Upload reviewsentiment-analysis.ipynb

reviewsentiment-analysis.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "import tensorflow as tf\n",
+    "import opendatasets as od\n",
+    "import numpy as np\n",
+    "from tensorflow.keras import layers\n",
+    "from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline\n",
+    "\n",
+    "tf.get_logger().setLevel('ERROR')\n",
+    "tokenizer = AutoTokenizer.from_pretrained(\"blanchefort/rubert-base-cased-sentiment-rurewiews\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "model = AutoModelForSequenceClassification.from_pretrained(\"blanchefort/rubert-base-cased-sentiment-rurewiews\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "pipe = pipeline(\"text-classification\", model=\"blanchefort/rubert-base-cased-sentiment-rurewiews\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[{'label': 'NEUTRAL', 'score': 0.5040543079376221}]"
+      ]
+     },
+     "execution_count": 28,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pipe(\"Product is ok ok sounds also good but I am not feeling like 525 watts and weight also very less 525 watts means atleast 8kg or 10kg will be there and in paper they mentioned 5 modes are different on speaker what they given modes are different totally confused with this product\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Skipping, found downloaded files in \"restaurent_review\\reviews\" (use force=True to force download)\n"
+     ]
+    }
+   ],
+   "source": [
+    "import gradio as gr\n",
+    "import pandas as pd\n",
+    "import opendatasets as od\n",
+    "\n",
+    "od.download_kaggle_dataset('vigneshwarsofficial/reviews', data_dir='restaurent_review')\n",
+    "prediction_data = pd.read_csv('restaurent_review/reviews/Restaurant_Reviews.tsv',  delimiter='\\t')\n",
+    "\n",
+    "prediction_data.pop(\"Liked\")\n",
+    "\n",
+    "data = list(prediction_data[\"Review\"])\n",
+    "results = pipe(data)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['Wow... Loved this place.',\n",
+       " 'Crust is not good.',\n",
+       " 'Not tasty and the texture was just nasty.',\n",
+       " 'Stopped by during the late May bank holiday off Rick Steve recommendation and loved it.',\n",
+       " 'The selection on the menu was great and so were the prices.']"
+      ]
+     },
+     "execution_count": 30,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data[:5]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>count</th>\n",
+       "      <th>sentiment</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>283</td>\n",
+       "      <td>Positive</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>419</td>\n",
+       "      <td>Negative</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>298</td>\n",
+       "      <td>Neutral</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   count sentiment\n",
+       "0    283  Positive\n",
+       "1    419  Negative\n",
+       "2    298   Neutral"
+      ]
+     },
+     "execution_count": 31,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "positive_counter = 0 \n",
+    "negative_counter = 0\n",
+    "neutral_counter = 0\n",
+    "for x in results:\n",
+    "    if x['label'] == 'POSITIVE':\n",
+    "        positive_counter = positive_counter + 1\n",
+    "    elif x['label'] == 'NEGATIVE':\n",
+    "        negative_counter = negative_counter + 1\n",
+    "    else:\n",
+    "        neutral_counter = neutral_counter + 1\n",
+    "\n",
+    "result_data = pd.DataFrame({\n",
+    "    'count': [positive_counter, negative_counter, neutral_counter],\n",
+    "    'sentiment': ['Positive', 'Negative', 'Neutral']\n",
+    "})\n",
+    "\n",
+    "result_data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Running on local URL:  http://127.0.0.1:7866\n",
+      "Running on public URL: https://af39480688d32c192a.gradio.live\n",
+      "\n",
+      "This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from Terminal to deploy to Spaces (https://huggingface.co/spaces)\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div><iframe src=\"https://af39480688d32c192a.gradio.live\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": []
+     },
+     "execution_count": 32,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "single_input_demo = gr.Interface.from_pipeline(pipe, title=\"Sentiment Analysis\")\n",
+    "single_input_demo.launch(share=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Running on local URL:  http://127.0.0.1:7867\n",
+      "Running on public URL: https://4ce90a546387218f07.gradio.live\n",
+      "\n",
+      "This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from Terminal to deploy to Spaces (https://huggingface.co/spaces)\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div><iframe src=\"https://4ce90a546387218f07.gradio.live\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": []
+     },
+     "execution_count": 33,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import plotly.express as plt\n",
+    "\n",
+    "def plotly_plot(): \n",
+    "    p = plt.bar(result_data, x='sentiment', y='count', title='Restaurent Review Analysis', color=\"count\")\n",
+    "    return p\n",
+    "\n",
+    "# show the results\n",
+    "outputs = gr.Plot()\n",
+    "\n",
+    "demo = gr.Interface(fn=plotly_plot, inputs=None, outputs=outputs, title=\"Restaurant Customer Review Sentiment Analysis\")\n",
+    "\n",
+    "demo.launch(share=True)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}