![\"Open](\"https://colab.research.google.com/assets/colab-badge.svg\"){kind=icon}
"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "X2Pw5uR1SxCB"
- },
- "source": [
- "---\n",
- "# **Emotion Analysis - Cancer Narratives**\n",
- "---\n",
- "\n"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 2,
- "metadata": {
- "id": "B3vU8SJ5CchM"
- },
- "outputs": [],
- "source": [
- "examples = [\"At first I thought she might make a good recovery because she started eating well and seemed happy.\", \"Going into town I will enjoy the delightful offerings from del taco and a Xanex. We dine like kings!\" ,\"I’m going to die, and I’m going to do it with as much dignity as possible, and have the best last few months I can possibly have.\", \"I made him breakfast, and dinner and tried to keep a positive mindset and just do the happy stuff we always loved doing, jamming, joking, eating waffles.\",\n",
- "\"Today I am officially 25 years cancer free.\", \"Hello comrades, just wanted to share my story after a surgery where I scored another goal against cancer and made it 3-0.\", \"I told her I loved her and held her hand while they ended life support.\",\n",
- "\"But hearing the phrase, 'you no longer have cancer' makes me feel invincible again.\", \"I’m still battling side effects but I’m so relieved to be done!!\" \"I get to come home to my beautiful wife and loving dog every time.\",\n",
- "\"I’m trying to take it all in and enjoy my family and the festivities. There’s so much to enjoy.\", \"I have been told I will never be cancer free, I have learnt to accept that. \", \"Finished a year of treatment and continued on maintenance chemotherapy for another year and was cancer free for a while until I relapsed at 22.\", \"I’ve completed 8 rounds of chemotherapy and 25 sessions of chemoradiation.\", \"This morning was my last day of radiation!\", \"They were able to cut out the tumor but weren't successful in getting clean margins on the first pass.\"]"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 3,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "WnOFNt9bFTr1",
- "outputId": "e4bf9fd7-6ff0-4843-9ebe-6af3b1e9b9a0"
- },
- "outputs": [
- {
- "output_type": "execute_result",
- "data": {
- "text/plain": [
- "['At first I thought she might make a good recovery because she started eating well and seemed happy.',\n",
- " 'Going into town I will enjoy the delightful offerings from del taco and a Xanex. We dine like kings!',\n",
- " 'I’m going to die, and I’m going to do it with as much dignity as possible, and have the best last few months I can possibly have.',\n",
- " 'I made him breakfast, and dinner and tried to keep a positive mindset and just do the happy stuff we always loved doing, jamming, joking, eating waffles.',\n",
- " 'Today I am officially 25 years cancer free.',\n",
- " 'Hello comrades, just wanted to share my story after a surgery where I scored another goal against cancer and made it 3-0.',\n",
- " 'I told her I loved her and held her hand while they ended life support.',\n",
- " \"But hearing the phrase, 'you no longer have cancer' makes me feel invincible again.\",\n",
- " 'I’m still battling side effects but I’m so relieved to be done!!I get to come home to my beautiful wife and loving dog every time.',\n",
- " 'I’m trying to take it all in and enjoy my family and the festivities. There’s so much to enjoy.',\n",
- " 'I have been told I will never be cancer free, I have learnt to accept that. ',\n",
- " 'Finished a year of treatment and continued on maintenance chemotherapy for another year and was cancer free for a while until I relapsed at 22.',\n",
- " 'I’ve completed 8 rounds of chemotherapy and 25 sessions of chemoradiation.',\n",
- " 'This morning was my last day of radiation!',\n",
- " \"They were able to cut out the tumor but weren't successful in getting clean margins on the first pass.\"]"
- ]
- },
- "metadata": {},
- "execution_count": 3
- }
- ],
- "source": [
- "examples"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "bXPmDE6KCTSc"
- },
- "source": [
- "---\n",
- "# **Roberta Go**\n",
- "---\n",
- "\n"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 4,
- "metadata": {
- "colab": {
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- },
- "id": "kxj-PCNpCQ3y",
- "outputId": "fff18fa1-d44c-4f24-fde1-0c1cba9638f3"
- },
- "outputs": [
- {
- "output_type": "stream",
- "name": "stderr",
- "text": [
- "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_token.py:88: UserWarning: \n",
- "The secret `HF_TOKEN` does not exist in your Colab secrets.\n",
- "To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n",
- "You will be able to reuse this secret in all of your notebooks.\n",
- "Please note that authentication is recommended but still optional to access public models or datasets.\n",
- " warnings.warn(\n"
- ]
- },
- {
- "output_type": "display_data",
- "data": {
- "text/plain": [
- "config.json: 0%| | 0.00/1.92k [00:00. This is expected, and simply means that the `legacy` (previous) behavior will be used so nothing changes for you. If you want to use the new behaviour, set `legacy=False`. This should only be set if you understand what it means, and thoroughly read the reason why this was added as explained in https://github.com/huggingface/transformers/pull/24565\n",
- "/usr/local/lib/python3.10/dist-packages/transformers/models/auto/modeling_auto.py:1595: FutureWarning: The class `AutoModelWithLMHead` is deprecated and will be removed in a future version. Please use `AutoModelForCausalLM` for causal language models, `AutoModelForMaskedLM` for masked language models and `AutoModelForSeq2SeqLM` for encoder-decoder models.\n",
- " warnings.warn(\n"
- ]
- },
- {
- "output_type": "display_data",
- "data": {
- "text/plain": [
- "pytorch_model.bin: 0%| | 0.00/892M [00:00', return_tensors='pt')\n",
- "\n",
- " output = model.generate(input_ids=input_ids,\n",
- " max_length=2)\n",
- "\n",
- " dec = [tokenizer.decode(ids) for ids in output]\n",
- " label = dec[0]\n",
- " return label\n",
- "\n",
- "for ex in examples:\n",
- " t5.append(get_emotion(ex))\n"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "AvNLw5L3GzBt"
- },
- "source": [
- "---\n",
- "# **DistilBert**\n",
- "---\n"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 6,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 145,
- "referenced_widgets": [
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- ]
- },
- "id": "u1z3ASHxGxTN",
- "outputId": "5ac3d8da-4a85-4b3c-c752-82ef5f3244af"
- },
- "outputs": [
- {
- "output_type": "display_data",
- "data": {
- "text/plain": [
- "tokenizer_config.json: 0%| | 0.00/48.0 [00:00 1 else t\n",
- " t = 'http' if t.startswith('http') else t\n",
- " new_text.append(t)\n",
- " return \" \".join(new_text)\n",
- "MODEL = f\"cardiffnlp/twitter-roberta-base-sentiment-latest\"\n",
- "tokenizer = AutoTokenizer.from_pretrained(MODEL)\n",
- "config = AutoConfig.from_pretrained(MODEL)\n",
- "\n",
- "model = AutoModelForSequenceClassification.from_pretrained(MODEL)\n",
- "\n",
- "roberta = []\n",
- "for text in examples:\n",
- " text = preprocess(text)\n",
- " encoded_input = tokenizer(text, return_tensors='pt')\n",
- " output = model(**encoded_input)\n",
- " scores = output[0][0].detach().numpy()\n",
- " scores = softmax(scores)\n",
- " ranking = np.argsort(scores)\n",
- " ranking = ranking[::-1]\n",
- " for i in range(scores.shape[0]):\n",
- " l = config.id2label[ranking[i]]\n",
- " s = scores[ranking[i]]\n",
- " # roberta.append(f\"{l} {np.round(float(s), 4)}\")\n",
- " roberta.append(l)\n",
- "\n",
- "roberta = [v for i, v in enumerate(roberta) if i%3 == 0]"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "qmM8Tsd3G8Qf"
- },
- "source": [
- "---\n",
- "# **NRCLex**\n",
- "---"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 8,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "kJNVnLgtHekU",
- "outputId": "6459c3de-1e9c-47ed-fb30-9c8a9a10d908"
- },
- "outputs": [
- {
- "output_type": "stream",
- "name": "stdout",
- "text": [
- "Collecting NRCLex\n",
- " Downloading NRCLex-4.0-py3-none-any.whl (4.4 kB)\n",
- "Requirement already satisfied: textblob in /usr/local/lib/python3.10/dist-packages (from NRCLex) (0.17.1)\n",
- "INFO: pip is looking at multiple versions of nrclex to determine which version is compatible with other requirements. This could take a while.\n",
- " Downloading NRCLex-3.0.0.tar.gz (396 kB)\n",
- "\u001b[?25l \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.0/396.4 kB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r\u001b[2K \u001b[91m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[91m╸\u001b[0m\u001b[90m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m194.6/396.4 kB\u001b[0m \u001b[31m5.8 MB/s\u001b[0m eta \u001b[36m0:00:01\u001b[0m\r\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m396.4/396.4 kB\u001b[0m \u001b[31m7.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
- "\u001b[?25h Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
- "Requirement already satisfied: nltk>=3.1 in /usr/local/lib/python3.10/dist-packages (from textblob->NRCLex) (3.8.1)\n",
- "Requirement already satisfied: click in /usr/local/lib/python3.10/dist-packages (from nltk>=3.1->textblob->NRCLex) (8.1.7)\n",
- "Requirement already satisfied: joblib in /usr/local/lib/python3.10/dist-packages (from nltk>=3.1->textblob->NRCLex) (1.3.2)\n",
- "Requirement already satisfied: regex>=2021.8.3 in /usr/local/lib/python3.10/dist-packages (from nltk>=3.1->textblob->NRCLex) (2023.12.25)\n",
- "Requirement already satisfied: tqdm in /usr/local/lib/python3.10/dist-packages (from nltk>=3.1->textblob->NRCLex) (4.66.2)\n",
- "Building wheels for collected packages: NRCLex\n",
- " Building wheel for NRCLex (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
- " Created wheel for NRCLex: filename=NRCLex-3.0.0-py3-none-any.whl size=43309 sha256=f722e3e5f017a71bbe4281b3d6fa5d6d685cfb5fb1f1a74770f16eeecd5c0b47\n",
- " Stored in directory: /root/.cache/pip/wheels/d2/10/44/6abfb1234298806a145fd6bcaec8cbc712e88dd1cd6cb242fa\n",
- "Successfully built NRCLex\n",
- "Installing collected packages: NRCLex\n",
- "Successfully installed NRCLex-3.0.0\n"
- ]
- }
- ],
- "source": [
- "!pip install NRCLex"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 9,
- "metadata": {
- "id": "QfDXnbPUHh2y",
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "outputId": "96c4fd94-8f5d-42b7-f2c3-ead095e30341"
- },
- "outputs": [
- {
- "output_type": "stream",
- "name": "stderr",
- "text": [
- "[nltk_data] Downloading package stopwords to /root/nltk_data...\n",
- "[nltk_data] Unzipping corpora/stopwords.zip.\n",
- "[nltk_data] Downloading package punkt to /root/nltk_data...\n",
- "[nltk_data] Unzipping tokenizers/punkt.zip.\n"
- ]
- },
- {
- "output_type": "execute_result",
- "data": {
- "text/plain": [
- "True"
- ]
- },
- "metadata": {},
- "execution_count": 9
- }
- ],
- "source": [
- "from nrclex import NRCLex\n",
- "import nltk\n",
- "nltk.download('stopwords')\n",
- "nltk.download('punkt')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 10,
- "metadata": {
- "id": "iutZE_Y1I4QZ"
- },
- "outputs": [],
- "source": [
- "nrclex = []\n",
- "for ex in examples:\n",
- " text_object = NRCLex(ex)\n",
- " nrclex.append(text_object.top_emotions)"
- ]
- },
- {
- "cell_type": "markdown",
- "source": [
- "---\n",
- "# **USAS**\n",
- "---\n",
- "\n"
- ],
- "metadata": {
- "id": "DgooMfOBPQg2"
- }
- },
- {
- "cell_type": "code",
- "source": [
- "# Install the PyDrive wrapper & import libraries.\n",
- "!pip install import-ipynb\n",
- "!pip install -U -q PyDrive"
- ],
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "NBimLKVGQR83",
- "outputId": "27033fa7-9e6c-45c1-bbc3-629843f3e501"
- },
- "execution_count": 11,
- "outputs": [
- {
- "output_type": "stream",
- "name": "stdout",
- "text": [
- "Collecting import-ipynb\n",
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- "Requirement already satisfied: platformdirs>=2.5 in /usr/local/lib/python3.10/dist-packages (from jupyter-core->nbformat->import-ipynb) (4.2.0)\n",
- "Installing collected packages: jedi, import-ipynb\n",
- "Successfully installed import-ipynb-0.1.4 jedi-0.19.1\n"
- ]
- }
- ]
- },
- {
- "cell_type": "code",
- "source": [
- "import import_ipynb\n",
- "# This only needs to be done once per notebook.\n",
- "from pydrive.auth import GoogleAuth\n",
- "from pydrive.drive import GoogleDrive\n",
- "from google.colab import auth\n",
- "from oauth2client.client import GoogleCredentials\n",
- "\n",
- "# Authenticate and create the PyDrive client.\n",
- "# This only needs to be done once per notebook.\n",
- "auth.authenticate_user()\n",
- "gauth = GoogleAuth()\n",
- "gauth.credentials = GoogleCredentials.get_application_default()\n",
- "drive = GoogleDrive(gauth)"
- ],
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "B08M5Wl8PWez",
- "outputId": "5e508348-99a8-49e9-fa5c-2eb629638520"
- },
- "execution_count": 12,
- "outputs": [
- {
- "output_type": "stream",
- "name": "stderr",
- "text": [
- "WARNING:root:pydrive is deprecated and no longer maintained. We recommend that you migrate your projects to pydrive2, the maintained fork of pydrive\n"
- ]
- }
- ]
- },
- {
- "cell_type": "code",
- "source": [
- "# Copy the link and remove the front part of the link (i.e. https://drive.google.com/open?id=) to get the file ID.\n",
- "your_module = drive.CreateFile({'id':'1qd531E2R36wwqGa9wlTZa5MquLKlFFaS'})\n",
- "your_module.GetContentFile('usas_sentiment_classifier.ipynb')\n",
- "import usas_sentiment_classifier"
- ],
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "0S5u3DSOP6dy",
- "outputId": "ac71146c-ec80-4095-82bf-4c79bce7281f"
- },
- "execution_count": 13,
- "outputs": [
- {
- "output_type": "stream",
- "name": "stdout",
- "text": [
- "importing Jupyter notebook from usas_sentiment_classifier.ipynb\n",
- "Mounted at /content/gdrive/\n",
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- "Installing collected packages: click, pymusas, en-dual-none-contextual\n",
- " Attempting uninstall: click\n",
- " Found existing installation: click 8.1.7\n",
- " Uninstalling click-8.1.7:\n",
- " Successfully uninstalled click-8.1.7\n",
- "Successfully installed click-8.0.4 en-dual-none-contextual-0.3.3 pymusas-0.3.0\n",
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- " Downloading https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-3.7.1/en_core_web_sm-3.7.1-py3-none-any.whl (12.8 MB)\n",
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- "\u001b[38;5;2m✔ Download and installation successful\u001b[0m\n",
- "You can now load the package via spacy.load('en_core_web_sm')\n",
- "\u001b[38;5;3m⚠ Restart to reload dependencies\u001b[0m\n",
- "If you are in a Jupyter or Colab notebook, you may need to restart Python in\n",
- "order to load all the package's dependencies. You can do this by selecting the\n",
- "'Restart kernel' or 'Restart runtime' option.\n",
- "Collecting colorama\n",
- " Downloading colorama-0.4.6-py2.py3-none-any.whl (25 kB)\n",
- "Installing collected packages: colorama\n",
- "Successfully installed colorama-0.4.6\n"
- ]
- },
- {
- "output_type": "stream",
- "name": "stderr",
- "text": [
- "[nltk_data] Downloading package punkt to /root/nltk_data...\n",
- "[nltk_data] Package punkt is already up-to-date!\n"
- ]
- }
- ]
- },
- {
- "cell_type": "code",
- "source": [
- "usas_sents = []\n",
- "for ex in examples:\n",
- " emo_dict = usas_sentiment_classifier.usas_emotion_tags(ex)\n",
- " sent, pos, neg, neu = usas_sentiment_classifier.usas_sentiment_classifier(emo_dict, 0, 0, 0)\n",
- " probs = usas_sentiment_classifier.text_sentiment_prob(ex, pos, neg, neu)\n",
- " usas_sents.append(probs)"
- ],
- "metadata": {
- "id": "dATSwb-CSWUz"
- },
- "execution_count": 14,
- "outputs": []
- },
- {
- "cell_type": "code",
- "source": [
- "usas_sents"
- ],
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "2VOq4GGcV0km",
- "outputId": "d3aaed3f-0b3e-4194-a71a-e96c3381696a"
- },
- "execution_count": 15,
- "outputs": [
- {
- "output_type": "execute_result",
- "data": {
- "text/plain": [
- "['positive=0.5, negative=0.5, neutral=0.0',\n",
- " 'positive=0.6666666666666666, negative=0.0, neutral=0.3333333333333333',\n",
- " 'positive=0.0, negative=0.0, neutral=1.0',\n",
- " 'positive=0.8, negative=0.2, neutral=0.0',\n",
- " 'positive=0.0, negative=0.0, neutral=1.0',\n",
- " 'positive=0.0, negative=0.0, neutral=1.0',\n",
- " 'positive=0.0, negative=0.0, neutral=1.0',\n",
- " 'positive=0.0, negative=0.0, neutral=1.0',\n",
- " 'positive=0.5, negative=0.5, neutral=0.0',\n",
- " 'positive=0.6666666666666666, negative=0.0, neutral=0.3333333333333333',\n",
- " 'positive=0.0, negative=0.0, neutral=1.0',\n",
- " 'positive=0.0, negative=0.0, neutral=1.0',\n",
- " 'positive=0.0, negative=0.0, neutral=1.0',\n",
- " 'positive=0.0, negative=0.0, neutral=1.0',\n",
- " 'positive=0.0, negative=1.0, neutral=0.0']"
- ]
- },
- "metadata": {},
- "execution_count": 15
- }
- ]
- },
- {
- "cell_type": "markdown",
- "source": [
- "---\n",
- "# **Comparative Analysis**\n",
- "---"
- ],
- "metadata": {
- "id": "Q3BpdhXCPwMZ"
- }
- },
- {
- "cell_type": "code",
- "execution_count": 16,
- "metadata": {
- "id": "fd2ByFd6KsqJ"
- },
- "outputs": [],
- "source": [
- "import pandas as pd\n",
- "\n",
- "eval_set = pd.DataFrame()\n",
- "eval_set['Sentences'] = examples\n",
- "eval_set['USAS'] = usas_sents\n",
- "eval_set['Roberta'] = roberta\n",
- "eval_set['DistilBERT'] = distil\n",
- "eval_set['NRCLex'] = nrclex\n",
- "eval_set['T5'] = t5\n",
- "eval_set['RobertaGo'] = robertaGo"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 17,
- "metadata": {
- "id": "kx6p93hqNVdZ",
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 762
- },
- "outputId": "cca2886e-4e50-4146-cdb2-e75de081433d"
- },
- "outputs": [
- {
- "output_type": "execute_result",
- "data": {
- "text/plain": [
- " Sentences \\\n",
- "0 At first I thought she might make a good recov... \n",
- "1 Going into town I will enjoy the delightful of... \n",
- "2 I’m going to die, and I’m going to do it with ... \n",
- "3 I made him breakfast, and dinner and tried to ... \n",
- "4 Today I am officially 25 years cancer free. \n",
- "5 Hello comrades, just wanted to share my story ... \n",
- "6 I told her I loved her and held her hand while... \n",
- "7 But hearing the phrase, 'you no longer have ca... \n",
- "8 I’m still battling side effects but I’m so rel... \n",
- "9 I’m trying to take it all in and enjoy my fami... \n",
- "10 I have been told I will never be cancer free, ... \n",
- "11 Finished a year of treatment and continued on ... \n",
- "12 I’ve completed 8 rounds of chemotherapy and 25... \n",
- "13 This morning was my last day of radiation! \n",
- "14 They were able to cut out the tumor but weren'... \n",
- "\n",
- " USAS Roberta DistilBERT \\\n",
- "0 positive=0.5, negative=0.5, neutral=0.0 positive POSITIVE \n",
- "1 positive=0.6666666666666666, negative=0.0, neu... positive POSITIVE \n",
- "2 positive=0.0, negative=0.0, neutral=1.0 positive POSITIVE \n",
- "3 positive=0.8, negative=0.2, neutral=0.0 positive POSITIVE \n",
- "4 positive=0.0, negative=0.0, neutral=1.0 positive POSITIVE \n",
- "5 positive=0.0, negative=0.0, neutral=1.0 positive POSITIVE \n",
- "6 positive=0.0, negative=0.0, neutral=1.0 positive POSITIVE \n",
- "7 positive=0.0, negative=0.0, neutral=1.0 positive POSITIVE \n",
- "8 positive=0.5, negative=0.5, neutral=0.0 positive POSITIVE \n",
- "9 positive=0.6666666666666666, negative=0.0, neu... positive POSITIVE \n",
- "10 positive=0.0, negative=0.0, neutral=1.0 negative POSITIVE \n",
- "11 positive=0.0, negative=0.0, neutral=1.0 neutral NEGATIVE \n",
- "12 positive=0.0, negative=0.0, neutral=1.0 neutral NEGATIVE \n",
- "13 positive=0.0, negative=0.0, neutral=1.0 positive NEGATIVE \n",
- "14 positive=0.0, negative=1.0, neutral=0.0 neutral NEGATIVE \n",
- "\n",
- " NRCLex T5 \\\n",
- "0 [(positive, 0.2727272727272727), (anticipation... | \n", - " | Sentences | \n", - "USAS | \n", - "Roberta | \n", - "DistilBERT | \n", - "NRCLex | \n", - "T5 | \n", - "RobertaGo | \n", - "
|---|---|---|---|---|---|---|---|
| 0 | \n", - "At first I thought she might make a good recov... | \n", - "positive=0.5, negative=0.5, neutral=0.0 | \n", - "positive | \n", - "POSITIVE | \n", - "[(positive, 0.2727272727272727), (anticipation... | \n", - "<pad> joy | \n", - "{'label': 'joy', 'score': 0.7537976503372192} | \n", - "
| 1 | \n", - "Going into town I will enjoy the delightful of... | \n", - "positive=0.6666666666666666, negative=0.0, neu... | \n", - "positive | \n", - "POSITIVE | \n", - "[(trust, 0.25), (positive, 0.25), (joy, 0.25),... | \n", - "<pad> joy | \n", - "{'label': 'joy', 'score': 0.8973855972290039} | \n", - "
| 2 | \n", - "I’m going to die, and I’m going to do it with ... | \n", - "positive=0.0, negative=0.0, neutral=1.0 | \n", - "positive | \n", - "POSITIVE | \n", - "[(fear, 0.2), (trust, 0.2), (positive, 0.2), (... | \n", - "<pad> joy | \n", - "{'label': 'optimism', 'score': 0.6296710968017... | \n", - "
| 3 | \n", - "I made him breakfast, and dinner and tried to ... | \n", - "positive=0.8, negative=0.2, neutral=0.0 | \n", - "positive | \n", - "POSITIVE | \n", - "[(positive, 0.5714285714285714)] | \n", - "<pad> joy | \n", - "{'label': 'joy', 'score': 0.6845877170562744} | \n", - "
| 4 | \n", - "Today I am officially 25 years cancer free. | \n", - "positive=0.0, negative=0.0, neutral=1.0 | \n", - "positive | \n", - "POSITIVE | \n", - "[(fear, 0.2), (anger, 0.2), (negative, 0.2), (... | \n", - "<pad> joy | \n", - "{'label': 'joy', 'score': 0.3095731735229492} | \n", - "
| 5 | \n", - "Hello comrades, just wanted to share my story ... | \n", - "positive=0.0, negative=0.0, neutral=1.0 | \n", - "positive | \n", - "POSITIVE | \n", - "[(fear, 0.18181818181818182), (sadness, 0.1818... | \n", - "<pad> joy | \n", - "{'label': 'desire', 'score': 0.3054072856903076} | \n", - "
| 6 | \n", - "I told her I loved her and held her hand while... | \n", - "positive=0.0, negative=0.0, neutral=1.0 | \n", - "positive | \n", - "POSITIVE | \n", - "[(fear, 0.0), (anger, 0.0), (anticip, 0.0), (t... | \n", - "<pad> love | \n", - "{'label': 'love', 'score': 0.90290766954422} | \n", - "
| 7 | \n", - "But hearing the phrase, 'you no longer have ca... | \n", - "positive=0.0, negative=0.0, neutral=1.0 | \n", - "positive | \n", - "POSITIVE | \n", - "[(fear, 0.2857142857142857), (negative, 0.2857... | \n", - "<pad> joy | \n", - "{'label': 'joy', 'score': 0.3020244836807251} | \n", - "
| 8 | \n", - "I’m still battling side effects but I’m so rel... | \n", - "positive=0.5, negative=0.5, neutral=0.0 | \n", - "positive | \n", - "POSITIVE | \n", - "[(positive, 0.3333333333333333), (joy, 0.33333... | \n", - "<pad> joy | \n", - "{'label': 'joy', 'score': 0.7250108122825623} | \n", - "
| 9 | \n", - "I’m trying to take it all in and enjoy my fami... | \n", - "positive=0.6666666666666666, negative=0.0, neu... | \n", - "positive | \n", - "POSITIVE | \n", - "[(trust, 0.25), (positive, 0.25), (joy, 0.25),... | \n", - "<pad> joy | \n", - "{'label': 'joy', 'score': 0.8999956250190735} | \n", - "
| 10 | \n", - "I have been told I will never be cancer free, ... | \n", - "positive=0.0, negative=0.0, neutral=1.0 | \n", - "negative | \n", - "POSITIVE | \n", - "[(fear, 0.2), (anger, 0.2), (negative, 0.2), (... | \n", - "<pad> joy | \n", - "{'label': 'approval', 'score': 0.4906566739082... | \n", - "
| 11 | \n", - "Finished a year of treatment and continued on ... | \n", - "positive=0.0, negative=0.0, neutral=1.0 | \n", - "neutral | \n", - "NEGATIVE | \n", - "[(fear, 0.16666666666666666), (anger, 0.166666... | \n", - "<pad> joy | \n", - "{'label': 'neutral', 'score': 0.596493124961853} | \n", - "
| 12 | \n", - "I’ve completed 8 rounds of chemotherapy and 25... | \n", - "positive=0.0, negative=0.0, neutral=1.0 | \n", - "neutral | \n", - "NEGATIVE | \n", - "[(fear, 0.0), (anger, 0.0), (anticip, 0.0), (t... | \n", - "<pad> joy | \n", - "{'label': 'neutral', 'score': 0.602870762348175} | \n", - "
| 13 | \n", - "This morning was my last day of radiation! | \n", - "positive=0.0, negative=0.0, neutral=1.0 | \n", - "positive | \n", - "NEGATIVE | \n", - "[(fear, 0.5), (negative, 0.5)] | \n", - "<pad> sadness | \n", - "{'label': 'excitement', 'score': 0.48605513572... | \n", - "
| 14 | \n", - "They were able to cut out the tumor but weren'... | \n", - "positive=0.0, negative=1.0, neutral=0.0 | \n", - "neutral | \n", - "NEGATIVE | \n", - "[(trust, 0.2222222222222222), (positive, 0.222... | \n", - "<pad> joy | \n", - "{'label': 'neutral', 'score': 0.680145263671875} | \n", - "