",
    "model.summary()\n",
    "\n"
   ]
  },
  {
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     "text": [
      "Epoch 1/15\n",
      "358/358 [==============================] - 62s 173ms/step - loss: 0.3313 - accuracy: 0.8569 - val_loss: 0.2938 - val_accuracy: 0.8826\n",
      "Epoch 2/15\n",
      "358/358 [==============================] - 58s 163ms/step - loss: 0.1950 - accuracy: 0.9246 - val_loss: 0.2358 - val_accuracy: 0.9067\n",
      "Epoch 3/15\n",
      "358/358 [==============================] - 58s 163ms/step - loss: 0.1244 - accuracy: 0.9523 - val_loss: 0.2472 - val_accuracy: 0.9102\n",
      "Epoch 4/15\n",
      "358/358 [==============================] - 58s 163ms/step - loss: 0.0773 - accuracy: 0.9716 - val_loss: 0.2646 - val_accuracy: 0.9151\n",
      "Epoch 5/15\n",
      "358/358 [==============================] - 59s 164ms/step - loss: 0.0500 - accuracy: 0.9837 - val_loss: 0.3116 - val_accuracy: 0.9109\n",
      "Epoch 6/15\n",
      "358/358 [==============================] - 58s 163ms/step - loss: 0.0298 - accuracy: 0.9901 - val_loss: 0.3614 - val_accuracy: 0.9154\n",
      "Epoch 7/15\n",
      "358/358 [==============================] - 58s 163ms/step - loss: 0.0228 - accuracy: 0.9927 - val_loss: 0.3552 - val_accuracy: 0.9106\n",
      "Epoch 8/15\n",
      "358/358 [==============================] - 58s 163ms/step - loss: 0.0165 - accuracy: 0.9946 - val_loss: 0.3864 - val_accuracy: 0.9182\n",
      "Epoch 9/15\n",
      "358/358 [==============================] - 59s 164ms/step - loss: 0.0119 - accuracy: 0.9961 - val_loss: 0.4346 - val_accuracy: 0.9133\n",
      "Epoch 10/15\n",
      "358/358 [==============================] - 58s 163ms/step - loss: 0.0122 - accuracy: 0.9956 - val_loss: 0.3899 - val_accuracy: 0.9165\n",
      "Epoch 11/15\n",
      "358/358 [==============================] - 59s 163ms/step - loss: 0.0112 - accuracy: 0.9961 - val_loss: 0.4039 - val_accuracy: 0.9168\n",
      "Epoch 12/15\n",
      "358/358 [==============================] - 59s 164ms/step - loss: 0.0097 - accuracy: 0.9968 - val_loss: 0.4163 - val_accuracy: 0.9182\n",
      "Epoch 13/15\n",
      "358/358 [==============================] - 59s 164ms/step - loss: 0.0094 - accuracy: 0.9971 - val_loss: 0.4464 - val_accuracy: 0.9095\n",
      "Epoch 14/15\n",
      "358/358 [==============================] - 59s 164ms/step - loss: 0.0078 - accuracy: 0.9976 - val_loss: 0.4791 - val_accuracy: 0.9088\n",
      "Epoch 15/15\n",
      "358/358 [==============================] - 59s 165ms/step - loss: 0.0066 - accuracy: 0.9976 - val_loss: 0.4385 - val_accuracy: 0.9189\n"
     ]
    }
   ],
   "source": [
    "history = model.fit(x = train_ids, y = train_labels, epochs = 15, verbose = 1, batch_size = 64, validation_data = (dev_ids, dev_labels))"
   ]
  },
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     "iopub.status.busy": "2021-05-21T12:31:05.482010Z",
     "iopub.status.idle": "2021-05-21T12:31:06.245598Z",
     "shell.execute_reply": "2021-05-21T12:31:06.244269Z",
     "shell.execute_reply.started": "2021-05-21T11:55:57.906817Z"
    },
    "papermill": {
     "duration": 2.687893,
     "end_time": "2021-05-21T12:31:06.245748",
     "exception": false,
     "start_time": "2021-05-21T12:31:03.557855",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1250x750 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1250x750 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#from matplotlib.pyplot import figure\n",
    "\n",
    "\n",
    "def plot_graphs(history, string):\n",
    "  plt.figure(figsize=(5, 3), dpi=250)\n",
    "    \n",
    "  plt.plot(history.history[string])\n",
    "  plt.plot(history.history['val_'+string])\n",
    "  plt.xlabel(\"Epochs\")\n",
    "  plt.ylabel(string)\n",
    "  plt.legend(['train_'+string, 'val_'+string])\n",
    "  \n",
    "  plt.savefig(string+'.png')\n",
    "  plt.show()\n",
    "  \n",
    "\n",
    "plot_graphs(history, 'accuracy')\n",
    "plot_graphs(history, 'loss')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-05-21T12:31:10.404085Z",
     "iopub.status.busy": "2021-05-21T12:31:10.402997Z",
     "iopub.status.idle": "2021-05-21T12:31:17.307453Z",
     "shell.execute_reply": "2021-05-21T12:31:17.308264Z",
     "shell.execute_reply.started": "2021-05-21T11:56:13.408475Z"
    },
    "papermill": {
     "duration": 9.157229,
     "end_time": "2021-05-21T12:31:17.308503",
     "exception": false,
     "start_time": "2021-05-21T12:31:08.151274",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.91      0.95      0.93      1464\n",
      "           1       0.95      0.90      0.92      1398\n",
      "\n",
      "    accuracy                           0.93      2862\n",
      "   macro avg       0.93      0.92      0.93      2862\n",
      "weighted avg       0.93      0.93      0.93      2862\n",
      "\n"
     ]
    }
   ],
   "source": [
    "pred_=model.predict(test_ids)\n",
    "\n",
    "from sklearn.metrics import classification_report\n",
    "pred_thrs=[]\n",
    "for i in pred_:\n",
    "    if i<0.5:\n",
    "        pred_thrs.append(0)\n",
    "    else:\n",
    "        pred_thrs.append(1)\n",
    "print(classification_report(test_labels, pred_thrs))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-05-21T12:31:21.520041Z",
     "iopub.status.busy": "2021-05-21T12:31:21.519379Z",
     "iopub.status.idle": "2021-05-21T12:31:21.526077Z",
     "shell.execute_reply": "2021-05-21T12:31:21.526633Z",
     "shell.execute_reply.started": "2021-05-21T09:33:03.489312Z"
    },
    "papermill": {
     "duration": 2.264178,
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    "    output.write(str(pred_thrs))"
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    "test_sents1=['obama says voting barriers are directly linked to jim crow and slavery']\n",
    "test_sents1_ids=encoder(test_sents1)\n",
    "pred_=model.predict(test_sents1_ids)\n",
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    "import pickle\n",
    "\n",
    "#pickle.dump(model, open('bert_sarcasm_classifier.pkl', 'wb'))\n",
    "model.save_weights('bert_sarcasm_classifier')"
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    "with open(\"test_sents.txt\", \"w\") as output:\n",
    "    output.write(str(test_sents.tolist()))"
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