Untitled.ipynb

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  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "3f6a5c56",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np \n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "6857a3c7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: transformers in /home/shirshak/anaconda3/envs/major_project/lib/python3.11/site-packages (4.30.2)\n",
      "Requirement already satisfied: filelock in /home/shirshak/anaconda3/envs/major_project/lib/python3.11/site-packages (from transformers) (3.12.2)\n",
      "Requirement already satisfied: huggingface-hub<1.0,>=0.14.1 in /home/shirshak/anaconda3/envs/major_project/lib/python3.11/site-packages (from transformers) (0.15.1)\n",
      "Requirement already satisfied: numpy>=1.17 in /home/shirshak/anaconda3/envs/major_project/lib/python3.11/site-packages (from transformers) (1.24.3)\n",
      "Requirement already satisfied: packaging>=20.0 in /home/shirshak/anaconda3/envs/major_project/lib/python3.11/site-packages (from transformers) (23.0)\n",
      "Requirement already satisfied: pyyaml>=5.1 in /home/shirshak/anaconda3/envs/major_project/lib/python3.11/site-packages (from transformers) (6.0)\n",
      "Requirement already satisfied: regex!=2019.12.17 in /home/shirshak/anaconda3/envs/major_project/lib/python3.11/site-packages (from transformers) (2022.7.9)\n",
      "Requirement already satisfied: requests in /home/shirshak/anaconda3/envs/major_project/lib/python3.11/site-packages (from transformers) (2.27.1)\n",
      "Requirement already satisfied: tokenizers!=0.11.3,<0.14,>=0.11.1 in /home/shirshak/anaconda3/envs/major_project/lib/python3.11/site-packages (from transformers) (0.13.3)\n",
      "Requirement already satisfied: safetensors>=0.3.1 in /home/shirshak/anaconda3/envs/major_project/lib/python3.11/site-packages (from transformers) (0.3.1)\n",
      "Requirement already satisfied: tqdm>=4.27 in /home/shirshak/anaconda3/envs/major_project/lib/python3.11/site-packages (from transformers) (4.65.0)\n",
      "Requirement already satisfied: fsspec in /home/shirshak/anaconda3/envs/major_project/lib/python3.11/site-packages (from huggingface-hub<1.0,>=0.14.1->transformers) (2023.6.0)\n",
      "Requirement already satisfied: typing-extensions>=3.7.4.3 in /home/shirshak/anaconda3/envs/major_project/lib/python3.11/site-packages (from huggingface-hub<1.0,>=0.14.1->transformers) (4.6.3)\n",
      "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /home/shirshak/anaconda3/envs/major_project/lib/python3.11/site-packages (from requests->transformers) (1.26.8)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in /home/shirshak/anaconda3/envs/major_project/lib/python3.11/site-packages (from requests->transformers) (2023.5.7)\n",
      "Requirement already satisfied: charset-normalizer~=2.0.0 in /home/shirshak/anaconda3/envs/major_project/lib/python3.11/site-packages (from requests->transformers) (2.0.4)\n",
      "Requirement already satisfied: idna<4,>=2.5 in /home/shirshak/anaconda3/envs/major_project/lib/python3.11/site-packages (from requests->transformers) (3.3)\n"
     ]
    }
   ],
   "source": [
    "!pip install transformers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "e2c85d49",
   "metadata": {},
   "outputs": [],
   "source": [
    "from transformers import BertTokenizer, BertForSequenceClassification"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "6bc4671b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "eaa21c272e1244fd826e2fcbb16ace4a",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Downloading model.safetensors:   0%|          | 0.00/440M [00:00<?, ?B/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Some weights of the model checkpoint at bert-base-uncased were not used when initializing BertForSequenceClassification: ['cls.seq_relationship.bias', 'cls.predictions.transform.dense.weight', 'cls.predictions.transform.dense.bias', 'cls.seq_relationship.weight', 'cls.predictions.transform.LayerNorm.weight', 'cls.predictions.bias', 'cls.predictions.transform.LayerNorm.bias']\n",
      "- This IS expected if you are initializing BertForSequenceClassification from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n",
      "- This IS NOT expected if you are initializing BertForSequenceClassification from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n",
      "Some weights of BertForSequenceClassification were not initialized from the model checkpoint at bert-base-uncased and are newly initialized: ['classifier.weight', 'classifier.bias']\n",
      "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n"
     ]
    }
   ],
   "source": [
    "tokenizer = BertTokenizer.from_pretrained('bert-base-uncased')\n",
    "model = BertForSequenceClassification.from_pretrained('bert-base-uncased')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "c65d16c0",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('dataset2.txt',sep=';')\n",
    "df.columns = ['text','sentiment']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "7962e873",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>text</th>\n",
       "      <th>sentiment</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>i feel like i am still looking at a blank canv...</td>\n",
       "      <td>sadness</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>i feel like a faithful servant</td>\n",
       "      <td>love</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>i am just feeling cranky and blue</td>\n",
       "      <td>anger</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>i can have for a treat or if i am feeling festive</td>\n",
       "      <td>joy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>i start to feel more appreciative of what god ...</td>\n",
       "      <td>joy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1994</th>\n",
       "      <td>im having ssa examination tomorrow in the morn...</td>\n",
       "      <td>sadness</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995</th>\n",
       "      <td>i constantly worry about their fight against n...</td>\n",
       "      <td>joy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1996</th>\n",
       "      <td>i feel its important to share this info for th...</td>\n",
       "      <td>joy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1997</th>\n",
       "      <td>i truly feel that if you are passionate enough...</td>\n",
       "      <td>joy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1998</th>\n",
       "      <td>i feel like i just wanna buy any cute make up ...</td>\n",
       "      <td>joy</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1999 rows × 2 columns</p>\n",
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       "                                                   text sentiment\n",
       "0     i feel like i am still looking at a blank canv...   sadness\n",
       "1                        i feel like a faithful servant      love\n",
       "2                     i am just feeling cranky and blue     anger\n",
       "3     i can have for a treat or if i am feeling festive       joy\n",
       "4     i start to feel more appreciative of what god ...       joy\n",
       "...                                                 ...       ...\n",
       "1994  im having ssa examination tomorrow in the morn...   sadness\n",
       "1995  i constantly worry about their fight against n...       joy\n",
       "1996  i feel its important to share this info for th...       joy\n",
       "1997  i truly feel that if you are passionate enough...       joy\n",
       "1998  i feel like i just wanna buy any cute make up ...       joy\n",
       "\n",
       "[1999 rows x 2 columns]"
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     "execution_count": 7,
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